Literature DB >> 11119639

Conserved key amino acid positions (CKAAPs) derived from the analysis of common substructures in proteins.

B V Reddy1, W W Li, I N Shindyalov, P E Bourne.   

Abstract

An all-against-all protein structure comparison using the Combinatorial Extension (CE) algorithm applied to a representative set of PDB structures revealed a gallery of common substructures in proteins (http://cl.sdsc.edu/ce.html). These substructures represent commonly identified folds, domains, or components thereof. Most of the subsequences forming these similar substructures have no significant sequence similarity. We present a method to identify conserved amino acid positions and residue-dependent property clusters within these subsequences starting with structure alignments. Each of the subsequences is aligned to its homologues in SWALL, a nonredundant protein sequence database. The most similar sequences are purged into a common frequency matrix, and weighted homologues of each one of the subsequences are used in scoring for conserved key amino acid positions (CKAAPs). We have set the top 20% of the high-scoring positions in each substructure to be CKAAPs. It is hypothesized that CKAAPs may be responsible for the common folding patterns in either a local or global view of the protein-folding pathway. Where a significant number of structures exist, CKAAPs have also been identified in structure alignments of complete polypeptide chains from the same protein family or superfamily. Evidence to support the presence of CKAAPs comes from other computational approaches and experimental studies of mutation and protein-folding experiments, notably the Paracelsus challenge. Finally, the structural environment of CKAAPs versus non-CKAAPs is examined for solvent accessibility, hydrogen bonding, and secondary structure. The identification of CKAAPs has important implications for protein engineering, fold recognition, modeling, and structure prediction studies and is dependent on the availability of structures and an accurate structure alignment methodology. Proteins 2001;42:148-163. Copyright 2000 Wiley-Liss, Inc.

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Year:  2001        PMID: 11119639     DOI: 10.1002/1097-0134(20010201)42:2<148::aid-prot20>3.0.co;2-r

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  14 in total

1.  CKAAPs DB: a conserved key amino acid positions database.

Authors:  W W Li; B V Reddy; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2001-01-01       Impact factor: 16.971

2.  Persistently conserved positions in structurally similar, sequence dissimilar proteins: roles in preserving protein fold and function.

Authors:  Iddo Friedberg; Hanah Margalit
Journal:  Protein Sci       Date:  2002-02       Impact factor: 6.725

3.  CKAAPs DB: a Conserved Key Amino Acid Positions DataBase.

Authors:  Wilfred W Li; Boojala V B Reddy; John G Tate; Ilya N Shindyalov; Philip E Bourne
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

4.  MAMMOTH (matching molecular models obtained from theory): an automated method for model comparison.

Authors:  Angel R Ortiz; Charlie E M Strauss; Osvaldo Olmea
Journal:  Protein Sci       Date:  2002-11       Impact factor: 6.725

Review 5.  Structural genomics: computational methods for structure analysis.

Authors:  Sharon Goldsmith-Fischman; Barry Honig
Journal:  Protein Sci       Date:  2003-09       Impact factor: 6.725

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

Authors:  A Bhaduri; G Pugalenthi; N Gupta; R Sowdhamini
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

7.  Automatic generation and evaluation of sparse protein signatures for families of protein structural domains.

Authors:  Matthew J Blades; Jon C Ison; Ranjeeva Ranasinghe; John B C Findlay
Journal:  Protein Sci       Date:  2005-01       Impact factor: 6.725

Review 8.  Template-based protein structure modeling.

Authors:  Andras Fiser
Journal:  Methods Mol Biol       Date:  2010

9.  Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction.

Authors:  Eric D Scheeff; Philip E Bourne
Journal:  BMC Bioinformatics       Date:  2006-09-14       Impact factor: 3.169

10.  ProfileGrids as a new visual representation of large multiple sequence alignments: a case study of the RecA protein family.

Authors:  Alberto I Roca; Albert E Almada; Aaron C Abajian
Journal:  BMC Bioinformatics       Date:  2008-12-22       Impact factor: 3.169

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