Improved Modeling of Side-Chain-Base Interactions and Plasticity in Protein-DNA Interface Design

Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Journal of Molecular Biology (Impact Factor: 3.96). 03/2012; 419(3-4):255-74. DOI: 10.1016/j.jmb.2012.03.005
Source: PubMed

ABSTRACT Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Homing endonucleases (HEs) can be used to induce targeted genome modification to reduce the fitness of pathogen vectors such as the malaria-transmitting Anopheles gambiae and to correct deleterious mutations in genetic diseases. We describe the creation of an extensive set of HE variants with novel DNA cleavage specificities using an integrated experimental and computational approach. Using computational modeling and an improved selection strategy, which optimizes specificity in addition to activity, we engineered an endonuclease to cleave in a gene associated with Anopheles sterility and another to cleave near a mutation that causes pyruvate kinase deficiency. In the course of this work we observed unanticipated context-dependence between bases which will need to be mechanistically understood for reprogramming of specificity to succeed more generally.
    Nucleic Acids Research 11/2013; 42(4). DOI:10.1093/nar/gkt1212 · 9.11 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Figure optionsDownload full-size imageDownload high-quality image (98 K)Download as PowerPoint slide
  • [Show abstract] [Hide abstract]
    ABSTRACT: Computational design is becoming an integral component in developing novel enzymatic activities. Catalytic efficiencies of man-made enzymes however are far behind their natural counterparts. The discrepancy between laboratory and naturally evolved enzymes suggests that a major catalytic factor is still missing in the computational process. Reorganization energy, which is the origin of catalytic power of natural enzymes, has not been exploited yet for design. As exemplified in case of KE07 Kemp eliminase, this quantity is optimized by directed evolution. Mutations beneficial for evolution, but without direct impact on catalysis can be identified based on contributions to reorganization energy. We propose to incorporate the reorganization energy in scaffold selection to provide highly evolvable initial designs.
    Current opinion in chemical biology 04/2014; 21C:34-41. DOI:10.1016/j.cbpa.2014.03.011 · 7.65 Impact Factor


1 Download
Available from