Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

Abstract

There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions.

Liquid–Liquid Phase Separation and Protective Protein Aggregates in Bacteria

“…However, developing high-resolution microscopy and single-molecule tracking techniques has enabled significant progress in this field in recent years. Information on LLPS-prone proteins and IDPs has been gathered in several rapidly growing databases, and over 100 predictors of disordered sequences have been developed in the last decade [ 99 ]. There are several examples of bacterial LLPS–dependent condensates that are involved in various physiological processes.…”

Availability of web servers significantly boosts citations rates of bioinformatics methods for protein function and disorder prediction

“…We settle for the 10-year window to include relatively recent methods, be able to analyze results longitudinally, and reduce the impact of difficulty/inability with deploying web server for the older methods. We use a combination of PUBMED searches, surveys ( Zhang et al 2011 , Miao and Westhof 2015 , Si et al 2015a , b , Varadi et al 2015 , Yan et al 2016 , Dosztányi and Tompa 2017 , Jiang et al 2017 , Meng et al 2017a , b , Katuwawala et al 2019a , b , Liu et al 2019 , Barik and Kurgan 2020 , Katuwawala and Kurgan 2020 , Necci et al 2021 , Zhao and Kurgan 2021 , Cui et al 2022 , Kurgan 2022 , Zhang et al 2022 , Basu et al 2023 , Uversky and Kurgan 2023 , Zhao and Kurgan 2023 ), and Google scholar citations scanning to identify a comprehensive collection of methods. We list these methods in Supplementary Table S1 (43 predictors of functions of structured proteins), Supplementary Table S2 (24 predictors of functions of intrinsically disordered proteins), and Supplementary Table S3 (33 predictors of intrinsic disorder).…”