{"title":"Structural insights into molecular and cellular level FXR binding potentials of GW4064 and LY2562175 hybrids by multi in silico modelling analyses","authors":"Tanmoy Banerjee, Soumya Mitra, Shuvam Sar, Amit Kumar Halder, Parthasarathi Panda, Nilanjan Ghosh","doi":"10.1007/s00894-025-06336-5","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>Non-alcoholic fatty liver disease (NAFLD) has become a significant health concern. Existing farnesoid X receptor (FXR) agonists like GW4064 and LYS2562175 show poor pharmacokinetics, prompting researchers to develop alternative molecules. This study aims to pinpoint the structural features responsible for exhibiting FXR agonism of a series of hybrid structures of GW4064 and LYS2562175 with improved pharmacokinetic properties which supersede the existing parent ligands. Electronegative components were found to critically influence biological activity on the molecular level, supported by 2D- and 3D-Quantitative Structure Activity Relationship (2D- and 3D-QSAR) analyses. Quantitative Activity-Activity Relationship (QAAR) highlighted key descriptors impacting cellular level FXR binding potential. Molecular dynamics (MD) simulations identified pivotal interactions, such as π-π and H-bond interactions with key residues. Furthermore, binding free energy calculated with Molecular Mechanics with Generalised Born and Surface Area solvation (MM-GBSA) analyses with selected compounds reflected the variations in their binding potential towards FXR protein.</p><h3>Methods</h3><p>The study began by curating ligand SMILES and preparing a dataset with molecular and cellular activity as dependent variables. AlvaDesc descriptors and interpretable descriptors were calculated using the OCHEM webserver. QSAR analyses were performed using Sequential Forward Selection (SFS) and Genetic Algorithm (GA) methods, while QAAR analysis used 50% effective concentration at the molecular level as an independent variable with the same algorithms. 3D QSAR analysis was performed with the Open3DQSAR tool. Docking studies in AutoDock 4.2 with FXR protein identified optimal ligand poses, and 500 ns MD simulations were performed with Amber 20. The use of open-access tools ensures reproducibility and accessibility for future research.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 4","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Modeling","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s00894-025-06336-5","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Context
Non-alcoholic fatty liver disease (NAFLD) has become a significant health concern. Existing farnesoid X receptor (FXR) agonists like GW4064 and LYS2562175 show poor pharmacokinetics, prompting researchers to develop alternative molecules. This study aims to pinpoint the structural features responsible for exhibiting FXR agonism of a series of hybrid structures of GW4064 and LYS2562175 with improved pharmacokinetic properties which supersede the existing parent ligands. Electronegative components were found to critically influence biological activity on the molecular level, supported by 2D- and 3D-Quantitative Structure Activity Relationship (2D- and 3D-QSAR) analyses. Quantitative Activity-Activity Relationship (QAAR) highlighted key descriptors impacting cellular level FXR binding potential. Molecular dynamics (MD) simulations identified pivotal interactions, such as π-π and H-bond interactions with key residues. Furthermore, binding free energy calculated with Molecular Mechanics with Generalised Born and Surface Area solvation (MM-GBSA) analyses with selected compounds reflected the variations in their binding potential towards FXR protein.
Methods
The study began by curating ligand SMILES and preparing a dataset with molecular and cellular activity as dependent variables. AlvaDesc descriptors and interpretable descriptors were calculated using the OCHEM webserver. QSAR analyses were performed using Sequential Forward Selection (SFS) and Genetic Algorithm (GA) methods, while QAAR analysis used 50% effective concentration at the molecular level as an independent variable with the same algorithms. 3D QSAR analysis was performed with the Open3DQSAR tool. Docking studies in AutoDock 4.2 with FXR protein identified optimal ligand poses, and 500 ns MD simulations were performed with Amber 20. The use of open-access tools ensures reproducibility and accessibility for future research.
期刊介绍：
The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling.
Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry.
Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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