Computational Methods to Study Intrinsically Disordered Proteins
Document Type
Book Chapter
Publication Date
2022
Digital Object Identifier (DOI)
https://doi.org/10.1016/B978-0-323-90264-9.00030-1
Abstract
In the 21st century, evolving computational power has provided great help to understand, build, and execute numerous ideas in almost every field. The improvements in understanding the biology of several diseases have been made easy using computational tools. The most prominent example is investigating the conformations of proteins. It solves multiple purposes, such as understanding protein folding and dynamics, protein–protein interactions, and structure-based drug designing. One of the most exciting applications of computational approaches in understanding unstructured regions or intrinsically disordered proteins or regions (IDPs/IDPRs). This chapter has thoroughly discussed the history of IDPs, their role in diseases, and their significance with the current research in structured and unstructured biology. Specifically, the focus lies in using common predictors, which are then used to study the unstructured or disordered regions, disordered-based binding regions, and nucleotide-binding regions in proteins. The detailed insight into IDPs and molecular recognition features (MoRFs) will help understand their significance in protein functioning and drug designing.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Computational Methods to Study Intrinsically Disordered Proteins, in T. Tripathi & V. K. Dubey (Eds.), Advances in Protein Molecular and Structural Biology Methods, Academic Press, p. 489-504
Scholar Commons Citation
Kumar, Prateek; Bhardwaj, Aparna; Uversky, Vladimir N.; Tripathi, Timir; and Giri, Rajanish, "Computational Methods to Study Intrinsically Disordered Proteins" (2022). Molecular Medicine Faculty Publications. 1140.
https://digitalcommons.usf.edu/mme_facpub/1140
