Assessment of flexible backbone protein design methods for sequence library prediction in the therapeutic antibody Herceptin–HER2 interface

Authors

  • Mariana Babor,

    1. California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, California 94158-2330
    2. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94158-2330
    Current affiliation:
    1. Mariana Babor's current address is Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, California 92037
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  • Daniel J. Mandell,

    1. California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, California 94158-2330
    2. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94158-2330
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  • Tanja Kortemme

    Corresponding author
    1. California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, California 94158-2330
    2. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94158-2330
    • University of California, San Francisco, 1700 4th Street, Byers Hall 308E, San Francisco, CA 94158-2330===

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  • Author contributions: M.B.: conceived and designed the experiments, performed the experiments and analyzed the data, discussed the data and wrote the manuscript; T.K.: conceived and designed the experiments, discussed the data and wrote the manuscript; D.J.M.: developed the KIC refinement design protocol, discussed the data and wrote the manuscript.

Abstract

Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low-energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that should broaden the range of predicted low-energy sequences. Here, we evaluate computational predictions of sequence libraries from different protocols for modeling backbone flexibility using the complex between the therapeutic antibody Herceptin and its target human epidermal growth factor receptor 2 (HER2) as a model system. Within the program RosettaDesign, three methods are compared: The first two use ensembles of structures generated by Monte Carlo protocols for near-native conformational sampling: kinematic closure (KIC) and backrub, and the third method uses snapshots from molecular dynamics (MD) simulations. KIC or backrub methods were better able to identify the amino acid residues experimentally observed by phage display in the Herceptin–HER2 interface than MD snapshots, which generated much larger conformational and sequence diversity. KIC and backrub, as well as fixed backbone simulations, captured the key mutation Asp98Trp in Herceptin, which leads to a further threefold affinity improvement of the already subnanomolar parental Herceptin-HER2 interface. Modeling subtle backbone conformational changes may assist in the design of sequence libraries for improving the affinity of antibody–antigen interfaces and could be suitable for other protein complexes for which structural information is available.

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