Computational identification of novel SIRT4 inhibitors for diabetic nephropathy using pharmacophore modeling, molecular simulations, and DFT calculations

Abstract

Sirtuin 4 (SIRT4) plays a critical role in regulating oxidative stress, apoptosis, and mitochondrial dysfunction in diabetic nephropathy (DN). This study employed a multi-step in silico strategy to identify novel SIRT4 modulators with potential therapeutic relevance for DN. A ligand-based pharmacophore model was developed using UBCS182, followed by virtual screening of 3,285 compounds from major chemical libraries. Molecular docking revealed strong binding affinities (−9.46 to −8.41 kcal/mol), with CSC057320968, PubChem-162316407, and ChemDiv-V013-1548 emerging as top candidates. ADMET analysis confirmed their favorable pharmacokinetic and toxicity profiles. Subsequent 200 ns molecular dynamics simulations demonstrated the stability of protein–ligand complexes, with CSC057320968 exhibiting the most stable interaction profile based on RMSD, RMSF, Rg, and contact frequency analyses. Principal component analysis and free energy landscapes indicated conformational rigidity and energetic favorability for CSC057320968. Density Functional Theory (DFT) analysis further validated its reactivity and chemical softness, supporting its potential as a lead scaffold. This integrated computational pipeline provides novel insights into SIRT4 modulation and offers a rational framework for targeting mitochondrial dysfunction in DN.