Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions
نویسندگان
چکیده
منابع مشابه
MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins
MOTIVATION Molecular recognition features (MoRFs) are short binding regions located within longer intrinsically disordered regions that bind to protein partners via disorder-to-order transitions. MoRFs are implicated in important processes including signaling and regulation. However, only a limited number of experimentally validated MoRFs is known, which motivates development of computational m...
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Many cell functions in all living organisms rely on protein-based molecular recognition involving disorder-to-order transitions upon binding by molecular recognition features (MoRFs). A well accepted computational tool for identifying likely protein-protein interactions is sequence alignment. In this paper, we propose the combination of sequence alignment and disorder prediction as a tool to im...
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متن کاملStructural bioinformatics Computational identification of MoRFs in protein sequences
Motivation: Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is the binding of molecular recognition features (MoRFs) to globular protein domains in a process known as a disorder-to-order transition. Predicting the location of MoRFs in protein sequences with high accuracy remains an important ...
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ژورنال
عنوان ژورنال: Computational and Structural Biotechnology Journal
سال: 2019
ISSN: 2001-0370
DOI: 10.1016/j.csbj.2019.03.013