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QSAR modeling and pharmacoinformatics of SARS coronavirus 3C-like protease inhibitors.

ABSTRACT: The search for effective treatment against novel coronavirus (COVID-19) remains a global challenge due to controversies on available vaccines. In this study, data of SARS coronavirus 3C-like protease (3CLpro) inhibitors; a key drug target in the coronavirus genome was retrieved from CHEMBL database. Quantitative Structure-Activity Relationship (QSAR) studies, Molecular docking, Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) and molecular dynamics simulation (MDS) were carried out using these 3CLpro inhibitors. QSAR model constructed using the data had correlation coefficient R² value of 0.907; cross-validated correlation coefficient Q² value of 0.866 and test set predicted correlation coefficient R²_pred value of 0.517. Variance inflation factor (VIF) values for descriptors contained in the model ranged from 1.352 to 1.68, hence, these descriptors were orthogonal to one another. Therefore, the model was statistically significant and can be used to screen and design new molecules for their inhibitory activity against 3CLpro. Molecular docking showed that seven of the compounds (inhibitors) used in the study had a remarkable binding affinity (-9.2 to -10.3 kcal/mol) for 3CLpro. ADMET study revealed that five (CHEMBL Accession IDs 19438, 196635, 377150, 208763, and 210097) of the seven compounds with good binding ability obeyed Lipinski's rule of five. Hence, they were compounds with drug-like properties. MDS analysis revealed that 3CLpro-compound 21, 3CLpro-compound 22, 3CLpro-compound 40 complexes are very stable as compared to the reference 3CLpro-X77 complex. Therefore, this study identified three potent inhibitors of 3CLpro viz. CHEMBL194398, CHEMBL196635, and CHEMBL210097 that can be further explored for the treatment of COVID-19.

SUBMITTER: Ishola AA

PROVIDER: S-EPMC8111888 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Although the initial outbreaks of the deadly coronavirus that causes severe acute respiratory syndrome (SARS-CoV) were controlled by public health measures, the development of vaccines and antiviral agents for SARS-CoV is essential for improving control and treatment of future outbreaks. One potential target for SARS-CoV antiviral drug development is the 3C-like protease (3CLpro). This enzyme is an attractive target since it is essential for viral replication, and since there are now a number of high resolution X-ray structures of SARS-CoV 3CLpro available making structure-based drug-design possible. As a result, SARS-CoV 3CLpro has become the focus of numerous drug discovery efforts worldwide, but as a consequence, a variety of different 3CLpro expression constructs and kinetic assays have been independently developed making evaluation and comparison between potential inhibitors problematic. Here, we review the literature focusing on different SARS-CoV 3CLpro expression constructs and assays used to measure enzymatic activity. Moreover, we provide experimental evidence showing that the activity of 3CLpro enzymatic is significantly reduced when non-native sequences or affinity-tags are added to the N- or C-termini of the enzyme, or when the enzyme used in assays is at concentrations below the equilibrium dissociation constant of the 3CLpro dimer. We demonstrate for the first time the utility of a highly sensitive and novel Alexa488-QSY7 FRET-based peptide substrate designed for routine analysis and high-throughput screening, and show that kinetic constants determined from FRET-based assays that are uncorrected for inner-filter effects can lead to artifacts. Finally, we evaluated the effects of common assay components including DTT, NaCl, EDTA and DMSO on enzymatic activity, and we recommend standardized assay conditions and constructs for routine SARS-CoV 3CLpro assays to facilitate direct comparisons between SARS-CoV 3CLpro inhibitors under development worldwide.

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QSAR modeling and pharmacoinformatics of SARS coronavirus 3C-like protease inhibitors.

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