IN SILICO DISCOVERY: NATURAL SESQUITERPENES AS NOVEL QUORUM SENSING INHIBITORS TARGETING THE LASR QSLA INTERACTION

Abstract

SBDD is now recognized as an effective computational method in the design of new therapeutics- both in the presence of a detailed 3D crystal structure of the target protein. In this thesis LasR-QslA complex (PDB ID: 4NG2) of Pseudomonas aeruginosa was taken as structure drug target. We only worked with a structural and computational approach, exploiting the precise geometry of the autoinducer-binding space of the complex to discover a more specific inhibitor. A curated library of 2,500 natural phytochemicals filtered by physicochemical drug-likeness criteria was screened using the PyRx-integrated AutoDock Vina engine. The grid box is precisely focused on the coordinates of the co-crystallized native ligand 3-oxo-C12-HSL in the LasR LBD. Validation of the docking protocol was performed by redocking of beta caryophyllene, which exactly reproduced the published affinity value (-5.5 kcal/mol) confirming that the computational setup was methodologically sound. The top-ranked compound was Glomeremophilane B (PubChem CID: 139589801), with a binding affinity of -7.9 kcal/mol thermodynamically superior to both the native autoinducer 3 oxo-C12-HSL (-5.2 kcal/mol) and the reference beta-caryophyllene (-5.5 kcal/mol). Post docking 2D and 3D interaction analysis in BIOVIA Discovery Studio revealed that Glomeremophilane B forms six conventional hydrogen bonds with critical polar residues TRP75, TRP76, THR76, and GLN103 of the LasR binding pocket a dense polar engagement pattern that is structurally far superior to the single H-bond interaction of the native ligand. This thesis primarily argues that the eremophilane sesquiterpene scaffold of glomeremophilane B achieves the ideal pharmacophoric fit for the LasR-QslA autoinducer pocket due to its rigid ring geometry, oxygen-bearing substituents, and multi-point hydrogen bonding capacity. This is a purely structural and mechanistic perspective presented as a 25-page computational study.