Molecular Modeling and Receptor‐Dependent (RD) 3D‐QSAR Approach to a Set of Antituberculosis Derivatives
Kerly Fernanda Mesquita Pasqualoto, Márcia M. C. Ferreira · QSAR & Combinatorial Science · 2009
Abstract In this study, receptor‐dependent (RD) 3D‐QSAR models were built for a set of thirty‐seven isoniazid derivatives bound to the enoyl‐acp reductase from M. tuberculosis, called InhA (PDB entry code 1zid). Ligand‐receptor (L‐R) molecular dynamics (MD) simulations [500 000 steps; the step size was 0.001 ps (1 fs)] were carried out at 310 K (biological assay temperature). The hypothesized active conformations resulting from a previously reported receptor‐independent (IR) 4D‐QSAR analysis were used as the molecular geometries of each ligand in this structure‐based L‐R binding research. The dependent variable is the reported MIC values against M. tuberculosis var. bovis. The independent variables (descriptors) are energy terms of a modified first‐generation AMBER force field combined with a hydration shell aqueous solvation model. Genetic function approximation (GFA) formalism and partial least squares (PLS) regression were employed as the fitting functions to develop 3D‐QSAR models. The bound ligand solvation energy, the sum of electrostatic and hydrogen bonding energies of the unbound ligand, the bending energy of the unbound ligand, the electrostatic intermolecular L‐R energy, and the change in hydrogen bonding energy upon binding were found as important energy contributions to the binding process. The 3D‐QSAR model at 310 K has good internal and external predictability and may be regarded as representative of the binding process of ligands to InhA.