Literature DB >> 8710826

Confronting the problem of interconnected structural changes in the comparative modeling of proteins.

R Samudrala1, J T Pedersen, H B Zhou, R Luo, K Fidelis, J Moult.   

Abstract

Comparative models of three proteins have been built using a variety of computational methods, heavily supplemented by visual inspection. We consider the accuracy obtained to be worse than expected. A careful analysis of the models shows that a major reason for the poor results is the interconnectedness of the structural differences between the target proteins and the template structures they were modeled from. Side chain conformations are often determined by details of the structure remote in the sequence, and can be influenced by relatively small main chain changes. Almost all of the regions of substantial main chain conformational change interact with at least one other such region, so that they often cannot be modeled independently. Visual inspection is sometimes effective in correcting errors in sequence alignment and in spotting when an alternative template structure is more appropriate. We expect some improvements in the near future through the development of structure-based sequence alignment tools, side chain interconnectedness rotamer choice algorithms, and a better understanding of the context sensitivity of conformational features.

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Year:  1995        PMID: 8710826     DOI: 10.1002/prot.340230307

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


  4 in total

1.  Factors limiting the performance of prediction-based fold recognition methods.

Authors:  X de la Cruz; J M Thornton
Journal:  Protein Sci       Date:  1999-04       Impact factor: 6.725

2.  PROTINFO: Secondary and tertiary protein structure prediction.

Authors:  Ling-Hong Hung; Ram Samudrala
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

3.  PROTINFO: new algorithms for enhanced protein structure predictions.

Authors:  Ling-Hong Hung; Shing-Chung Ngan; Tianyun Liu; Ram Samudrala
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

4.  A comprehensive analysis of 40 blind protein structure predictions.

Authors:  Ram Samudrala; Michael Levitt
Journal:  BMC Struct Biol       Date:  2002-08-01
  4 in total

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