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TTNPred SIGNED

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

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 TTNPred project word cloud

Explore the words cloud of the TTNPred project. It provides you a very rough idea of what is the project "TTNPred" about.

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Project "TTNPred" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITAT KONSTANZ 

Organization address
address: UNIVERSITATSSTRASSE 10
city: KONSTANZ
postcode: 78464
website: www.uni-konstanz.de/

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 171˙460 €
 EC max contribution 171˙460 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-01-01   to  2020-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITAT KONSTANZ DE (KONSTANZ) coordinator 171˙460.00

Map

 Project 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.

 Publications

year authors and title journal last update
List of publications.
2019 Yevheniia Nesterenko, Christopher J. Hill, Jennifer R. Fleming, Patricia Murray, Olga Mayans
The ZT Biopolymer: A Self-Assembling Protein Scaffold for Stem Cell Applications
published pages: 4299, ISSN: 1422-0067, DOI: 10.3390/ijms20174299
International Journal of Molecular Sciences 20/17 2019-09-09
2019 Christopher J. Hill, Jennifer R. Fleming, Masoumeh Mousavinejad, Rachael Nicholson, Svetomir B. Tzokov, Per A. Bullough, Julius Bogomolovas, Mark R. Morgan, Olga Mayans, Patricia Murray
Self-Assembling Proteins as High-Performance Substrates for Embryonic Stem Cell Self-Renewal
published pages: 1807521, ISSN: 0935-9648, DOI: 10.1002/adma.201807521
Advanced Materials 2019-06-03
2019 Michael Adams, Jennifer R. Fleming, Eva Riehle, Tiankun Zhou, Thomas Zacharchenko, Marija Markovic, Olga Mayans
Scalable, Non-denaturing Purification of Phosphoproteins Using Ga3+-IMAC: N2A and M1M2 Titin Components as Study case
published pages: 181-189, ISSN: 1572-3887, DOI: 10.1007/s10930-019-09815-w
The Protein Journal 38/2 2019-09-05

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