MOLECULAR DOCKING AND ADMET-BASED COMPUTATIONAL PRIORITIZATION OF CARBONIC ANHYDRASE IX INHIBITORS

Abstract

Cancer cells thrive in hostile environments by activating specific molecular pathways. Inhibiting these survival mechanisms presents a valuable approach for developing targeted anticancer therapies. In this study, a library of 27 natural and semi-synthetic ligands was screened through molecular docking against the CA IX extracellular domain (PDB ID: 3IAI) using AutoDock 4.2.6. Subsequently, pharmacokinetic and toxicological characteristics were assessed using ADMETlab 2.0. A composite scoring method integrating docking affinity, drug-likeness rules, and toxicity penalties enabled systematic prioritization of candidates. Drug-likeness evaluation showed full Lipinski rule compliance, with ~65% of compounds passing additional filters (Pfizer, GSK, Golden Triangle). Among them, Naringenin, 6-hydroxyflavone-3-sulfonic acid, and a coumarin–sulfonamide hybrid exhibited strong binding, rule compliance, and favorable ADMET profiles. The results support these scaffolds as promising leads for CA IX inhibition and demonstrate the value of integrated in silico approaches in anticancer drug design.