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Discovery of ASGR1 and HMGCR dual-target inhibitors based on supervised learning, molecular docking, molecular
Yanfeng Liu1, Liangying Deng2, Feng Ding3
1Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210028, China; Nanjing Lishui District Hospital of Traditional Chinese Medicine, Nanjing 211200, China; Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.
Abstract:
3-Hydroxy-3-Methylglutaryl-CoA Reductase (HMGCR) and Asialoglycoprotein Receptor 1 (ASGR1) are potential therapeutic targets for atherosclerotic cardiovascular disease (ASCVD). In this study, we employed an innovative approach that combined ligand-based supervised learning, molecular docking, molecular dynamics simulations, and various in-silico techniques. The objective was to effectively screen the Chemdiv and SPECS molecule databases to discover potential inhibitors targeting both HMGCR and ASGR1, resulting in a dual inhibition effect. Compound 8006-6092, K007-0721, and D011-1471 exhibited inhibition rates of 41.48 %, 61.48 %, and 49.63 %, respectively, at a concentration of 10 μM against HMGCR. In addition, they demonstrated significant binding to ASGR1, with dissociation constants (Kd) of 461.33 μM, 67.63 μM, and 695.50 μM, respectively. These findings suggest that these dual inhibitors, 8006-6092, K007-0721, and D011-1471, present promising outcomes, potentially warranting further optimization as lead compounds for the treatment of ASCVD.
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