SARAMA: A Standalone Suite of Programs for the Complementarity Plot—A Graphical Structure Validation Tool for Proteins
Sankar Basu, Dhananjay Bhattacharyya, Rahul Banerjee
2013
Journal of Bioinformatics and Intelligent Control
Structure validation is a crucial component not only in protein crystallography but also in model quality estimation in homology modeling, protein design and de-novo structure prediction. Two key attributes of a correctly determined atomic model are optimal packing between side-chains and absence of destabilizing unbalanced electric fields within the interior of a protein molecule. The complementarity plot (CP) combines them in a single unified measure. CP has now been compiled into a user
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... dly validation package and made available as a standalone suite of programs in the public domain (http://www.saha.ac.in/biop/www/sarama.html). The application of CP in the detection of wrong rotamer assignment has been surveyed. We report the free availability of a standalone suite of programs (Sarama) for the Complementarity Plot (Linux Platform) with detailed features and documentation available at the website: http://www.saha.ac.in/biop/www/sarama. html. The basic methodology has already been reported. 1 Briefly, the Complementarity Plot (CP) estimates the shape and electrostatic complementarity of interior residues of a globular protein and is a sensitive indicator of their harmony or disharmony with regard to the short and long range forces sustaining the native fold. A correctly determined natively folded protein structure should have optimal packing between its buried side-chains and absence of destabilizing unbalanced electric fields within the interior of the molecule. CP has already been demonstrated to be effective in detecting local regions of suboptimal packing or electrostatics which were found to be highly correlated to coordinate errors. CP has now been compiled into an user friendly validation package which should be an useful addition in the already existing repertoire of structure validation tools. A set of scores have now been included in the methodology which gives an estimate of the probabilities associated with the distribution of points in the plot and the propensities of specific residues to different degrees solvent exposure. As has been reported previously 1 CP requires the surface (S sc m ) and electrostatic (E sc m complementarity to be computed for buried residues. In this regard, the extent of * Authors to whom correspondence should be addressed. burial (Bur) of every amino acid residue with respect to the solvent was estimated by the ratio of the solvent accessible areas (probe radius: 1.4 Å) 2 of the residue (X) in the polypeptide chain to that of an identical residue in a Gly-X-Gly peptide fragment, in a fully extended conformation. Only those residues with the burial ratio Bur ≤ 0 30 were henceforth considered for the complementarity plot. The van der Waals surface was calculated for the entire polypeptide chain, sampled at 10 dots/Å 2 3 and surface (S sc m and electrostatic (E sc m complementarities calculated for buried or partially buried side-chains. 1 3 For surface complementarity S sc m , only side-chain surface points of buried residues (target) were considered and their nearest neighboring surface points identified from the rest of the polypeptide chain (within a distance of 3.5 Å). Surface points essentially being area elements are characterized by their positions (x y z) and the direction cosines (dl dm dn) of their normals. Then, adapted from Lawrence and Colman, 4 the following expression was calculated: where n a and n b are two unit normal vectors, corresponding to the dot surface point a (located on the side chain surface of the target residue) and b (the dot point nearest to a, within 3.5 Å) respectively, with d ab the distance between them and w, a scaling constant set to 0.5. S sc m was defined as the median of the distribution {S a b }
doi:10.1166/jbic.2013.1059
fatcat:m6prvlzttrhe7fddlq3uz27p4i