Prion‐like proteins: from computational approaches to proteome‐wide analysis

Gil-García, Marcos; Iglesias, Valentín; Pallarès, Irantzu; Ventura, Salvador

doi:10.1002/2211-5463.13213

Cited by 18 publications

(15 citation statements)

References 143 publications

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“…Around 1% of the total proteome of these species was predicted as PrLDs, spanning from 0.62% ( O. sativa ) to 1.57% ( A. thaliana ). In comparison with other studied model organisms ( Gil-Garcia et al., 2021 ), this average is similar to the proportion of human, bacteria, and viruses PrLDs and lower than S. cerevisiae (~3%) ( Figure 1 ; Table 1 ).…”

Section: Resultssupporting

confidence: 68%

Exploring cryptic amyloidogenic regions in prion-like proteins from plants

Pintado-Grima

Santos²,

Iglesias³

et al. 2023

Front. Plant Sci.

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Prion-like domains (PrLDs) are intrinsically disordered regions (IDRs) of low sequence complexity with a similar composition to yeast prion domains. PrLDs-containing proteins have been involved in different organisms’ regulatory processes. Regions of moderate amyloid propensity within IDRs have been shown to assemble autonomously into amyloid fibrils. These sequences tend to be rich in polar amino acids and often escape from the detection of classical bioinformatics screenings that look for highly aggregation-prone hydrophobic sequence stretches. We defined them as cryptic amyloidogenic regions (CARs) and recently developed an integrated database that collects thousands of predicted CARs in IDRs. CARs seem to be evolutionary conserved among disordered regions because of their potential to stablish functional contacts with other biomolecules. Here we have focused on identifying and characterizing CARs in prion-like proteins (pCARs) from plants, a lineage that has been poorly studied in comparison with other prionomes. We confirmed the intrinsic amyloid potential for a selected pCAR from Arabidopsis thaliana and explored functional enrichments and compositional bias of pCARs in plant prion-like proteins.

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Section: Resultssupporting

confidence: 68%

Exploring cryptic amyloidogenic regions in prion-like proteins from plants

Pintado-Grima

Santos²,

Iglesias³

et al. 2023

Front. Plant Sci.

Self Cite

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“…This is the basis for a number of algorithms for identifying candidate prionogenic domains [24,25]. One such algorithm is prion-like amino acid composition (PLAAC) analysis, which allows for the evaluation of prion-like domains based on the hidden Markov model (HMM) that also incorporates other prion-like domain-predictive algorithms PAPA, DIANA, and FoldIndex [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Prion-like Domains in Spike Protein of SARS-CoV-2 Differ across Its Variants and Enable Changes in Affinity to ACE2

Tetz

2022

Microorganisms

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Currently, the world is struggling with the coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Prions are proteins that possess a unique conformational conversion, with the ability to rapidly shift between multiple conformations due to residue hydrophobicity and net sequence charge, and viral prion-like proteins are known as potential regulators of viral infections. However, the prion-like domains (PrD) in the SARS-CoV-2 proteome have not been analyzed. In this in silico study, using the PLAAC algorithm, we identified the presence of prion-like domains in the SARS-CoV-2 spike protein. Compared with other viruses, a striking difference was observed in the distribution of prion-like domains in the spike protein since SARS-CoV-2 is the only coronavirus with a prion-like domain found in the receptor-binding domain of the S1 region of the spike protein. The presence and unique distribution of prion-like domains in the SARS-CoV-2 receptor-binding domains of the spike protein are particularly interesting since although the SARS-CoV-2 and SARS-CoV S proteins share the same host cell receptor, angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 demonstrates a 10- to 20-fold higher affinity for ACE2. We identified prion-like domains in the α1 helix of the ACE2 receptor that interact with the viral receptor-binding domain of SARS-CoV-2. Finally, we found substantial differences in the prion-like domain of the S1 region of the spike protein across emerging variants including Omicron (B.1.1.529). Taken together, the present findings indicate that the identified PrDs in the SARS-CoV-2 receptor-binding domain (RBD) and ACE2 region that interact with RBD play important functional roles in viral adhesion and entry.

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“…For example, amyloid fibrils which aggregate in the brain and central nervous system, are related to Alzheimer’s and Parkinson’s diseases ( 2 ). Another example is a prion conversion, where ingested misfolded proteins can seed the aggregation of their homologous polypeptide sequence ( 3 ). Similar mechanisms can trigger other amyloidoses ( 4 ), but experimental data considering such phenomena are dispersed and often very incompatible.…”

Section: Introductionmentioning

confidence: 99%

AmyloGraph: a comprehensive database of amyloid–amyloid interactions

Burdukiewicz

Rafacz

Barbach

et al. 2022

Nucleic Acids Research

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Information about the impact of interactions between amyloid proteins on their fibrillization propensity is scattered among many experimental articles and presented in unstructured form. We manually curated information located in almost 200 publications (selected out of 562 initially considered), obtaining details of 883 experimentally studied interactions between 46 amyloid proteins or peptides. We also proposed a novel standardized terminology for the description of amyloid–amyloid interactions, which is included in our database, covering all currently known types of such a cross-talk, including inhibition of fibrillization, cross-seeding and other phenomena. The new approach allows for more specific studies on amyloids and their interactions, by providing very well-defined data. AmyloGraph, an online database presenting information on amyloid–amyloid interactions, is available at (http://AmyloGraph.com/). Its functionalities are also accessible as the R package (https://github.com/KotulskaLab/AmyloGraph). AmyloGraph is the only publicly available repository for experimentally determined amyloid–amyloid interactions.

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Prion‐like proteins: from computational approaches to proteome‐wide analysis

Cited by 18 publications

References 143 publications

Exploring cryptic amyloidogenic regions in prion-like proteins from plants

Exploring cryptic amyloidogenic regions in prion-like proteins from plants

Prion-like Domains in Spike Protein of SARS-CoV-2 Differ across Its Variants and Enable Changes in Affinity to ACE2

AmyloGraph: a comprehensive database of amyloid–amyloid interactions

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