Experimental and AI-driven approach to disease understanding A collaborative effort by PDBe and IBDC-ISDA

Workshop Description: The workshop will provide hands-on training in analyzing macromolecular structure data using modern computational methods. Participants will learn how to analyze layers of protein structural data to derive useful biological insights and identify disease associations. This workshop aims to expose participants to 3D Structural Resources at IBDC and PBDe. Participants will explore multiple aspects of the structural data to establish a plausible mechanistic understanding and to generate hypotheses. Structural coordinates, meta-information, variants-disease associations, clinical knowledge mining, Protein-Protein Interface understanding using PDBePISA, AlphaFold, and Ensemble Waterphore Interaction feature modeling will be the major topics for which participants will receive theory and extensive hands-on sessions. Basic proficiency in Python programming to carry out large-scale analysis both in the command-line and Python Programmatic environment.

Participants will complete a rigorous seven-day structural biology training program delivered in a hybrid format: through a five-day preparatory curriculum (virtual mode), participants will build their computational foundations in 3D MacroMolecular Resources and Analysis components at IBDC, e.g., ISDA, BioNode-Structure, and 3DMMR; Python Components to handle structural data files, deeper data insight, and visualization; pyISDA for Sequence-Structure-Variants-Disease-Phenotype detailing; PDBe & 3D-Beacons APIs. This is followed by a two-day, intensive in-campus training at IBDC covering multiple workflows to analyze macromolecular structural data. The curriculum culminates in structural bioinformatics, teaching researchers how to leverage APIs to navigate ISDA/PDBe-KB data, parse structural data (PDB and mmCIF), mine protein-protein interfaces using PDBePISA, manage large structural ensemble analyses, and model interaction features using crystal Water molecules. At the end of the course, participants will be evaluated through a question-and-answer session and will have the opportunity to discuss their own projects with the instructors. The course will be primarily conducted by researchers from PDBe and ISDA-IBDC personnel. The resources at IBDC will be available to participants during the training sessions and on request for their further project work.

Keywords: PDBe, PDBe-KB, ISDA, BioNode-Structure, 3DMMR, Mol* viewer, Ligand-sites, Complex-Interactions, AlphaFold, PDBePISA, Scientific Python Learning, Structural Biology APIs, 3D-Beacons, 3D structural modeling, and Functional Mutation mining.