Literature DB >> 19422060

X-ray vs. NMR structures as templates for computational protein design.

Michael Schneider1, Xiaoran Fu, Amy E Keating.   

Abstract

Certain protein-design calculations involve using an experimentally determined high-resolution structure as a template to identify new sequences that can adopt the same fold. This approach has led to the successful design of many novel, well-folded, native-like proteins. Although any atomic-resolution structure can serve as a template in such calculations, most successful designs have used high-resolution crystal structures. Because there are many proteins for which crystal structures are not available, it is of interest whether nuclear magnetic resonance (NMR) templates are also appropriate. We have analyzed differences between using X-ray and NMR templates in side-chain repacking and design calculations. We assembled a database of 29 proteins for which both a high-resolution X-ray structure and an ensemble of NMR structures are available. Using these pairs, we compared the rotamericity, chi(1)-angle recovery, and native-sequence recovery of X-ray and NMR templates. We carried out design using RosettaDesign on both types of templates, and compared the energies and packing qualities of the resulting structures. Overall, the X-ray structures were better templates for use with Rosetta. However, for approximately 20% of proteins, a member of the reported NMR ensemble gave rise to designs with similar properties. Re-evaluating RosettaDesign structures with other energy functions indicated much smaller differences between the two types of templates. Ultimately, experiments are required to confirm the utility of particular X-ray and NMR templates. But our data suggest that the lack of a high-resolution X-ray structure should not preclude attempts at computational design if an NMR ensemble is available.

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Year:  2009        PMID: 19422060      PMCID: PMC2732408          DOI: 10.1002/prot.22421

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


  56 in total

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2.  Free-energy calculations highlight differences in accuracy between X-ray and NMR structures and add value to protein structure prediction.

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Journal:  Structure       Date:  2001-10       Impact factor: 5.006

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Authors:  B Kuhlman; D Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

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Authors:  Raphael Guerois; Jens Erik Nielsen; Luis Serrano
Journal:  J Mol Biol       Date:  2002-07-05       Impact factor: 5.469

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Journal:  J Mol Biol       Date:  2002-09-06       Impact factor: 5.469

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Journal:  Acta Crystallogr D Biol Crystallogr       Date:  1993-01-01

Review 7.  Computer-based design of novel protein structures.

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Journal:  Annu Rev Biophys Biomol Struct       Date:  2006

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Authors:  Shaun M Lippow; Bruce Tidor
Journal:  Curr Opin Biotechnol       Date:  2007-07-20       Impact factor: 9.740

9.  Assessing the quality of solution nuclear magnetic resonance structures by complete cross-validation.

Authors:  A T Brünger; G M Clore; A M Gronenborn; R Saffrich; M Nilges
Journal:  Science       Date:  1993-07-16       Impact factor: 47.728

10.  Computational de novo design and characterization of a four-helix bundle protein that selectively binds a nonbiological cofactor.

Authors:  Frank V Cochran; Sophia P Wu; Wei Wang; Vikas Nanda; Jeffery G Saven; Michael J Therien; William F DeGrado
Journal:  J Am Chem Soc       Date:  2005-02-09       Impact factor: 15.419

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  21 in total

1.  Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles.

Authors:  Benjamin D Allen; Alex Nisthal; Stephen L Mayo
Journal:  Proc Natl Acad Sci U S A       Date:  2010-11-02       Impact factor: 11.205

2.  Modeling protein-peptide recognition based on classical quantitative structure-affinity relationship approach: implication for proteome-wide inference of peptide-mediated interactions.

Authors:  Yang Zhou; Zhong Ni; Keping Chen; Haijun Liu; Liang Chen; Chaoqun Lian; Lirong Yan
Journal:  Protein J       Date:  2013-10       Impact factor: 2.371

3.  Optimization of rotamers prior to template minimization improves stability predictions made by computational protein design.

Authors:  James A Davey; Roberto A Chica
Journal:  Protein Sci       Date:  2015-01-13       Impact factor: 6.725

Review 4.  An overview of recent molecular dynamics applications as medicinal chemistry tools for the undruggable site challenge.

Authors:  Ugo Perricone; Maria Rita Gulotta; Jessica Lombino; Barbara Parrino; Stella Cascioferro; Patrizia Diana; Girolamo Cirrincione; Alessandro Padova
Journal:  Medchemcomm       Date:  2018-04-19       Impact factor: 3.597

Review 5.  Multistate approaches in computational protein design.

Authors:  James A Davey; Roberto A Chica
Journal:  Protein Sci       Date:  2012-08-10       Impact factor: 6.725

6.  Computational Analysis of Energy Landscapes Reveals Dynamic Features That Contribute to Binding of Inhibitors to CFTR-Associated Ligand.

Authors:  Graham T Holt; Jonathan D Jou; Nicholas P Gill; Anna U Lowegard; Jeffrey W Martin; Dean R Madden; Bruce R Donald
Journal:  J Phys Chem B       Date:  2019-11-27       Impact factor: 2.991

7.  Analyses of protein cores reveal fundamental differences between solution and crystal structures.

Authors:  Zhe Mei; John D Treado; Alex T Grigas; Zachary A Levine; Lynne Regan; Corey S O'Hern
Journal:  Proteins       Date:  2020-03-05

8.  EvoEF2: accurate and fast energy function for computational protein design.

Authors:  Xiaoqiang Huang; Robin Pearce; Yang Zhang
Journal:  Bioinformatics       Date:  2020-02-15       Impact factor: 6.937

Review 9.  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

10.  Tradeoff between stability and multispecificity in the design of promiscuous proteins.

Authors:  Menachem Fromer; Julia M Shifman
Journal:  PLoS Comput Biol       Date:  2009-12-24       Impact factor: 4.475

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