Towards predictive biophysical and mechanistic models for disease-causing protein variants
Author and article information
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 mutations in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense mutations 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 together providing a framework for understanding and predicting how mutations affect cellular protein stability.
Cite this as
2018. Towards predictive biophysical and mechanistic models for disease-causing protein variants. PeerJ Preprints 6:e27379v1 https://doi.org/10.7287/peerj.preprints.27379v1Author comment
This is a preprint submission to PeerJ Preprints.
Sections
Additional Information
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Amelie Stein conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Douglas M Fowler conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.
Rasmus Hartmann-Petersen conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Kresten Lindorff-Larsen conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.
Data Deposition
The following information was supplied regarding data availability:
This is a review manuscript.
Funding
Our work in this area has been supported by grants from the Lundbeck Foundation (A.S., R.H.-P. and K.L.-L.), The Danish Cancer Society (R.H.-P.), the Novo Nordisk Foundation (R.H.-P. and K.L.-L.), the Danish Council for Independent Research (Natural Sciences) (to R.H.-P), the National Institute of General Medical Sciences (1R01GM109110 to D.M.F.). D.M.F. is a CIFAR Azrieli Global Scholar. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
