Literature DB >> 14631067

SMoS: a database of structural motifs of protein superfamilies.

Saikat Chakrabarti1, K Venkatramanan, R Sowdhamini.   

Abstract

The Structural Motifs of Superfamilies (SMoS) database provides information about the structural motifs of aligned protein domain superfamilies. Such motifs among structurally aligned multiple members of protein superfamilies are recognized by the conservation of amino acid preference and solvent inaccessibility and are examined for the conservation of other features like secondary structural content, hydrogen bonding, non-polar interaction and residue packing. These motifs, along with their sequence and spatial orientation, represent the conserved core structure of each superfamily and also provide the minimal requirement of sequence and structural information to retain each superfamily fold.

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Year:  2003        PMID: 14631067     DOI: 10.1093/protein/gzg110

Source DB:  PubMed          Journal:  Protein Eng        ISSN: 0269-2139


  7 in total

1.  SCANMOT: searching for similar sequences using a simultaneous scan of multiple sequence motifs.

Authors:  Saikat Chakrabarti; A Prem Anand; Nitin Bhardwaj; Ganesan Pugalenthi; R Sowdhamini
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

2.  iMOTdb--a comprehensive collection of spatially interacting motifs in proteins.

Authors:  Ganesan Pugalenthi; Anirban Bhaduri; R Sowdhamini
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

3.  MegaMotifBase: a database of structural motifs in protein families and superfamilies.

Authors:  Ganesan Pugalenthi; P N Suganthan; R Sowdhamini; Saikat Chakrabarti
Journal:  Nucleic Acids Res       Date:  2007-10-11       Impact factor: 16.971

4.  Improvement of alignment accuracy utilizing sequentially conserved motifs.

Authors:  Saikat Chakrabarti; Nitin Bhardwaj; Prem A Anand; Ramanathan Sowdhamini
Journal:  BMC Bioinformatics       Date:  2004-10-28       Impact factor: 3.169

5.  Identification of structurally conserved residues of proteins in absence of structural homologs using neural network ensemble.

Authors:  Ganesan Pugalenthi; Ke Tang; P N Suganthan; Saikat Chakrabarti
Journal:  Bioinformatics       Date:  2008-11-27       Impact factor: 6.937

6.  PASS2: an automated database of protein alignments organised as structural superfamilies.

Authors:  Anirban Bhaduri; Ganesan Pugalenthi; Ramanathan Sowdhamini
Journal:  BMC Bioinformatics       Date:  2004-04-02       Impact factor: 3.169

7.  Motif-Aware PRALINE: Improving the alignment of motif regions.

Authors:  Maurits Dijkstra; Punto Bawono; Sanne Abeln; K Anton Feenstra; Wan Fokkink; Jaap Heringa
Journal:  PLoS Comput Biol       Date:  2018-11-01       Impact factor: 4.475

  7 in total

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