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. 2020 Mar 17:19:400-409.
doi: 10.17179/excli2020-1189. eCollection 2020.

Unrevealing sequence and structural features of novel coronavirus using in silico approaches: The main protease as molecular target

Joseph Thomas Ortega  1 , Maria Luisa Serrano  2 , Flor Helene Pujol  3 , Hector Rafael Rangel  3
Affiliations

Unrevealing sequence and structural features of novel coronavirus using in silico approaches: The main protease as molecular target

Joseph Thomas Ortega et al. EXCLI J. .

Abstract

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.

Keywords: Coronavirus; HIV; SARS-CoV-2; protease; treatment.

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Figures

Table 1
Table 1. Molecular docking of Protease inhibitors used against HIV-1 over SARS-CoVs main proteases
Table 2
Table 2. Binding energy (BE) values of the best 20 compounds selected as potential inhibitors of SARS-CoV-2 protease. Compound structures were obtained from ZINC database (Bold) and PubChem (italics), lowest BE compound of each group are shown in red.
Figure 1
Figure 1. Phylogenetic analysis of SARS-CoV-2 and other coronaviruses main protease protein. Phylogenetic tree constructed with Poisson correction and 100 bootstrap replicas. The sequences are named with their accession number. The percent homology with SARS-CoV-2 protease protein is shown for some proteins.
Figure 2
Figure 2. Coronavirus main proteases. Graphical representation for each protease was achieved in Biovia Discovery Studio Visualizer by using the coordinates obtained from the Protein Data Bank. Structure for A) Bat-CoV (2YNB), B) SARS-CoV (2GX4), C) SARS-CoV-2 (6LU7) are shown. Also, a comparison by molecular overlapping between these structures is shown in D. The main residues and changes in SARS-CoV-2 compared to SARS-CoV are shown in E. The HIV-1 protease (1MIU) is shown in F.
Figure 3
Figure 3. Coronavirus main proteases. Topological analysis of the catalytic site for SARS-CoV (A) and SARS-CoV-2 (B) main proteases. Conformational residues are highlighted in blue.
Figure 4
Figure 4. Molecular docking of HIV protease inhibitors on SARS-CoV-2 main protease. The molecular docking output represented as lower binding energy frame is shown for each inhibitor. 3D (left) and 2D (right) representations showing the main interaction between the inhibitor and the receptor are displayed. A) Saquinavir, B) Ritonavir, and C) Lopinavir
Figure 5
Figure 5. Hierarchical clustering of the top 20 best protease inhibitors obtained from public libraries (ZINC and PubChem) that could block SARS-CoV-2 protease. The compounds were clustered by chemical structure based in the Tanimoto coefficient where 0: the same structure and 1: no chemical relationship.
Figure 6
Figure 6. Chemical structure and ADME parameters of top five protease inhibitors obtained from public libraries (ZINC and PubChem) that could block SARS-CoV-2 protease. The colored zone is the suitable physicochemical space for oral bioavailability. LIPO (Lipophility): -0.7
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