MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods

• Published in: RSC advances Vol. 14; no. 27; pp. 18950 - 18956
• Main Authors: Thai, Quynh Mai, Nguyen, Trung Hai, Phung, Huong Thi Thu, Pham, Minh Quan, Pham, Nguyen Kim Tuyen, Horng, Jim-Tong, Ngo, Son Tung
• Format: Journal Article
• Language: English
• Published: England Royal Society of Chemistry 12.06.2024; The Royal Society of Chemistry
• Subjects: Affinity; Binding; Chemistry; Influenza; Ligands; Machine learning; Molecular docking; Molecular dynamics
• ISSN: 2046-2069; 2046-2069
• DOI: 10.1039/d4ra02661f

Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.