I enjoy making things. Here are a selection of projects that I have worked on over the years.
A deterministic compound triage service for molecular libraries. Ranks, deduplicates, and flags structural liabilities from SMILES inputs using transparent, citable RDKit descriptors and published structural alert catalogs.
A curated catalogue of 3,973 tools for medicinal and computational chemistry, paired with 27 actionable protocols guiding step-by-step drug discovery workflows, target validation against UniProt, and real-time PDB structure prioritization.
An open-access registry, selection wizard, and interactive benchmark dashboard for chemical and biological vector representations. Indexes foundation models across five modalities: small molecules, proteins, complexes, chemical reactions, and nucleic acids, with a programmatic JSON API.
An interactive, visual, first-principles web guide to computer-aided drug design. Covers 18 modules across ligand-receptor binding, molecular docking, pharmacophore modeling, QSAR, molecular dynamics, generative design, and ADMET prediction, each with hands-on browser playgrounds.
A flexible Python framework for building, validating, and applying gradient boosting-based QSAR models, with built-in support for molecular fingerprints, hyperparameter optimization, and model interpretation.
A Jupyter Notebook pipeline for building QSAR classification models for bioactivity prediction, supporting descriptor calculation, feature selection, model training, and applicability domain assessment.
A machine learning ensemble for predicting drug blood-brain barrier permeability. The models, fingerprints, and prediction script are in the GitHub repository. The hosted Streamlit app currently asks visitors to sign in, so the repository is the public entry point.
A curated resource list of computational methods for drug discovery, covering molecular modeling tools, machine learning frameworks, databases, and open-source pipelines organized by application area.
A curated database of secondary metabolites isolated from Artemisia L. species, providing chemical structures, molecular properties, and screening-ready compound libraries for virtual screening campaigns against therapeutic targets.
A manually curated database of naturally occurring coumarins, compiling chemical structures, physicochemical descriptors, and source organism data to support computational screening and structure-activity studies.
