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CMD: A Database to Store the Bonding States of Cysteine Motifs with Secondary Structures
Author(s) -
Hamed Bostan,
Naomie Salim,
ZetiAzura MohamedHussein,
Peter Klappa,
Mohd Shahir Shamsir
Publication year - 2012
Publication title -
advances in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 20
eISSN - 1687-8035
pISSN - 1687-8027
DOI - 10.1155/2012/849830
Subject(s) - uniprot , cysteine , computer science , protein data bank (rcsb pdb) , sequence motif , protein secondary structure , structural motif , motif (music) , database , sequence alignment , computational biology , peptide sequence , biology , genetics , biochemistry , gene , physics , acoustics , enzyme
Computational approaches to the disulphide bonding state and its connectivity pattern prediction are based on various descriptors. One descriptor is the amino acid sequence motifs flanking the cysteine residue motifs. Despite the existence of disulphide bonding information in many databases and applications, there is no complete reference and motif query available at the moment. Cysteine motif database (CMD) is the first online resource that stores all cysteine residues, their flanking motifs with their secondary structure, and propensity values assignment derived from the laboratory data. We extracted more than 3 million cysteine motifs from PDB and UniProt data, annotated with secondary structure assignment, propensity value assignment, and frequency of occurrence and coefficiency of their bonding status. Removal of redundancies generated 15875 unique flanking motifs that are always bonded and 41577 unique patterns that are always nonbonded. Queries are based on the protein ID, FASTA sequence, sequence motif, and secondary structure individually or in batch format using the provided APIs that allow remote users to query our database via third party software and/or high throughput screening/querying. The CMD offers extensive information about the bonded, free cysteine residues, and their motifs that allows in-depth characterization of the sequence motif composition.

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