Hydrophobicity A Single Parameter for the Accurate Prediction of Disordered Regions in Proteins

The prediction of disordered regionsin proteins is crucialforunderstanding their functions, dynamics, and interactions. Intrinsicallydisordered proteins (IDPs) play a key role in many biological processeslike cell signaling, recognition, and regulation, but experimentallydetermining these regions can be challenging due to their high mobility.To address this challenge, we present an algorithm called HydroDisPred(HDP). HDP uses a single parameter, the fraction of hydrophobicity(& lambda;) in each segment of the protein, to accurately predict disorderedregions. The algorithm was validated using experimental data fromthe DisProt database and was found to be on par and, in some cases,more effective than the existing algorithms. HDP is a simple and effectivemethod for identifying disordered regions in proteins, and its predictionis not affected by the availability of training data, unlike otherML approaches. The application is housed in the web server and canbe accessed through the URL https://proseqanalyser.iitgn.ac.in/hydrodispred/.

Automated summary

Predicting disordered regions in proteins is important for understanding their functions, dynamics, and interactions. The algorithm HydroDisPred (HDP) accurately predicts these regions using the fraction of hydrophobicity in each protein segment. HDP has been validated and found to be as effective as, if not better than, existing algorithms. It is a simple and effective method for identifying disordered regions in proteins and is not affected by the availability of training data.