The investigation of marine natural products (MNPs) as key resources for the discovery of drugs to mitigate the COVID-19 pandemic is a developing field. In this work, computer-aided drug design (CADD) approaches comprising ligand- and structure-based methods were explored for predicting SARS-CoV-2 main protease (M pro ) inhibitors. The CADD ligand-based method used a quantitative structure–activity relationship (QSAR) classification model that was built using 5276 organic molecules extracted from the ChEMBL database with SARS-CoV-2 screening data. The best model achieved an overall predictive accuracy of up to 67% for an external and internal validation using test and training sets. Moreover, based on the best QSAR model, a virtual screening campaign was carried out using 11,162 MNPs retrieved from the Reaxys ® database, 7 in-house MNPs obtained from marine-derived actinomycetes by the team, and 14 MNPs that are currently in the clinical pipeline. All the MNPs from the virtual screening libraries that were predicted as belonging to class A were selected for the CADD structure-based method. In the CADD structure-based approach, the 494 MNPs selected by the QSAR approach were screened by molecular docking against M pro enzyme. A list of virtual screening hits comprising fifteen MNPs was assented by establishing several limits in this CADD approach, and five MNPs were proposed as the most promising marine drug-like leads as SARS-CoV-2 M pro inhibitors, a benzo[f]pyrano[4,3-b]chromene, notoamide I, emindole SB beta-mannoside, and two bromoindole derivatives.
【저자키워드】 Drug discovery, molecular docking, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Virtual screening, marine natural products (MNPs), actinomycetes, quantitative structure–activity relationship (QSAR), machine learning (ML) techniques, main protease enzyme (Mpro), 【초록키워드】 SARS-CoV-2, COVID-19 pandemic, molecular docking, drug, protease, inhibitors, computer-aided drug design, database, SARS-CoV-2 main protease, Accuracy, resource, Quantitative, Ligand, leads, best, Predictive, training sets, quantitative structure–activity relationship, house, enzyme, M pro, list, ChEMBL, team, derivatives, mitigate, approach, FIVE, limit, selected, predicted, approach, carried, screened, MNP, retrieved, virtual screening library, 【제목키워드】 SARS-CoV-2, drug, inhibition, leads,