Mutagenesis of the central hydrophobic cluster in Aβ42 Alzheimer's peptide

Groot, Natalia Sánchez de; Aviles, Francesc X.; Vendrell, Josep; Ventura, Salvador

doi:10.1111/j.1742-4658.2005.05102.x

Cited by 161 publications

(153 citation statements)

References 53 publications

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“…The following methods are also available as Web services: The AGGRESCAN [Conchillo-Solé et al, 2007] method is based on aggregation propensity values assigned to each amino acid residue determined by experimental studies [de Groot et al, 2006]. TANGO [Fernandez-Escamilla et al, 2004] is a method based on secondary structure propensities and estimation of desolvation energy.…”

Section: Aggregationmentioning

confidence: 99%

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

2009

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Many gene defects are relatively easy to identify experimentally, but obtaining information about the effects of sequence variations and elucidation of the detailed molecular mechanisms of genetic diseases will be among the next major efforts in mutation research. Amino acid substitutions may have diverse effects on protein structure and function; thus, a detailed analysis of the mutations is essential. Experimental study of the molecular effects of mutations is laborious, whereas useful and reliable information about the effects of amino acid substitutions can readily be obtained by theoretical methods. Experimentally defined structures and molecular modeling can be used as a basis for interpretation of the mutations. The effects of missense mutations can be analyzed even when the 3D structure of the protein has not been determined, although structure-based analyses are more reliable. Structural analyses include studies of the contacts between residues, their implication for the stability of the protein, and the effects of the introduced residues. Investigations of steric and stereochemical consequences of substitutions provide insights on the molecular fit of the introduced residue. Mutations that change the electrostatic surface potential of a protein have wide-ranging effects. Analyses of the effects of mutations on interactions with ligands and partners have been performed for elucidation of functional mutations. We have employed numerous methods for predicting the effects of amino acid substitutions. We discuss the applicability of these methods in the analysis of genes, proteins, and diseases to reveal protein structure-function relationships, which is essential to gain insights into disease genotype-phenotype correlations.

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Section: Aggregationmentioning

confidence: 99%

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

2009

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“…However, the relationship between the protein aggregation propensities and the primary sequences remains poorly understood. Because it is empirically known that some proteins tend to aggregate, several groups systematically studied the effects of mutations in on proteins of interest that caused the formation of insoluble aggregates (6)(7)(8)(9). Subsequently, the information on the mutations has been used to build prediction tools for protein aggregation, and most of them were developed for amyloid formation (10)(11)(12)(13).…”

mentioning

confidence: 99%

Bimodal protein solubility distribution revealed by an aggregation analysis of the entire ensemble of Escherichia coli proteins

Niwa

Ying

Saito

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

275

412

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Protein folding often competes with intermolecular aggregation, which in most cases irreversibly impairs protein function, as exemplified by the formation of inclusion bodies. Although it has been empirically determined that some proteins tend to aggregate, the relationship between the protein aggregation propensities and the primary sequences remains poorly understood. Here, we individually synthesized the entire ensemble of Escherichia coli proteins by using an in vitro reconstituted translation system and analyzed the aggregation propensities. Because the reconstituted translation system is chaperone-free, we could evaluate the inherent aggregation propensities of thousands of proteins in a translation-coupled manner. A histogram of the solubilities, based on data from 3,173 translated proteins, revealed a clear bimodal distribution, indicating that the aggregation propensities are not evenly distributed across a continuum. Instead, the proteins can be categorized into 2 groups, soluble and aggregation-prone proteins. The aggregation propensity is most prominently correlated with the structural classification of proteins, implying that the prediction of aggregation propensity requires structural information about the protein.cell-free translation ͉ protein aggregation ͉ protein folding

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“…Naturally occurring point mutations in the amyloid precursor protein (APP) clustered around the central region of the Aβ residues are related to familial forms of AD [81]. However, designed synthetic point substitutions significantly alter the channel activity, suppressing Aβ toxicity.…”

Section: Figmentioning

confidence: 99%

Computational Methods for Structural and Functional Studies of Alzheimer’s Amyloid Ion Channels

Jang¹,

Arce²,

Lee³

et al. 2016

Methods in Molecular Biology

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Aggregation can be studied by a range of methods, experimental and computational. Aggregates form in solution, across solid surfaces, and on and in the membrane, where they may assemble into unregulated leaking ion channels. Experimental probes of ion channel conformations and dynamics are challenging. Atomistic molecular dynamics (MD) simulations are capable of providing insight into structural details of amyloid ion channels in the membrane at a resolution not achievable experimentally. Since data suggest that late stage Alzheimer's disease involves formation of toxic ion channels, MD simulations have been used aiming to gain insight into the channel shapes, morphologies, pore dimensions, conformational heterogeneity, and activity. These can be exploited for drug discovery. Here we describe computational methods to model amyloid ion channels containing the β-sheet motif at atomic scale and to calculate toxic pore activity in the membrane.

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Mutagenesis of the central hydrophobic cluster in Aβ42 Alzheimer's peptide

Cited by 161 publications

References 53 publications

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

Bimodal protein solubility distribution revealed by an aggregation analysis of the entire ensemble of Escherichia coli proteins

Computational Methods for Structural and Functional Studies of Alzheimer’s Amyloid Ion Channels

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