A New Method to Detect Related Function Among Proteins Independent of Sequence and Fold Homology

• Published in: Journal of molecular biology Vol. 323; no. 2; pp. 387 - 406
• Main Authors: Schmitt, Stefan, Kuhn, Daniel, Klebe, Gerhard
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 18.10.2002
• Subjects: Algorithms; Binding Sites; cavity comparison; data mining; Databases, Protein; de novo design; functional comparison of proteins; Models, Molecular; Molecular Structure; physicochemical properties; Protein Binding; Protein Folding; Protein Structure, Tertiary; Proteins - chemistry; Proteins - metabolism; Reproducibility of Results; de novo design; cavity comparison; physicochemical properties; data mining; functional comparison of proteins
• ISSN: 0022-2836; 1089-8638
• DOI: 10.1016/S0022-2836(02)00811-2

A new method has been developed to detect functional relationships among proteins independent of a given sequence or fold homology. It is based on the idea that protein function is intimately related to the recognition and subsequent response to the binding of a substrate or an endogenous ligand in a well-characterized binding pocket. Thus, recognition of similar ligands, supposedly linked to similar function, requires conserved recognition features exposed in terms of common physicochemical interaction properties via the functional groups of the residues flanking a particular binding cavity. Following a technique commonly used in the comparison of small molecule ligands, generic pseudocenters coding for possible interaction properties were assigned for a large sample set of cavities extracted from the entire PDB and stored in the database Cavbase. Using a particular query cavity a series of related cavities of decreasing similarity is detected based on a clique detection algorithm. The detected similarity is ranked according to property-based surface patches shared in common by the different clique solutions. The approach either retrieves protein cavities accommodating the same (e.g. co-factors) or closely related ligands or it extracts proteins exhibiting similar function in terms of a related catalytic mechanism. Finally the new method has strong potential to suggest alternative molecular skeletons in de novo design. The retrieval of molecular building blocks accommodated in a particular sub-pocket that shares similarity with the pocket in a protein studied by drug design can inspire the discovery of novel ligands.