Article ; Online: Predicting binding sites from unbound versus bound protein structures.
2020 Volume 10, Issue 1, Page(s) 15856
Abstract: We present the application of seven binding-site prediction algorithms to a meticulously curated dataset of ligand-bound and ligand-free crystal structures for 304 unique protein sequences (2528 crystal structures). We probe the influence of starting ... ...
Abstract | We present the application of seven binding-site prediction algorithms to a meticulously curated dataset of ligand-bound and ligand-free crystal structures for 304 unique protein sequences (2528 crystal structures). We probe the influence of starting protein structures on the results of binding-site prediction, so the dataset contains a minimum of two ligand-bound and two ligand-free structures for each protein. We use this dataset in a brief survey of five geometry-based, one energy-based, and one machine-learning-based methods: Surfnet, Ghecom, LIGSITE |
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MeSH term(s) | Algorithms ; Apoproteins/chemistry ; Apoproteins/metabolism ; Binding Sites ; Computational Biology ; Databases, Protein ; Proteins/chemistry ; Proteins/metabolism |
Chemical Substances | Apoproteins ; Proteins |
Language | English |
Publishing date | 2020-09-28 |
Publishing country | England |
Document type | Journal Article ; Research Support, N.I.H., Extramural |
ZDB-ID | 2615211-3 |
ISSN | 2045-2322 ; 2045-2322 |
ISSN (online) | 2045-2322 |
ISSN | 2045-2322 |
DOI | 10.1038/s41598-020-72906-7 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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