Amrita Mohan

TL;DR: The development of a database of MoRFs derived from the RCSB Protein Data Bank is described and preliminary results of bioinformatics analyses of these sequences are presented, suggesting that functionally significant residual structure can exist in MoRF regions prior to the actual binding event.

TL;DR: It is shown that gain and loss of predicted ubiquitination sites may likely represent a molecular mechanism behind a number of disease‐associatedmutations.

TL;DR: There are significant differences in residue composition and several geometric and physicochemical properties that can be used to discriminate, with a high degree of accuracy, between various interfaces in protein interaction data sets.

TL;DR: This work proposes an algorithm for detecting gene–disease associations based on the human protein–protein interaction network, known gene-diseases associations, protein sequence, and protein functional information at the molecular level, and provided evidence that, despite the noise/incompleteness of experimental data and unfinished ontology of diseases, identification of candidate genes can be successful even when a large number of candidate disease terms are predicted on simultaneously.

TL;DR: This study provides a bioinfomatics basis for the discovery and analysis of unfoldomes (the complement of intrinsically disordered proteins in a given proteome) of early-branching eukaryotes and provides new insights into the evolution of intrinsic disorder in the context of adapting to a parasitic lifestyle.