DOCKGROUND Protein Docking Benchmark Sets and Assessment Resource
type: CreativeWork
description: Proteins and nucleic acids are key components of cellular functions. To better understand these functions, it is essential to study protein-protein and protein-nucleic acids interactions at the structural level. Compared to the number of currently known proteins, there are relatively few experimentally determined protein-protein structures available. Protein-RNA structures are especially difficult to solve experimentally because of the significant flexibility of RNA. Thus, compared to the protein-protein complexes there are even fewer structures of protein-RNA complexes available. This gap between known, sequenced proteins and RNA and solved experimental structures can be bridged by computational modeling. One way to model protein and protein-RNA structures is macromolecular docking. In order to train and verify the effectiveness of docking methods, high quality datasets and benchmarking tools are needed. This work provides such datasets, and a tool for benchmarking protein docking methods. The datasets are the protein-protein bound dataset, and the protein-RNA bound dataset. Both sets automatically update regularly on a weekly basis. Many datasets become outdated from the time of their initial publication as new structures are released. Thus, the automatic updates are important to prevent this from occurring. The benchmarking tool, CAPRI-Q, evaluates docked protein-protein models against a reference structure and provides various scores to determine the accuracy of the models. The datasets and the benchmarking tool are publicly available on the DOCKGROUND website at https://dockground.compbio.ku.edu/.
abstract: Proteins and nucleic acids are key components of cellular functions. To better understand these functions, it is essential to study protein-protein and protein-nucleic acids interactions at the structural level. Compared to the number of currently known proteins, there are relatively few experimentally determined protein-protein structures available. Protein-RNA structures are especially difficult to solve experimentally because of the significant flexibility of RNA. Thus, compared to the protein-protein complexes there are even fewer structures of protein-RNA complexes available. This gap between known, sequenced proteins and RNA and solved experimental structures can be bridged by computational modeling. One way to model protein and protein-RNA structures is macromolecular docking. In order to train and verify the effectiveness of docking methods, high quality datasets and benchmarking tools are needed. This work provides such datasets, and a tool for benchmarking protein docking methods. The datasets are the protein-protein bound dataset, and the protein-RNA bound dataset. Both sets automatically update regularly on a weekly basis. Many datasets become outdated from the time of their initial publication as new structures are released. Thus, the automatic updates are important to prevent this from occurring. The benchmarking tool, CAPRI-Q, evaluates docked protein-protein models against a reference structure and provides various scores to determine the accuracy of the models. The datasets and the benchmarking tool are publicly available on the DOCKGROUND website at https://dockground.compbio.ku.edu/.
author: Collins, Keeley
language: en
keywords: Bioinformatics, benchmarking, CAPRI-Q, Dockground, protein docking, protein-protein interactions, protein-RNA
date published: 2024-12-31
date modified: 2026-07-24T02:46:05Z
provider: University of Kansas
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Kansas

PropertyValue
property ID: Handle
value: https://hdl.handle.net/1808/38419