r o t =\delta g_+\delta g_\sigma _+\delta g_\sigma _+\delta g_\left\vert a\right\vert +\delta g_ where: δg0 – empirically derived offset that in part corresponds to the overall loss of translational and rotational entropy of the ligand upon binding. δghb – contribution from hydrogen bonding δgionic – contribution from ionic interactions δglip – contribution from lipophilic interactions where |alipo| is surface area of lipophilic contact between the ligand and receptor δgrot – entropy penalty due to freezing a rotatable in the ligand bond upon binding a more general thermodynamic "master" equation is as follows: δ g bind = − r t ln ⁡ k d k d = [ ligand ] [ receptor ] [ complex ] δ g bind = δ g desolvation + δ g motion + δ g configuration + δ g interaction \delta g_=-rt\ln k_\\k_=\\\delta g_=\delta g_+\delta g_+\delta g_+\delta g_\end where: desolvation – enthalpic penalty for removing the ligand from solvent motion – entropic penalty for reducing the degrees of freedom when a ligand binds to its receptor configuration – conformational strain energy required to put the ligand in its "active" conformation interaction – enthalpic gain for "resolvating" the ligand with its receptor the basic idea is that the overall binding free energy can be decomposed into independent components that are known to be important for the binding process. each component reflects a certain kind of free energy alteration during the binding process between a ligand and its target receptor. the master equation is the linear combination of these components. according to gibbs free energy equation, the relation between dissociation equilibrium constant, kd, and the components of free energy was built. various computational methods are used to estimate each of the components of the master equation. for example, the change in polar surface area upon ligand binding can be used to estimate the desolvation energy. the number of rotatable bonds frozen upon ligand binding is proportional to the motion term. the configurational or strain energy can be estimated using molecular mechanics calculations. finally the interaction energy can be estimated using methods such as the change in non polar surface, statistically derived potentials of mean force, the number of hydrogen bonds formed, etc. in practice, the components of the master equation are fit to experimental data using multiple linear regression. this can be done with a diverse training set including many types of ligands and receptors to produce a less accurate but more general "global" model or a more restricted set of ligands and receptors to produce a more accurate but less general "local" model. examples a particular example of rational drug design involves the use of three-dimensional information about biomolecules obtained from such techniques as x-ray crystallography and nmr spectroscopy. computer-aided drug design in particular becomes much more tractable when there is a high-resolution structure of a target protein bound to a potent ligand. this approach to drug discovery is sometimes referred to as structure-based drug design. the first unequivocal example of the application of structure-based drug design leading to an approved drug is the carbonic anhydrase inhibitor dorzolamide, which was approved in 1995. another important case study in rational drug design is imatinib, a tyrosine kinase inhibitor designed specifically for the bcr-abl fusion protein that is characteristic for philadelphia chromosome-positive leukemias (chronic myelogenous leukemia and occasionally acute lymphocytic leukemia). imatinib is substantially different from previous drugs for cancer, as most agents of chemotherapy simply target rapidly dividing cells, not differentiating between cancer cells and other tissues. additional examples include: many of the atypical antipsychotics cimetidine, the prototypical h2-receptor antagonist from which the later members of the class were developed selective cox-2 inhibitor nsaids enfuvirtide, a peptide hiv entry inhibitor nonbenzodiazepines like zolpidem and zopiclone raltegravir, an hiv integrase inhibitor ssris (selective serotonin reuptake inhibitors), a class of antidepressants zanamivir, an antiviral drug case studies 5-ht3 antagonists acetylcholine receptor agonists angiotensin receptor antagonists bcr-abl tyrosine-kinase inhibitors cannabinoid receptor antagonists ccr5 receptor antagonists cyclooxygenase 2 inhibitors dipeptidyl peptidase-4 inhibitors hiv protease inhibitors nk1 receptor antagonists non-nucleoside reverse transcriptase inhibitors nucleoside and nucleotide reverse transcriptase inhibitors pde5 inhibitors proton pump inhibitors renin inhibitors triptans trpv1 antagonists c-met inhibitors criticism it has been argued that the highly rigid and focused nature of rational drug design suppresses serendipity in drug discovery.