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Identification and characterization of novel RdRp and Nsp15 inhibitors for SARS-COV2 using computational approach.

ABSTRACT: The World Health Organization has declared COVID-19 as a global health emergency. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and highlights an urgent need for therapeutics. Here, we have employed a series of computer-aided drug repurposing campaign to discover inhibitors of RNA dependent RNA polymerase (RdRp) and Nsp15/EndoU. Subsequently, MD simulation has been performed to observe dynamic behavior of identified leads at the active site of RdRp and Nsp15. We successfully identified novel lead molecule such as Alectinib for RdRp while Naldemedine and Ergotamine for NSP15. These lead molecules were accommodated in the active site of the enzyme and stabilized by the networks of the hydrogen bond, pi type and hydrophobic interaction with key residues of either target. Interestingly, identified compounds show molecular mimicry in terms of molecular interactions with key residues of RdRp and Nsp15 essential for catalysis and substrate interaction. Previously, Alectinib, Naldemedine and Ergotamine were used as drug in different diseases might be repurposed against selected protein targets of COVID19. Finally, we propose that the identified inhibitors represent a novel lead molecule to design a more effective inhibitor to stop the progress of pathogen. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Barage S

PROVIDER: S-EPMC7651200 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The rapid outbreak of the COVID-19 also known as SARS-CoV2 has been declared pandemic with serious global concern. As there is no effective therapeutic against COVID-19, there is an urgent need for explicit treatment against it. The focused objective of the current study is to propose promising drug candidates against the newly identified potential therapeutic target (endonuclease, NSP15) of SARS-CoV2. NSP15 is an attractive druggable target due to its critical role in SARS-CoV2 replication and virulence in addition to interference with the host immune system. Here in the present study, we integrated the high throughput computational screening and dynamic simulation approach to identify the most promising candidate lead compound against NSP15.5-fluoro-2-oxo-1H-pyrazine-3-carboxamide (favipiravir), (3R,4R, 5R)-3,4-Bis(benzyloxy)-5-((benzyloxy) methyl) dihydrofuran-2(3H)-one) remedesivir, 1,3-thiazol-5-ylmethyl N-[(2S,3S, 5S)-3-hydroxy-5-[[(2 S)-3-methyl-2-[[methyl-[(2-propan-2-yl-1,3-thiazol-4-yl)methyl]carbamoyl]amino]butanoyl]amino]-1,6-diphenylhexan-2-yl]carbamate (ritonavir), ethyl (3R,4R, 5S)-4-acetamido-5-amino-3-pentan-3-yloxycyclohexene-1-carboxylate (oseltamivir), and (2 S)-N-[(2S,4S, 5S)-5-[[2-(2,6-dimethylphenoxy)acetyl]amino]-4-hydroxy-1,6-diphenylhexan-2-yl]-3-methyl-2-(2-oxo-1,3-diazinan-1-yl)butanamide (lopinavir) were chosen as a training set to generate the pharmacophore model. A dataset of ~140,000 compounds library was screened against the designed pharmacophore model and 10 unique compounds were selected that passed successfully through geometry constraints, Lipinski Rule of 5, and ADME/Tox filters along with a strong binding affinity for NSP15 binding cavity. The best fit compound was selected for dynamic simulation to have detailed structural features critical for binding with the NSP15 protein. Given our detailed integrative computational analysis, a Small molecule (3,3-Dimethyl-N-[4-(1-piperidinylcarbonyl) phenyl] butanamide) with drug-like properties and high binding affinity with the NSP15 is proposed as a most promising potential drug against COVID-19. The current computational integrative approach may complement high-throughput screening and the shortlisted small molecule may contribute to selective targeting of NSP15 to stop the replication of SARS-CoV2.

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Identification and characterization of novel RdRp and Nsp15 inhibitors for SARS-COV2 using computational approach.

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