State-of-the-art tools unveil potent drug targets amongst clinically approved drugs to inhibit helicase in SARS-CoV-2

Abstract

Introduction: The extreme health and economic problems in the world due to the SARS-CoV-2 infection have led to an urgent need to identify potential drug targets for treating coronavirus disease 2019 (COVID-19). The present state-of-the-art tool-based screening was targeted to identify drug targets among clinically approved drugs by uncovering SARS-CoV-2 helicase inhibitors through molecular docking analysis.

Material and methods: Helicase is a vital viral replication enzyme, which unwinds nucleic acids and separates the double-stranded nucleic acids into single-stranded nucleic acids. Hence, the SARS-CoV-2 helicase protein 3D structure was predicted, validated, and used to screen the druggable targets among clinically approved drugs such as protease inhibitor, nucleoside reverse transcriptase inhibitor, and non-nucleoside reverse transcriptase inhibitors, used to treat HIV infection using molecular docking analysis.

Results: Interaction with SARS-CoV-2 helicase, approved drugs, vapreotide (affinity: -12.88; S score: -9.84 kcal/mol), and atazanavir (affinity: -11.28; S score: -9.32 kcal/mol), approved drugs for treating AIDS-related diarrhoea and HIV infection, respectively, are observed with significantly low binding affinity and MOE score or binding free energy. The functional binding pockets of the clinically approved drugs on SARS-CoV-2 helicase protein molecule suggest that vapreotide and atazanavir may interrupt the activities of the SARS-CoV-2 helicase.

Conclusions: The study suggests that vapreotide may be a choice of drug for wet lab studies to inhibit the infection of SARS-CoV-2.

Keywords: COVID-19; SARS-CoV-2; antiretroviral agents; clinically approved drugs; helicase; molecular docking.

Figure 1

Flow chart of the methodology for the selection of the best inhibitor of SARS-CoV-2 helicase

Figure 2

Phylogenetic analysis of SARS-CoV-2 helicase protein using RefSeq-protein BLAST results by maximum likelihood method. “The evolutionary history was inferred by using the Maximum Likelihood method based on the JTT matrix-based model [33]. The bootstrap consensus tree inferred from 500 replicates [34] is taken to represent the evolutionary history of the taxa analysed [34]. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. Initial tree(s) for the heuristic search was/were obtained automatically by applying Neighbour-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model, and then selecting the topology with superior log likelihood value. The analysis involved 101 amino acid sequences. All positions containing gaps and missing data were eliminated. There were a total of 74 positions in the final dataset. Evolutionary analyses were conducted in MEGA7 [13].” Sequence of COVID-19 helicase used for the phylogenetic analysis: DAVVYRGTTTYKLNVGDYFVLTSHTVMPLSAPTLVPQEHYVRITGLYPTLNISDEFSSNVANYQKVGMQKYSTLQGPPGTGKSHFAIGLALYYPSARIVYTACSHAAVDALCEKALKYLPIDKCSR IPARARVECFDKFKVNSTLEQYVFCTVNALPETTADIVVFDEISMATNYDLSVVNARLRAKHYVYIGDPAQLPAPRTLLTKGTLEPEYFNSVCRLMKTIGPDMFLGTCRRCPAEIVDTVSALVYDN LKAHKDKSAQCFKMFYKGVITHDVSSAINRPQIGVVREFLTRNPAWRKAVFISPYNSQNAVASKILGLPTQTVDSSQGSEYDYVIFTQTTETAHSCNVNRFNVAITRAKVGILCIMSDRDLYDKL FTSLEIPRRNVATLQAENVTGLFKDCSKVITGLHPTQAPT

Figure 3

Phylogenetic analysis by Maximum Likelihood method of SARS-CoV-2 helicase protein using PSI-BLAST results. “The evolutionary history was inferred by using the Maximum Likelihood method based on the JTT matrix- based model [34]. The tree with the highest log likelihood (–3764.53) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbour-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model, and then selecting the topology with superior log likelihood value. The analysis involved 501 amino acid sequences. All positions containing gaps and missing data were eliminated. There were a total of 384 positions in the final dataset. Evolutionary analyses were conducted in MEGA7 [13]”

Figure 4

Homology model of helicase. A – Helicase homology model. B – Model-Template Alignment. C – Ramachandran plot of SARS-CoV-2 helicase from PDBsum

Figure 5

The most significant drug – SARS-CoV-2 helicase interaction. A, B – SARS-CoV-2 helicase and vapreotide interaction; A – 2D plot of SARS-CoV-2 helicase and vapreotide interaction; B – 3D structure of saquinavir – SARSCoV- 2 helicase interaction. C – 2D plot of SARS-CoV-2 helicase and atazanavir interaction. D – 3D plot of SARS-CoV-2 helicase and atazanavir interaction. E – Binding affinity and MOE score (S) of available drugs and interaction with SARS-CoV-2 helicase. **Drug with the lowest binding affinity and S score or binding free energy; *drug with the second lowest binding affinity and S score or binding free energy. Details of the interaction can be seen in Table I