Literature DB >> 7942279

Predicting the conformation of proteins from sequences. Progress and future progress.

S A Benner1, T F Jenny, M A Cohen, G H Gonnet.   

Abstract

A new paradigm for predicting the secondary and tertiary structure of functional proteins from sequence data has emerged from detailed models of how natural selection, conservation, and neutral drift, the three fundamental factors in molecular evolution, leave their mark upon protein sequences. Structural information is extracted from a set of aligned homologous sequences via an analysis of patterns of conservation and variation between proteins with quantitatively defined evolutionary relationships. Tertiary structural information is obtained prior to the assignment of secondary structure, where it plays an important role. Throughout, structural predictions are made with the active involvement of a biochemist whose expertise and insight is critical both for making the prediction and in analyzing its successful and unsuccessful parts. Secondary structure predictions are evaluated based on their ability to sustain an effort to model tertiary structure. Several predictions made using the new paradigm can now be compared with those made under the classical paradigm, including a neural network. The results obtained from the new paradigm are clearly superior to those obtained with the classical paradigm, at least within the protein families that were examined.

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Year:  1994        PMID: 7942279     DOI: 10.1016/0065-2571(94)90021-3

Source DB:  PubMed          Journal:  Adv Enzyme Regul        ISSN: 0065-2571


  3 in total

1.  The identification of conserved interactions within the SH3 domain by alignment of sequences and structures.

Authors:  S M Larson; A R Davidson
Journal:  Protein Sci       Date:  2000-11       Impact factor: 6.725

2.  Improving protein secondary structure prediction with aligned homologous sequences.

Authors:  V Di Francesco; J Garnier; P J Munson
Journal:  Protein Sci       Date:  1996-01       Impact factor: 6.725

3.  A preference-based free-energy parameterization of enzyme-inhibitor binding. Applications to HIV-1-protease inhibitor design.

Authors:  A Wallqvist; R L Jernigan; D G Covell
Journal:  Protein Sci       Date:  1995-09       Impact factor: 6.725

  3 in total

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