Virtual screening approach for fragments selection and merging to lead-like compounds
-
Updated
Aug 20, 2021 - Python
Virtual screening approach for fragments selection and merging to lead-like compounds
Data and analysis scripts used in Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations
A single-file, browser-based chemical data platform for medicinal chemistry — SAR, ADME, MPO, kinase selectivity, AI/ML
Curated cheminformatics analysis of mutant-selective and covalent EGFR inhibitors using ChEMBL bioactivity data, RDKit descriptors, mutation-context labelling, warhead annotation and scaffold analysis.
AI-driven de novo drug discovery: LLM-in-the-loop molecular design + Vina docking + MM-GBSA + MD on EGFR T790M/L858R. Runs on a laptop, no commercial software.
⚡ A repository containing research outputs from my computational chemistry Honours project.
Deep Learning solution to predict kinase inhibitor selectivity using ProteinBERT embeddings and RDKit fingerprints. 2nd Place at PharmaHacks 2025.
Transfer learning computer vision for domain-specific drug-kinase assignment
To associate your repository with the kinase-inhibitors topic, visit your repo's landing page and select "manage topics."