6C2C

The molecular basis for the functional evolution of an organophosphate hydrolysing enzyme

Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.60 Å
  • R-Value Free: 0.204 
  • R-Value Work: 0.173 
  • R-Value Observed: 0.175 

wwPDB Validation   3D Report Full Report


This is version 1.2 of the entry. See complete history. 


Literature

Higher-order epistasis shapes the fitness landscape of a xenobiotic-degrading enzyme.

Yang, G., Anderson, D.W., Baier, F., Dohmen, E., Hong, N., Carr, P.D., Kamerlin, S.C.L., Jackson, C.J., Bornberg-Bauer, E., Tokuriki, N.

(2019) Nat Chem Biol 15: 1120-1128

  • DOI: 10.1038/s41589-019-0386-3
  • Primary Citation of Related Structures:  
    6C2C

  • PubMed Abstract: 

    • Characterizing the adaptive landscapes that encompass the emergence of novel enzyme functions can provide molecular insights into both enzymatic and evolutionary mechanisms. Here, we combine ancestral protein reconstruction with biochemical, structural and mutational analyses to characterize the functional evolution of methyl-parathion hydrolase (MPH), an organophosphate-degrading enzyme ...

    Characterizing the adaptive landscapes that encompass the emergence of novel enzyme functions can provide molecular insights into both enzymatic and evolutionary mechanisms. Here, we combine ancestral protein reconstruction with biochemical, structural and mutational analyses to characterize the functional evolution of methyl-parathion hydrolase (MPH), an organophosphate-degrading enzyme. We identify five mutations that are necessary and sufficient for the evolution of MPH from an ancestral dihydrocoumarin hydrolase. In-depth analyses of the adaptive landscapes encompassing this evolutionary transition revealed that the mutations form a complex interaction network, defined in part by higher-order epistasis, that constrained the adaptive pathways available. By also characterizing the adaptive landscapes in terms of their functional activities towards three additional organophosphate substrates, we reveal that subtle differences in the polarity of the substrate substituents drastically alter the network of epistatic interactions. Our work suggests that the mutations function collectively to enable substrate recognition via subtle structural repositioning.

    Related Citations: 
    • Higher-order epistatic networks underlie the evolutionary fitness landscape of a xenobiotic-degrading enzyme
      Baier, F., Hong, N.-S., Yang, G., Carr, P.D., Jackson, C., Tokuriki, N., Anderson, D., Dohman, E., Pabis, A., Bornberg-Bauer, E., Kamerlin, C.L.
      (2019) Biorxiv --: --
    Organizational Affiliation: 

    Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada. tokuriki@msl.ubc.ca.



Macromolecules
Find similar proteins by: 
(by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChainsSequence LengthOrganismDetailsImage
dihydrocoumarin hydrolase, AncDHCH1A, B299Pseudomonas sp.Mutation(s): 0 
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
Protein Feature View
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  • Reference Sequence
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.60 Å
  • R-Value Free: 0.204 
  • R-Value Work: 0.173 
  • R-Value Observed: 0.175 
  • Space Group: P 21 21 21
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 57.6α = 90
b = 88.15β = 90
c = 119.8γ = 90
Software Package:
Software NamePurpose
PHENIXrefinement
XDSdata reduction
Aimlessdata scaling
MOLREPphasing

Structure Validation

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Entry History 

Deposition Data

Revision History  (Full details and data files)

  • Version 1.0: 2019-01-16
    Type: Initial release
  • Version 1.1: 2019-01-23
    Changes: Data collection, Database references
  • Version 1.2: 2019-11-06
    Changes: Data collection, Database references