Combining Structural Aggregation Propensity and Stability Predictions to Redesign Protein Solubility

Marcos Gil-Garcia; Manuel Banó-Polo; Nathalia Varejao; Michal Jamroz; Aleksander Kuriata; Marta Díaz-Caballero; Jara Lascorz; Bertrand Morel; Susanna Navarro; David Reverter; Sebastian Kmiecik; Salvador Ventura

doi:10.1021/acs.molpharmaceut.8b00341

Combining Structural Aggregation Propensity and Stability Predictions to Redesign Protein Solubility

Marcos Gil-Garcia, Manuel Banó-Polo, Nathalia Varejao, Michal Jamroz, Aleksander Kuriata, Marta Díaz-Caballero, Jara Lascorz, Bertrand Morel, Susanna Navarro, David Reverter, Sebastian Kmiecik, Salvador Ventura

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43 Citations (Scopus)

Abstract

Copyright © 2018 American Chemical Society. The aggregation propensity of each particular protein seems to be shaped by evolution according to its natural abundance in the cell. The production and downstream processing of recombinant polypeptides implies attaining concentrations that are orders of magnitude above their natural levels, often resulting in their aggregation; a phenomenon that precludes the marketing of many globular proteins for biomedical or biotechnological applications. Therefore, there is a huge interest in methods aimed to increase the proteins solubility above their natural limits. Here, we demonstrate that an updated version of our AGGRESCAN 3D structural aggregation predictor, that now takes into account protein stability, allows for designing mutations at specific positions in the structure that improve the solubility of proteins without compromising their conformation. Using this approach, we have designed a highly soluble variant of the green fluorescent protein and a human single-domain VH antibody displaying significantly reduced aggregation propensity. Overall, our data indicate that the solubility of unrelated proteins can be easily tuned by in silico-designed nondestabilizing amino acid changes at their surfaces.

Original language	English
Pages (from-to)	3846-3859
Journal	Molecular Pharmaceutics
Volume	15
DOIs	https://doi.org/10.1021/acs.molpharmaceut.8b00341
Publication status	Published - 4 Sept 2018

Keywords

Aβ peptide
green fluorescent protein
protein aggregation
protein stability
protein structure
single-domain antibodies

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10.1021/acs.molpharmaceut.8b00341

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title = "Combining Structural Aggregation Propensity and Stability Predictions to Redesign Protein Solubility",

abstract = "Copyright {\textcopyright} 2018 American Chemical Society. The aggregation propensity of each particular protein seems to be shaped by evolution according to its natural abundance in the cell. The production and downstream processing of recombinant polypeptides implies attaining concentrations that are orders of magnitude above their natural levels, often resulting in their aggregation; a phenomenon that precludes the marketing of many globular proteins for biomedical or biotechnological applications. Therefore, there is a huge interest in methods aimed to increase the proteins solubility above their natural limits. Here, we demonstrate that an updated version of our AGGRESCAN 3D structural aggregation predictor, that now takes into account protein stability, allows for designing mutations at specific positions in the structure that improve the solubility of proteins without compromising their conformation. Using this approach, we have designed a highly soluble variant of the green fluorescent protein and a human single-domain VH antibody displaying significantly reduced aggregation propensity. Overall, our data indicate that the solubility of unrelated proteins can be easily tuned by in silico-designed nondestabilizing amino acid changes at their surfaces.",

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author = "Marcos Gil-Garcia and Manuel Ban{\'o}-Polo and Nathalia Varejao and Michal Jamroz and Aleksander Kuriata and Marta D{\'i}az-Caballero and Jara Lascorz and Bertrand Morel and Susanna Navarro and David Reverter and Sebastian Kmiecik and Salvador Ventura",

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doi = "10.1021/acs.molpharmaceut.8b00341",

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T1 - Combining Structural Aggregation Propensity and Stability Predictions to Redesign Protein Solubility

AU - Gil-Garcia, Marcos

AU - Banó-Polo, Manuel

AU - Varejao, Nathalia

AU - Jamroz, Michal

AU - Kuriata, Aleksander

AU - Díaz-Caballero, Marta

AU - Lascorz, Jara

AU - Morel, Bertrand

AU - Navarro, Susanna

AU - Reverter, David

AU - Kmiecik, Sebastian

AU - Ventura, Salvador

PY - 2018/9/4

Y1 - 2018/9/4

N2 - Copyright © 2018 American Chemical Society. The aggregation propensity of each particular protein seems to be shaped by evolution according to its natural abundance in the cell. The production and downstream processing of recombinant polypeptides implies attaining concentrations that are orders of magnitude above their natural levels, often resulting in their aggregation; a phenomenon that precludes the marketing of many globular proteins for biomedical or biotechnological applications. Therefore, there is a huge interest in methods aimed to increase the proteins solubility above their natural limits. Here, we demonstrate that an updated version of our AGGRESCAN 3D structural aggregation predictor, that now takes into account protein stability, allows for designing mutations at specific positions in the structure that improve the solubility of proteins without compromising their conformation. Using this approach, we have designed a highly soluble variant of the green fluorescent protein and a human single-domain VH antibody displaying significantly reduced aggregation propensity. Overall, our data indicate that the solubility of unrelated proteins can be easily tuned by in silico-designed nondestabilizing amino acid changes at their surfaces.

AB - Copyright © 2018 American Chemical Society. The aggregation propensity of each particular protein seems to be shaped by evolution according to its natural abundance in the cell. The production and downstream processing of recombinant polypeptides implies attaining concentrations that are orders of magnitude above their natural levels, often resulting in their aggregation; a phenomenon that precludes the marketing of many globular proteins for biomedical or biotechnological applications. Therefore, there is a huge interest in methods aimed to increase the proteins solubility above their natural limits. Here, we demonstrate that an updated version of our AGGRESCAN 3D structural aggregation predictor, that now takes into account protein stability, allows for designing mutations at specific positions in the structure that improve the solubility of proteins without compromising their conformation. Using this approach, we have designed a highly soluble variant of the green fluorescent protein and a human single-domain VH antibody displaying significantly reduced aggregation propensity. Overall, our data indicate that the solubility of unrelated proteins can be easily tuned by in silico-designed nondestabilizing amino acid changes at their surfaces.

KW - Aβ peptide

KW - green fluorescent protein

KW - protein aggregation

KW - protein stability

KW - protein structure

KW - single-domain antibodies

U2 - 10.1021/acs.molpharmaceut.8b00341

DO - 10.1021/acs.molpharmaceut.8b00341

M3 - Article

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SN - 1543-8384

VL - 15

SP - 3846

EP - 3859

JO - Molecular Pharmaceutics

JF - Molecular Pharmaceutics

ER -

Combining Structural Aggregation Propensity and Stability Predictions to Redesign Protein Solubility

Abstract

Keywords

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