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Protein docking using a single representation for protein surface, electrostatics and local dynamics

Rudden, Lucas S.P.; Degiacomi, Matteo T.

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Authors

Lucas S.P. Rudden



Abstract

Predicting the assembly of multiple proteins into specific complexes is critical to the understanding of their biological function in an organism, and thus the design of drugs to address their malfunction. Proteins are flexible molecules, and this inherently poses a problem to any protein docking computational method, where even a simple rearrangement of the side chain and backbone atoms at the interface of binding partners complicates the successful determination of the correct docked pose. Herein, we present a means of representing protein surface, electrostatics and local dynamics within a single volumetric descriptor. We show that our representations can be physically related to the surface accessible solvent area and mass of the protein. We then demonstrate that the application of this representation into a protein-protein docking scenario bypasses the need to compensate for, and predict, specific side chain packing at the interface of binding partners. This representation is leveraged in our de novo protein docking software, JabberDock, which we show can accurately and robustly predict difficult target complexes with an average success rate of >54%, which is comparable to or greater than currently available methods.

Citation

Rudden, L. S., & Degiacomi, M. T. (2019). Protein docking using a single representation for protein surface, electrostatics and local dynamics. Journal of Chemical Theory and Computation, 15(9), 5135-5143. https://doi.org/10.1021/acs.jctc.9b00474

Journal Article Type Article
Acceptance Date Aug 7, 2019
Online Publication Date Aug 7, 2019
Publication Date Sep 10, 2019
Deposit Date Aug 19, 2019
Publicly Available Date Aug 19, 2019
Journal Journal of Chemical Theory and Computation
Print ISSN 1549-9618
Electronic ISSN 1549-9626
Publisher American Chemical Society
Peer Reviewed Peer Reviewed
Volume 15
Issue 9
Pages 5135-5143
DOI https://doi.org/10.1021/acs.jctc.9b00474
Public URL https://durham-repository.worktribe.com/output/1295011

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Accepted Journal Article (3.7 Mb)
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Copyright Statement
This is an open access article published under a Creative Commons Attribution (CC-BY)
License, which permits unrestricted use, distribution and reproduction in any medium,
provided the author and source are cited.






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