Literature DB >> 20506260

Sequence and structure continuity of evolutionary importance improves protein functional site discovery and annotation.

A D Wilkins1, R Lua, S Erdin, R M Ward, O Lichtarge.   

Abstract

Protein functional sites control most biological processes and are important targets for drug design and protein engineering. To characterize them, the evolutionary trace (ET) ranks the relative importance of residues according to their evolutionary variations. Generally, top-ranked residues cluster spatially to define evolutionary hotspots that predict functional sites in structures. Here, various functions that measure the physical continuity of ET ranks among neighboring residues in the structure, or in the sequence, are shown to inform sequence selection and to improve functional site resolution. This is shown first, in 110 proteins, for which the overlap between top-ranked residues and actual functional sites rose by 8% in significance. Then, on a structural proteomic scale, optimized ET led to better 3D structure-function motifs (3D templates) and, in turn, to enzyme function prediction by the Evolutionary Trace Annotation (ETA) method with better sensitivity of (40% to 53%) and positive predictive value (93% to 94%). This suggests that the similarity of evolutionary importance among neighboring residues in the sequence and in the structure is a universal feature of protein evolution. In practice, this yields a tool for optimizing sequence selections for comparative analysis and, via ET, for better predictions of functional site and function. This should prove useful for the efficient mutational redesign of protein function and for pharmaceutical targeting.

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Year:  2010        PMID: 20506260      PMCID: PMC2974822          DOI: 10.1002/pro.406

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  71 in total

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Authors:  William S J Valdar
Journal:  Proteins       Date:  2002-08-01

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Authors:  Tal Pupko; Rachel E Bell; Itay Mayrose; Fabian Glaser; Nir Ben-Tal
Journal:  Bioinformatics       Date:  2002       Impact factor: 6.937

3.  Enzyme function less conserved than anticipated.

Authors:  Burkhard Rost
Journal:  J Mol Biol       Date:  2002-04-26       Impact factor: 5.469

4.  An accurate, sensitive, and scalable method to identify functional sites in protein structures.

Authors:  Hui Yao; David M Kristensen; Ivana Mihalek; Mathew E Sowa; Chad Shaw; Marek Kimmel; Lydia Kavraki; Olivier Lichtarge
Journal:  J Mol Biol       Date:  2003-02-07       Impact factor: 5.469

5.  ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information.

Authors:  Fabian Glaser; Tal Pupko; Inbal Paz; Rachel E Bell; Dalit Bechor-Shental; Eric Martz; Nir Ben-Tal
Journal:  Bioinformatics       Date:  2003-01       Impact factor: 6.937

6.  Automated discovery of 3D motifs for protein function annotation.

Authors:  Benjamin J Polacco; Patricia C Babbitt
Journal:  Bioinformatics       Date:  2006-01-12       Impact factor: 6.937

7.  Evolutionary and structural feedback on selection of sequences for comparative analysis of proteins.

Authors:  I Mihalek; I Res; O Lichtarge
Journal:  Proteins       Date:  2006-04-01

Review 8.  Rational design of competitive prolactin/growth hormone receptor antagonists.

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9.  De novo computational design of retro-aldol enzymes.

Authors:  Lin Jiang; Eric A Althoff; Fernando R Clemente; Lindsey Doyle; Daniela Röthlisberger; Alexandre Zanghellini; Jasmine L Gallaher; Jamie L Betker; Fujie Tanaka; Carlos F Barbas; Donald Hilvert; Kendall N Houk; Barry L Stoddard; David Baker
Journal:  Science       Date:  2008-03-07       Impact factor: 47.728

10.  Prediction of enzyme function based on 3D templates of evolutionarily important amino acids.

Authors:  David M Kristensen; R Matthew Ward; Andreas Martin Lisewski; Serkan Erdin; Brian Y Chen; Viacheslav Y Fofanov; Marek Kimmel; Lydia E Kavraki; Olivier Lichtarge
Journal:  BMC Bioinformatics       Date:  2008-01-11       Impact factor: 3.169

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  15 in total

1.  PyETV: a PyMOL evolutionary trace viewer to analyze functional site predictions in protein complexes.

Authors:  Rhonald C Lua; Olivier Lichtarge
Journal:  Bioinformatics       Date:  2010-10-06       Impact factor: 6.937

2.  Evolutionary trace for prediction and redesign of protein functional sites.

Authors:  Angela Wilkins; Serkan Erdin; Rhonald Lua; Olivier Lichtarge
Journal:  Methods Mol Biol       Date:  2012

Review 3.  Protein function prediction: towards integration of similarity metrics.

Authors:  Serkan Erdin; Andreas Martin Lisewski; Olivier Lichtarge
Journal:  Curr Opin Struct Biol       Date:  2011-02-24       Impact factor: 6.809

Review 4.  The use of evolutionary patterns in protein annotation.

Authors:  Angela D Wilkins; Benjamin J Bachman; Serkan Erdin; Olivier Lichtarge
Journal:  Curr Opin Struct Biol       Date:  2012-05-24       Impact factor: 6.809

Review 5.  Prediction and redesign of protein-protein interactions.

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6.  Accounting for epistatic interactions improves the functional analysis of protein structures.

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7.  Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities.

Authors:  Eric Venner; Andreas Martin Lisewski; Serkan Erdin; R Matthew Ward; Shivas R Amin; Olivier Lichtarge
Journal:  PLoS One       Date:  2010-12-13       Impact factor: 3.240

8.  Separation of recombination and SOS response in Escherichia coli RecA suggests LexA interaction sites.

Authors:  Anbu K Adikesavan; Panagiotis Katsonis; David C Marciano; Rhonald Lua; Christophe Herman; Olivier Lichtarge
Journal:  PLoS Genet       Date:  2011-09-01       Impact factor: 5.917

9.  Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and greater coronavirus family.

Authors:  Chen Wang; Daniel M Konecki; David C Marciano; Harikumar Govindarajan; Amanda M Williams; Brigitta Wastuwidyaningtyas; Thomas Bourquard; Panagiotis Katsonis; Olivier Lichtarge
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10.  Function prediction from networks of local evolutionary similarity in protein structure.

Authors:  Serkan Erdin; Eric Venner; Andreas Martin Lisewski; Olivier Lichtarge
Journal:  BMC Bioinformatics       Date:  2013-02-28       Impact factor: 3.169

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