NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection.
|NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection.
|Year of Publication
|Mudgal R, Sandhya S, Kumar G, Sowdhamini R, Chandra NR, Srinivasan N
|Nucleic Acids Res
|Computational Biology, Databases, Protein, Internet, Molecular Sequence Annotation, Protein Structure, Tertiary, Sequence Analysis, Protein, Sequence Homology, Amino Acid
NrichD (http://proline.biochem.iisc.ernet.in/NRICHD/) is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural 'intermediately related sequences' is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been 'enriched' with these artificial intermediary sequences. NrichD database currently contains 3,611,010 artificial sequences that have been generated between 27,882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.
|Nucleic Acids Res.
|PubMed Central ID