AUTHOR=Oliva Francesco , Musiani Francesco , Giorgetti Alejandro , De Rubeis Silvia , Sorokina Oksana , Armstrong Douglas J. , Carloni Paolo , Ruggerone Paolo 

TITLE=Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases

JOURNAL=Frontiers in Chemistry

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2022.1059593

DOI=10.3389/fchem.2022.1059593

ISSN=2296-2646

ABSTRACT=<p>The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the isoforms onto which mutations should be mapped due to there being several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task needs to be automatized. Here we present the MoNvIso (Modelling eNvironment for Isoforms) code, which identifies the most useful isoform for computational modelling, balancing the coverage of mutations of interest and the availability of templates to build a structural model of both the wild-type isoform and the related variants.</p>