Unknown

Dataset Information

0

Mechanistic investigation of SARS-CoV-2 main protease to accelerate design of covalent inhibitors.


ABSTRACT: Targeted covalent inhibition represents one possible strategy to block the function of SARS-CoV-2 Main Protease (MPRO), an enzyme that plays a critical role in the replication of the novel SARS-CoV-2. Toward the design of covalent inhibitors, we built a covalent inhibitor dataset using deep learning models followed by high throughput virtual screening of these candidates against MPRO. Two top-ranking inhibitors were selected for mechanistic investigations-one with an activated ester warhead that has a piperazine core and the other with an acrylamide warhead. Specifically, we performed a detailed analysis of the free energetics of covalent inhibition by hybrid quantum mechanics/molecular mechanics simulations. Cleavage of a fragment of the non-structured protein (NSP) from the SARS-CoV-2 genome was also simulated for reference. Simulations show that both candidates form more stable enzyme-inhibitor (E-I) complexes than the chosen NSP. It was found that both the NSP fragment and the activated ester inhibitor react with CYS145 of MPRO in a concerted manner, whereas the acrylamide inhibitor follows a stepwise mechanism. Most importantly, the reversible reaction and the subsequent hydrolysis reaction from E-I complexes are less probable when compared to the reactions with an NSP fragment, showing promise for these candidates to be the base for efficient MPRO inhibitors.

SUBMITTER: Kim H 

PROVIDER: S-EPMC9722715 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Mechanistic investigation of SARS-CoV-2 main protease to accelerate design of covalent inhibitors.

Kim Hoshin H   Hauner Darin D   Laureanti Joseph A JA   Agustin Kruel K   Raugei Simone S   Kumar Neeraj N  

Scientific reports 20221205 1


Targeted covalent inhibition represents one possible strategy to block the function of SARS-CoV-2 Main Protease (M<sup>PRO</sup>), an enzyme that plays a critical role in the replication of the novel SARS-CoV-2. Toward the design of covalent inhibitors, we built a covalent inhibitor dataset using deep learning models followed by high throughput virtual screening of these candidates against M<sup>PRO</sup>. Two top-ranking inhibitors were selected for mechanistic investigations-one with an activa  ...[more]

Similar Datasets

| S-EPMC9959744 | biostudies-literature
| S-EPMC8916680 | biostudies-literature
| S-EPMC10364469 | biostudies-literature
| S-EPMC9046211 | biostudies-literature
| S-EPMC10922772 | biostudies-literature
| S-EPMC8491553 | biostudies-literature
| S-EPMC8444677 | biostudies-literature
| S-EPMC11459967 | biostudies-literature
| S-EPMC7724992 | biostudies-literature
| S-EPMC10861299 | biostudies-literature