Introduction:

The interacting motif database or iMOTdb , lists interacting motifs that are identified for all structural entries in the PDB. The conserved patterns or finger prints are identified for individual structural entries and also grouped together for reporting the common motifs shared among all superfamily members. The iMOT package (Bhaduri et al., 2004 ) has been employed for identifying the motifs in the database.

Interacting motifs has been shown to assist our understanding of proteins structure and function. Information on such motifs should be of valuable in protein folding, modeling and engineering experiments. As shown in previous studies conserved spatially interacting motifs act as important constraint in pattern based remote homology search methods (Bhaduri et al., 2004 ). The iMOT DB is provided with links to aid sequence search protocol using PHI-BLAST (Zhang et al, 1998) and SCAN MOT (Chakrabarti., et al., 2005) employing the interacting motifs.

The interacting motifs representing the superfamilies of proteins are derived from structural alignments obtained from PASS2 (Bhaduri et al., 2004 ). These motifs are finger prints for a given protein family and provides useful insights regarding the structural and functional role regarding the protein. Pseudo potential evaluated between the various pairs of motifs reflects the interacting strength between the regions and highlights the thermodymanic stability of the local substructure. The database would thus provide useful insight into the understanding of the folding, structural modeling and envisaging mutational exercise on a given polypeptide.

References

1. Bhaduri, A., Pugalenthi, G., Gupta, N. and Sowdhamini, R. (2004). iMOT: an interactive package for the selection of spatially interacting motifs. Nucleic Acids Research 32, W602-W605

2. Bhaduri.A., Ravishankar, R. and Sowdhamini, R. (2004). Conserved spatially interacting motifs of protein superfamilies: Application to fold recognition and function annotation of genome data. Proteins, 54(4), 657-70.

3. Saikat Chakrabarti., Prem Anand., Nitin Bhardwaj., Pugalenthi, G. and Sowdhamini, R.(2005) SCANMOT: searching for similar sequences using a simultaneous scan of multiple sequence motif. Nucleic Acid Res., 33, 274-276.

4. Bhaduri, A., Pugalenthi, G. and Sowdhamini, R. (2004). PASS2: an automated database of protein alignments organised as structural superfamilies. BMC Bioinformatics 5:35

5. Zhang Z, Schaffer AA, Miller W, Madden TL, Lipman DJ, Koonin EV, Altschul SF. (1998): Protein sequence similarity searches using patterns as seeds. Nucleic Acids Res., 26(17):3986-3990.