Environmental impact on the tautomeric equilibrium of a pyrimidine-2,4-diol scaffold: In silico parametrization, structural transformation, and comparative docking analysis as multi-target directed ligands.
Abstract
Resolving small-molecule tautomeric behavior through predictive frameworks is vital to prevent structural ambiguity during computer-aided drug design. We report an in silico parametrization and structural transformation analysis of a functionalized pyrimidine-2,4-diol scaffold as a Multi-Target Directed Ligand (MTDL). While spectroscopic analysis (MS, NMR) confirms imide-lactim form 3 in organic media, in silico profiling reveals a solvent-dependent shift to amide-lactam tautomer 4 (65-98%) across physiological pH ranges (3.0-7.0). Framework design benefits from paired theoretical screening and optimization, mirroring advanced biomaterials and multi-targeted aminopyrimidine protocols. Unlike rigid standalone pyrimidine cores lacking specialized protein-anchoring networks, our functionalized architecture provides an adaptive pharmacophoric environment compatible with sustainable synthesis matrices. Comparative automated molecular docking (AutoDock Vina, JAMDA) against human carbonic anhydrase (CAXII), CDK2, PptAB, and lactic acid bacterium LAB systems showed superior binding for tautomer 4 over form 3, yielding balanced multi-target affinity (DAR = 0.83-0.92). Computational ADME validation confirmed favorable drug-like profiles matching baseline bioavailability (0.55) with enhanced water solubility (965 mg/mL) and a lowered topological polar surface area (TPSA = 116.64 Å2). Crucially, the automated preprocessing engine independently validated environmental impacts on tautomeric equilibrium, selectively prioritizing the keto form across three target pockets while preserving the structural diol state in the remaining cavity. Final binding topologies achieved high geometric convergence (RMSD down to 0.50 Å). This study provides a rigorous rationale for environmental tautomer bioactivity, establishing a resource-saving predictive filtering tier that highlights the absolute necessity of automated aqueous parametrization and geometric validation prior to physical screening campaigns.