Literature DB >> 19899154

Computational design of second-site suppressor mutations at protein-protein interfaces.

Deanne W Sammond1, Ziad M Eletr, Carrie Purbeck, Brian Kuhlman.   

Abstract

The importance of a protein-protein interaction to a signaling pathway can be established by showing that amino acid mutations that weaken the interaction disrupt signaling, and that additional mutations that rescue the interaction recover signaling. Identifying rescue mutations, often referred to as second-site suppressor mutations, controls against scenarios in which the initial deleterious mutation inactivates the protein or disrupts alternative protein-protein interactions. Here, we test a structure-based protocol for identifying second-site suppressor mutations that is based on a strategy previously described by Kortemme and Baker. The molecular modeling software Rosetta is used to scan an interface for point mutations that are predicted to weaken binding but can be rescued by mutations on the partner protein. The protocol typically identifies three types of specificity switches: knob-in-to-hole redesigns, switching hydrophobic interactions to hydrogen bond interactions, and replacing polar interactions with nonpolar interactions. Computational predictions were tested with two separate protein complexes; the G-protein Galpha(i1) bound to the RGS14 GoLoco motif, and UbcH7 bound to the ubiquitin ligase E6AP. Eight designs were experimentally tested. Swapping a buried hydrophobic residue with a polar residue dramatically weakened binding affinities. In none of these cases were we able to identify compensating mutations that returned binding to wild-type affinity, highlighting the challenges inherent in designing buried hydrogen bond networks. The strongest specificity switches were a knob-in-to-hole design (20-fold) and the replacement of a charge-charge interaction with nonpolar interactions (55-fold). In two cases, specificity was further tuned by including mutations distant from the initial design. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

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Year:  2010        PMID: 19899154      PMCID: PMC2903445          DOI: 10.1002/prot.22631

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


  35 in total

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Authors:  B Kuhlman; D Baker
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2.  Automated design of specificity in molecular recognition.

Authors:  James J Havranek; Pehr B Harbury
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Review 3.  Computational design of protein-protein interactions.

Authors:  Tanja Kortemme; David Baker
Journal:  Curr Opin Chem Biol       Date:  2004-02       Impact factor: 8.822

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Authors:  Mayssam H Ali; Christina M Taylor; Gevorg Grigoryan; Karen N Allen; Barbara Imperiali; Amy E Keating
Journal:  Structure       Date:  2005-02       Impact factor: 5.006

5.  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

6.  Hydrogen bonding stabilizes globular proteins.

Authors:  J K Myers; C N Pace
Journal:  Biophys J       Date:  1996-10       Impact factor: 4.033

Review 7.  Hydrogen bonding, hydrophobicity, packing, and protein folding.

Authors:  G D Rose; R Wolfenden
Journal:  Annu Rev Biophys Biomol Struct       Date:  1993

8.  Structure of an E6AP-UbcH7 complex: insights into ubiquitination by the E2-E3 enzyme cascade.

Authors:  L Huang; E Kinnucan; G Wang; S Beaudenon; P M Howley; J M Huibregtse; N P Pavletich
Journal:  Science       Date:  1999-11-12       Impact factor: 47.728

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.  Design of multi-specificity in protein interfaces.

Authors:  Elisabeth L Humphris; Tanja Kortemme
Journal:  PLoS Comput Biol       Date:  2007-07-05       Impact factor: 4.475

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  21 in total

1.  Control of protein signaling using a computationally designed GTPase/GEF orthogonal pair.

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2.  Structural determinants of affinity enhancement between GoLoco motifs and G-protein alpha subunit mutants.

Authors:  Dustin E Bosch; Adam J Kimple; Deanne W Sammond; Robin E Muller; Michael J Miley; Mischa Machius; Brian Kuhlman; Francis S Willard; David P Siderovski
Journal:  J Biol Chem       Date:  2010-11-29       Impact factor: 5.157

Review 3.  Protein binding specificity versus promiscuity.

Authors:  Gideon Schreiber; Amy E Keating
Journal:  Curr Opin Struct Biol       Date:  2010-11-09       Impact factor: 6.809

Review 4.  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

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

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6.  Computational design of an endo-1,4-beta-xylanase ligand binding site.

Authors:  Andrew Morin; Kristian W Kaufmann; Carie Fortenberry; Joel M Harp; Laura S Mizoue; Jens Meiler
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7.  Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition.

Authors:  Cristina Melero; Noah Ollikainen; Ian Harwood; Joel Karpiak; Tanja Kortemme
Journal:  Proc Natl Acad Sci U S A       Date:  2014-10-13       Impact factor: 11.205

Review 8.  Computational design of protein-ligand interfaces: potential in therapeutic development.

Authors:  Andrew Morin; Jens Meiler; Laura S Mizoue
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Review 9.  Specificity in computational protein design.

Authors:  James J Havranek
Journal:  J Biol Chem       Date:  2010-07-29       Impact factor: 5.157

10.  Structure-based redesign of the binding specificity of anti-apoptotic Bcl-x(L).

Authors:  T Scott Chen; Hector Palacios; Amy E Keating
Journal:  J Mol Biol       Date:  2012-11-12       Impact factor: 5.469

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