Literature DB >> 19709874

Backbone flexibility in computational protein design.

Daniel J Mandell1, Tanja Kortemme.   

Abstract

The field of computational protein design has produced striking successes, including the engineering of novel enzymes. Many of these achievements employed methodologies that sample amino acid side-chains on a fixed backbone, while methods that explicitly model backbone flexibility have so far largely focused on the design of new structures rather than functions. Recent methodological improvements in conformational sampling techniques, some borrowed from the field of robotics to model mechanically accessible conformations, now provide exciting opportunities to explore amino acid sequences and backbone structures simultaneously. Incorporating functional constraints into flexible backbone design should help to achieve challenging engineering goals that exploit the role of conformational variability in controlling biological processes, while more generally advancing biophysical understanding of the relationship between variations in protein sequence, structure, dynamics, and function.

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Year:  2009        PMID: 19709874     DOI: 10.1016/j.copbio.2009.07.006

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  49 in total

1.  Improving computational protein design by using structure-derived sequence profile.

Authors:  Liang Dai; Yuedong Yang; Hyung Rae Kim; Yaoqi Zhou
Journal:  Proteins       Date:  2010-08-01

Review 2.  Computational tools for epitope vaccine design and evaluation.

Authors:  Linling He; Jiang Zhu
Journal:  Curr Opin Virol       Date:  2015-03-31       Impact factor: 7.090

Review 3.  Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods.

Authors:  T Scott Chen; Amy E Keating
Journal:  Protein Sci       Date:  2012-06-08       Impact factor: 6.725

4.  Improving computational efficiency and tractability of protein design using a piecemeal approach. A strategy for parallel and distributed protein design.

Authors:  Derek J Pitman; Christian D Schenkelberg; Yao-Ming Huang; Frank D Teets; Daniel DiTursi; Christopher Bystroff
Journal:  Bioinformatics       Date:  2013-12-25       Impact factor: 6.937

Review 5.  Computer-aided design of functional protein interactions.

Authors:  Daniel J Mandell; Tanja Kortemme
Journal:  Nat Chem Biol       Date:  2009-11       Impact factor: 15.040

6.  Design of peptide inhibitors that bind the bZIP domain of Epstein-Barr virus protein BZLF1.

Authors:  T Scott Chen; Aaron W Reinke; Amy E Keating
Journal:  J Mol Biol       Date:  2011-02-25       Impact factor: 5.469

7.  Computational design of the sequence and structure of a protein-binding peptide.

Authors:  Deanne W Sammond; Dustin E Bosch; Glenn L Butterfoss; Carrie Purbeck; Mischa Machius; David P Siderovski; Brian Kuhlman
Journal:  J Am Chem Soc       Date:  2011-03-09       Impact factor: 15.419

Review 8.  Energy functions in de novo protein design: current challenges and future prospects.

Authors:  Zhixiu Li; Yuedong Yang; Jian Zhan; Liang Dai; Yaoqi Zhou
Journal:  Annu Rev Biophys       Date:  2013-02-28       Impact factor: 12.981

9.  Flexible backbone sampling methods to model and design protein alternative conformations.

Authors:  Noah Ollikainen; Colin A Smith; James S Fraser; Tanja Kortemme
Journal:  Methods Enzymol       Date:  2013       Impact factor: 1.600

10.  Pushing the Backbone in Protein-Protein Docking.

Authors:  Daisuke Kuroda; Jeffrey J Gray
Journal:  Structure       Date:  2016-08-25       Impact factor: 5.006

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