Literature DB >> 23139141

A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds.

P Benjamin Stranges1, Brian Kuhlman.   

Abstract

The accurate design of new protein-protein interactions is a longstanding goal of computational protein design. However, most computationally designed interfaces fail to form experimentally. This investigation compares five previously described successful de novo interface designs with 158 failures. Both sets of proteins were designed with the molecular modeling program Rosetta. Designs were considered a success if a high-resolution crystal structure of the complex closely matched the design model and the equilibrium dissociation constant for binding was less than 10 μM. The successes and failures represent a wide variety of interface types and design goals including heterodimers, homodimers, peptide-protein interactions, one-sided designs (i.e., where only one of the proteins was mutated) and two-sided designs. The most striking feature of the successful designs is that they have fewer polar atoms at their interfaces than many of the failed designs. Designs that attempted to create extensive sets of interface-spanning hydrogen bonds resulted in no detectable binding. In contrast, polar atoms make up more than 40% of the interface area of many natural dimers, and native interfaces often contain extensive hydrogen bonding networks. These results suggest that Rosetta may not be accurately balancing hydrogen bonding and electrostatic energies against desolvation penalties and that design processes may not include sufficient sampling to identify side chains in preordered conformations that can fully satisfy the hydrogen bonding potential of the interface.
Copyright © 2012 The Protein Society.

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Year:  2012        PMID: 23139141      PMCID: PMC3575862          DOI: 10.1002/pro.2187

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


  42 in total

1.  Electrostatically optimized Ras-binding Ral guanine dissociation stimulator mutants increase the rate of association by stabilizing the encounter complex.

Authors:  C Kiel; T Selzer; Y Shaul; G Schreiber; C Herrmann
Journal:  Proc Natl Acad Sci U S A       Date:  2004-06-14       Impact factor: 11.205

2.  Computational design of a symmetric homodimer using β-strand assembly.

Authors:  P Benjamin Stranges; Mischa Machius; Michael J Miley; Ashutosh Tripathy; Brian Kuhlman
Journal:  Proc Natl Acad Sci U S A       Date:  2011-12-05       Impact factor: 11.205

Review 3.  Phage display for engineering and analyzing protein interaction interfaces.

Authors:  Sachdev S Sidhu; Shohei Koide
Journal:  Curr Opin Struct Biol       Date:  2007-09-17       Impact factor: 6.809

4.  Structure-based protocol for identifying mutations that enhance protein-protein binding affinities.

Authors:  Deanne W Sammond; Ziad M Eletr; Carrie Purbeck; Randall J Kimple; David P Siderovski; Brian Kuhlman
Journal:  J Mol Biol       Date:  2007-06-08       Impact factor: 5.469

5.  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

6.  Modulating calmodulin binding specificity through computational protein design.

Authors:  Julia M Shifman; Stephen L Mayo
Journal:  J Mol Biol       Date:  2002-10-25       Impact factor: 5.469

7.  A de novo protein binding pair by computational design and directed evolution.

Authors:  John Karanicolas; Jacob E Corn; Irwin Chen; Lukasz A Joachimiak; Orly Dym; Sun H Peck; Shira Albeck; Tamar Unger; Wenxin Hu; Gaohua Liu; Scott Delbecq; Gaetano T Montelione; Clint P Spiegel; David R Liu; David Baker
Journal:  Mol Cell       Date:  2011-03-31       Impact factor: 17.970

8.  Hydration of protein-protein interfaces.

Authors:  Francis Rodier; Ranjit Prasad Bahadur; Pinak Chakrabarti; Joël Janin
Journal:  Proteins       Date:  2005-07-01

9.  Computational design of calmodulin mutants with up to 900-fold increase in binding specificity.

Authors:  Eliyahu Yosef; Regina Politi; Mee H Choi; Julia M Shifman
Journal:  J Mol Biol       Date:  2008-09-27       Impact factor: 5.469

10.  Computer-based redesign of a beta sandwich protein suggests that extensive negative design is not required for de novo beta sheet design.

Authors:  Xiaozhen Hu; Huanchen Wang; Hengming Ke; Brian Kuhlman
Journal:  Structure       Date:  2008-12-10       Impact factor: 5.006

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  77 in total

1.  Computational design and experimental verification of a symmetric protein homodimer.

Authors:  Yun Mou; Po-Ssu Huang; Fang-Ciao Hsu; Shing-Jong Huang; Stephen L Mayo
Journal:  Proc Natl Acad Sci U S A       Date:  2015-08-12       Impact factor: 11.205

2.  Signatures of n→π* interactions in proteins.

Authors:  Robert W Newberry; Gail J Bartlett; Brett VanVeller; Derek N Woolfson; Ronald T Raines
Journal:  Protein Sci       Date:  2014-03       Impact factor: 6.725

3.  Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

Authors:  Jack B Maguire; Scott E Boyken; David Baker; Brian Kuhlman
Journal:  J Chem Theory Comput       Date:  2018-04-20       Impact factor: 6.006

4.  DNA-mediated engineering of multicomponent enzyme crystals.

Authors:  Jeffrey D Brodin; Evelyn Auyeung; Chad A Mirkin
Journal:  Proc Natl Acad Sci U S A       Date:  2015-03-23       Impact factor: 11.205

5.  Computational-guided determination of the functional role of 447-52D long CDRH3.

Authors:  Edwin Kamau; Richard Bonneau; Xiang-Peng Kong
Journal:  Protein Eng Des Sel       Date:  2018-12-01       Impact factor: 1.650

6.  A structural bioinformatics approach for identifying proteins predisposed to bind linear epitopes on pre-selected target proteins.

Authors:  Eun Jung Choi; Ron Jacak; Brian Kuhlman
Journal:  Protein Eng Des Sel       Date:  2013-01-21       Impact factor: 1.650

Review 7.  Forces stabilizing proteins.

Authors:  C Nick Pace; J Martin Scholtz; Gerald R Grimsley
Journal:  FEBS Lett       Date:  2014-05-17       Impact factor: 4.124

8.  An improved Protein G with higher affinity for human/rabbit IgG Fc domains exploiting a computationally designed polar network.

Authors:  Ramesh K Jha; Tiziano Gaiotto; Andrew R M Bradbury; Charlie E M Strauss
Journal:  Protein Eng Des Sel       Date:  2014-03-14       Impact factor: 1.650

9.  Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

Authors:  J C Gaines; S Acebes; A Virrueta; M Butler; L Regan; C S O'Hern
Journal:  Proteins       Date:  2018-02-26

10.  Shape complementarity and hydrogen bond preferences in protein-protein interfaces: implications for antibody modeling and protein-protein docking.

Authors:  Daisuke Kuroda; Jeffrey J Gray
Journal:  Bioinformatics       Date:  2016-04-19       Impact factor: 6.937

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