**2.3 Crystallization of Na2SO4 and MgSO4**

Sodium sulfate is known to be a salt that causes the worst crystallization decay on porous materials and has become widely used in accelerated durability testing [38]. However, the sodium sulfate system is complicated, because under different conditions (temperature and relative humidity), it will form two stable phases (thenardite, Na2SO4 and mirabilite, Na2SO4·10H2O) or one metastable phase (heptahydrate, Na2SO4·7H2O) [12, 13] [39]. The metastable phase (Na2SO4·7H2O) is formed during the rehydration of the anhydrous sodium sulfate phase (Na2SO4) to the nucleation of mirabilite. Prior to mirabilite [12] [39], the crystallization pressure exerted by heptahydrate does not cause damage under the condition of the cooling experiments [36], and it can not be observed in building stone [13].

Regarding the damage caused by the crystallization of sodium sulfate, there are two views. One school thinks that the crystallization of thenardite is more destructive [40], because the crystallization of thenardite can generate higher pressure than mirabilite at the same supersaturation [41]. However, more and more experimental results support another school that the dissolution of thenardite producing a solution highly supersaturated with respect to mirabilite will cause the precipitation of mirabilite and result in the damage of porous materials [13] [38]. I.e. the transformation between thenardite and mirabilite can generate severe large crystallization pressure, resulting in porous materials damage.

The only naturally occurring members of the MgSO4·nH2O series on Earth are epsomite (MgSO4·7H2O, 51 wt% water), hexahydrite (MgSO4·6H2O, 47 wt% water) and kieserite (MgSO4·H2O, 13 wt% water). In aqueous systems, epsomite is stable at T below 48.4oC, hexahydrite is stable in the T range 48.4–68 oC, and kieserite is stable at T > 68 oC [42]. Thus, at the normal temperature, the crystallization of epsomite (MgSO4·7H2O,) is the distress reason.

#### **2.4 Summary**

In summary, according to above review, the following basic principles of salt weathering on porous materials can be concluded:

"Salt Weathering" Distress on Concrete by Sulfates? 439

2. As to the role of mineral additions, with the increase of dosage of fly ash and natural pozzolan, the concrete cylinders showed worse visual observation. This may be explained by the fact that salt crystallization in smaller pores can form higher crystallization stress due to the refinement of mineral additions. On the other hand, if we compare concrete H3 and H5, H4 and H6, we can find that with the same dosage the natural pozzolan (H5 and H6) played a more negative role in concrete damage than fly ash (H3 and H4). However the compressive strength of reference cylinders of H5 and H6 were higher than H3 and H4 respectively. The tests of PCA also showed similar

3. Comparing the normal concrete and blended concrete, Irassar et al [46] attributed an increase in capillary suction height caused by the pore size refinement of mineral addition to the more severe deterioration of blended concrete. However, this is in conflict with the following observations. Following the explanation based on the height of capillary sorption, concrete with a low W/C ratio should be more susceptible to salt weathering than with high W/C ratio. In the paper by Nehdi and Hayek [47], we can find that the sorption height of mortar with W/C of 0.45 is higher than with W/C of 0.6. If the above explanation is right, the mortar with low W/C (0.45) should be more susceptible to damage than the mortar with high W/C (0.6). Obviously, this conclusion

results. This appearance cannot be explained by the salt weathering.

Fig. 5. Evolution of visual rating at the atmosphere part of concrete [46]

Besides, there are also some field cases, in which a wide variety of efflorescence salts (sodium sulfate, sodium chloride and magnesium sulfate) were routinely observed on the evaporating surface of the foundation concrete in South California [48, 49] However, the damage was not caused by salt crystallization. Much of the cement paste had lost its integrity, mainly as a result of the removal of portlandite, de-calcification of the calcium silicate phases and the ultimate replacement of calcium with magnesium in many of the cementitious compounds. Many reaction products, in particular magnesium silicate hydrate, brucite, Friedel's salt (3CaO·Al2O3·CaCl2·10H2O), sodium carbonate and thaumasite were

Another interesting case [50] concerns the slabs of Yongan Dam, which is in Keshi, Xinjiang, P.R. China, where the land is arid and rich in various kinds of salts, especially sulfate salts. The slabs were constructed in August – October 2003. The air temperature fluctuates significantly: the highest temperature is up to 37 oC and at night it is only 15-20 oC. Within

is opposite to the result of field tests.

found at some depth within the concrete.


**14. Conclusion**

140 Dielectric Material

**Figure 22.** Coaxial dielectric resonators

**Figure 23.** Open dielectric resonators

should tend to zero; it is defined as:

vibration modes such as whispering gallery modes.

frequency of dielectric resonator in the temperature range ΔT.

over 1000. Since open resonators have a high Q value, they can be used in the decimeter

The size of open dielectric resonators operating on the characteristic modes TE01s and H01s becomes very small at frequencies above 30 GHz, which makes their use in this band impossible. Therefore, at frequencies above 30 GHz, it is expedient to use extraordinary

The modern communication systems in which dielectric resonators are used operate in a temperature range of – 40-80 0C. Therefore, high thermostability of dielectric resonator resonance frequency is required. It is necessary that the temperature coefficient of frequency

> 1 *p p f TK*

(9)

*f T*

where ƒr is the resonance frequency of dielectric resonator, Δ ƒr is change in the resonance

wave band (about 1 GHz), though in this case their size becomes large.

High-Q MW dielectrics with high thermostability of electrophysical properties can be developed on the basis of single-phase and multiphase systems. Single-phase MW dielectrics are produced on the basis of solid solutions [6, 15, 98] using heterovalent substitutions in one of the crystal sublattices and influencing thereby the phonon spectrum [10] and by making one of the sublattices "mobile" [151]. At the same time, high-Q thermostable MW dielectrics based on multiphase systems are developed using the volume temperature compensation effect [55-57, 124, 132, 135].

During the last decade, MW dielectrics with increased permittivity (ε ≥ 10) contribute, to a larger measure than other factors, to considerable miniaturization and reduction in the price of modern communication systems. It should be noted that there is still a great potential for further microminiaturization and reduction of prices of modern communication systems thanks to the use of components made on the basis of MW dielectrics.

Microwave Dielectrics Based on Complex Oxide Systems 143

Thus, the synthesis of novel high-Q MW dielectrics and the investigation of their structure

*V.I. Vernadskii Institute of General and Inorganic Chemistry of the Ukrainian NAS, Kyiv, Ukraine*

[1] Poplavko Yu.M., (1980) Physics of Dielectrics (in Russian), Vyshch. Shk., Kyiv 325. [2] Poplavko Yu.M., Belous A.G., (1984) Physical background of the temperature stability

[3] Chool-Woo Ahu, Hyun-Jung Jang, Sahn Nahm et al. (2003) Effects of microstructure on the microwave dielectric properties of Ba(Co1/3Nb2/3)O3 and (1−x)Ba(Co1/3Nb2/3)O3–

[4] J-Nan Lin, Chih-Ta Chia, Hsiang-Lin Liu et al. (2002) Dielectric Properties of xBa(Mg1/3Ta2/3)O3-(1-x)Ba(Mg1/3Nb2/3)O3 Complex Perovskite Ceramics. Jpn. J. Appl.

[5] Cheol-Woo Ahn, Sahn Hahm, Seok-Jin Yoou et al. (2003) Microstructure and Microwave Dielectric Properties of (1−*x*)Ba(Co13Nb23)O3–*x*Ba(Zn13Nb23)O3 Ceramics

[6] Nenesheva E. A., Mudroliuba L. P., and Kartenko N. F. (2003) Microwave dielectric properties of ceramics based on CaTiO3–LnMO3 system (Ln=La, Nd; M=Al, Ga). J. Eur.

[7] Moon J. H., Jung H. M., Park H. S., Shin J. Y., and Kim H. S. (1999) Sintering behaviour and microwave dielectric properties of (Ca,La)(Ti,Al)O3 ceramics. Jpn. J. Appl. Phys. 38:

[8] Belous A.G., Butko V.I., Novitskaya G.N. et al. (1985) Dielectric spectra of the

[9] Belous A.G., Butko V.I., Polyanetskaya S.V. (1984) Electrical parameters of the solid

[10] Belous A.G (1998) Physicochemical aspect of the development of new functional materials based on heterosubstituted titanates of rare-earth elements with the

[11] Butko V.I., Belous A.G., Yevtushenko N.P. (1986) Vibration spectra of the perovskites

[12] Knyazev A.S., Poplasvko Ye.M., Zakharov V.P., Alekseev V.V. (1973) Soft mode in the

[13] Ohsato H., Nishigaki S., Okuda T. Superlattice and Dielectric Properties of BaO-R2O3- TiO2 (R=La, Nd and Sm) Microwave Dielectric Compounds //Jpn. J. Appl. Phys. -1992. -

of microwave dielectrics. Dielektriki I Poluprovodniki. 25: 3-15.

xBa(Zn1/3Nb2/3)O3 ceramics J. Eur. Ceram. Soc. 23: 2473-2474.

perovskites La2/3-XM3XTiO3 Fizika Tv. Tela. 27: 2013-2016.

solutions of rare-earth titanates Ukr. Khim. Zhurn. 50: 1139-1142.

perovskite structure. Teoret. I Eksperim. Khimiya. 34: 301-318.

vibration spectrum of CaTiO3 Fiz. Tverd.Tela. 15: 3006-3010.

La2/3-xM3xTiO3 Fizika Tv. Tela. 28: 1181-1183.

and properties are an important scientific-technical trend in solid-state chemistry.

**Author details**

**15. References**

Phys. 41: 6952-6956.

Jpn. J. Appl. Phys. 42: 6964-6968.

Ceram. Soc. 23: 2443–2448.

6821–6827.

31. –P. 3136-3140.

A.G. Belous

Depending on the frequency range of modern communication systems, MW dielectrics with different properties are needed. In the decimeter wave band, high permittivity values (ε ≥ 100) are required along with the high thermostability of electrophysical properties and high Q, which enables effective solution of microminiaturization problems. At the present time, solid solutions based on barium-lanthanide titanates (Ba6-xLn8+2x/3Ti18O54 (Ln = La-Gd)), which have a potassium-tungsten bronze structure and ε ≈ 80-100, meet best these requirements. However, the nature of the thermostability of the electrophysical properties of these solid solutions has not been elucidated definitively; there are only qualitative explanations, which greatly restrains the search for new promising MW dielectrics with high permittivity (ε ≥ 100). The presence of spontaneous polarization in dielectrics causes, along with increase in ε, a considerable increase in dielectric loss (the Q value decreases), which impairs greatly the technical characteristics of communication system elements based on them. Therefore, the acquirement of fundamental knowledge, which is required for obtaining thermostable high-Q materials with ε ≥ 150-200, is the most important problem in developing modern decimeter wave band communication systems.

In the centimeter and millimeter wave bands, where the electromagnetic wavelength is much smaller as compared with the decimeter wave band, thermostable MW dielectrics with extremely high Q values are required. In this case, permittivity values may be relatively low (ε = 15-30). To date, tantalum-containing perovskites possess the highest Q values. However, the difficulty of their preparation and the high price call for search for new promising compounds, and it is going on in several directions. In particular, research is now under way to develop niobium-containing perovskites and to create multiphase systems, in which volume temperature compensation effect is realized. It is these directions that will probably be major directions in the next few years in developing high-Q centimeter and millimeter wave band MW dielectrics, though the search for new promising compounds will always be vital. Quite a number of problems pertaining to solid-state physics and chemistry will have to be solved. For instance, it is necessary to investigate the nature of extrinsic loss, which is coupled with various structural defects, as well as with the presence of grain boundaries, ordering of crystal sublattices and domain nanostructure. Research aimed at developing thermostable dielectrics, which will be used as millimeter wave band dielectric resonators using whispering gallery modes, will be of special scientific and practical interest. This requires considerable increase of the chemical and structural homogeneity of dielectrics.

An important problem is the creation of retunable resonant elements. To this end, multilayer bulk and film materials, which will contain a thermostable dielectric phase and a nonlinear magnetic or electrical phase at the same time, will probably have to be developed.

Thus, the synthesis of novel high-Q MW dielectrics and the investigation of their structure and properties are an important scientific-technical trend in solid-state chemistry.


**2. Human exposure routes to nanomaterials**

Nanomaterials or nano-sized particles can enter the body through various routes such as skin, olfactory tracts, weak or damaged skin, intestinal tracts, respiratory tract, and intravenous or intramuscular routes. Their entry can have adverse biological effects such as tumors, cardiac diseases, skin problems, allergic reactions, and respiratory diseases. As a result of human industrial activities, dust storms or volcanic eruptions, humans get exposed to nanoparticles continuously and their toxicity depends on the chemical composition of the nanoparticles. Based on the composition, nanoparticles are divided into inorganic, metallic and metal oxide, where their biological effects and toxicity level are explained.  Skin appendages and stratum corneum are the major routes of entry through the skin. The root of the hair or follicles gives space for nanoparticles to accumulate; during the follicle opening, they enter into deep layers of skin. Intercellular spaces along the lipid layers are the easiest route for the nanoparticles to penetrate the skin. The classical diffusion theory can understand the diffusion of aggregated particles through stratum corneum. Even though the stratum corneum is porous and allows facile entry of nanoparticles, the dose and exposure time affects the entry. Follicular penetration varies at different sites on the body. It is observed that the follicle morphology on the lateral forehead is the area of maximum penetration as it has maximum surface coverage. Follicle area is considered the best site for particle storage as it is not exposed to washing or fabric contact. This area is considered suitable for drug release and a shortcut to the systemic circulation [5, 6].

Polymeric nanoparticles or drug carriers cannot penetrate the skin without mechanical stress. Several studies have been conducted to study the drug release from polymeric particles through the skin. It has been found that the particles did not penetrate the skin without any mechanical stress. Studies on hairless animals showed that the drug could not penetrate and thus proved that hair follicles pave the way for entry. Most topical applicants or cosmetics include zinc oxide (ZnO) or titanium dioxide (TiO2) nanoparticles, which are mostly studied for skin penetration. It is shown that the size of the particles and exposure time effect the penetration. Titanium dioxide nanoparticles (TiO2 NP) of size 20 nm showed their presence in the first 3–5 layers of corneocytes. Very small sized TiO2 NP 4 nm size showed presence in the deep epidermis layer of pig's ear after 30 days of exposure. ZnO nanomaterials of size 30–40 nm could not penetrate deep into epidermis layer. Liquid type liposomes can penetrate epidermis layer, whereas gel type cannot. Metallic nanoparticles show

*Toxicity Evaluation and Biocompatibility of Nanostructured Biomaterials DOI: http://dx.doi.org/10.5772/intechopen.109078*

higher penetration rates. Another important aspect is the physical state of the skin. The damaged skin easily allows the nanoparticles whereas intact skin only paves the way for tiny nanoparticles below 10 nm to penetrate the epidermis layer [7, 8].

The shape of the nanoparticles also affects toxicity. Differently shaped silver nanoparticles penetrated differently into the various layers of skin. Tak et al. [9] showed that the intercellular penetration pathway plays a central role in the shapedependent penetration of AgNPs through the lipid matrix between corneocytes. The possible skin penetration pathways are shown in **Figure 1**.

The rate and depth of penetration of nanoparticles affect the toxicity level. Metallic nanoparticles can enter systemic circulation easily and thus can add to the toxicity depending on their dose. Thus, safety evaluation must be done before using nanoparticles in cosmetic formulations and drug delivery. Rapid penetrating nanoparticles pose more toxicity than slow penetrating ones as the latter can have efficient drug delivery and will be attacked by the immunological system of the body. In contrast, rapid penetrating NP can circumvent the macrophages and cause systemic toxicity. Argyria is a diseased condition due to the toxicity of silver nanoparticles leading to permanent pigmentation of eyes and skin [9].

#### **2.2 Inhalation as the entry route**

Airborne nanoparticles enter the lungs and cause respiratory disease by accumulating in the alveolar cells. They not only affect the lungs but also affect the

#### **Figure 1.**

*The schematic diagram of possible skin penetration pathways of three differently shaped AgNPs. (A) Two main possible skin penetration pathways are illustrated: (i) enters via hair follicles (the follicular penetration pathway); and (ii) diffuses through the gaps between corneocytes (the intercellular penetration pathway). Reproduced with Creative Commons Attribution 4.0 International License (CC BY. 4.0) from Ref. [9].*

extrapulmonary organs like the heart and liver. Metallic oxide and hydroxide NP cause pulmonary inflammation. The nanoparticles enter through olfactory tubes, pass the pharynx, and reach the alveoli. They have a good retention time, and the diameter of the particles affects the toxicity level. Some NP travel through the alveolar epithelium and capillary endothelial cells and reach the cardiovascular system and other internal organs [10]. Chronic obstructive pulmonary disease (COPD) is one of the major cause of death in the world as suggested by World Health Organization (WHO). Sarcoidosis and pulmonary fibrosis are other respiratory diseases caused by airborne pollutants. Wildfire, dust winds and volcanoes are sources of natural nanoparticles whereas engineered nanoparticles are found in gasoline exhausts, cosmetics and drug delivery carriers. These nanoparticles cause direct injury to lung tissues and cause inflammation. These nanoparticles then move to systemic circulation from the alveolar airspaces and thus cause toxicity to other internal organs. The high surface area of nanoparticles help them interact with enzymes or proteins of the immune system and thus causes inflammation and subsequent injury to the tissues, thus being detrimental to tissues [11].

The level of injury caused by nanoparticles is different in different regions of the lungs based on the clearance mechanism and cell types. In lung alveoli, there is only a single layer of cells; in bronchi and bronchioles, there is a layer of mucus for protection. Thus the nanoparticles which reach the alveoli can easily diffuse into blood capillaries and enter the systemic circulation, causing toxicity. Alveolar epithelial cells (AEC) are critical in protecting the respiratory tract and AEC in alveoli gets easily damaged by NP. AEC I gets damaged easily by NP and to replace it to maintain the alveolar structure, AEC II undergoes hyperplastic proliferation and repeated exposure to NP results in its aggregation in systemic circulation and thus leads to cardiovascular diseases. As cited above, the shape of nanoparticles determines the level of toxicity.

#### **Figure 2.**

*Systemic and pulmonary administrations of nanoparticles to target respiratory cell types. Reproduced with Creative Commons Attribution 4.0 International License from Ref. [13].*

*Toxicity Evaluation and Biocompatibility of Nanostructured Biomaterials DOI: http://dx.doi.org/10.5772/intechopen.109078*

Needle-like and rod-shaped NP cause more cellular destruction than spherical and flake-like structures. Other crucial factors to be considered are NP's degradation, solubility and chemical composition. The more they persist in the system, the more toxic they are to the cells. Metal NP like gold and silver persist in lungs for more than 7 days. This causes toxicity to all organs by creating oxidative stress, thus leading to cellular toxicity [12, 13] (**Figure 2**).

#### **2.3 Nanoparticle ingestion**

Metallic NP, carbon-based NP, ceramic NP, polymeric NP or dendrimers are the classes of nanoparticles that enter the gastrointestinal tract through ingestion. Implant materials have become very common, and orthopedic and dental implants use nanoparticle coatings to enhance their performance and bioactivity. However, intentionally or unintentionally, these implants release ions and NP over time, which cause adverse effects in the intestine and its related organs. The gastrointestinal tract (GIT) has a huge surface area of approximately 200 m2 , which is very much amenable to NP interaction. NP are absorbed by the GIT and thus enter the systemic circulation. Nanoparticles also damage the microbiome of the gut and thus affects digestion [14].

Targeted drug delivery through nanocarriers has been used in treating skeletal infections. But in many cases, these engineered nanomaterials create cytotoxicity. In order to achieve native bone tissue structure and more biocompatibility, nanomaterials have been used in orthopedic implants. Dental implants use a wide range of engineered materials, including nanomaterials. Titanium is used as dental implants, which can release titanium NP due to many activities like wear and tear caused by chewing or bacterial activity and chemical or physical deterioration. Titanium oxide nanoparticles from dental implants can dissolve in saliva reaching the intestine and other organs like the liver, spleen, kidney, and heart. Risk assessment of the engineered nanomaterials should be very focused on criteria like physicochemical characterization and thorough biological evaluation as per the regulatory agencies' guidelines [15]. Most implant failures occur due to wear and the release of particles which cause a chronic inflammatory response. A cobalt-chromium hip implant faced rejection due to the release of cobalt and chromium nanoparticles triggering an inflammatory response. A study conducted by Posada, 2015 showed the involvement of lymphocytes in such implant allergies, and within 48 hours of treatment, the metal nanoparticles caused apoptosis in the cells [16].

The most common nanoparticles that enter GIT are silver, iron oxide, titanium dioxide, zinc oxide etc. Organic NP, liposomes, engineered protein NP etc. pose little concern about their toxicity as many of them have been used by humans for centuries. Not many studies have been done in this area of nanotoxicology, and very little information is known about the toxicity of such nanoparticles. But the most important fact to be noted is that the properties of each type of nanoparticle differs on many factors and that these factors determine their toxicity. Dimension, morphology, composition, surface charge, aggregation state affects the fate of the nanoparticles in vivo. Most of the nanoparticles, after passing through various parts of the GIT change their properties due to interaction between the proteins and varying pH conditions. Thus, their fate is altered when compared with that in vitro. The properties of pristine nanoparticles will be very much different from the nanoparticles in vivo and thus, the studies related to their toxicity should be taken into consideration only for in vivo results. Most of the studies which show cytotoxicity in cell lines do not show any toxic effects when performed in animal models unless it is at a very high dose. Thus the in vivo studies should be concentrated more on the physiological aspects of the cells rather than on the organs as a whole [17, 18].


*2.4.2 Clinical presentation*

Worsening jaundice unamenable to phototherapy during the first 2 weeks of life, subsequently demonstrating unrelenting direct hyperbilirubinemia are characteristic. Laboratory values are consistent with biliary obstruction and demonstrate direct hyperbilirubinemia and elevated alkaline phosphatase. Signs of cholestasis, dark urine and light or gray colored stools are present.


*2.4. Statistical Analyses*

To test for significant di fferences between the UV and PAR treatments against the control in exp 1–3 at a 95% significance level, we applied a nonparametric one-way ANOVA on Ranks (Kruskal-Wallis test) with Dunn's post hoc test. All analyses were conducted with the program SigmaPlot version 12.5. Data of the same experiment and ciliate were pooled.


**2.2 The use of monofilament mesothreads for the treatment of synkinesis**

Patients, suffering from the lesion of the facial nerve, develop the synkinesis and contractures on the affected side of the face in 4–6 months amid already existing weakness of muscles of facial expression. Synkinesis is involuntary movements of the facial muscles of one muscle group in response to voluntary movements of another muscle group of the face [12, 13, 15]. Currently, there are three hypotheses for the occurrence of synkinesis. The theory that has received the greatest recognition is that

**Figure 12.** *Bell's palsy. Patient B. before injections.*

**Figure 13.** *Patient B, 1 month after injection.*

after damage, axons undergo aberrant regeneration forming the innervation of those muscles they had not previously been innervated. The second potential pathological mechanism involves ephaptic signaling, in which neighboring axons in the affected area stimulate each other, probably as a result of loss of myelin sheath. Finally, some studies indicate the possibility of a central mechanism of synkinesis origin as a result of overexcitation of the motor nucleus of the facial nerve [14, 15].

In clinical practice, the most common cases of synkinesis are oculo-oral (movement of the zygomaticus major and minor muscles, the orbicularis oris muscle while *Comprehensive Rehabilitation of Patients with Facial Expression Asymmetry and Synkinesis… DOI: http://dx.doi.org/10.5772/intechopen.106694*

**Figure 14.** *Bell's palsy. Patient B. before injections.*

**Figure 15.** *Patient B, 1 month after injection.*

the arbitrary closure of the palpebral fissure) and oral-ocular (narrowing of the palpebral fissure during mouth movement). To diagnose oculo-oral synkinesis, we use the "frequent blinking" test, when the patient is asked to blink frequently. In this case, there is a contraction of the zygomatic, buccal and perioral muscles observed. To diagnose oral-ocular synkinesis, the "u-e" or "b-p" test is used, which allows to trace the narrowing of the palpebral fissure on the side of the lesion, which manifests in the patient "winking" during a conversation.

**Figure 16.** *Bell's palsy. Patient А. before injections.*

**Figure 17.** *Patient А., 1 month after injection.*

Due to the fact that synkinesis is usually manifested by interchanging hyper- and hypokinesis zones, the applied methods of treatment should be aimed both at suppressing excessive muscle activity, depending on the area of the face, and at restoring mobility. Such physiotherapy methods as physiotherapy exercises, massage, electrical stimulations are very arduous and often do not bring the desired results, because they do not influence the pathological "chain of synkinesis," which is defined by the sequence of involvement of involuntary muscle contractions on the affected side in response to voluntary movement [12, 15]. Botulinum toxin type A is used to selectively suppress the

*Comprehensive Rehabilitation of Patients with Facial Expression Asymmetry and Synkinesis… DOI: http://dx.doi.org/10.5772/intechopen.106694*

**Figure 18.** *Bell's palsy. Patient А. before injections.*

**Figure 19.** *Patient А., 1 month after injection.*

activity of muscle fibers and is effectively used to correct synkinesis [11, 14]. However, after botulinum toxin therapy, temporary weakness of the facial muscles on the affected side may develop, which aggravates the asymmetry and causes frustration (anxiety) in patients. They start feeling as if the symptoms of the disease have reappeared, which makes many of them to refuse subsequent injections. Additionally, the effect of injections is short term (2–3 months). There are also known methods of surgical correction of synkinesis [12, 16], but they require the excision of areas of synkinesis and hospitalization in a surgical department. This can lead to persistent weakness of facial muscles and the formation of muscle contractures [11, 14].

**Figure 20.** *Bell's palsy. Patient А. before injections.*

**Figure 21.** *Patient А., 1 month after injection.*

We observed two groups of patients with Bell's palsy. All patients had oculo-oral and oral-ocular synkinesis, which developed within a year after the disease. The first group of patients received injections of botulinum toxin type A in the areas of synkinesis, while the second group of patients underwent implantation of monofilament mesothreads. The severity of pathological synkinesis was assessed using the Synkinesis Assessment Questionaire (SAQ, 2007).

*Comprehensive Rehabilitation of Patients with Facial Expression Asymmetry and Synkinesis… DOI: http://dx.doi.org/10.5772/intechopen.106694*

**Figure 22.** *Bell's palsy. Patient А. before injections.*

**Figure 23.** *Patient А., 1 month after injection.*


**1. Introduction**

Any biological products and services collected mainly from forests and other associated tree-based land use systems are known as non-timber forest products (NTFPs) [1–4]. Most of the rural and indigenous communities residing in and around forests rely for their livelihood on NTFPs socioeconomically and culturally [2, 3, 5–14]. Non-timber forest products (NTFPs) along with the tradition of plantsbased knowledge is distributed among the vast number of indigenous and rural communities [15, 16]. NTFPs provide natural insurance against hunger and malnutrition during scarcity and even during famines [5]. NTFPs are thus vital for the social development of the indigenous/forest fringe and rural communities [17]. In spite of the "right of ownership, i.e., access to collect, use and dispose of minor forest produce by the 'Forest Rights Act, 2006'" to the indigenous communities dependent on forest or forest dwellers, they still remain underprivileged and impoverished [18]. Having potential to address poverty, sustainable development, and tropical forest conservation without competing with agricultural activity, NTFPs is now receiving more academic and policy attention [2, 3, 19, 20].

The dependency of the indigenous forest and rural people on NTFP continues today because of their poor economic conditions and non-empowerment toward socioeconomic development [21] through its use in food, medicine, fiber, fuelwood and sale [2–4]. Plant and animal resources and their value as NTFPs are rich among the ethno-cultural groups [22, 23], but potentialities of many of these resources and valuable plants are yet to be explored [2, 3]. Unfortunately, till now, there are no serious efforts either to document the NTFP resources or to analyze their utilization and socioeconomic aspects [5]. Additionally, due to deforestation, modernization, unsustainable development, and ignorance of younger generation toward NTFPs, the traditional knowledge associated with them and their utilization is gradually eroding through acculturation and the loss of plant biodiversity [24–26]. Awareness, research, and education are needed to protect this diminishing knowledge of NTFPs and conserve bioresources for the benefit of our future generations [27].

Dependence on NTFP collection and utilization is still a crucial livelihood strategy for forest dwellers in the Terai foothills of eastern Himalayas in West Bengal [11, 24, 28–31]. Unfortunately, now the traditional knowledge associated with NTFPs in these regions is found mostly confined to the older generation of these communities, which is consequently in the verge of extinction [24]. Hence, identifying and documenting the diversity of NTFP resources with their utilization is important to conserve and manage these resources sustainably while also being helpful for restoration and preservation of their associated traditional knowledge [25, 26, 32–34]. More importantly, promoting the NTFPs-based activities has now become a crucial policy action of any developmental strategy for uplifting and empowering the rural and indigenous communities [35]. Such documentation will provide baseline data and information for conservation and sustainable utilization of the NTFP resources. Additionally, these documentations will be a proper testimony from specialists, which will also popularize the NTFPs to be introduced into the present-day farming systems and also get acceptance for utilization by the urban population [25, 26, 35, 36]. Therefore, the present study was conducted in the forest fringe villages in the Terai region of West Bengal with the following objectives:

*Non-Timber Forest Products: Diversity, Utilization, and Dependency in Fringe Areas… DOI: http://dx.doi.org/10.5772/intechopen.113271*


**3. Principles of ethics**

The important three core ethical principles are discussed in all documents. These are as below (**Figure 1**):

c.**Justice**: It is an obligation to provide all participants with whatever they are deserve. Basically, we have an obligation to treat all people equally, fairly, and impartially. All individuals should have an opportunity to participate in research unless contraindicated and we must not impose unfair burdens. All doubts of research participants should be cleared by concerned staff. We should make available all the safety concerns as demanded by research participants.


**1. Introduction**

Virgin olive oil has a fundamental role in the markets of alimentary oils because of its unique aroma, its stability and its healthy benefits. In this chapter the attention will be focused on Tunisian and Italian single cultivar olive oils.

The oils under investigation were produced by different extraction systems and characterised for their volatile and non-volatile compounds (Benincasa et al., 2003; Cerretani et al., 2005; Garcia et al., 1996). It is well known that volatile and non-volatile components of products of plant origin are dependent on genetic, agronomic and environmental factors. There are few reports (Angerosa et al., 1996, 1998a, 1998b, 1999; Morales et al., 1995; Solinas et al., 1998) on the evaluation of the relationships between the aroma components of virgin olive oil with the metabolic pathways and varietal factors. Olive ripening process and, to some extent, the fruit growing environment, affect also the composition of the volatile compounds of the oil (Aparicio & Morales, 1998; De Nino et al., 2000; Guth & Grosh, 1993; Montedoro & Garofalo, 1984; Morales et al., 1996). Volatile and non-volatile compounds are retained by virgin olive oils during their mechanical extraction process from olive fruits (*Olea europaea* L.). Non-volatile compounds such as phenolic compounds stimulate the tasting receptors such as the bitterness perception, the pungency, astringency and metallic attributes. Instead volatile compounds, stimulating the olfactive receptors, are responsible for the whole aroma of the virgin olive oil. The chromatograms of volatile compounds of olive oils were obtained by solid phase micro extraction-gas chromatography/mass spectrometry (SPME-GC/MS) (Hatanaka, 1993; Kataoka et al., 2000; Steffen & Pawliszyn, 1996). The method is based on the assay of the terminal species of the "lipoxygenase pathway" which are present in the volatile fraction of the sampled compounds (Hatanaka, 1993).

Volatile and Non-Volatile Compounds of Single Cultivar Virgin Olive Oils Produced

conducted as described in the following paragraphs.

results were given as mg of caffeic acid per Kg of oil.

**2.2.3 Free fatty acids, peroxides, ultra-violet light absorption**

assessment of virgin olive oil referenced COI/T.20/Doc. No 15/Rev. 2.

2568 91 of the European Union Commission (EEC, 1991).

**<IP_ADDRESS> Preparation of samples and standard solutions**

standard (ethyl isobutyrate) was prepared.

**2.2.1 Fatty acid methyl ester analysis (FAMEs)**

reference compounds.

**2.2.2 Total phenols analysis**

**2.2.4 Sensory analysis**

**2.2.5 SPME-GC/MS analysis**

in Italy and Tunisia with Regard to Different Extraction Systems and Storage Conditions 5

In particular, analysis of fatty acid methyl esters, total phenols, free acidity, peroxide number, conjugated dienes and trienes, sensory analysis and volatile compounds were

FAMEs analysis were carried out after performing alkaline treatment obtained by dissolving the oil (0.05 g) in n-hexane (1 mL) and adding a solution of potassium hydroxide (1 mL; 2 N) in methanol (Christie, 1998). FAMEs were analyzed by gas chromatography by mean of a Shimadzu 17A chromatograph equipped with detector flame ionization and a capillary column. Peaks were identified by comparing their retention times with those of authentic

The fatty acid composition was expressed as relative percentages of each fatty acid

Total phenols content was determined according to the method developed by Gutfinger (1981). Briefly, an amount of olive oil (2.5 g) was dissolved with hexane (5 mL) and extracted with a solution of methanol and water (5 mL; 60/40). The mixture was then vigorously agitated for 2 minutes. Folin-Ciocalteu reagent (0.5 mL) and bi-distilled water (4.8 mL) were added to the phenolic fraction. The absorbance of the mixture was measured at 725 nm and

Acidity value, peroxide value (PV) and ultra-violet light absorption, conjugated diene (K232) and conjugated trienes (K270), were determined according to the Regulation EEC

Olive oils were evaluated by a panel according to the official method for the Organoleptic

Aroma components of products of plant origin are dependent on genetic, agronomic and environmental factors (Benincasa et al., 2003). The complexity of the mass-chromatograms in terms of number of components might represent a drawback when different samples are to be matched. Therefore, in order to consider the minimum set of components that mostly reflect the biogenesis of an oil (Aparicio & Morales, 1998), hexanal (1), 1-hexanol (2), (E)-2 hexenal (3), (E)-2-hexen-1-ol (4) and (Z)-3-hexenyl acetate (5) were chosen as markers of

A solution (200 mg/Kg) was prepared by dissolving 0.04 g of each analytes (see paragraph 2.2.5) in 200 g of commercial seeds oil. In the same manner a solution containing the internal

linoleic and linolenic acids specific lipoxygenase oxidation [(path A and B ), Fig. 1].

calculated considering the internal normalization of the chromatographic peak area.


**Treatment Strategies for Eating Disorders in Collegiate Athletics**

Kendra Ogletree-Cusaac and Toni M. Torres-McGehee *University of South Carolina, Columbia, SC United States*

## **1. Introduction**

36 New Insights into the Prevention and Treatment of Bulimia Nervosa

blood sugar levels. This may disrupt the appetite control mechanisms and the utilisation and deposition of energy. Serotonin is implicated in appetite regulation (there may be a particular role in carbohydrate balance); disruptions in serotonin levels may be affected by the impact of insulin on its precursor, tryptophan, and in turn acute tryptophan depletion may lead to an increase in calorie intake and irritability in bulimia nervosa and may be related to decreased mood, increased rating in body image concern and subjective loss of control of eating in people who have recovered from bulimia nervosa (National

Bulimia nervosa is a common health problem in young people, has been reported worldwide both in developed regions and emerging economies, and its prevalence is arising. It can lead to serious medical complications. However, studies from the US and continental Europe suggest that only a fraction of people with bulimia receive specialised treatment for their eating disorder. The alimentary canal is the front line for the eating disorder patient. Therefore, the expression of the disease in the gastrointestinal tract may have a critical role in early diagnosis and management of the disease. New treatment strategies are now available, and evidence-based management of this disorder is possible. A specific form of cognitive behaviour therapy is the most effective treatment, although few

American Psychiatric Association. (1994). *Diagnostic and statistical manual of mental disorders*

Anderson L, Shaw JM, McCargar L. (1997). Physiological effects of bulimia nervosa on the

World Health Orgaganization. (1992). *International statistical classification of diseases and related health problems (ICD-10)*. ISBN 92-4-1546492, Geneva, Switzerland. Treasure J, Claudino AM, Zucker N. (2010). Eating disorders. *Lancet*, Vol.375, (February

Fairburn CG, Harrison PJ. (2003). Eating disorders. *Lancet,* Vol.361, (February 2003), pp. 407-

National Collaborating Centre for Mental Health. (2004) National Clinical Practice

Guideline: eating disorders: core interventions in the treatment and management of anorexia nervosa, bulimia nervosa, and related eating disorders. National Institute

gastrointestinal tract. *Can J Gastroenterol*, Vol.11, No.5, (July-August 1997), pp. 451-

*(4th edn)*, ISBN 0-89042-062-9, Washington, USA.

for Clinical Excellence. Available from 27.10.2009 at http://www.nice.org.uk/search/guidancesearchresults.

Collaborating Centre for Mental Health, 2004).

patients seem to receive it in practice.

9, ISSN 0835-7900.

16, ISSN 0140-6736.

2010), pp. 583-93, ISSN 0140-6736.

**7. Conclusions**

**8. References**

Eating disorders such as Anorexia Nervosa, Bulimia Nervosa, not otherwise specified eating disorders, and binge eating disorder are on the rise in collegiate athletes and aesthetic dancers (Greenleaf, Petrie, Carter, & Reel, 2009; Johnson, Powers, & Dick, 1999; Torres-McGehee et al., 2009; Torres-McGehee, Monsma, Gay, Minton, & Mady, In Press). Due to the nature of specific sports and pressures of sport participation, eating disorder symptoms and etiology in athletes are slightly different than their non-athletic counterparts. Therefore, it is critical that treatment for eating disorders is unique to athletes. Preferably, the treatment of the athlete should be multi-dimensional (e.g., psychosocial interventions, nutritional management, and pharmacological interventions when necessary).

Treatment of Anorexia Nervosa in the early 1900s was considered a biologically based disease resulting from hormonal insufficiencies; therefore, treatment focused on correcting hormonal imbalances such as pituitary extract, insulin, estrogen, thyroid extract, and corticosteroids (Brumberg, 1998; Parry-Jones, 1985). Incorporation of psychotherapy was integrated as part of treatment in the 1930s. Bulimia on the other hand was not defined as a specific eating disorder until the late 1970s (Russel, 1979); and treatment then was primarily centered around eliminating patient's hungry appetites by imposing strict diets and prescribing medicines that were supposed to warm the stomach creating a sensation of being full. Additionally, individuals who have clinical eating disorders, like Bulimia, characteristically have low mood and higher-than-average levels of depressive symptoms, and are at greater risk of clinical depression (Fairburn et al., 1999; Fisher et al., 1995; Palmer, 1998; Muscat & Long, 2008). It was theorized by Koenig and Wasserman (1995) that the high rates of co-morbidity found between eating disorders and depression may, in part, be caused by common features such as negative self-evaluation and general dissatisfaction with one's physical appearance (Muscat & Long, 2008). It is plausible that precursors to binge-eating which is the disordered eating behavior that can lead to Bulimia appear to be depression symptoms and low self-esteem. Therefore, psychologists integrate strategies to alleviate depressed mood that is often plagued with Bulimia Nervosa (Gleaves., 2000).

Current treatments focus on both the underlying psychopathologies and the obvious behaviors using protocols including: individual, family, and group psychotherapy; nutritional counseling; medications; exercise therapy, and experiential therapies (e.g., art, music, movement). This chapter will examine current treatment and prognosis strategies for comorbid conditions among collegiate athletes. The goal of this chapter is to provide

Treatment Strategies for Eating Disorders in Collegiate Athletics 39

sociological and psychological issues related to disordered eating in the general population, athletes experience issues such as evaluation criteria, sport-specific weight restrictions, peer comparison, peer and coach pressure, and athletic performance demands (Moore et al., 2007). Also due to sport pressures, athletes are probably less likely to personally seek treatment for Bulimia Nervosa. If athletes are slow to seek treatment, that extends the

The collegiate student athlete experiences life transitional issues similar to other college students, such as independence, responsibility, coping strategies, and building new relationships. In addition to these experiences, collegiate student athletes have transitional issues related to their sport, such as adjusting to a new team structure (i.e., coaches, teammates, trainers, etc.), balancing sport and academics, and the pressures of being a student-athlete (i.e., peers, expectations, media). The practitioner needs to be thoroughly knowledgeable about the complexities of eating disorders in athletes, for example, knowing the physical warning signs, general psychosocial functioning, emotion regulation, parental and coaching pressures, weight restrictions for competition, perceptions about body size and shape, perceived environmental control, self-worth, and any other factors that may place an athlete at risk for developing an eating disorder (Moore et al., 2007). Thus, interventions developed for athletes need to address general and sport-specific factors regarding the presence of Bulimia and disordered eating behaviors (Smith & Petrie, 2008).

The cognitive-behavioral theory for treatment of eating disorders such as Bulimia Nervosa, stresses that central to the maintenance of Bulimia is clients' dysfunctional scheme for selfevaluation. This self-evaluation is largely or even exclusively, in terms of their shape and weight and their ability to control them (Fairburn & Cooper, 2010). Cognitive behavioral theory can also be used to identify dysfunctional thought patterns (e.g., "I am a bad person") that trigger eating disordered behaviors (Stien et al., 2001), and reestablishing those thought patterns to reduce behaviors. This dysfunction is observed throughout all facets of their life, including dietary intake and restraint, perceived body image, and methods related to weight control. If the dysfunctional scheme is central to the maintenance of bulimic symptoms and is considered the core psychopathology, this criterion is especially problematic when working with collegiate student athletes. Collegiate student athletes with Bulimia Nervosa or disordered eating symptoms potentially experience the dysfunctional scheme for self-evaluation significantly differently from their nonathlete peers. They tend to internalize the pressures of their sport and physical appearance and it is not clear that their self-evaluation regarding their athletic potential as related to their physical appearance is

Another essential feature of Bulimia Nervosa is binge eating episodes. The cognitivebehavioral theory proposes that binge eating is largely a product of the clients' distinctive form of dietary restraint, which then maintains the core psychopathology by intensifying concerns about their ability to control their eating and weight (Cooper & Fairburn, 2010). Athletes are trained to pay attention to their dietary intake particularly as it relates to the interaction of their physique and athletic performance. It is inherently expected that athletes exhibit some form of dietary restraint which can inadvertently lead to the disordered eating cycle of dietary slips and binges. Purging and compensatory behaviors could be viewed as shortcuts to those slips and binges. However, they do not realize that vomiting, for example, only retrieves part of what has been eaten and that laxative misuse has little or no effect on

potential success of intervention applied for treatment.

**2.2 Cognitive behavioral theory**

always considered dysfunctional.

clinicians/professionals with a deeper understanding of current treatments strategies tailored to collegiate athletes. It should be emphasized that this approach is a team approach that integrates a multi-dimensional approach by the dietitian, physician, athletic trainer, psychologist, coach and other health professionals as needed.


*Article* **Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System**

**Ziad Tareq Naman 1 , Salim Kadhim 2 , Zahraa J. K. Al-Isawi 3 , Christopher J. Butch 4,5, \* and Ziyad Tariq Muhseen 4,6, \***

**Abstract:** Macrodomain-I of the NSP3 (non-structural protein 3) is responsible for immune response hijacking in the SARS-CoV-2 infection known as COVID-19. In the omicron variant (B.1.1.529), this domain harbors a new mutation, V1069I, which may increase the binding of ADPr and consequently the infection severity. This macrodomain-I, due to its significant role in infection, is deemed to be an important drug target. Hence, using structural bioinformatics and molecular simulation approaches, we performed a virtual screening of the traditional Chinese medicines (TCM) database for potential antiviral drugs. The screening of 57,000 compounds yielded the 10 best compounds with docking scores better than the control ADPr. Among the top ten, the best three hits—TCM42798, with a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, and TCM30675 of −12.49 kcal/mol—were chosen as the best hits. Structural dynamic features were explored including stability, compactness, flexibility, and hydrogen bonding, further demonstrating the anti-viral potential of these hits. Using the MM/GBSA approach, the total binding free energy for each complex was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and −47.64 kcal/mol, respectively, which consequently reflect the stronger binding and inhibitory potential of these compounds. These agents might suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.

**Keywords:** SARS-CoV-2; COVID-19; NSP3; TCM; MD simulations

### **1. Introduction**

Coronavirus disease-2019 (COVID-19) is defined as a disease caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1]. SARS CoV-2 rapidly spread from person to person, and serious human disease was in recent times described in the city of Wuhan, Hubei Province, China. Coronavirus causes headache, fever, and respiratory disease, e.g., cough and shortness of breathing. SARS-CoV-2 infects humans through direct binding to host cell entry proteins (spike). The six functional open reading frames (ORFs) are well-arranged in order from 5 ′ to 3 ′ replicas (ORF1a/ORF1b), membrane (M), envelope (E), spike (S), and nucleocapsid (N), whereas nonstructural protein include3-chymotrypsin-like protease, papain-like protease, and RNA-dependent RNA polymerase, is encoded by the ORF region [2,3].

**Citation:** Naman, Z.T.; Kadhim, S.; Al-Isawi, Z.J.K.; Butch, C.J.; Muhseen, Z.T. Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System. *Pharmaceuticals* **2022**, *15*, 741. https://doi.org/ 10.3390/ph15060741

Academic Editor: Osvaldo Andrade Santos-Filho

Received: 4 May 2022 Accepted: 31 May 2022 Published: 13 June 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

A SARS-CoV-2-associated global pandemic, with unceasing chaos, has now reported many variants of the virus [4]. Among the reported variants, many are particularly associated with immune response evasion, higher transmissibility, increased morbidity, and re-infection. Until now, these variants have been deemed either as variants of interest (VOIs) or variants of concern (VOCs) based on the threat they pose to public health. For instance, the alpha variant, also known as B.1.1.7, with 40–80% increased transmission, includes 69–70 del, N501Y, and P681H mutations, while beta, also called B.1.1.351, gamma, delta, and B.1.1.529 variants are classified as VOCs [5,6]. Moreover, a new version of B.1.1.7 supplemented with the E484K mutation was reported to be associated with 39 confirmed patients [7]. Moreover, B.1.351, which was reported in South Africa and harbors K417N, E484K, and N501Y variations, which were reported to increase the transmission and decrease the T cell-triggered immune response against COVID-19 infection, was recorded. In early 2021, P.1 variant was discovered in Brazil with K417T, E484K, and N501Y mutations in the RBD with transmission increased by 38% and mortality by 50% [8]. A molecular modelling study based on protein coupling deciphered the mechanism of higher infection associated with these variants of SARS-CoV-2 [9]. The binding variations were deeply discovered by demonstrating the interaction pattern and dynamic features of the complexes. In October 2020, India detected a more lethal strain of SARS-CoV-2, officially known as B.1.617.2. This variation has L452R, T478K, and P681R in the RBD, resulting in an 87 percent increase in transmissibility, an 85 percent increase in hospitalizations, and a 137 percent rise in death. Later, in India and the United Kingdom, a novel variant known as "Delta plus" was discovered with an additional mutation, K417N [10]. Similarly, a novel variant termed as Mu or B.1.621 was discovered to have spike protein alterations, some of which are shared with other VOCs. R346K, Y144T, Y145S, and insertion at position 146N are among the new mutations in this variant [11]. L452Q and F490S mutations in RBD are found in a unique VOI known as C.37 or its variant, which lowers antibody-mediated neutralization [12]. The B.1.617.1 strain with the L452R mutation in the (RBD) receptor-binding domain, on the other hand, has been attributed to decreased antibody neutralization by altering the corresponding conformational epitopes. Furthermore, the VOI Iota (lineage B.1.526) carries the mutation E484K, which confers resistance to therapeutic monoclonal antibodies and makes it more resistant to neutralization [13].

The most recent omicron strain, formally known as B.1.1.529, was discovered in November 2019 in South Africa and has 30 mutations in the spike protein including A67V, ∆69–70, T95I, G142D, ∆143–145, ∆211, L212I, ins214EPE, G339D, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, D796Y, N856K, Q954H, N969K, and L981F, among which 15 mutations lie in the RBD [14]. Other proteins also reported mutations, such as NSP3 (K38R, V1069I , ∆1265, L1266I, A1892T), NSP4 (T492I), NSP5 (P132H), NSP6 (∆105–107, A189V), and NSP12 (P323L), while I42V was reported in NSP14. Furthermore, sub-lineages, i.e., BA.1/B.1.1.529.1, BA.2/B.1.1.529.2, and BA.3/B.1.1.529.3, were reported by WHO (World Health Organization) as a threat to public health [15]. The variant is a major health concern all around the globe, and the therapeutic effectiveness of existing vaccines against it is yet unknown [16,17]. More research is needed to determine the molecular basis of pathogenicity in the omicron variant. Furthermore, new therapies against the recently emerging SARS-CoV-2 strains would require the use of advanced techniques.

The novel coronavirus-2019 genome encodes four structural proteins (S, M, E, and N), in which the S-protein gives the virus its corona-like shape, which is mainly responsible for the attachment to host cell receptors (ACE2s) or surface proteins, and 16 non-structural proteins (NSP1 to NSP16). The binding of spike protein to ACE2 (Angiotensin-Converting Enzyme 2) of the host initiates the infection in cells. The ACE2 is mainly expressed in the lungs, kidney, and small intestine, leading to serious illness [18]. During infection, the host cell protease cleaves the S-protein at the S1/S2 cleavage site. This priming (cleavage of S-protein) results in the division of protein into the S1 ectodomain at the N-terminal and the S2 membrane-anchored domain at the C-terminal. The S1 subunit recognizes the

associated cell surface receptor, while the latter assists viral entry [19]. The SARS-CoV S1 subunit of the spike protein has conserved 14 aa in the RBD, which functions to recognize ACE2 and can infect both humans and bats. Among this conserved 14 aa in SARS-CoV, eight residues are highly conserved in 2019-nCoV, supporting the assumption that ACE2 is also the receptor of this new virus [20]. Among these proteins, the main proteins, PLpro, spike, and RdRp, are deemed to be direct drug and vaccine targets, but other proteins are also essential for drug design [21]. For instance, the Mac-I of the largest protein, NSP3, has also been deemed as an attractive drug target because of its role in disrupting the innate immune reaction and increasing of virulent properties of the virus [22]. NSP3 is comprised of three macrodomains and two adjacent SUD-M-like domains that have been reported to be associated with NSP3 functional modulation. Mac-I has a significant role in viral pathogenesis and increases interferons' responses for viral neutralization [23]. Further reports have also disclosed the hijacking of the host immune response by Mac, which is carried out through interference with the IFN (Interferons) pathway and malfunctioning of STAT1 (signal transducer and activator of transcription 1) [24,25]. This hijacking of the IFN and STAT1 pathways has been reported to be possibly linked with the cytokines storm phenomena [26,27].

More research is needed to cope with this alarming pandemic situation in order to create safe and effective treatments swiftly. In this context, the macrodomain is thought to be the most druggable target for the development of COVID-19 therapy [28,29]. As a result, we used computational molecular screening to investigate the binding affinity of drugs against the macrodomain-I of the omicron (B.1.1.529) variant. The current study employs molecular docking and simulation-based methods [30–32] to identify potential anti-viral compounds from the TCM database against SARS-CoV-2. The findings provide crucial information on the antiviral effectiveness of the evaluated drugs against SARS-CoV-2. The findings will aid in the development and identification of potential medicinal solutions for the treatment of COVID-19.

#### **2. Results and Discussion**

#### *2.1. Macrodomain of Omicron (B.1.1.529) and Structural Modelling*

The continuously emerging variants of SARS-CoV-2 are a greater threat to public health [33]. These variants are associated with high infection, transmission, and re-infection. Moreover, some of the previous variants such as B.1.1.7, B.1.617, P.1, and A.30 have also been reported to escape the immune response. Recently, B.1.1.529, or the omicron variant, first identified in South Africa with the highest number of mutations ever, has been reported to be associated with higher transmissibility than other variants. All the proteins encoded by the genome of SARS-CoV-2 are responsible for essential roles in virulence and replication in different stages of infection [34–36]. Among these proteins, the largest and multidomain protein called non-structural protein 3 or NSP3 is an essential factor for efficient translational and replication processes. NSP3 has eight functional domains that also include macrodomains, which play significant roles in viral escaping when attacked by the innate immune response. Among the macrodomains, macrodomain-I (X-domain) in particular also shares high sequence and structural conservation. Mac-I binds ADPr, and the strength of binding is directly associated with the pathogenicity level [37]. For instance, binding strength reduction or the complete loss of ADPr binding has been reported to be related to less or no infection in the IBV model [38]. Any mutation in the structure is associated with functional variations induced by conformation changes in the protein structures. For instance, K38R, V1069I, L1266I, and A1892T, as well as a deletion (∆1266I) have recently been reported in the NSP3 protein of the omicron variant, as shown in Figure 1A. The Mac-I in the NSP3 starts from 1025–1194, and a single V1096I has been reported in this region, which may increase the binding of ADPr and consequently increase the pathogenesis by hijacking the innate immune response given in Figure 1A. Mac-I is also a potential therapeutic target; therefore, finding small molecule inhibitors for this domain might aid in the restoration of the host immunological innate response. For instance, a carbazole-based

drug known as GeA-69 has been previously tested to target the human macrodomain to treat various types of cancers [39]. Similarly, structure-based approaches are being used to find drugs that target viral macrodomains [40]. New powerful therapies are needed to block Mac-I involvement in SARS-CoV-2 pathogenesis. Hence, our research combines structure-based drug discovery with molecular modelling to find new compounds that effectively target the Mac-I and salvage the innate response. The wild-type structure was used to construct a V1069I mutant of the Mac-I from the omicron variant (Figure 1B). The modelled V1069I-Mac-I, as shown in Figure 1C, demonstrated an RMSD (root mean square deviation) difference of 0.132 Å. The minimal RMSD difference demonstrated the accurate folding and distribution of secondary structural elements. stance, a carbazole-based drug known as GeA-69 has been previously tested to target the human macrodomain to treat various types of cancers [39]. Similarly, structure-based approaches are being used to find drugs that target viral macrodomains [40]. New powerful therapies are needed to block Mac-I involvement in SARS-CoV-2 pathogenesis. Hence, our research combines structure-based drug discovery with molecular modelling to find new compounds that effectively target the Mac-I and salvage the innate response. The wild-type structure was used to construct a V1069I mutant of the Mac-I from the omicron variant (Figure 1B). The modelled V1069I-Mac-I, as shown in Figure 1C, demonstrated an RMSD (root mean square deviation) difference of 0.132 Å. The minimal RMSD difference demonstrated the accurate folding and distribution of secondary structural elements.

*Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 4 of 15

reported in this region, which may increase the binding of ADPr and consequently increase the pathogenesis by hijacking the innate immune response given in Figure 1A. Mac-I is also a potential therapeutic target; therefore, finding small molecule inhibitors for this domain might aid in the restoration of the host immunological innate response. For in-

**Figure 1.** (**A**) NSP3 and reported mutations in the omicron variant. (**B**) Surface representation of Mac-I in complex with ADPr. (**C**) Superimposed wild type a V1069I mutation in Mac-I. **Figure 1.** (**A**) NSP3 and reported mutations in the omicron variant. (**B**) Surface representation of Mac-I in complex with ADPr. (**C**) Superimposed wild type a V1069I mutation in Mac-I.

#### *2.2. Virtual Screening and Re-Docking of TCM 2.2. Virtual Screening and Re-Docking of TCM*

Using EasyVS, an online web tool, the entire TCM database was screened against the Mac-I of the omicron variant. Prior to screening, the RO5 filter was applied, which reported 20,124 drugs that violated Lipinski's rule of five. Among the total of 57,000 compounds, 36,876 compounds were screened against the binding site of ADPr. Among these, 14,255 compounds reported a docking score less than −4.0 kcal/mol, and 16,453 compounds reported a docking score less than −8.0 kcal/mol. Among the remaining compounds, 5221 compounds reported a docking score of less than −9.0 kcal/mol. Among the remaining 947 compounds, only 356 were reported to have docking scores greater than −9.5 kcal/mol. Compounds with docking scores greater than −9.50 kcal/mol were considered as the threshold, because for ADPr the docking score was previously reported to be −9.46 kcal/mol. The top scoring 50 compounds were selected for re-docking using Auto-Dock Vina. Among these 50 compounds, 10 compounds reported the best docking score and are given in Table 1. Among the top 10 compounds, TCM42798 had a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, TCM30675 of −12.49 kcal/mol, TCM27763 of −11.93 kcal/mol, TCM33425 of −11.72 kcal/mol, TCM28788 of −11.46 kcal/mol, TCM42159 of −11.45 kcal/mol, TCM47184 of −11.36 kcal/mol, TCM31603 of −11.04 kcal/mol, and TCM31784 of −11.02 kcal/mol. Among the top 10 compounds re-Using EasyVS, an online web tool, the entire TCM database was screened against the Mac-I of the omicron variant. Prior to screening, the RO5 filter was applied, which reported 20,124 drugs that violated Lipinski's rule of five. Among the total of 57,000 compounds, 36,876 compounds were screened against the binding site of ADPr. Among these, 14,255 compounds reported a docking score less than −4.0 kcal/mol, and 16,453 compounds reported a docking score less than −8.0 kcal/mol. Among the remaining compounds, 5221 compounds reported a docking score of less than −9.0 kcal/mol. Among the remaining 947 compounds, only 356 were reported to have docking scores greater than −9.5 kcal/mol. Compounds with docking scores greater than −9.50 kcal/mol were considered as the threshold, because for ADPr the docking score was previously reported to be −9.46 kcal/mol. The top scoring 50 compounds were selected for re-docking using AutoDock Vina. Among these 50 compounds, 10 compounds reported the best docking score and are given in Table 1. Among the top 10 compounds, TCM42798 had a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, TCM30675 of −12.49 kcal/mol, TCM27763 of −11.93 kcal/mol, TCM33425 of −11.72 kcal/mol, TCM28788 of −11.46 kcal/mol, TCM42159 of −11.45 kcal/mol, TCM47184 of −11.36 kcal/mol, TCM31603 of −11.04 kcal/mol, and TCM31784 of −11.02 kcal/mol. Among the top 10 compounds reported to have higher docking scores than ADPr, only the top three were selected for further analysis, such as interactions, simulation, and post-simulation analysis. In addition to the top three compounds, TCM27763 and apigenin-bioside have been previously reported to have anti-adenovirus activity, which confirms the anti-viral activity of these compounds [41]. It was reported that apigenin reduces adenovirus replication and associated cellular toxicity. For instance, TCM28788 and TCM42159 have been

reported to have anti-dengue viral properties, which demonstrate the anti-viral potential of these molecules [42]. The anti-herpes simplex virus type 2 infection activity of tibeticanol and the other compounds are well documented, and it has been reported that these compounds halt viral replication [43].

**Table 1.** List of top 11 scoring compounds with their TCM IDs, compounds names, 3D structures, and docking scores. −1

−1

−1

−9

−9

−1

−1

−1

−1

−1

−1

'

'

'

**Table 1.** *Cont. Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 6 of 15

−1 −9 −1 −9 −1 −9 TCM42798, or *mucic acid 1-methyl ester 2-O-gallate*, was reported to have the best docking score of −13.70 kcal/mol. Mucic acid 1-methyl ester 2-O-gallate established a total of nine hydrogen bonds with Ala1060, Asn1062, Gly1068, Val1071, Ala1072, Leu1148, Ala1176, and Phe1178. For instance, these residues were previously reported to have an important role in the binding of ADPr. Comparatively, the docking score for ADPr has been reported to be −9.46 kcal/mol [22]. This shows the strongest binding of TCM42798 and consequently produces an inhibitory effect on Mac-I. The binding pattern of TCM42798 is given in Figure 2. TCM42798, or *mucic acid 1-methyl ester 2-O-gallate*, was reported to have the best docking score of −13.70 kcal/mol. Mucic acid 1-methyl ester 2-O-gallate established a total of nine hydrogen bonds with Ala1060, Asn1062, Gly1068, Val1071, Ala1072, Leu1148, Ala1176, and Phe1178. For instance, these residues were previously reported to have an important role in the binding of ADPr. Comparatively, the docking score for ADPr has been reported to be −9.46 kcal/mol [22]. This shows the strongest binding of TCM42798 and consequently produces an inhibitory effect on Mac-I. The binding pattern of TCM42798 is given in Figure 2.

−1

−1

−1

**Figure 2.** Binding of TCM42798 in the cavity of Mac-I. The right surface representation shows the binding mode of *mucic acid 1-methyl ester 2-O-gallate* (yellow sticks) inside the binding cavity. The right panel represent the 3D interaction pattern, where the TCM42798 is shown as yellow sticks, while the interacting residues are given in green sticks. The interactions (hydrogen bonds) are shown in pink color.

On the other hand, TCM47007, or *(2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O–D-glucuronopyranoside*, also demonstrated a good interaction profile by predicting the docking score of −13.25 kcal/mol. Unlike TCM42798, this complex reported only seven hydrogen bonds with the key residues required for interaction with ADPr. As shown in Figure 3, Ala1043, Ala1060, Gly1068, Val1071, Ala1072, and Ala1176 are involved in hydrogen bonding interactions. This shows the strongest binding of TCM47007 and consequently produces an inhibitory effect on Mac-I. Moreover, the interaction pattern for TCM30675, or *(5S,6S,7S,8R)- 5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1*, was also analyzed to demonstrate the binding mode of TCM30675. Residues such as Ala1060, Val1176, Phe1178, and Asp1179 are involved in direct interactions with the Mac-I. This shows the strongest binding of TCM30675 and consequently produces an inhibitory effect on Mac-I. The binding pattern of TCM42798 is given in Figure 4. *nopyranoside*, also demonstrated a good interaction profile by predicting the docking score of −13.25 kcal/mol. Unlike TCM42798, this complex reported only seven hydrogen bonds with the key residues required for interaction with ADPr. As shown in Figure 3, Ala1043, Ala1060, Gly1068, Val1071, Ala1072, and Ala1176 are involved in hydrogen bonding interactions. This shows the strongest binding of TCM47007 and consequently produces an inhibitory effect on Mac-I. Moreover, the interaction pattern for TCM30675, or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1*, was also analyzed to demonstrate the binding mode of TCM30675. Residues such as Ala1060, Val1176, Phe1178, and Asp1179 are involved in direct interactions with the Mac-I. This shows the strongest binding of TCM30675 and consequently produces an inhibitory effect on Mac-I. The binding pattern of TCM42798 is given in Figure 4.

**Figure 2.** Binding of TCM42798 in the cavity of Mac-I. The right surface representation shows the binding mode of *mucic acid 1-methyl ester 2-O-gallate* (yellow sticks) inside the binding cavity. The right panel represent the 3D interaction pattern, where the TCM42798 is shown as yellow sticks, while the interacting residues are given in green sticks. The interactions (hydrogen bonds) are

On the other hand, TCM47007, or *(2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuro-*

*Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 7 of 15

shown in pink color.

**Figure 3.** Binding of TCM47007 in the cavity of Mac-I. The right surface representation shows the binding mode of TCM47007 or *(2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside* (orange sticks) inside the binding cavity. The right panel represents the 3D interaction pattern, where the TCM47007 or *(2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside* is shown as orange sticks, while the interacting residues are given in green sticks. The interactions (hydrogen bonds) are shown in blue color. **Figure 3.** Binding of TCM47007 in the cavity of Mac-I. The right surface representation shows the binding mode of TCM47007 or *(2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O–D-glucuronopyranoside* (orange sticks) inside the binding cavity. The right panel represents the 3D interaction pattern, where the TCM47007 or *(2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O–D-glucuronopyranoside* is shown as orange sticks, while the interacting residues are given in green sticks. The interactions (hydrogen bonds) are shown in blue color.

#### *2.3. Dynamic Stability Analysis of the Top Compounds*

Analysis of the drug-bound protein complexes to decipher the structural stability is a key process in determining the inhibitory potential of the interacting compound. To foresee the dynamic stability of each top-scoring compound, we calculated the root mean square deviation (RMSD) for all of the simulation trajectories. As given in Figure 5A–C, all the complexes attained equilibrium at the earlier simulation and reached stability at 1.0 Å. In the case of *mucic acid 1-methyl ester 2-O-gallate*, the complex demonstrated overall stable dynamics with no significant deviation, except at the start of the simulation (1–10 ns) when the structure reported minor acceptable deviation and then reached the equilibrium point with a uniform RMSD graph. The average RMSD reported for the *mucic acid 1-methyl ester 2-O-gallate* complex was reported to be 1.0 Å. The RMSD for *mucic acid 1-methyl ester 2-O-gallate* is given in Figure 5A. The RMSD for TCM47007 or *(2S)-5,7,2',5'- Tetrahydroxyflavanone 7-O–D-glucuronopyranoside* reported comparatively small unstable dynamics until 15 ns, but then RMSD stabilized and attained equilibrium. As given in Figure 5B, after 15 ns the structure attained stability and demonstrated an average RMSD of 1.1 Å. Furthermore, the RMSD of TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2- [2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* demonstrated more similar behavior to the *mucic acid 1-methyl ester 2-O-gallate* complex. The RMSD initially

increased until 10 ns and then attained equilibrium. The complex reported no significant deviation except a small deviation between 10 and 20 ns, and then it stabilized again. An average RMSD of 1.2 Å was reported for TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2- [2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1*, as given in Figure 5C. Consequently, this shows the stronger binding and inhibitory potential of these compounds to rescue the host immune response against the COVID-19 infection. *Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 8 of 15

**Figure 4.** Binding of TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* in the cavity of Mac-I. The right surface representation shows the binding mode of TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4 methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* (blue sticks) inside the binding cavity. The right panel represent the 3D interaction pattern, where the TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* is shown as orange sticks, while the interacting residues are given in green sticks. The interactions (hydrogen bonds) are shown in blue color. *2.3. Dynamic Stability Analysis of the Top Compounds*  **Figure 4.** Binding of TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4 methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* in the cavity of Mac-I. The right surface representation shows the binding mode of TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3 hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* (blue sticks) inside the binding cavity. The right panel represent the 3D interaction pattern, where the TCM30675 or *(5S,6S,7S,8R)-5,6,7,8- Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1* is shown as orange sticks, while the interacting residues are given in green sticks. The interactions (hydrogen bonds) are shown in blue color. *Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 9 of 15

deviation except a small deviation between 10 and 20 ns, and then it stabilized again. An average RMSD of 1.2 Å was reported for TCM30675 or *(5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1*, as given in Figure 5C. Consequently, this shows the stronger binding and inhibitory potential of these compounds to rescue the host immune response against the COVID-19 infection. **Figure 5.** Dynamic stability analysis of the TCM42798, TCM47007, and TCM30675 complexes. (**A**) The RMSD graph for mucic acid 1-methyl ester 2-O-gallate. (**B**) The RMSD graph for TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside. (**C**) The RMSD graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8 tetrahydro-4H-chromen-4-1 complex. **Figure 5.** Dynamic stability analysis of the TCM42798, TCM47007, and TCM30675 complexes. (**A**) The RMSD graph for mucic acid 1-methyl ester 2-O-gallate. (**B**) The RMSD graph for TCM47007 or (2S)- 5,7,2',5'-Tetrahydroxyflavanone 7-O–D-glucuronopyranoside. (**C**) The RMSD graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4Hchromen-4-1 complex.

events demonstrated significant information regarding the binding stability and could be used to select the best compounds for the inhibition potential determination in the experimental setup. Thus, to determine the structural compactness, we calculated radius of gyration (Rg) over the simulation time as a function of time for each complex. As given in Figure 6A–C, all the complexes followed a similar pattern as RMSD. The TCM42798 complex demonstrated a uniform pattern of Rg with no increase or decrease over the simulation time. The structure reported no significant deviation, and the average Rg was reported to be 14.90 Å. The Rg for TCM42798 is shown in Figure 6A. On the other hand, TCM47007 demonstrated a small deviation between 23 and 28 ns and then reported a stable straight graph, which showed the stable binding steered by different kinds of bonds between TCM47007 and Mac-I. The TCM47007-Mac-I complex reported an average Rg of 14.96 Å. The Rg for TCM47007 is shown in Figure 6B. Furthermore, TCM30675 also reported a similar pattern of Rg as RMSD with no major significant deviation. A straight uniform Rg graph can be seen in Figure 6C, where a small fluctuation between 20 and 22 ns can be observed, while the Rg then stabilized and no significant deviation was reported. An average Rg of 15.90 Å was also reported for TCM30675. The Rg for TCM30675 is shown

*2.4. Structural Compactness Analysis*

in Figure 6C.

#### *2.4. Structural Compactness Analysis*

Analysis of structural compactness in a dynamic environment is essential to understand the binding and unbinding events that happened during the simulation. These events demonstrated significant information regarding the binding stability and could be used to select the best compounds for the inhibition potential determination in the experimental setup. Thus, to determine the structural compactness, we calculated radius of gyration (Rg) over the simulation time as a function of time for each complex. As given in Figure 6A–C, all the complexes followed a similar pattern as RMSD. The TCM42798 complex demonstrated a uniform pattern of Rg with no increase or decrease over the simulation time. The structure reported no significant deviation, and the average Rg was reported to be 14.90 Å. The Rg for TCM42798 is shown in Figure 6A. On the other hand, TCM47007 demonstrated a small deviation between 23 and 28 ns and then reported a stable straight graph, which showed the stable binding steered by different kinds of bonds between TCM47007 and Mac-I. The TCM47007-Mac-I complex reported an average Rg of 14.96 Å. The Rg for TCM47007 is shown in Figure 6B. Furthermore, TCM30675 also reported a similar pattern of Rg as RMSD with no major significant deviation. A straight uniform Rg graph can be seen in Figure 6C, where a small fluctuation between 20 and 22 ns can be observed, while the Rg then stabilized and no significant deviation was reported. An average Rg of 15.90 Å was also reported for TCM30675. The Rg for TCM30675 is shown in Figure 6C. *Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 10 of 15

**Figure 6.** Structural compactness analysis in a dynamic environment of the TCM42798, TCM47007, and TCM30675 complexes calculated as Rg. (**A**) The Rg graph for mucic acid 1-methyl ester 2-Ogallate. (**B**) The Rg graph for TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside. (**C**) The Rg graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1 complex. **Figure 6.** Structural compactness analysis in a dynamic environment of the TCM42798, TCM47007, and TCM30675 complexes calculated as Rg. (**A**) The Rg graph for mucic acid 1-methyl ester 2-O-gallate. (**B**) The Rg graph for TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O–Dglucuronopyranoside. (**C**) The Rg graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3 hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1 complex.

#### *2.5. Residues Flexibility Profiling 2.5. Residues Flexibility Profiling*

Residue flexibility is strongly correlated with the functional relevance of a protein, as it confers strength to the binding between the interacting molecules. Assessment of residue flexibility for the key residues demonstrates the impact of the small molecule binding. Thus, to determine how the residue flexibility is affected by the binding of these drugs, we calculated the root mean square fluctuation (RMSF) for each complex. As given in Figure 7, all the complexes demonstrated a similar pattern of residue flexibility. All the residues in each complex displayed minimal fluctuation, which showed the stronger bind-Residue flexibility is strongly correlated with the functional relevance of a protein, as it confers strength to the binding between the interacting molecules. Assessment of residue flexibility for the key residues demonstrates the impact of the small molecule binding. Thus, to determine how the residue flexibility is affected by the binding of these drugs, we calculated the root mean square fluctuation (RMSF) for each complex. As given in Figure 7, all the complexes demonstrated a similar pattern of residue flexibility. All the residues in each complex displayed minimal fluctuation, which showed the stronger binding of these

demonstrated comparatively higher fluctuations due to the loop distribution.

ing of these compounds. The regions between 40 and 50, 90 and 100, and 120 and 140

**Figure 7.** Residual flexibility analysis of the TCM42798, TCM47007, and TCM30675 complexes.

Hydrogen bonds confer strength to the binding of small molecules. The binding of small molecules is steered by hydrogen and many other bonds, which consequently show the inhibitory features. To determine the binding strength, we calculated the total number of hydrogen bonds and the population, and the simulation trajectories were analyzed. In TCM42798 or mucic acid 1-methyl ester 2-O-gallate, the average number of hydrogen bonds was reported to be 82, while in the case of TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside, the average number of hydrogen bonds

*2.6. Hydrogen Bonding Analysis*

compounds. The regions between 40 and 50, 90 and 100, and 120 and 140 demonstrated comparatively higher fluctuations due to the loop distribution. ing of these compounds. The regions between 40 and 50, 90 and 100, and 120 and 140 demonstrated comparatively higher fluctuations due to the loop distribution.

droxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1 complex.

*2.5. Residues Flexibility Profiling*

**Figure 6.** Structural compactness analysis in a dynamic environment of the TCM42798, TCM47007, and TCM30675 complexes calculated as Rg. (**A**) The Rg graph for mucic acid 1-methyl ester 2-Ogallate. (**B**) The Rg graph for TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside. (**C**) The Rg graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hy-

Residue flexibility is strongly correlated with the functional relevance of a protein, as it confers strength to the binding between the interacting molecules. Assessment of residue flexibility for the key residues demonstrates the impact of the small molecule binding. Thus, to determine how the residue flexibility is affected by the binding of these drugs, we calculated the root mean square fluctuation (RMSF) for each complex. As given in Figure 7, all the complexes demonstrated a similar pattern of residue flexibility. All the residues in each complex displayed minimal fluctuation, which showed the stronger bind-

*Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 10 of 15

**Figure 7.** Residual flexibility analysis of the TCM42798, TCM47007, and TCM30675 complexes. **Figure 7.** Residual flexibility analysis of the TCM42798, TCM47007, and TCM30675 complexes.

#### *2.6. Hydrogen Bonding Analysis 2.6. Hydrogen Bonding Analysis*

Hydrogen bonds confer strength to the binding of small molecules. The binding of small molecules is steered by hydrogen and many other bonds, which consequently show the inhibitory features. To determine the binding strength, we calculated the total number of hydrogen bonds and the population, and the simulation trajectories were analyzed. In TCM42798 or mucic acid 1-methyl ester 2-O-gallate, the average number of hydrogen bonds was reported to be 82, while in the case of TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside, the average number of hydrogen bonds Hydrogen bonds confer strength to the binding of small molecules. The binding of small molecules is steered by hydrogen and many other bonds, which consequently show the inhibitory features. To determine the binding strength, we calculated the total number of hydrogen bonds and the population, and the simulation trajectories were analyzed. In TCM42798 or mucic acid 1-methyl ester 2-O-gallate, the average number of hydrogen bonds was reported to be 82, while in the case of TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O–D-glucuronopyranoside, the average number of hydrogen bonds was also reported to be 79, while TCM30675 or the (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4 methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1 complex reported 78 average hydrogen bonds. The total number of hydrogen bonds in each complex is shown in Figure 8A–C. Moreover, the hydrogen bonding population for the key interacting residues was estimated and revealed in each complex, namely Ala1060 (63%, 74%, 58%), Asn1062 (66%, 53%, 61%), Gly1068 (51%, 43%, 34%) Val1071 (32%, 24%, 23%), Ala1072 (4%, 17%, 13%), Leu1148 (1%, 6%, 12%), Ala1176 (0%, 0%, 7%), and Phe1178 (0.36%, 2%, 11%) in TCM42798, TCM47007, and TCM30675 complexes, respectively. Together these results show that these compounds bind more strongly to the Mac-I and thus produce inhibitory properties that could help to rescue the host immune response against COVID-19 infection. *Pharmaceuticals* **2022**, *15*, x FOR PEER REVIEW 11 of 15 was also reported to be 79, while TCM30675 or the (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2- [2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8-tetrahydro-4H-chromen-4-1 complex reported 78 average hydrogen bonds. The total number of hydrogen bonds in each complex is shown in Figure 8A–C. Moreover, the hydrogen bonding population for the key interacting residues was estimated and revealed in each complex, namely Ala1060 (63%, 74%, 58%), Asn1062 (66%, 53%, 61%), Gly1068 (51%, 43%, 34%) Val1071 (32%, 24%, 23%), Ala1072 (4%, 17%, 13%), Leu1148 (1%, 6%, 12%), Ala1176 (0%, 0%, 7%), and Phe1178 (0.36%, 2%, 11%) in TCM42798, TCM47007, and TCM30675 complexes, respectively. Together these results show that these compounds bind more strongly to the Mac-I and thus produce inhibitory properties that could help to rescue the host immune response against COVID-19 infection.

**Figure 8.** Hydrogen bonding analysis of the TCM42798, TCM47007, and TCM30675 complexes. (**A**) The H-bonds graph for mucic acid 1-methyl ester 2-O-gallate. (**B**) The H-bonds graph for TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O--D-glucuronopyranoside. (**C**) The H-bonds graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]-5,6,7,8 tetrahydro-4H-chromen-4-1 complex. *2.7. Binding Free Energy Estimation*  **Figure 8.** Hydrogen bonding analysis of the TCM42798, TCM47007, and TCM30675 complexes. (**A**) The H-bonds graph for mucic acid 1-methyl ester 2-O-gallate. (**B**) The H-bonds graph for TCM47007 or (2S)-5,7,2',5'-Tetrahydroxyflavanone 7-O–D-glucuronopyranoside. (**C**) The H-bonds graph for TCM30675 or (5S,6S,7S,8R)-5,6,7,8-Tetrahydroxy-2-[2-(3-hydroxy-4-methoxyphenyl)ethyl]- 5,6,7,8-tetrahydro-4H-chromen-4-1 complex.

ing functions, it is one of the most accurate techniques. Keeping in mind the implementation of this approach, we also employed the same method to compute the binding free energy for TCM42798, TCM47007, and TCM30675 complexes. The vdWs for these complexes were reported to be −84.26 kcal/mol, −59.79 kcal/mol, and −53.24 kcal/mol, respectively, while the electrostatic energies were reported to be −12.22 kcal/mol, −13.22 kcal/mol, and −15.66 kcal/mol, respectively. Moreover, the ESURF values were reported to be 17.45 kcal/mol, 14.68 kcal/mol, and 12.25 kcal/mol, respectively. The total binding free energy for these complexes was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and

The binding strength of small molecules using the binding free energy method, MM-GBSA, is a widely used method for re-demonstrating docking stability and correct bind-

#### *2.7. Binding Free Energy Estimation*

The binding strength of small molecules using the binding free energy method, MM-GBSA, is a widely used method for re-demonstrating docking stability and correct binding. The above-mentioned MM-GBSA technique is more computationally economical than the more expensive alchemical free energy method. When compared to rational scoring functions, it is one of the most accurate techniques. Keeping in mind the implementation of this approach, we also employed the same method to compute the binding free energy for TCM42798, TCM47007, and TCM30675 complexes. The vdWs for these complexes were reported to be −84.26 kcal/mol, −59.79 kcal/mol, and −53.24 kcal/mol, respectively, while the electrostatic energies were reported to be −12.22 kcal/mol, −13.22 kcal/mol, and −15.66 kcal/mol, respectively. Moreover, the ESURF values were reported to be 17.45 kcal/mol, 14.68 kcal/mol, and 12.25 kcal/mol, respectively. The total binding free energy for these complexes was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and −47.64 kcal/mol, respectively, which consequently reflected the stronger binding and inhibitory potential of these compounds. The MM/GBSA results are given in Table 2.

**Table 2.** Binding free energy calculated as MM/GBSA. All the values are given in kcal/mol.

#### **3. Material and Methods**

#### *3.1. Modelling of the Macrodomain-I (Mac-I) of B.1.1.529 Variant*

The experimentally reported structure in the protein database was collected through accession number 6W02 to model the V1069I mutations reported in the Mac-I of NSP3 of the omicron variant [44]. For this purpose, the amino acid sequence using P0DTD1 accession number was obtained from UniProt, European union [45]. For modelling of the variant structure, AlphaFold 2.0 Seoul National University, Seoul, South Korea, was used, which is currently the best and most accurate approach for 3D structural modelling [46].

#### *3.2. Virtual Screening of Traditional Chinese Medicine Database*

The Traditional Chinese Medicine Database (TCM) currently holds 57,000 entries of different medicinal compounds isolated from Chinese herbs. It is considered as an important medicinal repository for discovering novel treatments that are safe and effective. Thus, we screened the complete TCM database against Mac-I of the B.1.1.529 variant. For screening, we used the EasyVS (http://biosig.unimelb.edu.au/easyvs, accessed on 10 April 2022) webserver [47]. Custom parameters were used and defined, such as the active site, and the RO5 filter was enabled for the filtration and removal of molecules that violated Lipinski's rules. Furthermore, for the top 100 hits, a second round of screening was performed using the Auto Dock Vina algorithm [48]. Finally, the top-selected compounds were used for the Induced-Fit docking (IFD) approach to remove the false-positive results. The top hits were identified based on the docking score for ADPr, taken as a control, as previously reported [22].

#### *3.3. Molecular Dynamics Simulation (MDS)*

Characterization of dynamic features to accurately portray the inhibitory potential of the top hits was studied by performing molecular dynamics simulation [49]. The top three hits were investigated by using AMBER20 simulation software by adding an optimal point charge water model and sodium ions for neutralizing the effect of any charge. Protein

and drug parameterization was achieved by recruiting FF19SB and GAFF forcefields. Each system after gentle minimization was subjected to heating followed by equilibration. The production runs for 50 ns each were completed. For any long-range electrostatic interactions (10.0 Å cutoff), the PME (particle mesh Ewald algorithm) was used, while covalent bonds were treated with the SHAKE algorithm.

#### *3.4. Trajectories Analysis Using CPPTRAJ and PTRAJ*

Evaluation of the simulation trajectories to forecast the dynamic stability, flexibility index, hydrogen bonding, structural compactness, and other parameters was completed by using CPPTRAJ and PTRAJ modules [50]. Root mean square deviation (RMSD) was estimated for stability, root mean square fluctuation (RMSF) to index the flexibility of each residue, radius of gyration (Rg) to foresee the compactness, and hydrogen bonding analysis to estimate the bonding population.

#### *3.5. Estimation of Post-Simulation Binding Energy*

The most generally utilized strategy in many related studies is to evaluate the strength of small molecule binding by employing the binding free energy (BFE) approach [51–54]. We also adopted the MMPBSA.py script to compute the binding free energy of the protein– ligand complexes by evaluating 2500 snapshots, keeping in mind the relevance of this strategy in re-ranking the binding conformations. For this purpose, the following equation was used to estimate the BFE:

$$f'' \Delta Gbind = \Delta Gcomplex - [\Delta Greceptor + \Delta Gligand]''$$

The ∆*Gbind* represents the total binding energy, while ∆*Greceptor*, ∆*Gligand*, and ∆*Gcomplex* represent the binding energy of protein, drug, and complex, respectively. The following equation was used to estimate individual binding energies such as bonded (G*bond*), electrostatic (G*ele*), polar (G*pol*), and non-polar (G*npol*), which contribute to the total binding free energy.

"*G* = *GbondGelectrostatic* − *Gvan der Waal* − *GpolarGnon* − *polar*"

#### **4. Conclusions**

The present study employs molecular modelling and MD simulation approaches to target the macrodomain-I of the B.1.1.529 variant of SARS-CoV-2. Three novel compounds, namely TCM42798, TCM47007, and TCM30675, were identified as potential inhibitors of Mac-I. These agents may suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.

**Author Contributions:** Conceptualization, C.J.B. and Z.T.M.; Data curation, Z.T.N.; S.K. and Z.J.K.A.-I.; Formal analysis, Z.T.N. and Z.T.M.; Funding acquisition, C.J.B.; Investigation, Z.T.N.; Methodology, S.K. and Z.J.K.A.-I.; Project administration, C.J.B. and Z.T.M.; Resources, C.J.B. and Z.T.M.; Software, Z.T.M.; Supervision, C.J.B.; Validation, S.K.; Z.J.K.A.-I. and C.J.B.; Visualization, Z.T.N. and Z.T.M.; Writing—original draft, Z.T.N. and Z.T.M.; Writing—review and editing, S.K.; Z.J.K.A.-I. and C.J.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research work was supported by the Nanjing University startup research funds.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available within the article.

**Acknowledgments:** The authors would like to acknowledge Nanjing University, China, for providing facilities for this research.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**