Article

Hydropathy patterning complements charge patterning to describe conformational preferences of disordered proteins

2020-01-25

Abstract excerpt

Understanding the conformational ensemble of an intrinsically disordered protein (IDP) is of great interest due to its relevance to critical intracellular functions and diseases. It is now well established that the polymer scaling behavior can provide a great deal of information about the conformational properties as well as liquid-liquid phase separation of an IDP. It is, therefore, extremely desirable to be able...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d21a1039-f1c8-51ff-9f7a-1a6d1192938b
DOI: 10.1101/2020.01.25.919498

Open publication

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Click a neighbor to travelStep 1 · 12 closest

Hydropathy patterning complements charge patterning to describe conformational preferences of disordered proteinsDOI 10.1101/2020.01.25.919498Read

Expanding the molecular language of protein liquid-liquid phase separationSemantic proximity Read

A Systematic Evaluation of Protein Phase Separation Predictors Across Diverse Protein LandscapesSemantic proximity Read

Dipeptides are minimalistic but sufficient for liquid-liquid phase separationSemantic proximity Read

Resolving Local and Global Conformational Heterogeneity of the Human Intrinsically Disordered ProteomeSemantic proximity Read

Sequence-encoded conformational biases shape self-assembly modes of intrinsically disordered proteinsSemantic proximity Read

Variants of intrinsic disorder: structural characterizationSemantic proximity Read

Sequence Determinants of the Aggregation of Proteins Within Condensates Generated by Liquid-liquid Phase Separation.Semantic proximity Read

Assessing the helical stability of polyXYs at the boundaries of Intrinsically Disordered Regions with MD simulationsSemantic proximity Read

FuzDrop on AlphaFold: visualizing the sequence-dependent propensity of liquid-liquid phase separation and aggregation of proteins.Semantic proximity Read

A machine learning framework for predicting and modulating condition-dependent protein phase separation.Semantic proximity Read

A machine learning framework for predicting and modulating condition-dependent protein phase separationSemantic proximity Read

Drude2019IDPC polarizable force field reveals structure-function relationship of insulin.Semantic proximity Read