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Abstract Comparative docking is based on experimentally determined structures of protein‐protein complexes (templates), following the paradigm that proteins with similar sequences and/or structures form similar complexes. Modeling utilizing structure similarity of target monomers to template complexes significantly expands structural coverage of the interactome. Template‐based docking by structure alignment can be performed for the entire structures or by aligning targets to the bound interfaces of the experimentally determined complexes. Systematic benchmarking of docking protocols based on full and interface structure alignment showed that both protocols perform similarly, with top 1 docking success rate 26%. However, in terms of the models' quality, the interface‐based docking performed marginally better. The interface‐based docking is preferable when one would suspect a significant conformational change in the full protein structure upon binding, for example, a rearrangement of the domains in multidomain proteins. Importantly, if the same structure is selected as the top template by both full and interface alignment, the docking success rate increases 2‐fold for both top 1 and top 10 predictions. Matching structural annotations of the target and template proteins for template detection, as a computationally less expensive alternative to structural alignment, did not improve the docking performance. Sophisticated remote sequence homology detection added templates to the pool of those identified by structure‐based alignment, suggesting that for practical docking, the combination of the structure alignment protocols and the remote sequence homology detection may be useful in order to avoid potential flaws in generation of the structural templates library.
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Dockground resource for protein recognition studies
Abstract Structural information of protein–protein interactions is essential for characterization of life processes at the molecular level. While a small fraction of known protein interactions has experimentally determined structures, computational modeling of protein complexes (protein docking) has to fill the gap. TheDockgroundresource (http://dockground.compbio.ku.edu) provides a collection of datasets for the development and testing of protein docking techniques. Currently,Dockgroundcontains datasets for the bound and the unbound (experimentally determined and simulated) protein structures, model–model complexes, docking decoys of experimentally determined and modeled proteins, and templates for comparative docking. TheDockgroundbound proteins dataset is a core set, from which otherDockgrounddatasets are generated. It is devised as a relational PostgreSQL database containing information on experimentally determined protein–protein complexes. This report on theDockgroundresource describes current status of the datasets, new automated update procedures and further development of the core datasets. We also present a newDockgroundinteractive web interface, which allows search by various parameters, such as release date, multimeric state, complex type, structure resolution, and so on, visualization of the search results with a number of customizable parameters, as well as downloadable datasets with predefined levels of sequence and structure redundancy.
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- Award ID(s):
- 1917263
- PAR ID:
- 10481699
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Protein Science
- Volume:
- 31
- Issue:
- 12
- ISSN:
- 0961-8368
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/pro.4481
