IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation

By Gábor Erdös, Mátyás Pajkos, Zsuzsanna Dosztányi. Nucleic Acids Res., 2021

508 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/046e768229e41b3db78b7a8a68f4a065cd718ee9

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Citations in the corpus

The high mobility group protein HMG20A cooperates with the histone reader PHF14 to modulate TGFβ and Hippo pathways (2022, background): “Prediction of IDRs by the IUPred3 web server (32) also identified a region with low probability of secondary structure in the amino terminus of HMG20A (Supplementary Figure S1A).”
ProtGPT2 is a deep unsupervised language model for protein design (2022, methodology): “Since our goal is to provide high-level comparisons of globularity and prevalent disorder across data-sets, we further performed an analysis of the protein sequences at the amino acid level using IUPred3.”