Cel As a result of the rapid development of next generation sequencing, we now have access to hundreds and often many thousands of sequences which belong to the same family. Such a large amount of sequence data for a particular protein family, along with recent developments in computational statistics, enables an entirely new kind of evolutionary analysis to be performed on sequences, where for the first time we can compute statistically significant networks of correlated mutations. The proposal describes an integrated programme of work to fully explore the potential applications of the new amino acid covariation techniques in predicting aspects of protein structure and function. A particular emphasis in this proposal are proteins which are difficult to study by experimental techniques i.e. disordered proteins, transmembrane proteins and large complexes. The first objective will be to explore key developments in the underpinning algorithms, tackling both the issue of needing very large numbers of homologous sequences and also the downstream 3-D embedding to produce viable models. The second objective will involve experimental work with a collaborator where the idea that de novo protein design techniques might be exploited to artificially expand the set of available sequences for a given proto-family will be explored. The third objective will focus specifically on transmembrane protein modelling, where covariation-based approaches have proven to be highly effective. Here the goal will be to extend our existing FILM3 method to encompass both beta-barrel type TM proteins, but also to try to handle the issue of homomultimers, which is a critical aspect of TM protein modelling as so many families are known to adopt higher orders of structure than the fold level alone. Finally, applications of covariation analysis to probing multiple conformations of disordered proteins will be developed, with a specific focus on interactions of disordered proteins with DNA and RNA. Dziedzina nauki natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomicsnatural sciencesbiological sciencesbiochemistrybiomoleculesnucleic acidsnatural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learningnatural sciencesbiological sciencesgeneticsRNAnatural scienceschemical sciencesorganic chemistryamines Słowa kluczowe Protein co-evolution protein structure prediction transmembrane proteins natively disordered proteins protein design correlated mutations protein-protein interactions Program(-y) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Temat(-y) ERC-ADG-2015 - ERC Advanced Grant Zaproszenie do składania wniosków ERC-2015-AdG Zobacz inne projekty w ramach tego zaproszenia System finansowania ERC-ADG - Advanced Grant Instytucja przyjmująca UNIVERSITY COLLEGE LONDON Wkład UE netto € 2 433 679,00 Adres GOWER STREET WC1E 6BT London Zjednoczone Królestwo Zobacz na mapie Region London Inner London — West Camden and City of London Rodzaj działalności Higher or Secondary Education Establishments Linki Kontakt z organizacją Opens in new window Strona internetowa Opens in new window Uczestnictwo w unijnych programach w zakresie badań i innowacji Opens in new window sieć współpracy HORIZON Opens in new window Koszt całkowity € 2 433 679,00 Beneficjenci (1) Sortuj alfabetycznie Sortuj według wkładu UE netto Rozwiń wszystko Zwiń wszystko UNIVERSITY COLLEGE LONDON Zjednoczone Królestwo Wkład UE netto € 2 433 679,00 Adres GOWER STREET WC1E 6BT London Zobacz na mapie Region London Inner London — West Camden and City of London Rodzaj działalności Higher or Secondary Education Establishments Linki Kontakt z organizacją Opens in new window Strona internetowa Opens in new window Uczestnictwo w unijnych programach w zakresie badań i innowacji Opens in new window sieć współpracy HORIZON Opens in new window Koszt całkowity € 2 433 679,00