Missense3D-TM: predicting the effect of missense variants in helical transmembrane protein regions using 3D protein structures
File(s)
Published version
Author(s)
Hanna, Gordon
Khanna, Tarun
Islam, Suhail
David, Alessia
Sternberg, Michael
Type
Journal Article
Abstract
Variant effect predictors assess if a substitution is pathogenic or benign. Most predictors, including those that are structure-based, are designed for globular proteins in aqueous environments and do not consider that the variant residue is located within the membrane. We report Missense3D-TM that provides a structure-based assessment of the impact of a missense variant located within a membrane.
On a dataset of 2,078 pathogenic and 1,060 benign variants, spanning 711 proteins from 706 structures, Missense3D-TM achieved an accuracy of 66%, Mathews correlation coefficient of 0.37, sensitivity of 58% and specificity of 81%. Missense3D-TM performed similarly to mCSM-membrane: accuracy 66% vs 61% (p=0.02) on an unbalanced test set and 70% vs 67% (p=0.20) on a balanced test set.
The Missense3D-TM website provides an analysis of the structural effects of the variant along with its predicted position within the membrane. The web server is available at http://missense3d.bc.ic.ac.uk/.
On a dataset of 2,078 pathogenic and 1,060 benign variants, spanning 711 proteins from 706 structures, Missense3D-TM achieved an accuracy of 66%, Mathews correlation coefficient of 0.37, sensitivity of 58% and specificity of 81%. Missense3D-TM performed similarly to mCSM-membrane: accuracy 66% vs 61% (p=0.02) on an unbalanced test set and 70% vs 67% (p=0.20) on a balanced test set.
The Missense3D-TM website provides an analysis of the structural effects of the variant along with its predicted position within the membrane. The web server is available at http://missense3d.bc.ic.ac.uk/.
Date Issued
2024-01-15
Date Acceptance
2023-11-20
Citation
Journal of Molecular Biology, 2024, 436 (2)
ISSN
0022-2836
Publisher
Elsevier
Journal / Book Title
Journal of Molecular Biology
Volume
436
Issue
2
Copyright Statement
© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://doi.org/10.1016/j.jmb.2023.168374
Publication Status
Published
Article Number
168374
Date Publish Online
2023-12-07