Modelling ENvironment for Isoforms (MoNvIso): A General Platform to Predict Structural Determinants of Protein Isoforms in Genetic Diseases

Overview

Journal Front Chem

Specialty Chemistry

Date 2023 Jan 26

PMID 36700074

Authors

Francesco Oliva

Francesco Musiani

Alejandro Giorgetti

Silvia De Rubeis

Oksana Sorokina

Douglas J Armstrong

Paolo Carloni

Paolo Ruggerone

Affiliations

Soon will be listed here.

Abstract

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.

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