Mátyás Pajkos

TL;DR: Recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website are reported.

Abstract: Intrinsically disordered proteins and protein regions (IDPs/IDRs) exist without a single well-defined conformation. They carry out important biological functions with multifaceted roles which is also reflected in their evolutionary behavior. Computational methods play important roles in the characterization of IDRs. One of the commonly used disorder prediction methods is IUPred, which relies on an energy estimation approach. The IUPred web server takes an amino acid sequence or a Uniprot ID/accession as an input and predicts the tendency for each amino acid to be in a disordered region with an option to also predict context-dependent disordered regions. In this new iteration of IUPred, we added multiple novel features to enhance the prediction capabilities of the server. First, learning from the latest evaluation of disorder prediction methods we introduced multiple new smoothing functions to the prediction that decreases noise and increases the performance of the predictions. We constructed a dataset consisting of experimentally verified ordered/disordered regions with unambiguous annotations which were added to the prediction. We also introduced a novel tool that enables the exploration of the evolutionary conservation of protein disorder coupled to sequence conservation in model organisms. The web server is freely available to users and accessible at https://iupred3.elte.hu.

TL;DR: The Database of Intrinsically Disordered Proteins (DisProt) as discussed by the authors is a repository of manually curated annotations of intrinsically disordered proteins and regions from the literature, including a restyled web interface.

TL;DR: It is demonstrated that while neutral polymorphisms were more likely to occur within disordered segments, cancer-associated mutations had a preference for ordered regions, and an alternative explanation for the association of protein disorder and the involvement in cancer with the consideration of functional annotations is proposed.

TL;DR: A novel bioinformatic filtering protocol is established to efficiently explore interaction network of a hub protein, a ubiquitous eukaryotic hub protein that has been suggested to be involved in motor-related functions as well as promoting the dimerization of various proteins by recognizing linear motifs in its partners.