Usage of a Dataset of NMR Resolved Protein Structures to Test Aggregation Versus Solubility Prediction Algorithms

Overview

Journal Protein Sci

Specialty Biochemistry

Date 2017 Jul 8

PMID 28685932

Citations 9

Authors

Daniel B Roche

Etienne Villain

Andrey V Kajava

Affiliations

Soon will be listed here.

Abstract

There has been an increased interest in computational methods for amyloid and (or) aggregate prediction, due to the prevalence of these aggregates in numerous diseases and their recently discovered functional importance. To evaluate these methods, several datasets have been compiled. Typically, aggregation-prone regions of proteins, which form aggregates or amyloids in vivo, are more than 15 residues long and intrinsically disordered. However, the number of such experimentally established amyloid forming and non-forming sequences are limited, not exceeding one hundred entries in existing databases. In this work, we parsed all available NMR-resolved protein structures from the PDB and assembled a new, sevenfold larger, dataset of unfolded sequences, soluble at high concentrations. We proposed to use these sequences as a negative set for evaluating methods for predicting aggregation in vivo. We also present the results of benchmarking cutting edge tools for the prediction of aggregation versus solubility propensity.

Citing Articles

Identification of New FG-Repeat Nucleoporins with Amyloid Properties.

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NOS1AP Interacts with α-Synuclein and Aggregates in Yeast and Mammalian Cells.

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Solubility of proteins.

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The Human NUP58 Nucleoporin Can Form Amyloids In Vitro and In Vivo.

Danilov L, Moskalenko S, Matveenko A, Sukhanova X, Belousov M, Zhouravleva G Biomedicines. 2021; 9(10).

PMID: 34680573 PMC: 8533070. DOI: 10.3390/biomedicines9101451.

Solubility and Aggregation of Selected Proteins Interpreted on the Basis of Hydrophobicity Distribution.

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