Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Garrett M, Morris"'
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 3 (2024)
Externí odkaz:
https://doaj.org/article/1a414d0c59fb4f0780c57be4229e641b
Autor:
Serena Vales, Jhanna Kryukova, Soumyanetra Chandra, Gintare Smagurauskaite, Megan Payne, Charlie J. Clark, Katrin Hafner, Philomena Mburu, Stepan Denisov, Graham Davies, Carlos Outeiral, Charlotte M. Deane, Garrett M. Morris, Shoumo Bhattacharya
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-17 (2023)
Abstract CC and CXC-chemokines are the primary drivers of chemotaxis in inflammation, but chemokine network redundancy thwarts pharmacological intervention. Tick evasins promiscuously bind CC and CXC-chemokines, overcoming redundancy. Here we show th
Externí odkaz:
https://doaj.org/article/4d4b476ec059431cbb9a7a4c796377b7
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-16 (2023)
Abstract Introduction and methodology Pairs of similar compounds that only differ by a small structural modification but exhibit a large difference in their binding affinity for a given target are known as activity cliffs (ACs). It has been hypothesi
Externí odkaz:
https://doaj.org/article/76f3ade697194633a3b30a6242ae3645
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Drug resistance caused by mutations is a public health threat for existing and emerging viral diseases. A wealth of evidence about these mutations and their clinically associated phenotypes is scattered across the literature, but a comprehen
Externí odkaz:
https://doaj.org/article/c309742550b34f8fb0a789ce52afb184
Publikováno v:
Journal of Cheminformatics, Vol 13, Iss 1, Pp 1-19 (2021)
Abstract Scoring functions for the prediction of protein-ligand binding affinity have seen renewed interest in recent years when novel machine learning and deep learning methods started to consistently outperform classical scoring functions. Here we
Externí odkaz:
https://doaj.org/article/7f4da096e1a94782b493f06d57758b6e
Publikováno v:
Frontiers in Bioinformatics, Vol 2 (2022)
The rapid and accurate in silico prediction of protein-ligand binding free energies or binding affinities has the potential to transform drug discovery. In recent years, there has been a rapid growth of interest in deep learning methods for the predi
Externí odkaz:
https://doaj.org/article/89fff38ec3314be196ff3d9f42d513ad
Publikováno v:
Journal of Cheminformatics, Vol 11, Iss 1, Pp 1-11 (2019)
Abstract Generating low-energy molecular conformers is a key task for many areas of computational chemistry, molecular modeling and cheminformatics. Most current conformer generation methods primarily focus on generating geometrically diverse conform
Externí odkaz:
https://doaj.org/article/bdac2ad431034711afcb83fea6fe8d7d
Autor:
Angelina R. Sekirnik, Jessica K. Reynolds, Larissa See, Joseph P. Bluck, Amy R. Scorah, Cynthia Tallant, Bernadette Lee, Katarzyna B. Leszczynska, Rachel L. Grimley, R. Ian Storer, Marta Malattia, Sara Crespillo, Sofia Caria, Stephanie Duclos, Ester M. Hammond, Stefan Knapp, Garrett M. Morris, Fernanda Duarte, Philip C. Biggin, Stuart J. Conway
Publikováno v:
ACS Chemical Biology. 17:2753-2768
TRIM33 is a member of the tripartite motif (TRIM) family of proteins, some of which possess E3 ligase activity and are involved in the ubiquitin-dependent degradation of proteins. Four of the TRIM family proteins, TRIM24 (TIF1α), TRIM28 (TIF1β), TR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3e2aeb12794430ed27bbc1291d39218
https://doi.org/10.1021/acschembio.2c00266
https://doi.org/10.1021/acschembio.2c00266
Here we introduce a novel method to interpret the predictions of graph neural networks (GNNs) based on Myerson values from cooperative game theory. Myerson values are closely related to Shapley values and thus provide an interpretability approach sim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::faf11b59efcc1e47073cffe01cb98157
https://doi.org/10.26434/chemrxiv-2023-1hxxc
https://doi.org/10.26434/chemrxiv-2023-1hxxc
Autor:
Carlos Outeiral, Garrett M Morris, Jiye Shi, Martin Strahm, Simon C Benjamin, Charlotte M Deane
Publikováno v:
New Journal of Physics, Vol 23, Iss 10, p 103030 (2021)
Protein folding is a central challenge in computational biology, with important applications in molecular biology, drug discovery and catalyst design. As a hard combinatorial optimisation problem, it has been studied as a potential target problem for
Externí odkaz:
https://doaj.org/article/ff0b0e914a274b299dffeeb04d6b0359