Computational approaches to understanding the biological behaviour of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) represent a class of proteins that lack a persistent folded conformation and exist as dynamic ensembles in their native state. Inherent lack of a well-defined structure and remarkable structural plasticity have facilitated their functioning in a wide range of crucial cellular processes such as signalling transduction and cell cycle regulation as well as responsible for their aberrant toxic amyloidogenic conformations implicated in a wide range of neurodegenerative diseases, cancer, etc. Their ubiquitous presence in nature, role in biological function and diseases have spurred interest in the biophysical and conformational characterization of IDPs. Conventional methods of structure determination are less feasible owing to structural and spatiotemporal heterogeneity of IDPs, which demand the development of novel biophysical methods as well as rigorous computational techniques for their characterization. In this review, we provide a brief overview of the widely used computational techniques probing the rugged conformational energy landscape of IDPs, their kinetics of structural transitions and molecular interactions key to their functions. Advances in the development of calibrated computational approaches for statistical representation of highly dynamic structural ensemble of IDPs are provided with examples. Challenges in modelling this unique class of proteins as well as the existing and futuristic avenues are also discussed.