TY  - JOUR
AU  - Oliva, Francesco
AU  - Musiani, Francesco
AU  - Giorgetti, Alejandro
AU  - De Rubeis, Silvia
AU  - Sorokina, Oksana
AU  - Armstrong, Douglas J.
AU  - Carloni, Paolo
AU  - Ruggerone, Paolo
TI  - Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases
JO  - Frontiers in Chemistry
VL  - 10
SN  - 2296-2646
CY  - Lausanne
PB  - Frontiers Media
M1  - FZJ-2024-02219
SP  - 1059593
PY  - 2023
AB  - The seamless integration of human disease-related mutation data into proteinstructures is an essential component of any attempt to correctly assess theimpact of the mutation. The key step preliminary to any structural modelling isthe identification of the isoforms onto which mutations should be mapped dueto there being several functionally different protein isoforms from the samegene. To handle large sets of data coming from omics techniques, thischallenging task needs to be automatized. Here we present the MoNvIso(Modelling eNvironment for Isoforms) code, which identifies the most usefulisoform for computational modelling, balancing the coverage of mutations ofinterest and the availability of templates to build a structural model of both thewild-type isoform and the related variants.
LB  - PUB:(DE-HGF)16
C6  - 36700074
UR  - <Go to ISI:>//WOS:000921373000001
DO  - DOI:10.3389/fchem.2022.1059593
UR  - https://juser.fz-juelich.de/record/1024532
ER  -