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Modeling and fitting protein-protein complexes to predict change of binding energy
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
2016 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, 25406Article in journal (Refereed) Published
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Abstract [en]

It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (Delta Delta G), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue Delta Delta G prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict Delta Delta G, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental Delta Delta G measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.

Place, publisher, year, edition, pages
2016. Vol. 6, 25406
National Category
Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-297785DOI: 10.1038/srep25406ISI: 000375797500001PubMedID: 27173910OAI: oai:DiVA.org:uu-297785DiVA: diva2:943599
Funder
eSSENCE - An eScience CollaborationThe Swedish Foundation for International Cooperation in Research and Higher Education (STINT)
Available from: 2016-06-28 Created: 2016-06-28 Last updated: 2017-11-28Bibliographically approved

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