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I will use ml to source compounds for protein interaction
molecular docking, Ai Driven Drug Discovery,3D models
Hey guys, I am a computational biologist and 3D artist.
I use trained API models using pyhton to clean large datasets finding best targets for protein inhibition using lipenski rule of five.
With that...
About this Gig
Target Receptor Preparation: Retrieval, cleaning, and optimization of protein crystal structures directly from the Protein Data Bank (PDB) (e.g., handling missing residues, charging, and grid box mapping).
Ligand Library Curation & Filtering: Fetching compound libraries from databases like ChEMBL or PubChem, followed by strict physicochemical filtering using Python (RDKit) to guarantee drug-likeness (Lipinskis Rule of Five and Veber Criteria).
High-Throughput Virtual Screening (HTVS): Setting up precise binding site coordinates and executing high-throughput screening.
Molecular Docking Simulations: Comprehensive structural docking using AutoDock Vina to generate multi-pose conformational data and extract precise Gibbs free energy binding affinities ($\Delta G$ in kcal/mol).
Data Analytics & Reporting: A clean, publication-ready statistical breakdown (minimum/maximum/mean affinities, standard deviation tracking) identifying your absolute top-tier advanced lead candidates.
