You will be given a definition of a task first, then some input of the task.
In this task, you are given a paragraph (from a research paper) and your task is to classify each sentence of the paragraph (assume n sentence) into the following categories: Background, Purpose, Method, Finding/Contribution, or Other. Return the output in this format: 1 - category of sentence 1, 2 - category of sentence 2, ..., n - category of sentence n; where each number indicates the order of the sentence. The categories can be identified using the following questions: 
 Background: - Why is this problem important? - What relevant works have been done before? - What did the previous works miss? - What are the high-level research questions? - How might this help other researchers?
 Purpose: - What specific things do the researchers want to do? - What specific knowledge do the researchers want to know? - What specific hypothesis do the researchers want to test?
 Method: - How did the researchers do it or find it out? - What are the procedures and steps of this research?
 Finding/Contribution: - What did the researchers find out? Did the proposed methods work? - Did things behave as the researchers expected?
Other: put every text fragment that does not fit into any of the categories above here. Put a sentence here if its not in English, is not part of the article, contains numbers and dates, is a caption of a figure or a table, is a formatting error, or you are not sure about it.

Direct-acting antivirals are effective tools to control viral infections. SARS-CoV-2 is a coronavirus associated with the epidemiological outbreak in late 2019. Previous reports showed that HIV-1 protease inhibitors could block SARS-CoV main protease. Based on that and using an in silico approach, we evaluated SARS-CoV-2 main protease as a target for HIV-1 protease inhibitors to reveal the structural features related to their antiviral effect. Our results showed that several HIV inhibitors such as lopinavir, ritonavir, and saquinavir produce strong interaction with the active site of SARS-CoV-2 main protease. Furthermore, broad library protease inhibitors obtained from PubChem and ZINC (www.zinc.docking.org) were evaluated. Our analysis revealed 20 compounds that could be clustered into three groups based on their chemical features. Then, these structures could serve as leading compounds to develop a series of derivatives optimizing their activity against SARS-CoV-2 and other coronaviruses. Altogether, the results presented in this work contribute to gain a deep understanding of the molecular pharmacology of SARS-CoV-2 treatment and validate the use of protease inhibitors against SARS-CoV-2.
Output:
1 - background, 2 - background, 3 - background, 4 - background, 5 - finding, 6 - finding, 7 - finding, 8 - finding, 9 - finding, 10 - finding, 11 - finding