Paweł Dudzic

PDV provides a lightweight, browser-based molecular visualization tool with validated quantitative structural analysis and antibody-specific features.

NAStructuralDB provides a processed dataset of antibody, Nanobody, and protein structures with molecular contact information and annotations to aid in predictive tasks.

The paper develops the ASD database to aggregate antibody-antigen interaction data from multiple sources, providing a standardized resource for computational model development.

This study benchmarks inverse folding methods for antibody design to assess their effectiveness in predicting binder sequences given a structure.

The paper curates a database of therapeutic antibodies linked to clinical trial outcomes, identifies poor performance of existing tools in predicting immunogenicity, and highlights the need for systems immunology approaches.

The paper creates a dataset of antibody-antigen complexes with mutations and evaluates affinity prediction methods, finding that current models poorly predict binding effects compared to empirical methods.

PairedAbNGS pools 58 single-cell bioprojects of natural paired human and mouse antibodies, revealing heavy/light V gene pairing biases beyond usage frequencies and conserved CDR3-FWR2 inter-chain contacts.

The paper introduces nanoFOLD, an inverse folding method for designing nanobodies, and applies it to binder enrichment and novel design.

RIOT annotates immunoglobulin sequences by handling nucleotide and amino acid data, using an open germline database, and improving speed and accuracy over existing tools.

The paper shows that pre-training deep learning models on physically accurate antibody structures improves the prediction of physically plausible CDR-H3 loop geometries.