Imperial College London

ProfessorMichaelSternberg

Faculty of Natural SciencesDepartment of Life Sciences

Director Centre for Bioinformatics
 
 
 
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Contact

 

+44 (0)20 7594 5212m.sternberg Website

 
 
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Location

 

306Sir Ernst Chain BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Ittisoponpisan:2019:10.1016/j.jmb.2019.04.009,
author = {Ittisoponpisan, S and Islam, S and Khanna, T and Alhuzimi, E and David, A and Sternberg, M},
doi = {10.1016/j.jmb.2019.04.009},
journal = {Journal of Molecular Biology},
pages = {2197--2212},
title = {Can predicted protein 3D-structures provide reliable insights into whether missense variants are disease-associated?},
url = {http://dx.doi.org/10.1016/j.jmb.2019.04.009},
volume = {431},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Knowledge of protein structure can be used to predict the phenotypic consequence of a missense variant. Since structural coverage of the human proteome can be roughly tripled to over 50% of the residues if homology-predicted structures are included in addition to experimentally determined coordinates, it is important to assess the reliability of using predicted models when analyzing missense variants. Accordingly, we assess whether a missense variant is structurally damaging by using experimental and predicted structures. We considered 606 experimental structures and show that 40% of the 1965 disease-associated missense variants analyzed have a structurally damaging change in the mutant structure. Only 11% of the 2134 neutral variants are structurally damaging. Importantly, similar results are obtained when 1052 structures predicted using Phyre2 algorithm were used, even when the model shares low (< 40%) sequence identity to the template. Thus, structure-based analysis of the effects of missense variants can be effectively applied to homology models. Our in-house pipeline, Missense3D, for structurally assessing missense variants was made available at http://www.sbg.bio.ic.ac.uk/~missense3d
AU - Ittisoponpisan,S
AU - Islam,S
AU - Khanna,T
AU - Alhuzimi,E
AU - David,A
AU - Sternberg,M
DO - 10.1016/j.jmb.2019.04.009
EP - 2212
PY - 2019///
SN - 0022-2836
SP - 2197
TI - Can predicted protein 3D-structures provide reliable insights into whether missense variants are disease-associated?
T2 - Journal of Molecular Biology
UR - http://dx.doi.org/10.1016/j.jmb.2019.04.009
UR - http://hdl.handle.net/10044/1/70153
VL - 431
ER -