Large-scale annotation of biochemically relevant pockets and tunnels in cognate enzyme-ligand complexes.

ABSTRACT: Tunnels in enzymes with buried active sites are key structural features allowing the entry of substrates and the release of products, thus contributing to the catalytic efficiency. Targeting the bottlenecks of protein tunnels is also a powerful protein engineering strategy. However, the identification of functional tunnels in multiple protein structures is a non-trivial task that can only be addressed computationally. We present a pipeline integrating automated structural analysis with an in-house machine-learning predictor for the annotation of protein pockets, followed by the calculation of the energetics of ligand transport via biochemically relevant tunnels. A thorough validation using eight distinct molecular systems revealed that CaverDock analysis of ligand un/binding is on par with

SUBMITTER: Vavra O 

PROVIDER: S-EPMC11481355 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature