Revolutionizing diabetes treatment: computational insights into 4-hydroxy isoleucine derivatives and advanced molecular screening for antidiabetic compounds

Abstract

Aim: This study aimed to computationally identify and optimize 4-hydroxy isoleucine (4HILe) derivatives from fenugreek as multitarget antidiabetic agents against α-glucosidase, α-amylase, and aldose reductase [PDB (protein data bank) IDs: 5NN8, 4GQR, 4QX4].

Methods: A multi-step computational workflow was employed to identify and optimize 4HILe derivatives as antidiabetic agents. Molecular docking using the Schrödinger Suite screened 23 ligands against three enzyme targets to evaluate binding affinities and interactions. Molecular dynamic (MD) simulations conducted with GROMACS (Groningen machine chemical simulations) over 100 ns assessed conformational stability through RMSD (root mean square deviation) and RMSF (root mean square fluctuation) analysis. Binding free energy calculations [MM-GBSA (molecular mechanics-generalized Born surface area)] and free energy landscape (FEL) studies are performed to validate the thermodynamics of protein-ligand interactions. Additionally, generative AI modeling using LigDream generated 100 novel compounds derived from 4HILe, subsequently validated through docking studies to identify promising inhibitors.

Results: The study identified 4HILe-4, 2R-3S-4R-4HILe, and 4HILe-Amide-2 as potent derivatives with superior binding affinities [ΔG (Gibbs free energy): −49.3 to −42.3 kcal/mol] compared to co-crystal ligands (−45.3 kcal/mol), as determined by docking and MM-GBSA calculations. MD revealed stable protein-ligand complexes, evidenced by low RMSD values (0.2–0.4 nm) and minimal residue fluctuations (RMSF), confirming their structural integrity. The generative AI approach using LigDream also generated 100 novel 4HILe derivatives, with top candidates exhibiting strong docking scores and key molecular interactions against α-glucosidase, α-amylase, and aldose reductase. Notably, compound 10 (−9.424 kcal/mol), compound 4 (−8.167 kcal/mol), and compound 28 (−13.760 kcal/mol) emerged as promising inhibitors for further investigation.

Conclusions: The study highlights 4HILe derivatives as promising inhibitors for diabetes-associated enzymes, demonstrating robust binding and dynamic stability. Integrating molecular dynamics, free energy calculations, and AI-driven generative modeling provides a strong framework for accelerating antidiabetic drug discovery. These findings pave the way for experimental validation and the development of next-generation therapeutics targeting insulin resistance and hyperglycemia.

Keywords

Diabetes / α-glucosidase / α-amylase / aldose reductase / inhibitors / docking / molecular dynamics / binding free energy

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