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dc.contributor.authorKotthoff, Ian
dc.contributor.authorKundrotas, Petras J.
dc.contributor.authorVakser, Ilya A.
dc.date.accessioned2022-07-08T19:41:20Z
dc.date.available2022-07-08T19:41:20Z
dc.date.issued2022-05-17
dc.identifier.citationKotthoff I, Kundrotas PJ, Vakser IA. DOCKGROUND membrane protein-protein set. PLoS One. 2022 May 17;17(5):e0267531. doi: 10.1371/journal.pone.0267531. PMID: 35580077; PMCID: PMC9113569.en_US
dc.identifier.urihttp://hdl.handle.net/1808/32811
dc.description.abstractMembrane proteins are significantly underrepresented in Protein Data Bank despite their essential role in cellular mechanisms and the major progress in experimental protein structure determination. Thus, computational approaches are especially valuable in the case of membrane proteins and their assemblies. The main focus in developing structure prediction techniques has been on soluble proteins, in part due to much greater availability of the structural data. Currently, structure prediction of protein complexes (protein docking) is a well-developed field of study. However, the generic protein docking approaches are not optimal for the membrane proteins because of the differences in physicochemical environment and the spatial constraints imposed by the membranes. Thus, docking of the membrane proteins requires specialized computational methods. Development and benchmarking of the membrane protein docking approaches has to be based on high-quality sets of membrane protein complexes. In this study we present a new dataset of 456 non-redundant alpha helical binary interfaces. The set is significantly larger and more representative than the previously developed sets. In the future, it will become the basis for the development of docking and scoring benchmarks, similar to the ones for soluble proteins in the Dockground resource http://dockground.compbio.ku.edu.en_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2022 Kotthoff et al. This is an open access article distributed under the terms of the Creative Commons Attribution License.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.titleDOCKGROUND membrane protein-protein seten_US
dc.typeArticleen_US
kusw.kuauthorKotthoff, Ian
kusw.kuauthorKundrotas, Petras J.
kusw.kuauthorVakser, Ilya A.
kusw.kudepartmentComputational Biology Programen_US
dc.identifier.doi10.1371/journal.pone.0267531en_US
dc.identifier.orcidhttps://orcid.org/ 0000-0002-5743-2934en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC35580077en_US
dc.rights.accessrightsopenAccessen_US


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© 2022 Kotthoff et al. This is an open access article distributed under the terms of the Creative Commons Attribution License.
Except where otherwise noted, this item's license is described as: © 2022 Kotthoff et al. This is an open access article distributed under the terms of the Creative Commons Attribution License.