Prediction of Protein Aggregation and Amyloid Formation

Graña-Montes, Ricardo; Pujols-Pujol, Jordi; Gómez-Picanyol, Carlota; Ventura, Salvador

doi:10.1007/978-94-024-1069-3_7

Cited by 4 publications

(4 citation statements)

References 213 publications

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“…The development of in silico tools able to predict protein aggregation propensities has provided scientists with a versatile toolbox to assist and guide basic research and protein engineering processes [12]. These algorithms exploit the evidence that protein aggregation is driven by short and specific stretches, known as aggregation-prone regions (APRs), displaying unique physicochemical features: low net charge, high hydrophobicity and, frequently, a preference for β-sheet secondary structure [13]. AGGRESCAN, Amylpred, Amyloid Mutants, FoldAmyloid, MetAmyl, PASTA, Tango, Waltz and Zyggregator [14][15][16][17][18][19][20][21][22][23] are some examples of this kind of program.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, APRs usually comprise highly hydrophobic sequence stretches [27,28] and mutations of polar residues to nonpolar ones exacerbate aggregation [29], whereas changes in the opposite direction promote solubility. Therefore, it is not surprising that hydrophobicity is given a major weight, directly or indirectly, in the different equations implemented in sequence-based aggregation predictors [13,30]. Of note, all the aforementioned algorithms assume that the lipophilicity of the sequence is independent of the pH.…”

Section: Introductionmentioning

confidence: 99%

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pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

Santos

Iglesias

Santos-Suárez

et al. 2020

Cells

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Protein aggregation is associated with an increasing number of human disorders and premature aging. Moreover, it is a central concern in the manufacturing of recombinant proteins for biotechnological and therapeutic applications. Nevertheless, the unique architecture of protein aggregates is also exploited by nature for functional purposes, from bacteria to humans. The relevance of this process in health and disease has boosted the interest in understanding and controlling aggregation, with the concomitant development of a myriad of algorithms aimed to predict aggregation propensities. However, most of these programs are blind to the protein environment and, in particular, to the influence of the pH. Here, we developed an empirical equation to model the pH-dependent aggregation of intrinsically disordered proteins (IDPs) based on the assumption that both the global protein charge and lipophilicity depend on the solution pH. Upon its parametrization with a model IDP, this simple phenomenological approach showed unprecedented accuracy in predicting the dependence of the aggregation of both pathogenic and functional amyloidogenic IDPs on the pH. The algorithm might be useful for diverse applications, from large-scale analysis of IDPs aggregation properties to the design of novel reversible nanofibrillar materials.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

Santos

Iglesias

Santos-Suárez

et al. 2020

Cells

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“…Leishmania differentiation from promastigotes to amastigotes is induced by acid pH and high temperature ( 39 , 40 ), two factors which increase protein aggregation ( 41 , 42 ). The antileishmanial effect of certain peptide aggregation inhibitors on amastigotes might be related to the upsetting of some essential differentiation mechanism in the parasite.…”

Section: Resultsmentioning

confidence: 99%

Effect of the aggregated protein dye YAT2150 on Leishmania parasite viability

Román-Álamo,

Avalos-Padilla,

Bouzón-Arnáiz

et al. 2024

Antimicrob Agents Chemother

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The problems associated with the drugs currently used to treat leishmaniasis, including resistance, toxicity, and the high cost of some formulations, call for the urgent identification of new therapeutic agents with novel modes of action. The aggregated protein dye YAT2150 has been found to be a potent antileishmanial compound, with a half-maximal inhibitory concentration (IC 50 ) of approximately 0.5 µM against promastigote and amastigote stages of Leishmania infantum . The encapsulation in liposomes of YAT2150 significantly improved its in vitro IC 50 to 0.37 and 0.19 µM in promastigotes and amastigotes, respectively, and increased the half-maximal cytotoxic concentration in human umbilical vein endothelial cells to >50 µM. YAT2150 became strongly fluorescent when binding intracellular protein deposits in Leishmania cells. This fluorescence pattern aligns with the proposed mode of action of this drug in the malaria parasite Plasmodium falciparum , the inhibition of protein aggregation. In Leishmania major , YAT2150 rapidly reduced ATP levels, suggesting an alternative antileishmanial mechanism. To the best of our knowledge, this first-in-class compound is the only one described so far having significant activity against both Plasmodium and Leishmania , thus being a potential drug for the treatment of co-infections of both parasites.

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“…Those programs find difficulties predicting APRs of folded globular proteins, failing to detect APRs when residues are not contiguous in sequence or mistaking APRs for the buried hydrophobic core. These problems motivated the development of a second generation of algorithms that use structure-based approaches for their predictions (6). In 2015, we developed the Aggrescan3D (A3D) web server for prediction of aggregation properties of protein structures (7).…”

Section: Introductionmentioning

confidence: 99%

Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility

Kuriata

Iglesias

Pujols

et al. 2019

Nucleic Acids Research

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120

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Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and assist the engineering of soluble protein-based drugs. A few years ago, we developed a method for structure-based prediction of aggregation properties that takes into account the dynamic fluctuations of proteins. The method has been made available as the Aggrescan3D (A3D) web server and applied in numerous studies of protein structure-aggregation relationship. Here, we present a major update of the A3D web server to version 2.0. The new features include: extension of dynamic calculations to significantly larger and multimeric proteins, simultaneous prediction of changes in protein solubility and stability upon mutation, rapid screening for functional protein variants with improved solubility, a REST-ful service to incorporate A3D calculations in automatic pipelines, and a new, enhanced web server interface. A3D 2.0 is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/

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Prediction of Protein Aggregation and Amyloid Formation

Cited by 4 publications

References 213 publications

pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

Effect of the aggregated protein dye YAT2150 on Leishmania parasite viability

Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility

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