Biomedical subjects

G Pugalenthi

Publications and source records attributed to G Pugalenthi.

5 recordsLinked to original sources

PubMed2006

HARMONY: a server for the assessment of protein structures.

Protein structure validation is an important step in computational modeling and structure determination. Stereochemical assessment of protein structures examine internal parameters such as bond lengths and Ramachandran (varphi,psi) angles. Gross structure prediction methods such as inverse folding procedure and structure determination especially at low resolution can sometimes give rise to models that are incorrect due to assignment of misfolds or mistracing of electron density maps. Such errors are not reflected as strain in internal parameters. HARMONY is a procedure that examines the compatibility between the sequence and the structure of a protein by assigning scores to individual residues and their amino acid exchange patterns after considering their local environments. Local environments are described by the backbone conformation, solvent accessibility and hydrogen bonding patterns. We are now providing HARMONY through a web server such that users can submit their protein structure files and, if required, the alignment of homologous sequences. Scores are mapped on the structure for subsequent examination that is useful to also recognize regions of possible local errors in protein structures. HARMONY server is located at http://caps.ncbs.res.in/harmony/

Algorithms↗

PubMed2005

Native and modeled disulfide bonds in proteins: knowledge-based approaches toward structure prediction of disulfide-rich polypeptides.

Structure prediction and three-dimensional modeling of disulfide-rich systems are challenging due to the limited number of such folds in the structural databank. We exploit the stereochemical compatibility of substructures in known protein structures to accommodate disulfide bonds in predicting the structures of disulfide-rich polypeptides directly from disulfide connectivity pattern and amino acid sequence in the absence of structural homologs and any other structural information. This knowledge-based approach is illustrated using structure prediction of 40 nonredundant bioactive disulfide-rich polypeptides such as toxins, growth factors, and endothelins available in the structural databank. The polypeptide conformation could be predicted in 35 out of 40 nonredundant entries (87%). Nonhomologous templates could be identified and models could be obtained within 2 A deviation from the query in 29 peptides (72%). This procedure can be accessed from the World Wide Web (http://www.ncbs.res.in/ approximately faculty/mini/dsdbase/dsdbase.html).

Algorithms↗

PubMed2004

iMOT: an interactive package for the selection of spatially interacting motifs.

Functional selection and three-dimensional structural constraints of proteins relate to the retention of significant sequence similarity between proteins of similar fold and function despite poor overall sequence identity and evolutionary pressures. We report the availability of 'iMOT' (interacting MOTif) server, an interactive package for the automatic identification of spatially interacting motifs among distantly related proteins sharing similar folds and possessing common ancestral lineage. Spatial interactions between conserved stretches of a protein are evaluated by calculations of pseudo-potentials that describe the strength of interactions. Such an evaluation permits the automatic identification of highly interacting conserved regions of a protein. Interacting motifs have been shown to be useful in searching for distant homologues and establishing remote homologies among the largely unassigned sequences in genome databases. Information on such motifs should also be of value in protein folding, modelling and engineering experiments. The iMOT server can be accessed from http://www.ncbs.res.in/~faculty/mini/imot/iMOTserver.html. Supplementary Material can be accessed from: http://www.ncbs.res.in/~faculty/mini/imot/supplementary.html.

Amino Acid Motifs↗

PubMed2004

DSDBASE: a consortium of native and modelled disulphide bonds in proteins.

DSDBASE is a database of disulphide bonds in proteins, which provides information on native disulphides and those that are stereochemically possible between pairs of residues for all known protein structural entries. The modelling of disulphides has been performed, using MODIP, by the identification of residue pairs that can strainlessly accommodate a covalent cross-link. We also assess the stereochemical quality of the covalent cross-link and grade them appropriately. One of the potential uses of the database is to design site-directed mutants in order to enhance the thermal stability of a protein. The proposed sites of mutations can be viewed specifically with respect to active sites of enzymes and across physiological dimers. The occurrence of native and modelled disulphides increases the dimensions of the database enormously. This database can also be employed for proposing three-dimensional models of disulphide-rich short polypeptides. The database can be accessed from http://www.ncbs.res.in/ approximately faculty/mini/dsdbase/dsdbase.html. Supplementary information can be accessed from http://www.ncbs.res.in/ approximately faculty/mini/dsdbase/nar/suppl.htm.

Animals↗

PubMed2003

DDBASE2.0: updated domain database with improved identification of structural domains.

MOTIVATION: Although many methods are available for the identification of structural domains from protein three-dimensional structures, accurate definition of protein domains and the curation of such data for a large number of proteins are often possible only after manual intervention. The availability of domain definitions for protein structural entries is useful for the sequence analysis of aligned domains, structure comparison, fold recognition procedures and understanding protein folding, domain stability and flexibility. RESULTS: We have improved our method of domain identification starting from the concept of clustering secondary structural elements, but with an intention of reducing the number of discontinuous segments in identified domains. The results of our modified and automatic approach have been compared with the domain definitions from other databases. On a test data set of 55 proteins, this method acquires high agreement (88%) in the number of domains with the crystallographers' definition and resources such as SCOP, CATH, DALI, 3Dee and PDP databases. This method also obtains 98% overlap score with the other resources in the definition of domain boundaries of the 55 proteins. We have examined the domain arrangements of 4592 non-redundant protein chains using the improved method to include 5409 domains leading to an update of the structural domain database. AVAILABILITY: The latest version of the domain database and online domain identification methods are available from http://www.ncbs.res.in/~faculty/mini/ddbase/ddbase.html SUPPLEMENTARY INFORMATION: http://www.ncbs.res.in/~faculty/mini/ddbase/supplementary/supplementary.html

Amino Acid Sequence↗