Publication Details

Computational Design of Stable and Soluble Biocatalysts

MUSIL, M.; KONEGGER, H.; HON, J.; BEDNÁŘ, D.; DAMBORSKÝ, J. Computational Design of Stable and Soluble Biocatalysts. ACS Catalysis, 2019, vol. 9, no. 2, p. 1033-1054. ISSN: 2155-5435.
Czech title
Výpočetní návrh stabilních a solubilních biokatalyzátorů
Type
journal article
Language
English
Authors
Musil Miloš, Ing., Ph.D. (DIFS)
Konegger Hannes
Hon Jiří, Ing., Ph.D.
Bednář David
Damborský Jiří, prof. Mgr., Dr. (UMEL)
URL
Keywords

Aggregation,Computational Design,Force Field,Expressibility,Machine
Learning,Phylogenetic Analysis,Enzyme Stability,Enzyme Solubility

Abstract

Natural enzymes are delicate biomolecules possessing only marginal thermodynamic
stability. Poorly stable, misfolded, and aggregated proteins lead to huge
economic losses in the biotechnology and biopharmaceutical industries.
Consequently, there is a need to design optimized protein sequences that maximize
stability, solubility, and activity over a wide range of temperatures and pH
values, in buffers of different composition, and in the presence of organic
co-solvents. This has created great interest in using computational methods to
enhance biocatalysts robustness and solubility. Suitable methods include (i)
energy calculations, (ii) machine learning, (iii) phylogenetic analyses and (iv)
combinations of these approaches. We have witnessed impressive progress in the
design of stable enzymes over the last two decades, but predictions of protein
solubility and expressibility are scarce. Stabilizing mutations can be predicted
accurately using available force fields, the number of sequences available for
phylogenetic analyses is growing, and complex computational workflows are being
implemented in intuitive web tools, enhancing the quality of protein stability
predictions. Conversely, solubility predictors are limited by the lack of robust
and balanced experimental data, an inadequate understanding of fundamental
principles of protein aggregation, and a dearth of structural information on
folding intermediates. Here we summarize recent progress in the development of
computational tools for predicting protein stability and solubility, critically
assess their strengths and weaknesses, and identify apparent gaps in data and
knowledge. We also present perspectives on the computational design of stable and
soluble biocatalysts.

Published
2019
Pages
1033–1054
Journal
ACS Catalysis, vol. 9, no. 2, ISSN 2155-5435
DOI
UT WoS
000458707000028
EID Scopus
BibTeX
@article{BUT155120,
  author="Miloš {Musil} and Hannes {Konegger} and Jiří {Hon} and David {Bednář} and Jiří {Damborský}",
  title="Computational Design of Stable and Soluble Biocatalysts",
  journal="ACS Catalysis",
  year="2019",
  volume="9",
  number="2",
  pages="1033--1054",
  doi="10.1021/acscatal.8b03613",
  issn="2155-5435",
  url="https://pubs.acs.org/doi/10.1021/acscatal.8b03613"
}
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