University of Dundee

“Towards improved biophysical models of protein folding to identify disease-causing mutations”

Event Date: 
Friday, October 1, 2021 - 11:00 to 12:00
Event Location: 
Zoom
Event Speaker: 
Professor Kresten Lindorff-Larsen
Institution: 
Structural Biology and NMR Laboratory Linderstrøm-Lang Centre for Protein Science University of Copenaghen
Event Type: 
Seminar
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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 at a single site, yet we only understand the molecular and phenotypic consequences of a small fraction of these. Within protein science and biotechnology, high-throughput multiplexed assays enable us to probe the effects of thousands of variants in a single experiment [1]. 

We have used computational and experimental approaches to determine the consequences of missense variants in proteins, with the aim of using such models both for diagnosing genetic diseases, and for providing mechanistic insight into disease. In particular, we have focused on the effects of individual amino acid changes on protein folding and stability, linking biophysical calculations with protein degradation and abundance in cells [1,2]. By examining a range of proteins and diseases we have found that loss of stability is a common drive for genetic diseases, and that predictions of changes in thermodynamic protein stability are useful to assess the pathogenicity of genetic variation. I will discuss these ideas using recent examples from our laboratories [3–6]. 

At the same time, our work has also revealed areas where our understanding and ability to predict the effect of amino acid changes is still imperfect. I will discuss how we are using sequence analyses and high-throughput, multiplexed assays of variant effects (deep mutational scanning) experiments to understand the origins of loss of function [7–9], thus paving the way for more accurate biophysical models and machine learning methods for use in personalized medicine [1,8]. 

 

 

References:

1. Stein et al. “Biophysical and Mechanistic Models for Disease-Causing Protein Variants.” Trends in biochemical sciences 44 (2019): 575–588

2. Clausen et al. “Protein stability and degradation in health and disease.” Advances in protein chemistry and structural biology 114 (2019): 61–84.

3. Nielsen et al. “Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations.” PLOS Genetics 13 (2017): e1006739.

4. Scheller et al. “Toward mechanistic models for genotype–phenotype correlations in phenylketonuria using protein stability calculations.” Human mutation 40 (2019): 444–457.

5. Abildgaard et al. “Structural destabilization and chaperone-assisted proteasomal degradation of MLH1 as a mechanism for Lynch syndrome.” eLIFE 8 (2019): e49138

6. Clausen et al “Folliculin variants linked to Birt-Hogg-Dubé syndrome are targeted for proteasomal degradation” PLOS Genetics 16 (2020): e1009187

7. Cagiada et al. “Understanding the origins of loss of protein function by analyzing the effects of thousands of variants on activity and abundance” Molecular Biology and Evolution (2021): 3235-3246

8. Høie, Magnus H., et al. "Predicting and interpreting large scale mutagenesis data using analyses of protein stability and conservation." bioRxiv (2021) 10.1101/2021.06.26.450037

9. Jepsen et al. "Classifying disease-associated variants using measures of protein activity and stability." Protein Homeostasis Diseases, Ch. 6 (2020): 111–125