Skip to main content

Development of novel computational biology pipeline for the efficient classification of titin SNPs for clinical use

Objective

Mutations in the giant muscle protein titin are a major cause of heart disorders in human populations. Routine DNA screening of patient cohorts is now becoming feasible, with a staggering number of titin truncations and missense single nucleotide polymorphisms (mSNPs) rapidly accumulating in genomics databases (>17,000 mSNPs). While the link between titin truncation and disease is now becoming clarified, detecting the pathogenic potential of mSNPs remains a substantial challenge. In mSNPs classification, bioinformatics evaluation is a necessary first filtering step, but existing predictors are poorly reliable. To address this problem, we aim to develop a new titin-centric scoring function that predicts the mechanistic effect of an mSNP exchange in the titin protein by considering the specific characteristics of its poly-domain chain. For this work, we will build a medium-throughput molecular diagnostic pipeline that harvest existent structural models of titin components in estimating mSNPs-induced changes in free energy and conformational dynamics in the protein. Calculations will be benchmarked against experimentally obtained biophysical and biochemical data. To develop this methodology, we will use a clinically pertinent training set of 75 mSNPs. However, in a subsequent step, stable predictions will be extrapolated to the rest of the titin chain by exploiting the repetition of structural and functional loci within the chain. A titin map of vulnerability “hot-spots” so calculated will be distributed to the research community. Ultimately, we aim to produce a tool that can aid clinicians to identify patients at risk of developing a titin-based heart condition at early disease stages, where intervention is still possible.

Field of science

  • /natural sciences/computer and information sciences/databases
  • /natural sciences/biological sciences/genetics and heredity/mutation
  • /natural sciences/biological sciences/genetics and heredity/nucleotide

Call for proposal

H2020-MSCA-IF-2016
See other projects for this call

Funding Scheme

MSCA-IF-EF-ST - Standard EF

Coordinator

UNIVERSITAT KONSTANZ
Address
Universitatsstrasse 10
78464 Konstanz
Germany
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 171 460,80