AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs used currently in the clinic necessitate the development of novel potent and broad therapeutic agents targeting different vulnerable spots of the viral proteins. In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. As a result, the seven best scoring compounds that exhibited low values of binding free energy comparable with those calculated for two potent inhibitors of Mpro, via the same computational protocol, were selected as the most probable inhibitors of the enzyme catalytic site. In light of the data obtained, the identified compounds are assumed to present promising scaffolds for the development of new potent and broad-spectrum drugs inhibiting SARS-CoV-2 Mpro, an attractive therapeutic target for anti-COVID-19 agents.

Metabolomic profiling of three Araucaria species, and their possible potential role against COVID-19.

The COVID-19 pandemic in Egypt is a part of the worldwide global crisis of coronavirus 2 (SARS-CoV-2). The contagious life-threatening condition causes acute respiratory syndrome. The present study aimed to assess the compounds identified by LC-MS of the methanolic leaves extracts from three conifers trees cultivated in Egypt (Araucaria bidwillii, Araucaria. cunninghamii and Araucaria heterophylla) via docking technique as potential inhibitor of COVID-19 virus on multiple targets; viral main protease (Mpro, 6LU7), non-structural protein-16 which is a methyl transferase (nsp16, 6W4H) and RNA dependent RNA polymerase (nsp12, 7BV2). Among the three targets, nsp16 was the best target recognized by the tested compounds as can be deduced from docking studies. Moreover, the methanolic extract of A. cunninghamii showed the highest radical-scavenging activity using (DPPH test) with 53.7 µg/mL comparable to ascorbic acid with IC50 = 46 µg/mL The anti-inflammatory potential carried using enzyme linked immunoassay showed the highest activity for A. cunninghamii and A. bidwillii followed by A. heterophylla with IC50 = 23.20 ± 1.17 µg/mL, 82.83 ± 3.21 µg/mL and 221.13 ± 6.7 µg/mL, respectively (Celecoxib was used as a standard drug with IC50 = 141.92 ± 4.52 µg/mL). Moreover, a molecular docking study was carried for the LC-MS annotated metabolites to validate their anti-inflammatory inhibitory effect using Celecoxib as a reference compound and showed a high docking score (-7.7 kcal/mol) for Octadecyl (E) P-coumarate and (-7.3 kcal/mol) for secoisolariciresinol rhamnoside.Communicated by Ramaswamy H. Sarma.

Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease.

A computational approach to in silico drug discovery was carried out to identify small drug-like compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (MPro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-MPro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 MPro were generated by molecular docking, quantum chemical calculations and molecular dynamics simulations. At the final point, analysis of the interaction modes of the identified compounds with MPro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 MPro. Insights into the ligand - MPro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 MPro, in line with the low values ​​of binding free energy and dissociation constant. Mechanism of binding of these compounds to MPro is mainly provided by van der Waals interactions with the functionally important residues of the enzyme, such as His-41, Met-49, Cys-145, Met-165, and Gln-189 that play a role of the binding hot spots assisting the predicted molecules to effectively interact with the MPro active site. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 MPro.Communicated by Ramaswamy H. Sarma.

IDENTIFICATION OF POTENTIAL INHIBITORS OF CORONAVIRUS SARS-CoV-2 USING THE METHODS OF VIRTUAL SCREENING AND MOLECULAR MODELING

To find small-molecule compounds that can simulate the structural and functional properties of the high affinity X77 ligand of the main protease of SiRS-CoV-2 - etiologic agent of COVID-19, the virtual screening of 9 molecular libraries of the Pharmit web server containing over 213.5 million chemical structures was performed. Using molecular modeling, the neutralizing activity of the identified molecules was evaluated, resulting in 5 leader compounds promising for synthesis and testing for antiviral activity. The data obtained indicate that these compounds may be used as basic structures for the development of effective drugs to treat the novel coronavirus infection.