Literature DB >> 21800121

Fast side chain replacement in proteins using a coarse-grained approach for evaluating the effects of mutation during evolution.

Johan A Grahnen1, Jan Kubelka, David A Liberles.   

Abstract

For high-throughput structural genomic and evolutionary bioinformatics approaches, there is a clear need for fast methods to evaluate substitutions structurally. Coarse-grained methods are both powerful and fast, and a coarse-grained approach to position the substituted side chains is presented. Through the application of a coarse-grained method, a speed-up on the single- residue replacement, of at least sevenfold is achieved compared with modern all-atom approaches. At the same time, this approach maintains a small median RMSD from the leading all-atom approach (as measured in coarse-grained space), and predicts the conformation of point mutants with similar accuracy and generates biologically realistic side chain angles. This method is also substantially more predictable in its run time, making it useful for high-throughput studies of protein structural evolution. To demonstrate the utility of this method, it has been implemented in a forward simulation of sequences threaded through the SH2 domains, with selective pressures to fold and bind specifically. The relative substitution rates across the protein structure and at the binding interface are reflective of those observed in SH2 domain evolution. The algorithm has been implemented in C++, with the source code and binaries (currently supported for Linux systems) freely available as SARA at http://www.wyomingbioinformatics.org/LiberlesGroup/SARA . © Springer Science+Business Media, LLC 2011

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Year:  2011        PMID: 21800121     DOI: 10.1007/s00239-011-9454-3

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  39 in total

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Review 3.  Binding constraints on the evolution of enzymes and signalling proteins: the important role of negative pleiotropy.

Authors:  David A Liberles; Makayla D M Tisdell; Johan A Grahnen
Journal:  Proc Biol Sci       Date:  2011-04-13       Impact factor: 5.349

4.  Improving protein secondary structure prediction using a simple k-mer model.

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5.  Conserved residues and the mechanism of protein folding.

Authors:  E Shakhnovich; V Abkevich; O Ptitsyn
Journal:  Nature       Date:  1996-01-04       Impact factor: 49.962

6.  Lineage-specific differences in the amino acid substitution process.

Authors:  Snehalata Huzurbazar; Grigory Kolesov; Steven E Massey; Katherine C Harris; Alexander Churbanov; David A Liberles
Journal:  J Mol Biol       Date:  2010-01-15       Impact factor: 5.469

7.  A united residue force-field for calcium-protein interactions.

Authors:  Mey Khalili; Jeffrey A Saunders; Adam Liwo; Stanislaw Ołdziej; Harold A Scheraga
Journal:  Protein Sci       Date:  2004-10       Impact factor: 6.725

8.  Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions.

Authors:  Vladimir Potapov; Mati Cohen; Yuval Inbar; Gideon Schreiber
Journal:  BMC Bioinformatics       Date:  2010-07-12       Impact factor: 3.169

9.  ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions.

Authors:  M D Shaji Kumar; K Abdulla Bava; M Michael Gromiha; Ponraj Prabakaran; Koji Kitajima; Hatsuho Uedaira; Akinori Sarai
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

10.  An epistatic ratchet constrains the direction of glucocorticoid receptor evolution.

Authors:  Jamie T Bridgham; Eric A Ortlund; Joseph W Thornton
Journal:  Nature       Date:  2009-09-24       Impact factor: 49.962

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  2 in total

1.  A new parameter-rich structure-aware mechanistic model for amino acid substitution during evolution.

Authors:  Peter B Chi; Dohyup Kim; Jason K Lai; Nadia Bykova; Claudia C Weber; Jan Kubelka; David A Liberles
Journal:  Proteins       Date:  2017-12-12

2.  Biophysical and structural considerations for protein sequence evolution.

Authors:  Johan A Grahnen; Priyanka Nandakumar; Jan Kubelka; David A Liberles
Journal:  BMC Evol Biol       Date:  2011-12-16       Impact factor: 3.260

  2 in total

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