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

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AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures

Protein aggregation underlies an increasing number of disorders and constitutes a major bottleneck in the development of therapeutic proteins. Our present understanding on the molecular determinants of protein aggregation has crystalized in a series of predictive algorithms to identify aggregation-prone sites. A majority of these methods rely only on sequence. Therefore, they find difficulties ...

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Sequence-based prediction of protein solubility.

In order to investigate the relationship between the thermodynamics and kinetics of protein aggregation, we compared the solubility of proteins with their aggregation rates. We found a significant correlation between these two quantities by considering a database of protein solubility values measured using an in vitro reconstituted translation system containing about 70% of Escherichia coli pro...

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Protein solubility: sequence based prediction and experimental verification

MOTIVATION Obtaining soluble proteins in sufficient concentrations is a recurring limiting factor in various experimental studies. Solubility is an individual trait of proteins which, under a given set of experimental conditions, is determined by their amino acid sequence. Accurate theoretical prediction of solubility from sequence is instrumental for setting priorities on targets in large-scal...

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SOLpro: accurate sequence-based prediction of protein solubility

MOTIVATION Protein insolubility is a major obstacle for many experimental studies. A sequence-based prediction method able to accurately predict the propensity of a protein to be soluble on overexpression could be used, for instance, to prioritize targets in large-scale proteomics projects and to identify mutations likely to increase the solubility of insoluble proteins. RESULTS Here, we firs...

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ژورنال

عنوان ژورنال: Nucleic Acids Research

سال: 2019

ISSN: 0305-1048,1362-4962

DOI: 10.1093/nar/gkz321