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Zaucha, J.* ; Softley, C. ; Sattler, M. ; Frishman, D.* ; Popowicz, G.M.

Deep learning model predicts water interaction sites on the surface of proteins using limited-resolution data.

Chem. Commun. 56, 15454-15457 (2020)
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We develop a residual deep learning model, hotWater (https://pypi.org/project/hotWater/), to identify key water interaction sites on proteins for binding models and drug discovery. This is tested on new crystal structures, as well as cryo-EM and NMR structures from the PDB and in crystallographic refinement with promising results.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Molecules; Design
Language english
Publication Year 2020
HGF-reported in Year 2020
ISSN (print) / ISBN 0009-241X
e-ISSN 1364-548X
Quellenangaben Volume: 56, Issue: 98, Pages: 15454-15457 Article Number: , Supplement: ,
Publisher Royal Society of Chemistry (RSC)
Publishing Place Thomas Graham House, Science Park, Milton Rd, Cambridge Cb4 0wf, Cambs, England
Reviewing status Peer reviewed
POF-Topic(s) 30203 - Molecular Targets and Therapies
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-503000-001
Grants Sattler group
Popowicz group
Frishman group
Deutsche Forschungsgemeinschaft
European Union
Scopus ID 85098472072
Erfassungsdatum 2021-02-09