Computational Screening of Inhibitory Compounds for SARS-Cov-2 3CL Protease with a Database Consisting of Approved and Investigational Chemicals.
Chem Pharm Bull (Tokyo)
; 71(5): 360-367, 2023.
Artículo
en Inglés
| MEDLINE | ID: covidwho-2317290
ABSTRACT
Computational screening is one of the fundamental techniques in drug discovery. Each compound in a chemical database is bound to the target protein in virtual, and candidate compounds are selected from the binding scores. In this work, we carried out combinational computation of docking simulation to generate binding poses and molecular mechanics calculation to estimate binding scores. The coronavirus infectious disease has spread worldwide, and effective chemotherapy is strongly required. The viral 3-chymotrypsin-like (3CL) protease is a good target of low molecular-weight inhibitors. Hence, computational screening was performed to search for inhibitory compounds acting on the 3CL protease. As a preliminary assessment of the performance of this approach, we used 51 compounds for which inhibitory activity had already been confirmed. Docking simulations and molecular mechanics calculations were performed to evaluate binding scores. The preliminary evaluation suggested that our approach successfully selected the inhibitory compounds identified by the experiments. The same approach was applied to 8820 compounds in a database consisting of approved and investigational chemicals. Hence, docking simulations, molecular mechanics calculations, and re-evaluation of binding scores including solvation effects were performed, and the top 200 poses were selected as candidates for experimental assays. Consequently, 25 compounds were chosen for in vitro measurement of the enzymatic inhibitory activity. From the enzymatic assay, 5 compounds were identified to have inhibitory activities against the 3CL protease. The present work demonstrated the feasibility of a combination of docking simulation and molecular mechanics calculation for practical use in computational virtual screening.
Palabras clave
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
SARS-CoV-2
/
COVID-19
Tipo de estudio:
Estudio experimental
/
Estudio pronóstico
Límite:
Humanos
Idioma:
Inglés
Revista:
Chem Pharm Bull (Tokyo)
Año:
2023
Tipo del documento:
Artículo
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