Unique and exclusive peptide signatures directly identify intrinsically disordered proteins from sequences without structural information

Mittal, Aditya; Changani, Anandkumar Madhavjibhai; Taparia, Sakshi

doi:10.1080/07391102.2020.1756410

Cited by 5 publications

(3 citation statements)

References 49 publications

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“…While IUPRED2-long does not predict disorderedness in the protein, PONDR-VLXT predicts regions 1–2, 48–52, 11–82, and 92–94 as the disordered regions. Our prediction (21–40) segment is in close agreement with the experimentally predicted regions. − Although we have compared our prediction with only two state-of-the-art algorithms here, in Figures S1 and S2, we have compared the prediction with a few more algorithms like PONDER-FIT, IUPRED2-SHORT, PONDER-XL1, PONDER-VL3, and ESPRITZ-DISPROT to be thorough.…”

Section: Resultssupporting

confidence: 75%

“…The asymmetry in amino acid compositions in terms of hydropathy has been previously applied to predict the transmembrane domains (TMDs) of integral membrane proteins across various organisms and organelles. However, it has to be noted that TMDs are structural proteins with a high helical content and a very high proportion of hydrophobic amino acids, which makes them very distinct from IDRs. − …”

Section: Introductionmentioning

confidence: 99%

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

Singh

Bhardwaj

Radhakrishna

2023

J. Chem. Inf. Model.

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The prediction of disordered regions in proteins is crucial for understanding their functions, dynamics, and interactions. Intrinsically disordered proteins (IDPs) play a key role in many biological processes like cell signaling, recognition, and regulation, but experimentally determining 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 (λ) in each segment of the protein, to accurately predict disordered regions. The algorithm was validated using experimental data from the DisProt database and was found to be on par and, in some cases, more effective than the existing algorithms. HDP is a simple and effective method for identifying disordered regions in proteins, and its prediction is not affected by the availability of training data, unlike other ML approaches. The application is housed in the web server and can be accessed through the URL https:// proseqanalyser.iitgn.ac.in/hydrodispred/.

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Section: Resultssupporting

confidence: 75%

Section: Introductionmentioning

confidence: 99%

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

Singh

Bhardwaj

Radhakrishna

2023

J. Chem. Inf. Model.

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“…Recently, it emerged that naturally occurring folded/structured proteins have clear compositional constraints (Mittal et al 2010 , 2020 ; Mittal and Jayaram 2011a , b ). It was also shown that amino acid compositions beyond those constraints are signs of intrinsic disorder in proteins, i.e., lack of specific conformations/structures corresponding to functions (Mittal et al 2021a , b , c ). Thus, considering structural classifications in fusogenic components of VMPs (White et al 2008 ), it was natural to test whether VMPs obey “stoichiometry-driven protein folding” (Agutter 2011 ).…”

Section: From Influenza Ha-mediated Membrane Fusion To Other Envelope...mentioning

confidence: 99%

Aspects of Biological Replication and Evolution Independent of the Central Dogma: Insights from Protein-Free Vesicular Transformations and Protein-Mediated Membrane Remodeling

Mittal

Chauhan

2022

J Membrane Biol

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Biological membrane remodeling is central to living systems. In spite of serving as “containers” of whole-living systems and functioning as dynamic compartments within living systems, biological membranes still find a “blue collar” treatment compared to the “white collar” nucleic acids and proteins in biology. This may be attributable to the fact that scientific literature on biological membrane remodeling is only 50 years old compared to ~ 150 years of literature on proteins and a little less than 100 years on nucleic acids. However, recently, evidence for symbiotic origins of eukaryotic cells from data only on biological membranes was reported. This, coupled with appreciation of reproducible amphiphilic self-assemblies in aqueous environments (mimicking replication), has already initiated discussions on origins of life beyond nucleic acids and proteins. This work presents a comprehensive compilation and meta-analyses of data on self-assembly and vesicular transformations in biological membranes—starting from model membranes to establishment of Influenza Hemagglutinin-mediated membrane fusion as a prototypical remodeling system to a thorough comparison between enveloped mammalian viruses and cellular vesicles. We show that viral membrane fusion proteins, in addition to obeying “stoichiometry-driven protein folding”, have tighter compositional constraints on their amino acid occurrences than general-structured proteins, regardless of type/class. From the perspective of vesicular assemblies and biological membrane remodeling (with and without proteins) we find that cellular vesicles are quite different from viruses. Finally, we propose that in addition to pre-existing thermodynamic frameworks, kinetic considerations in de novo formation of metastable membrane structures with available “third-party” constituents (including proteins) were not only crucial for origins of life but also continue to offer morphological replication and/or functional mechanisms in modern life forms, independent of the central dogma. Graphic Abstract

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Tools for Characterizing Proteins: Circular Variance, Mutual Proximity, Chameleon Sequences, and Subsequence Propensities

Mezei

2022

Methods in Molecular Biology

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Unique and exclusive peptide signatures directly identify intrinsically disordered proteins from sequences without structural information

Cited by 5 publications

References 49 publications

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

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

Aspects of Biological Replication and Evolution Independent of the Central Dogma: Insights from Protein-Free Vesicular Transformations and Protein-Mediated Membrane Remodeling

Tools for Characterizing Proteins: Circular Variance, Mutual Proximity, Chameleon Sequences, and Subsequence Propensities

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