CAPIM: Catalytic activity and site prediction and analysis tool in multimer proteins

Artikel i vetenskaplig tidskrift, 2025

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.