Structural Similarity Enhances Interaction Propensity of Proteins

Structural similarity enhances interaction propensity of proteins.

We study statistical properties of interacting protein-like surfaces and predict two strong, related effects: (i) statistically enhanced self-attraction of proteins; (ii) statistically enhanced attraction of proteins with similar structures. The effects originate in the fact that the probability to find a pattern self-match between two identical, even randomly organized interacting protein surf...

Structural propensity database of 1 proteins

An overwhelming amount of experimental evidence suggests that elucidations of 7 protein function, interactions, and pathology are incomplete without inclusion of intrinsic protein 8 disorder and structural dynamics. Thus, to expand our understanding of intrinsic protein disorder, 9 we have created a database of secondary structure (SS) propensities for proteins (dSPP) as a 10 reference resource...

Search for structural similarity in proteins

MOTIVATION The expanding protein sequence and structure databases await methods allowing rapid similarity search. Geometric parameters-dihedral angle between two sequential peptide bond planes (V) and radius of curvature (R) as they appear in pentapeptide fragments in polypeptide chains-are proposed for use in evaluating structural similarity in proteins (VeaR). The parabolic (empirical) functi...

INTERACTION OF PROTEINS WITH SMALL MOLECULES

Review Comparison of proteins based on segments structural similarity

We present here a simple method for fast and accurate comparison of proteins using their structures. The algorithm is based on structural alignment of segments of C chains (with size of 99 or 199 residues). The method is optimized in terms of speed and accuracy. We test it on 97 representative proteins with the similarity measure based on the SCOP classification. We compare our algorithm with t...