4HOP

Crystal structure of the computationally designed NNOS-Syntrophin complex


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.29 Å
  • R-Value Free: 0.273 
  • R-Value Work: 0.223 
  • R-Value Observed: 0.226 

wwPDB Validation   3D Report Full Report


This is version 1.4 of the entry. See complete history


Literature

Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition.

Melero, C.Ollikainen, N.Harwood, I.Karpiak, J.Kortemme, T.

(2014) Proc Natl Acad Sci U S A 111: 15426-15431

  • DOI: https://doi.org/10.1073/pnas.1410624111
  • Primary Citation of Related Structures:  
    4HOP

  • PubMed Abstract: 

    Reengineering protein-protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of "second-site suppressors," where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in protein-protein interfaces. To extend this approach, it would be advantageous to be able to "transplant" existing engineered and experimentally validated specificity changes to other homologous protein-protein complexes. Here, we test this strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domain-peptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous protein-protein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. Although the context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing protein-protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.


  • Organizational Affiliation

    Department of Bioengineering and Therapeutic Sciences.


Macromolecules
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChains Sequence LengthOrganismDetailsImage
Alpha-1-syntrophin
A, C, E
88Mus musculusMutation(s): 1 
Gene Names: Snt1Snta1
UniProt
Find proteins for Q61234 (Mus musculus)
Explore Q61234 
Go to UniProtKB:  Q61234
Entity Groups  
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UniProt GroupQ61234
Sequence Annotations
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  • Reference Sequence
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 2
MoleculeChains Sequence LengthOrganismDetailsImage
Nitric oxide synthase, brain
B, D, F
123Rattus norvegicusMutation(s): 1 
Gene Names: BnosNos1
EC: 1.14.13.39
UniProt
Find proteins for P29476 (Rattus norvegicus)
Explore P29476 
Go to UniProtKB:  P29476
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupP29476
Sequence Annotations
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  • Reference Sequence
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.29 Å
  • R-Value Free: 0.273 
  • R-Value Work: 0.223 
  • R-Value Observed: 0.226 
  • Space Group: P 1 21 1
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 61.196α = 90
b = 102.503β = 118.61
c = 64.1γ = 90
Software Package:
Software NamePurpose
MOLREPphasing
REFMACrefinement
HKL-2000data reduction
HKL-2000data scaling

Structure Validation

View Full Validation Report



Entry History 

Deposition Data

Revision History  (Full details and data files)

  • Version 1.0: 2013-11-06
    Type: Initial release
  • Version 1.1: 2014-10-15
    Changes: Database references
  • Version 1.2: 2014-10-29
    Changes: Database references
  • Version 1.3: 2014-11-12
    Changes: Database references
  • Version 1.4: 2023-09-20
    Changes: Data collection, Database references, Refinement description