Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods.

ABSTRACT:

Background

Moonlighting proteins (MPs) are a subclass of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Identification of unknown cellular processes, understanding novel protein mechanisms, improving the prediction of protein functions, and gaining information about protein evolution are the main reasons to study MPs. They also play an important role in disease pathways and drug-target discovery. Since detecting MPs experimentally is quite a challenge, most of them are detected randomly. Therefore, introducing an appropriate computational approach to predict MPs seems reasonable.

Results

In this study, we introduced a competent model for detecting moonlighting and non-MPs through extracted featur

SUBMITTER: Shirafkan F 

PROVIDER: S-EPMC8142502 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature