Zbynek Prokop

Dr. Zbynek Prokop


Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 October 2013 in ACS Catalysis
Verified
Journal Article
Closed access
VSVeronika Stepankova
Veronika Stepankova
SBSarka Bidmanova
Sarka Bidmanova
TKTana Koudelakova
Tana Koudelakova
ZPZbynek Prokop
Zbynek Prokop
RCRadka Chaloupkova
Radka Chaloupkova
JDJiri Damborsky
Jiri Damborsky

13 December 2019 in ACS Catalysis
Verified
Journal Article
Closed access
SMStanislav Mazurenko
Stanislav Mazurenko
ZPZbynek Prokop
Zbynek Prokop
JDJiri Damborsky
Jiri Damborsky

23 August 2009 in Nature Chemical Biology
Verified
Journal Article
Closed access
MPMartina Pavlova
Martina Pavlova
MKMartin Klvana
Martin Klvana
ZPZbynek Prokop
Zbynek Prokop
RCRadka Chaloupkova
Radka Chaloupkova
PBPavel Banas
Pavel Banas
JDJiri Damborsky
Jiri Damborsky

21 December 2015 in Microbial Cell Factories
Verified
Journal Article
Open access
PDF file
PDPavel Dvorak
Pavel Dvorak
LCLukas Chrast
Lukas Chrast
PNPablo I. Nikel
Pablo I. Nikel
RFRadek Fedr
Radek Fedr
KSKarel Souček
Karel Souček
JDJiri Damborsky
Jiri Damborsky
Heterologous expression systems based on promoters inducible with isopropyl-β-D-1-thiogalactopyranoside (IPTG), e.g., Escherichia coli BL21(DE3) and cognate LacIQ/P lacUV5 -T7 vectors, are commonly used for production of recombinant proteins and metabolic pathways. The applicability of such cell factories is limited by the complex physiological burden imposed by overexpression of the exogenous genes during a bioprocess. This burden originates from a combination of stresses that may include competition for the expression machinery, side-reactions due to the activity of the recombinant proteins, or the toxicity of their substrates, products and intermediates. However, the physiological impact of IPTG-induced conditional expression on the recombinant host under such harsh conditions is often overlooked. The physiological responses to IPTG of the E. coli BL21(DE3) strain and three different recombinants carrying a synthetic metabolic pathway for biodegradation of the toxic anthropogenic pollutant 1,2,3-trichloropropane (TCP) were investigated using plating, flow cytometry, and electron microscopy. Collected data revealed unexpected negative synergistic effect of inducer of the expression system and toxic substrate resulting in pronounced physiological stress. Replacing IPTG with the natural sugar effector lactose greatly reduced such stress, demonstrating that the effect was due to the original inducer’s chemical properties. IPTG is not an innocuous inducer; instead, it exacerbates the toxicity of haloalkane substrate and causes appreciable damage to the E. coli BL21(DE3) host, which is already bearing a metabolic burden due to its content of plasmids carrying the genes of the synthetic metabolic pathway. The concentration of IPTG can be effectively tuned to mitigate this negative effect. Importantly, we show that induction with lactose, the natural inducer of P lac , dramatically lightens the burden without reducing the efficiency of the synthetic TCP degradation pathway. This suggests that lactose may be a better inducer than IPTG for the expression of heterologous pathways in E. coli BL21(DE3).

26 April 2017 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
MMMilos Musil
Milos Musil
JSJan Stourac
Jan Stourac
JBJaroslav Bendl
Jaroslav Bendl
Jan BrezovskyJan Brezovsky
Jan Brezovsky
ZPZbynek Prokop
Zbynek Prokop
JDJiri Damborsky
Jiri Damborsky
There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot.

3 November 2015 in PLOS Computational Biology
Verified
Journal Article
Open access
PDF file
DBDavid Bednar
David Bednar
KBKoen Beerens
Koen Beerens
ESEva Sebestova
Eva Sebestova
JBJaroslav Bendl
Jaroslav Bendl
SKSagar Khare
Sagar Khare
JDJiri Damborsky
Jiri Damborsky
There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt’s reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications. Proteins are increasingly used in numerous biotechnological applications. A key property determining proteins’ applicability is their stability under operating conditions. Natural proteins can be stabilized by modification of their structure. Methods of molecular biology allow introduction of modifications–mutations–to the protein structure at will, but it is not straightforward where to mutate and which amino acid to introduce for better stability. Computational methods can be used for prediction of stabilizing mutations using computers. Current computational methods predict libraries of single-point mutations, which need to be constructed individually, tested and recombined, resulting in non-trivial experimental effort. Here we present a robust computational strategy for predicting multiple-point mutants, providing extremely stabilized proteins with a minimal experimental effort.