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Biophysical and Mechanistic models for disease-causing protein variants
- Source :
- Trends Biochem Sci
- Publication Year :
- 2019
-
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.
- Subjects :
- Mutation, Missense
Genomics
Disease
Computational biology
Biology
Biochemistry
DNA sequencing
Article
Cellular protein
03 medical and health sciences
0302 clinical medicine
Protein sequencing
Protein stability
Missense mutation
Humans
Molecular Biology
030304 developmental biology
0303 health sciences
Models, Genetic
Protein Stability
Computational Biology
Genetic Variation
Proteins
Phenotype
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Trends Biochem Sci
- Accession number :
- edsair.doi.dedup.....5828631d0f60d3878a8f84be3a2514b7