Biophysical and Mechanistic Models for Disease-Causing Protein Variants

Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt

Standard

Biophysical and Mechanistic Models for Disease-Causing Protein Variants. / Stein, Amelie; Fowler, Douglas M.; Hartmann-Petersen, Rasmus; Lindorff-Larsen, Kresten.

I: Trends in Biochemical Sciences, Bind 44, Nr. 7, 2019, s. 575-588.

Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt

Harvard

Stein, A, Fowler, DM, Hartmann-Petersen, R & Lindorff-Larsen, K 2019, 'Biophysical and Mechanistic Models for Disease-Causing Protein Variants', Trends in Biochemical Sciences, bind 44, nr. 7, s. 575-588. https://doi.org/10.1016/j.tibs.2019.01.003

APA

Stein, A., Fowler, D. M., Hartmann-Petersen, R., & Lindorff-Larsen, K. (2019). Biophysical and Mechanistic Models for Disease-Causing Protein Variants. Trends in Biochemical Sciences, 44(7), 575-588. https://doi.org/10.1016/j.tibs.2019.01.003

Vancouver

Stein A, Fowler DM, Hartmann-Petersen R, Lindorff-Larsen K. Biophysical and Mechanistic Models for Disease-Causing Protein Variants. Trends in Biochemical Sciences. 2019;44(7):575-588. https://doi.org/10.1016/j.tibs.2019.01.003

Author

Stein, Amelie ; Fowler, Douglas M. ; Hartmann-Petersen, Rasmus ; Lindorff-Larsen, Kresten. / Biophysical and Mechanistic Models for Disease-Causing Protein Variants. I: Trends in Biochemical Sciences. 2019 ; Bind 44, Nr. 7. s. 575-588.

Bibtex

@article{f702c7e4dfc646558b0de10e6f905285,
title = "Biophysical and Mechanistic Models for Disease-Causing Protein Variants",
abstract = "The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.",
keywords = "computational biophysics, deep mutational scanning, genomics, protein quality control, protein stability, variant classification",
author = "Amelie Stein and Fowler, {Douglas M.} and Rasmus Hartmann-Petersen and Kresten Lindorff-Larsen",
year = "2019",
doi = "10.1016/j.tibs.2019.01.003",
language = "English",
volume = "44",
pages = "575--588",
journal = "Trends in Biochemical Sciences",
issn = "0968-0004",
publisher = "Elsevier",
number = "7",

}

RIS

TY - JOUR

T1 - Biophysical and Mechanistic Models for Disease-Causing Protein Variants

AU - Stein, Amelie

AU - Fowler, Douglas M.

AU - Hartmann-Petersen, Rasmus

AU - Lindorff-Larsen, Kresten

PY - 2019

Y1 - 2019

N2 - The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

AB - The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

KW - computational biophysics

KW - deep mutational scanning

KW - genomics

KW - protein quality control

KW - protein stability

KW - variant classification

U2 - 10.1016/j.tibs.2019.01.003

DO - 10.1016/j.tibs.2019.01.003

M3 - Review

C2 - 30712981

AN - SCOPUS:85060866336

VL - 44

SP - 575

EP - 588

JO - Trends in Biochemical Sciences

JF - Trends in Biochemical Sciences

SN - 0968-0004

IS - 7

ER -

ID: 214460833