In silico identification of novel PTP1B inhibitors by the investigation of molecular mechanism, QSAR, and DFT studies
TL;DR
Overall, the synergy of the computational methods has made CID 44560744 a lead scaffold for the development and optimization of selective PTP1B inhibitors for T2DM therapy.
Abstract
Protein tyrosine phosphatase 1B (PTP1B) is a well-known and promising drug target involved in the negative regulation of insulin and leptin signaling, and new anti-diabetic molecules for the treatment of type 2 diabetes are directly in its hands. A series of PTP1B inhibitors was discovered and characterized using in silico techniques, including virtual screening, molecular docking, ADMET profiling, toxicity prediction, VEGA-QSAR analysis, molecular dynamics (MD) simulation, and density functional theory (DFT) calculations. A starting library of 1000 anti-diabetic compounds was screened, and PubChem CID 44560696 was identified as the most successful hit. The most potent inhibitor was then identified as CID 44560744 through chemical analogy-based refinement, with a binding free energy of − 9.13 kcal/mol and the ability to form several stabilizing hydrogen bonds and hydrophobic interactions with the key catalytic residues. DFT-optimized geometry and docking revealed that the lead compound shows high stability and strong PTP1B inhibition, showing superior binding affinity compared to ursolic acid, which exhibited a lower binding energy of − 6.34 kcal mol−1. The MD simulations showed that the PTP1B-ligand complex was structurally stable and compacted during the 200 ns simulation, with desirable profiles for RMSD, RMSF, Rg, SASA, and hydrogen bonds. The DFT and FMO analyses indicated that the compound exhibits extreme chemical reactivity and electron-transfer capability, owing to its low HOMO-LUMO gap, high softness, and moderate electrophilicity. The results of ADMET and toxicity evaluations (SwissADME, ProTox-II, and VEGA-QSAR) pointed to satisfactory solubility, non-carcinogenicity, no mutagenicity, and high pharmacological safety. Overall, the synergy of the computational methods has made CID 44560744 a lead scaffold for the development and optimization of selective PTP1B inhibitors for T2DM therapy.