Publication in Journal of Chemical Information and Modeling

Marques SM,  Dunajova Z, Prokop Z, Chaloupkova R, Brezovsky J, Damborsky J, 2017: Catalytic Cycle of Haloalkane Dehalogenases towards Unnatural Substrates Explored by Computational Modeling. Journal of Chemical Information and Modeling 57: 1970–1989. full text

Abstract Image

The anthropogenic toxic compound 1,2,3-trichloropropane is poorly degradable by natural enzymes. We have previously constructed the haloalkane dehalogenase DhaA31 by focused directed evolution (Pavlova, M. et al. Nat. Chem. Biol. 2009, 5, 727−733), which is 32 times more active than the wild-type enzyme and is currently the most active variant known against that substrate. Recent evidence has shown that the structural basis responsible for the higher activity of DhaA31 was poorly understood. Here we have undertaken a comprehensive computational study of the main steps involved in the biocatalytic hydrolysis of 1,2,3-trichloropropane to decipher the structural basis for such enhancements. Using molecular dynamics and quantum mechanics approaches we have surveyed (i) the substrate binding, (ii) the formation of the reactive complex, (iii) the chemical step, and (iv) the release of the products. We showed that the binding of the substrate and its transport through the molecular tunnel to the active site is a relatively fast process. The cleavage of the carbon–halogen bond was previously identified as the rate-limiting step in the wild-type. Here we demonstrate that this step was enhanced in DhaA31 due to a significantly higher number of reactive configurations of the substrate and a decrease of the energy barrier to the SN2 reaction. C176Y and V245F were identified as the key mutations responsible for most of those improvements. The release of the alcohol product was found to be the rate-limiting step in DhaA31 primarily due to the C176Y mutation. Mutational dissection of DhaA31 and kinetic analysis of the intermediate mutants confirmed the theoretical observations. Overall, our comprehensive computational approach has unveiled mechanistic details of the catalytic cycle which will enable a balanced design of more efficient enzymes. This approach is applicable to deepen the biochemical knowledge of a large number of other systems and may contribute to robust strategies in the development of new biocatalysts.

Publication in Nucleic Acids Research

Musil M, Stourac J, Bendl J, Brezovsky J, Prokop Z, Zendulka J, Martinek T, Bednar D, Damborsky J, 2017: FireProt: Web Server for Automated Design of Thermostable Proteins. Nucleic Acids Research (in press, doi:10.1093/nar/gkx285). full text

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

Publication in ChemBioChem

Babkova P, Sebestova E, Brezovsky J, Chaloupkova R, Damborsky J, 2017: Ancestral Haloalkane Dehalogenases Show Robustness and Unique Substrate Specificity. ChemBioChem (in press, doi:10.1002/cbic.201700197). full text.

Ancestral sequence reconstruction (ASR) represents a powerful approach for empirical testing structure-function relationships of diverse proteins. We employed ASR to predict sequences of five ancestral haloalkane dehalogenases (HLDs) from the HLD-II subfamily. Genes encoding the inferred ancestral sequences were synthesized and expressed in Escherichia coli and the resurrected ancestral enzymes AncHLD1-5 were experimentally characterized. Strikingly, the ancestral HLDs exhibited significantly enhanced thermodynamic stability compared to extant enzymes (ΔTm up to 24 °C). Compared to extant HLDs, the ancestors displayed higher specific activities with preference for short multi-substituted halogenated substrates. Moreover, multivariate statistical analysis revealed a shift in the substrate specificity profiles of AncHLD1 and AncHLD2, which would be extremely difficult to achieve by rational protein engineering. The study highlights that ASR is an efficient approach for development of novel biocatalysts and robust templates for directed evolution.

Publication in Angewandte Chemie International Edition

Liskova V, Stepankova V, Bednar D, Brezovsky J, Prokop Z, Chaloupkova R, Damborsky J, 2017: Different Structural Origins of the Enantioselectivity of Haloalkane Dehalogenases toward Linear β-Haloalkanes: Open–Solvated versus Occluded–Desolvated Active Sites. Angewandte Chemie International Edition (in press, doi:10.1002/anie.201611193). full text

Two recipes for success: Two distinct mechanisms are described for the enantiodiscrimination of 2-bromopentane by haloalkane dehalogenases. Highly enantioselective DbjA has a very open, solvent-accessible active site. The engineered enzyme DhaA31 has a more occluded and less solvated cavity (see picture) but shows similar enantioselectivity as a result of steric hindrance imposed by two specific residues, rather than hydration as in DbjA.

Publication in Journal of Molecular Catalysis B: Enzymatic

Grulich M, Brezovsky J, Stepanek V, Palyzova A, Maresova H, Zahradnik J, Kyslikova E, Kyslik P, 2016: In-silico driven engineering of enantioselectivity of a penicillin G acylase towards active pharmaceutical ingredients. Journal of Molecular Catalysis B: Enzymatic (in press, doi:10.1016/j.molcatb.2016.11.014). full text

Penicillin G acylase is one of the most employed enzymes in the pharmaceutical industry due to its role in the biotransformation of semi-synthetic β-lactam antibiotics. Recently, the enantioselectivity of the penicillin G acylase markedly broadened its application potential. In this study, we have evaluated effects of in-silico replacements of acyl-binding subsite residue Phe24β of the enzyme from Achromobacter sp. CCM 4824 to seven markedly smaller amino acids on its enantioselectivity towards industrially relevant compounds. Models of the two most promising mutants bearing substitutions Pheβ24Ala and Pheβ24Cys were investigated using molecular docking calculations. The Cys substitution revealed much better enantioselectivity traits with a set of seven substrates. To verify the relevance of in-silico predictions, we constructed a PGAA + Phe24βCys mutant and determined its enantioselectivity in biocatalytic reactions. Since we experimentally confirmed all these predictions, we expanded our in-silico analysis to another set of seven compounds: the prediction suggested increased enantioselectivity for N-phenylacetyl-p-F-α-phenylalanine.The (R)-enantiomer of this substrate is used as a building block in synthesis of important anti-cancer agent Abarelix. The enantioselectivity of PGAA + Phe24βCys mutant towards this substrate was improved by 75% reaching E-value of about 70. Our results suggest the rapid identification of interesting replacements altering enantioselectivity using in-silico approach as the way for further expanding biotechnological application of penicillin G acylase.