This study examines the structure-based polypharmacology of six synthetic glycosidic compounds against six PCOS-related targets using BioSolveIT tools (SeeSAR, FlexX, and infiniSee). It combines residue-level interaction analysis, cross-target score normalization, and large-scale analog expansion to support multi-target lead prioritization. The workflow includes protein preparation, 3D conformer generation, docking of 36 compound-target pairs, HYDE-based pose selection, and redocking validation with success defined as RMSD ≤ 1.5 Å. Downstream analysis will use CPI ranking, interaction fingerprints, and ADMET filtering via SwissADME and pkCSM. The aim is to identify glycosidic scaffolds that modulate steroidogenic, androgen signaling, inflammatory, metabolic, and apoptotic pathways and to prioritize at least two compounds with CPI ≥ +0.5 for follow-up.
Ahmed intends to achieve the following milestones:
- Prepare and validate 6 PCOS targets (CYP17A1, CYP19A1, AR, TNF-α, NAMPT, Caspase-3) and generate 3D conformers.
- Complete FlexX docking and HYDE scoring of the glycosidic compoundس against all six validated targets, with redocking RMSD
- Generate initial compound–target interaction profiles, calculate CPI scores, and rank the top candidates for multi-target activity.