FUNCLAN - FUNctional annotations through Conformational Landscape Analysis

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We will develop FUNCLAN, a framework to provide comparative analyses of conformations and associated annotations. This will be achieved through major improvements to the superposition software GESAMT and will deliver a robust process for superposing and clustering of macromolecular assemblies, protein chains and ligand-binding sites across the Protein Data Bank archive. We will perform a comprehensive analysis of the clustered molecular entities, link them to experimental validation information and map annotations of biological and biophysical contexts to them. We will use this enriched and integrated data to refine the superposition and clustering processes, provide a representative structure for each cluster and design metrics that can be used to evaluate clustered assemblies, protein chains or ligand-binding sites. The FUNCLAN framework will support superposing macromolecular assemblies, where the challenge is partly due to the possibility of changes in topologies accompanied by changes in the conformation of individual components. The project will tackle challenges unique to the superposition of ligand-binding sites, such as superposing amino acid residues interacting with the same small molecule versus superposing small molecules bound in different binding sites.
The project will provide:
1. Software suite and web server for analysing assemblies, proteins chains and ligand binding sites;
2. High-quality manually curated benchmarking datasets of conformational clusters and their biological and biophysical annotations;
3. A robust and iteratively improved pipeline for superposing macromolecular assemblies, proteins chains and ligand-binding sites;
4. Data standards and evaluation metrics for superposed and clustered molecular entities;
5. Clustered molecular entities linked to their validation information and their biological annotations which will be made available programmatically via API and will be displayed on the PDBe-KB entry page