Research Information System
Protein Science, vol.34, no.11, 2025 (SCI-Expanded, Scopus)
Enzymes play a fundamental role in living organisms by catalyzing vital chemical reactions. While much is known about enzyme function, a substantial portion of the proteome remains uncharacterized. Computational tools have become indispensable in this field, yet most focus exclusively on either enzymatic activity prediction or active site detection, creating a gap between residue-level annotation and functional characterization. To bridge this gap, we present Catalytic Activity and Site Prediction and Analysis Tool In Multimer Proteins (CAPIM) —an integrative computational pipeline that combines binding pocket identification and catalytic site annotation with enzymatic activities, along with functional validation via enzyme–substrate docking. CAPIM unifies the capabilities of three established tools: P2Rank, GASS, and AutoDock Vina. P2Rank uses a machine learning-based approach to predict binding pockets, while genetic active site search (GASS) identifies catalytically active residues and annotates them with Enzyme Commission numbers. These outputs are merged to generate residue-level activity profiles within predicted pockets. Functional validation is then performed using AutoDock Vina, enabling substrate docking simulations for user-defined ligands. CAPIM supports any number of peptide chains in the protein complex—which may be crucial for enzymatic functions dependent on quaternary and/or polymeric (e.g., amyloid) structures. The utility of CAPIM is demonstrated through case studies involving both well-characterized enzymes and unannotated multi-chain targets. By delivering residue-level predictions and docking analyses in a unified framework, CAPIM offers a powerful resource with broad applications in drug discovery and protein engineering. CAPIM is available both as a standalone application at https://git.chalmers.se/ozsari/capim-app and as a hosted web service at https://capim-app.serve.scilifelab.se.