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Combined structure-based virtual screening and machine learning approach for the identification of potential dual inhibitors of ACC and DGAT2.
- Source :
-
International journal of biological macromolecules [Int J Biol Macromol] 2024 Oct; Vol. 278 (Pt 1), pp. 134363. Date of Electronic Publication: 2024 Jul 31. - Publication Year :
- 2024
-
Abstract
- Acetyl-coenzyme A carboxylase (ACC) and diacylglycerol acyltransferase 2 (DGAT2) are recognized as potential therapeutic targets for nonalcoholic fatty liver disease (NAFLD). Inhibitors targeting ACC and DGAT2 have exhibited the capacity to reduce hepatic fat in individuals afflicted with NAFLD. However, there are no reports of dual inhibitors targeting ACC and DGAT2 for the treatment of NAFLD. Here, we aimed to identify potential dual inhibitors of ACC and DGAT2 using an integrated in silico approach. Machine learning-based virtual screening of commercial molecule databases yielded 395,729 hits, which were subsequently subjected to molecular docking aimed at both the ACC and DGAT2 binding sites. Based on the docking scores, nine compounds exhibited robust interactions with critical residues of both ACC and DGAT2, displaying favorable drug-like features. Molecular dynamics simulations (MDs) unveiled the substantial impact of these compounds on the conformational dynamics of the proteins. Furthermore, binding free energy assessments highlighted the notable binding affinities of specific compounds (V003-8107, G340-0503, Y200-1700, E999-1199, V003-6429, V025-4981, V006-1474, V025-0499, and V021-8916) to ACC and DGAT2. The compounds proposed in this study, identified using a multifaceted computational strategy, warrant experimental validation as potential dual inhibitors of ACC and DGAT2, with implications for the future development of novel drugs targeting NAFLD.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier B.V. All rights reserved.)
- Subjects :
- Humans
Binding Sites
Protein Binding
Drug Evaluation, Preclinical
Non-alcoholic Fatty Liver Disease drug therapy
Diacylglycerol O-Acyltransferase antagonists & inhibitors
Diacylglycerol O-Acyltransferase chemistry
Diacylglycerol O-Acyltransferase metabolism
Molecular Docking Simulation
Acetyl-CoA Carboxylase antagonists & inhibitors
Acetyl-CoA Carboxylase chemistry
Acetyl-CoA Carboxylase metabolism
Enzyme Inhibitors chemistry
Enzyme Inhibitors pharmacology
Molecular Dynamics Simulation
Machine Learning
Subjects
Details
- Language :
- English
- ISSN :
- 1879-0003
- Volume :
- 278
- Issue :
- Pt 1
- Database :
- MEDLINE
- Journal :
- International journal of biological macromolecules
- Publication Type :
- Academic Journal
- Accession number :
- 39089556
- Full Text :
- https://doi.org/10.1016/j.ijbiomac.2024.134363