Identification of natural compound inhibitors for substrate-binding site of MTHFD2 enzyme: Insights from structure-based drug design and biomolecular simulations

A computational structure-based drug design approach was employed to identify inhibitors targeting the active site of the MTHFD2 enzyme. From a virtual screening of 2,36,561 natural product molecules, 12,764 molecules were retrieved, and 3,277 unique molecules were screened. After drug-likeness and pharmacokinetic filtering, 209 molecules were docked into the active site of the enzyme, and 20 candidates were shortlisted based on docking score and crucial interactions with residues Asn87, Lys88, Gly310, and Gln132. HYDE (HYdrogen Bond and Dehydration Energies) analysis further refined the selection to eight promising molecules (C1-C8) with docking score >= -30.12 kcal/mol. Through 300 ns molecular dynamics simulations, key properties such as RMSD, RMSF, RoG, H-bond count and lifetime, SASA, PCA, FEL (2D and 3D), and DCCM were evaluated to predict the system stability. The protein-ligand interaction energy analysis revealed that compounds C3, C4, and C6 demonstrated the highest Coulombic energies (-211.58 kJ/mol, -113.25 kJ/mol, and -210.28 kJ/mol, respectively) and Lennard-Jones energies (-150.73 kJ/mol, -161.73 kJ/mol, and -127.70 kJ/mol, respectively), indicating strong binding energies. MM/PBSA free energy calculations supported these findings, with C3 (-33.26 kcal/mol) and C6 (-32.11 kcal/mol) displaying the strongest binding energies, while C5 (-20.59 kcal/mol) exhibited moderate binding affinity. The stability and compactness observed on RoG, H-bond analyses, and FEL results corroborate these binding energies profiles, reinforcing the selectivity and strength of these compounds. These findings demonstrated that compounds C3, C5, and C6 exhibit high stability, and strong binding interactions towards the MTHFD2 enzyme. By integrating multicomplex pharmacophore modeling, molecular dynamics, protein-ligand interaction energy analysis, and free energy calculations, this study offers a framework for identifying novel anticancer agents.