Drug Potency Prediction of SARS-CoV-2 Main Protease Inhibitors Based on a Graph Generative Model
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Published:2023-05-15
Issue:10
Volume:24
Page:8779
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ISSN:1422-0067
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Container-title:International Journal of Molecular Sciences
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language:en
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Short-container-title:IJMS
Author:
Fadlallah Sarah1ORCID, Julià Carme1ORCID, García-Vallvé Santiago2ORCID, Pujadas Gerard2ORCID, Serratosa Francesc1ORCID
Affiliation:
1. Research Group ASCLEPIUS: Smart Technology for Smart Healthcare, Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona, Spain 2. Research Group in Cheminformatics and Nutrition, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43007 Tarragona, Spain
Abstract
The prediction of a ligand potency to inhibit SARS-CoV-2 main protease (M-pro) would be a highly helpful addition to a virtual screening process. The most potent compounds might then be the focus of further efforts to experimentally validate their potency and improve them. A computational method to predict drug potency, which is based on three main steps, is defined: (1) defining the drug and protein in only one 3D structure; (2) applying graph autoencoder techniques with the aim of generating a latent vector; and (3) using a classical fitting model to the latent vector to predict the potency of the drug. Experiments in a database of 160 drug-M-pro pairs, from which the pIC50 is known, show the ability of our method to predict their drug potency with high accuracy. Moreover, the time spent to compute the pIC50 of the whole database is only some seconds, using a current personal computer. Thus, it can be concluded that a computational tool that predicts, with high reliability, the pIC50 in a cheap and fast way is achieved. This tool, which can be used to prioritize which virtual screening hits, will be further examined in vitro.
Funder
Universitat Rovira i Virgili through the Martí Franquès program in addition to AGAUR research groups
Subject
Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis
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