ArticleBMC bioinformatics2015
Simulated unbound structures for benchmarking of protein docking in the DOCKGROUND resource.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 14 citations in OpenAlex.
- Dockground resource for protein recognition studies.Protein science : a publication of the Protein Society · 2022Article
- ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction.Nature methods · 2022Article
- DOCKGROUND membrane protein-protein set.PloS one · 2022Article
- Modeling CAPRI targets 110-120 by template-based and free docking using contact potential and combined scoring function.Proteins · 2018Article
- Dockground: A comprehensive data resource for modeling of protein complexes.Protein science : a publication of the Protein Society · 2018Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
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Abstract
backgroundProteins play an important role in biological processes in living organisms. Many protein functions are based on interaction with other proteins. The structural information is important for adequate description of these interactions. Sets of protein structures determined in both bound and unbound states are essential for benchmarking of the docking procedures. However, the number of such proteins in PDB is relatively small. A radical expansion of such sets is possible if the unbound structures are computationally simulated.
resultsThe DOCKGROUND public resource provides data to improve our understanding of protein-protein interactions and to assist in the development of better tools for structural modeling of protein complexes, such as docking algorithms and scoring functions. A large set of simulated unbound protein structures was generated from the bound structures. The modeling protocol was based on 1 ns Langevin dynamics simulation. The simulated structures were validated on the ensemble of experimentally determined unbound and bound structures. The set is intended for large scale benchmarking of docking algorithms and scoring functions.
conclusionsA radical expansion of the unbound protein docking benchmark set was achieved by simulating the unbound structures. The simulated unbound structures were selected according to criteria from systematic comparison of experimentally determined bound and unbound structures. The set is publicly available at http://dockground.compbio.ku.edu.
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