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Author Spotlight: Unlocking the World of Intrinsically Disordered Regions with Cellular Sensing and Responses
Published on: January 12, 2024
Structural insights into molecular and cellular level FXR binding potentials of GW4064 and LY2562175 hybrids by multi
Tanmoy Banerjee1, Soumya Mitra1,2, Shuvam Sar1
1Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India.
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.
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