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11 pages, 1479 KiB

Open AccessArticle

How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL

by Hiroto Anbo, Koya Sakuma, Satoshi Fukuchi and Motonori Ota

Biology 2023, 12(2), 182; https://doi.org/10.3390/biology12020182 - 25 Jan 2023

Cited by 5 | Viewed by 4289

AlphaFold2 (AF2) is a protein structure prediction program which provides accurate models. In addition to predicting structural domains, AF2 assigns intrinsically disordered regions (IDRs) by identifying regions with low prediction reliability (pLDDT). Some regions in IDRs undergo disorder-to-order transition upon binding the interaction partner. Here we assessed model structures of AF2 based on the annotations in IDEAL, in which segments with disorder-to-order transition have been collected as Protean Segments (ProSs). We non-redundantly selected ProSs from IDEAL and classified them based on the root mean square deviation to the corresponding region of AF2 models. Statistical analysis identified 11 structural and sequential features, possibly contributing toward the prediction of ProS structures. These features were categorized into two groups: one that contained pLDDT and the other that contained normalized radius of gyration. The typical ProS structures in the former group comprise a long α helix or a whole or part of the structural domain and those in the latter group comprise a short α helix with terminal loops. Full article

(This article belongs to the Special Issue Intrinsically Disordered Proteins Interactions with Their Molecular Environment at the Crossroad between Theory and Experiments)

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19 pages, 2358 KiB

Open AccessFeature PaperArticle

Bioinformatic Analysis of Lytic Polysaccharide Monooxygenases Reveals the Pan-Families Occurrence of Intrinsically Disordered C-Terminal Extensions

by Ketty C. Tamburrini, Nicolas Terrapon, Vincent Lombard, Bastien Bissaro, Sonia Longhi and Jean-Guy Berrin

Biomolecules 2021, 11(11), 1632; https://doi.org/10.3390/biom11111632 - 4 Nov 2021

Cited by 28 | Viewed by 4369

Abstract

Lytic polysaccharide monooxygenases (LPMOs) are monocopper enzymes secreted by many organisms and viruses. LPMOs catalyze the oxidative cleavage of different types of polysaccharides and are today divided into eight families (AA9–11, AA13–17) within the Auxiliary Activity enzyme class of the CAZy database. LPMOs minimal architecture encompasses a catalytic domain, to which can be appended a carbohydrate-binding module. Intriguingly, we observed that some LPMO sequences also display a C-terminal extension of varying length not associated with any known function or fold. Here, we analyzed 27,060 sequences from different LPMO families and show that 60% have a C-terminal extension predicted to be intrinsically disordered. Our analysis shows that these disordered C-terminal regions (dCTRs) are widespread in all LPMO families (except AA13) and differ in terms of sequence length and amino-acid composition. Noteworthily, these dCTRs have so far only been observed in LPMOs. LPMO-dCTRs share a common polyampholytic nature and an enrichment in serine and threonine residues, suggesting that they undergo post-translational modifications. Interestingly, dCTRs from AA11 and AA15 are enriched in redox-sensitive, conditionally disordered regions. The widespread occurrence of dCTRs in LPMOs from evolutionarily very divergent organisms, hints at a possible functional role and opens new prospects in the field of LPMOs. Full article

(This article belongs to the Special Issue Lytic Polysaccharide Monooxygenases: Diversity and Molecular Events)

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12 pages, 1441 KiB

Open AccessArticle

DispHred: A Server to Predict pH-Dependent Order–Disorder Transitions in Intrinsically Disordered Proteins

by Jaime Santos, Valentín Iglesias, Carlos Pintado, Juan Santos-Suárez and Salvador Ventura

Int. J. Mol. Sci. 2020, 21(16), 5814; https://doi.org/10.3390/ijms21165814 - 13 Aug 2020

Cited by 18 | Viewed by 4920

Abstract

The natively unfolded nature of intrinsically disordered proteins (IDPs) relies on several physicochemical principles, of which the balance between a low sequence hydrophobicity and a high net charge appears to be critical. Under this premise, it is well-known that disordered proteins populate a defined region of the charge–hydropathy (C–H) space and that a linear boundary condition is sufficient to distinguish between folded and disordered proteins, an approach widely applied for the prediction of protein disorder. Nevertheless, it is evident that the C–H relation of a protein is not unalterable but can be modulated by factors extrinsic to its sequence. Here, we applied a C–H-based analysis to develop a computational approach that evaluates sequence disorder as a function of pH, assuming that both protein net charge and hydrophobicity are dependent on pH solution. On that basis, we developed DispHred, the first pH-dependent predictor of protein disorder. Despite its simplicity, DispHred displays very high accuracy in identifying pH-induced order/disorder protein transitions. DispHred might be useful for diverse applications, from the analysis of conditionally disordered segments to the synthetic design of disorder tags for biotechnological applications. Importantly, since many disorder predictors use hydrophobicity as an input, the here developed framework can be implemented in other state-of-the-art algorithms. Full article

(This article belongs to the Special Issue Intrinsically Disordered Proteins (IDPs): From Physical Chemistry to Pathogenic Mechanisms)

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