Our Team Members Publications
J. Brezovsky, P. Babkova, O. Degtjarik, A. Fortova, A. Gora, I. Iermak, P. Rezacova, P. Dvorak, I. Smatanova, Z. Prokop, R. Chaloupkova, and J. Damborsky, ACS Catalysis 2016, 6, 7597-7610 DOI: 10.1021/acscatal.6b02081 ARTICLE
Transport of ligands between buried active sites and bulk solvent is a key step in the catalytic cycle of many enzymes. Absence of evolutionary optimized transport tunnels is an important barrier limiting the efficiency of biocatalysts prepared by computational design. Creating a structurally defined and functional “hole” into the protein represents an engineering challenge. Here we describe the computational design and directed evolution of a de novo transport tunnel in haloalkane dehalogenase. Mutants with a blocked native tunnel and newly opened auxiliary tunnel in a distinct part of the structure showed dramatically modified properties. The mutants with blocked tunnels acquired specificity never observed with native family members, up to 32-times increased substrate inhibition and 17-times reduced catalytic rates. Opening of the auxiliary tunnel resulted in specificity and substrate inhibition similar to the native enzyme, and the most proficient haloalkane dehalogenase reported to date (kcat = 57 s-1 with 1,2-dibromoethane at 37oC and pH=8.6). Crystallographic analysis and molecular dynamics simulations confirmed successful introduction of structurally defined and functional transport tunnel. Our study demonstrates that whereas we can open the transport tunnels with reasonable proficiency, we cannot accurately predict the effects of such change on the catalytic properties. We propose that one way to increase efficiency of an enzyme is the direct its substrates and products into spatially distinct tunnels. The results clearly show the benefits of enzymes with de novo transport tunnels and we anticipate that this engineering strategy will facilitate creation of a wide range of useful biocatalysts.
J. Polanski, U. Kucia, R. Duszkiewicz, A. Kurczyk, T. Magdziarz and J. Gasteiger, „Molecular descriptor data explain market prices of a large commercial chemical compound library” Scientific Reports 6, Article number: 28521 (2016). doi:10.1038/srep28521 ARTICLEOpen Access
The relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry.
C. Yang, A. Tarkhov, J. Marusczyk, B. Bienfait, J. Gasteiger, T. Kleinoeder, T. Magdziarz, O. Sacher, C. H. Schwab, J. Schwoebel, L. Terfloth, K. Arvidson, A. Richard, A. Worth, and J. Rathman, “New Publicly Available Chemical Query Language, CSRML, To Support Chemotype Representations for Application to Data Mining and Modeling,” J. Chem. Inf. Model., vol. 55, no. 3, pp. 510–528, Mar. 2015.
Chemotypes are a new approach for representing molecules, chemical substructures and patterns, reaction rules, and reactions. Chemotypes are capable of integrating types of information beyond what is possible using current representation methods (e.g., SMARTS patterns) or reaction transformations (e.g., SMIRKS, reaction SMILES). Chemotypes are expressed in the XML-based Chemical Subgraphs and Reactions Markup Language (CSRML), and can be encoded not only with connectivity and topology but also with properties of atoms, bonds, electronic systems, or molecules. CSRML has been developed in parallel with a public set of chemotypes, i.e., the ToxPrint chemotypes, which are designed to provide excellent coverage of environmental, regulatory, and commercial-use chemical space, as well as t represent chemical patterns and properties especially relevant to various toxicity concerns. A software application, ChemoTyper has also been developed and made publicly available in order to enable chemotype searching and fingerprinting against a target structure set. The public ChemoTyper houses the ToxPrint chemotype CSRML dictionary, as well as reference implementation so that the query specifications may be adopted by other chemical structure knowledge systems. The full specifications of the XML-based CSRML standard used to express chemotypes are publicly available to facilitate and encourage the exchange of structural knowledge.
F. Sanz, P. Carrió, O. López, L. Capoferri, D. P. Kooi, N. P. E. Vermeulen, D. P. Geerke, F. Montanari, G. F. Ecker, C. H. Schwab, T. Kleinöder, T. Magdziarz, and M. Pastor, “Integrative Modeling Strategies for Predicting Drug Toxicities at the eTOX Project,” Mol. Inform., p. n/a–n/a, Jun. 2015.
Early prediction of safety issues in drug development is at the same time highly desirable and highly challenging. Recent advances emphasize the importance of understanding the whole chain of causal events leading to observable toxic outcomes. Here we describe an integrative modeling strategy based on these ideas that guided the design of eTOXsys, the prediction system used by the eTOX project. Essentially, eTOXsys consists of a central server that marshals requests to a collection of independent prediction models and offers a single user interface to the whole system. Every of such model lives in a self-contained virtual machine easy to maintain and install. All models produce toxicity-relevant predictions on their own but the results of some can be further integrated and upgrade its scale, yielding in vivo toxicity predictions. Technical aspects related with model implementation, maintenance and documentation are also discussed here. Finally, the kind of models currently implemented in eTOXsys is illustrated presenting three example models making use of diverse methodology (3D-QSAR and decision trees, Molecular Dynamics simulations and Linear Interaction Energy theory, and fingerprint-based QSAR).
B. Kozlikova, E. Sebestova, V. Sustr, J. Brezovsky, O. Strnad, L. Daniel, D. Bednar, A. Pavelka, M. Manak, M. Bezdeka, P. Benes, M. Kotry, A. Gora, J. Damborsky, and J. Sochor, “CAVER Analyst 1.0: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures,” Bioinforma. Oxf. Engl., vol. 30, no. 18, pp. 2684–2685, Sep. 2014.
The transport of ligands, ions or solvent molecules into proteins with buried binding sites or through the membrane is enabled by protein tunnels and channels. CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics.
B. Łozowicka, P. Kaczyński, T. Magdziarz, and A. T. Dubis, “Synthesis, antifeedant activity against Coleoptera and 3D QSAR study of alpha-asarone derivatives,” SAR QSAR Environ. Res., vol. 25, no. 3, pp. 173–188, Mar. 2014.
For the first time, a set of 56 compounds representing structural derivatives of naturally occurring alpha-asarone as an antifeedants against stored product pests Sitophilus granarius L., Trogoderma granarium Ev., and Tribolium confusum Duv., were subjected to the 3D QSAR studies. Three-dimensional quantitative structure–activity relationships (3D-QSAR) for 56 compounds, including 15 newly synthesized, were performed using comparative molecular field analysis s-CoMFA and SOM-CoMSA techniques. QSAR was conducted based on a combination of biological activity (against Coleoptera larvae and beetles) and various geometrical, topological, quantum-mechanical, electronic, and chromatographic descriptors. The CoMSA formalism coupled with IVE (CoMSA–IVE) allowed us to obtain highly predictive models for Trogoderma granarium Ev. larvae. We have found that this novel method indicates a clear molecular basis for activity and lipophilicity. This investigation will facilitate optimization of the design of new potential antifeedants.
A. Bak, M. Wyszomirski, T. Magdziarz, A. Smolinski, and J. Polanski, “Structure-Based Modeling of Dye-Fiber Affinity with SOM-4D-QSAR Paradigm: Application to Set of Anthraquinone Derivatives,” Comb. Chem. High Throughput Screen., vol. 17, no. 6, pp. 485–502, 2014.
A comparative structure-affinity study of anthraquinone dyes adsorption on cellulose fibre is presented in this paper. We used receptor-dependent 4D-QSAR methods based on grid and neural (SOM) methodology coupled with IVEPLS procedure. The applied RD 4D-QSAR approach focuses mainly on the ability of mapping dye properties to verify the concept of tinctophore in dye chemistry. Moreover, the stochastic SMV procedure to investigate the predictive ability of the method for a large population of 4D-QSAR models was employed. The obtained findings were compared with the previously published RI 3D/4D-QSAR models for the corresponding anthraquinone trainings sets. The neutral (protonated) and anionic (deprotonated) forms of anthraquinone scaffold were examined in order to deal with the uncertainty of the dye ionization state. The results are comparable to both the neutral and anionic dye sets regardless of the occupancy and charge descriptors applied, respectively. It is worth noting that the SOM-4D-QSAR behaves comparably to the cubic counterpart which is observed in each training/test subset specification (4D-QSAR-Jo vs SOM- 4D-QSARo and 4D-QSAR-Jq vs SOM-4D-QSARq). Additionally, an attempt was made to specify a common set of variables contributing significantly to dye-fiber binding affinity; it was simultaneously performed for some arbitrary chosen SMV models. The presented RD 4D-QSAR methodology together with IVE-PLS procedure provides a robust and predictive modeling technique, which facilitates detailed specification of the molecular motifs significantly contributing to the fiber-dye affinity.
A. Bak, T. Magdziarz, A. Kurczyk, K. Serafin, and J. Polanski, “Probing a Chemical Space for Fragmental Topology-Activity Landscapes (FRAGTAL): Application for Diketo Acid and Catechol HIV Integrase Inhibitor Offspring Fragments,” Comb. Chem. High Throughput Screen., vol. 16, no. 4, pp. 274–287, 2013.
Fragmental topology-activity landscapes (FRAGTAL), a new concept for encoding molecular descriptors for fragonomics into the framework of the molecular database records is presented in this paper. Thus, a structural repository containing biological activity data was searched in a substructure mode by a series of molecular fragments constructed in an incremental or decremental manner. The resulted series of database hits annotated with their activities construct FRAGTAL descriptors encoding a frequency of the certain fragments among active compounds and/or their activities. Actually, this method might be interpreted as a simplified adaptation of the frequent subgraph mining (FSM) method. The FRAGTAL method reconstructs the way in which medicinal chemists are used to designing a prospective drug structure intuitively. A representative example of the practical application of FRAGTAL within the ChemDB Anti-HIV/OI/TB database for disclosing new fragments for HIV-1 integrase inhibition is discussed. In particular, FRAGTAL method identifies ethyl malonate amide (EMA) as the diketo acid (DKA) related arrangement. Since new molecular constructs based on the EMA fragment are still a matter of future investigations we referred to this as anthe DKA offspring.
A. Gora, J. Brezovsky, and J. Damborsky, “Gates of Enzymes,” Chem. Rev., vol. 113, no. 8, pp. 5871–5923, 2013. ARTICLEOpen Access
Table of Contents
- Molecular Function of Gates
- Structural Basis of Gates
- Locations of Gates
- Engineering of Gates
K. Hasan, A. Gora, J. Brezovsky, R. Chaloupkova, H. Moskalikova, A. Fortova, Y. Nagata, J. Damborsky, and Z. Prokop, “The effect of a unique halide-stabilizing residue on the catalytic properties of haloalkane dehalogenase DatA from Agrobacterium tumefaciens C58,” FEBS J., vol. 280, no. 13, pp. 3149–3159, July 2013.
Haloalkane dehalogenases catalyse the hydrolysis of carbon-halogen bonds in various chlorinated, brominated and iodinated compounds. These enzymes have a conserved pair of halide-stabilising residues that are important in substrate binding and stabilisation of the transition state and the halide ion product via hydrogen bonding. In all previously known haloalkane dehalogenase, these residues are either a pair of tryptophans or a tryptophan-asparagine pair. The newly isolated haloalkane dehalogenase DatA from Agrobacterium tumefaciens C58 possesses a unique halide-stabilising tyrosine residue, Y109, in place of the conventional tryptophan. A variant of DatA with the Y109W mutation was created and the effects of this mutation on the enzyme’s structure and catalytic properties were studied using spectroscopy and pre-steady-state kinetic experiments. Quantum mechanical and molecular dynamics calculations were used to obtain a detailed analysis of the hydrogen bonding patterns within the active sites of the wild-type and the mutant, and of the stabilisation of the ligands as the reaction proceeds. Fluorescence quenching experiments suggested that replacing the tyrosine with tryptophan improves halide binding 3.7-fold, presumably due to the introduction of an additional hydrogen bond. Kinetic analysis revealed that the mutation affected the enzyme’s substrate specificity and reduced its K0.5 for selected halogenated substrates by a factor of 2-4, without impacting the rate-determining hydrolytic step. We conclude that DatA is the first natural haloalkane dehalogenase that stabilises its substrate in the active site using only a single hydrogen bond, which is a new paradigm in catalysis by this enzyme family.
J. Brezovsky, E. Chovancova, A. Gora, A. Pavelka, L. Biedermannova, and J. Damborsky, “Software tools for identification, visualization and analysis of protein tunnels and channels,” Biotechnol. Adv., vol. 31, no. 1, pp. 38–49, Jan. 2013. ARTICLE
Protein structures contain highly complex systems of voids, making up specific features such as surface clefts or grooves, pockets, protrusions, cavities, pores or channels, and tunnels. Many of them are essential for the migration of solvents, ions and small molecules through proteins, and their binding to the functional sites. Analysis of these structural features is very important for understanding of structure-function relationships, for the design of potential inhibitors or proteins with improved functional properties. Here we critically review existing software tools specialized in rapid identification, visualization, analysis and design of protein tunnels and channels. The strengths and weaknesses of individual tools are reported together with examples of their applications for the analysis and engineering of various biological systems. This review can assist users with selecting a proper software tool for study of their biological problem as well as highlighting possible avenues for further development of existing tools. Development of novel descriptors representing not only geometry, but also electrostatics, hydrophobicity or dynamics, is needed for reliable identification of biologically relevant tunnels and channels.
A. Bak, T. Magdziarz, and J. Polanski, “Pharmacophore-based database mining for probing fragmental drug-likeness of diketo acid analogues,” SAR QSAR Environ. Res., vol. 23, no. 1–2, pp. 185–204, 2012.
L. Biedermannová, Z. Prokop, A. Gora, E. Chovancová, M. Kovács, J. Damborsky, and R. C. Wade, “A single mutation in a tunnel to the active site changes the mechanism and kinetics of product release in haloalkane dehalogenase LinB,” J. Biol. Chem., vol. 287, no. 34, pp. 29062–29074, Aug. 2012.ARTICLE
Many enzymes have buried active sites. The properties of the tunnels connecting the active site with bulk solvent affect ligand binding and unbinding and also the catalytic properties. Here, we investigate ligand passage in the haloalkane dehalogenase enzyme LinB and the effect of replacing leucine by a bulky tryptophan at a tunnel-lining position. Transient kinetic experiments show that the mutation significantly slows down the rate of product release. Moreover, the mechanism of bromide ion release is changed from a one-step process in the wild type enzyme to a two-step process in the mutant. The rate constant of bromide ion release corresponds to the overall steady-state turnover rate constant, suggesting that product release became the rate-limiting step of catalysis in the mutant. We explain the experimental findings by investigating the molecular details of the process computationally. Analysis of trajectories from molecular dynamics simulations with a tunnel detection software reveals differences in the tunnels available for ligand egress. Corresponding differences are seen in simulations of product egress using a specialized enhanced sampling technique. The differences in the free energy barriers for egress of a bromide ion obtained using potential of mean force calculations are in good agreement with the differences in rates obtained from the transient kinetic experiments. Interactions of the bromide ion with the introduced tryptophan are shown to affect the free energy barrier for its passage. The study demonstrates how the mechanism of an enzymatic catalytic cycle and reaction kinetics can be engineered by modification of protein tunnels.
E. Chovancova, A. Pavelka, P. Benes, O. Strnad, J. Brezovsky, B. Kozlikova, A. Gora, V. Sustr, M. Klvana, P. Medek, L. Biedermannova, J. Sochor, and J. Damborsky, “CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic Protein Structures,” PLoS Comput Biol, vol. 8, no. 10, p. e1002708, Oct. 2012.ARTICLEOpen Access
Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures.
Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.
R. Musiol, T. Magdziarz, and A. Kurczyk, “Quinoline scaffold as a privileged substructure in antimicrobial drugs,” Sci. Microb. Pathog. Commun. Curr. Res. Technol. Adv. Badajoz Spain Formatex, pp. 72–83, 2011.
A. Bak, T. Magdziarz, A. Kurczyk, and J. Polanski, “Mapping fragmental drug-likeness in the MoStBioDat environment: intramolecular hydrogen bonding motifs in β-ketoenols,” Comb. Chem. High Throughput Screen., vol. 14, no. 7, pp. 560–569, 2011.
A. Bak, T. Magdziarz, A. Kurczyk, and J. Polanski, “Mapping drug architecture by MoStBioDat: rapid screening of intramolecular hydrogen bonded motifs in catechols,” Drug Dev. Res., vol. 72, no. 2, pp. 209–218, 2011.
P. Mazur, T. Magdziarz, A. Bak, Z. Chilmonczyk, T. Kasprzycka-Guttman, I. Misiewicz-Krzemińska, K. Skupińska, and J. Polanski, “Does molecular docking reveal alternative chemopreventive mechanism of activation of oxidoreductase by sulforaphane isothiocyanates?,” J. Mol. Model., vol. 16, no. 7, pp. 1205–1212, 2010.
T. Magdziarz, P. Mazur, and J. Polanski, “Receptor independent and receptor dependent CoMSA modeling with IVE-PLS: application to CBG benchmark steroids and reductase activators,” J. Mol. Model., vol. 15, no. 1, pp. 41–51, 2009.
A. Gora and E. Broclawik, “Mechanism of hydrogen abstraction by O- species in oxidative dehydrogenation of early alkanes: Propane, ethane and methane. Model theoretical DFT study,” Pol. J. Chem., vol. 82, pp. 1779–1791, 2008.
J. Polanski, A. Bak, R. Gieleciak, and T. Magdziarz, “Modeling robust QSAR.,” J. Chem. Inf. Model., vol. 46, no. 6, pp. 2310–8, 2006.
T. Magdziarz, B. \Lozowicka, R. Gieleciak, A. Bąk, J. Polański, and Z. Chilmonczyk, “3D QSAR study of hypolipidemic asarones by comparative molecular surface analysis,” Bioorg. Med. Chem., vol. 14, no. 5, pp. 1630–1643, 2006.
A. Gora, D. A. P. Tanaka, F. Mizukami, and T. M. Suzuki, “Lower temperature dehydrogenation of methylcyclohexane by membrane-assisted equilibrium shift,” Chem. Lett., vol. 35, pp. 1372–1373, 2006.ARTICLE
Selective removal of hydrogen by the palladium membrane of novel configuration shifts the equilibrium in the dehydrogenation of methylcyclohexane allowing a continuous operation at below the critical temperature of palladium α–β phase transition.
E. Broclawik, A. Gora, P. Liguzinski, P. Petelenz, and H. A. Witek, “Quantum chemical modeling of electrochromism of tungsten oxide films,” J. Chem. Phys., vol. 124, 2006.ARTICLE
R. Gieleciak, T. Magdziarz, A. Bak, and J. Polanski, “Modeling Robust QSAR. 1. Coding Molecules in 3D-QSAR from a Point to Surface Sectors and Molecular Volumes,” J. Chem. Inf. Model., vol. 45, no. 5, pp. 1447–1455, Sep. 2005.
E. Broclawik, A. Gora, P. Liguzinski, P. Petelenz, and M. Slawik, “Quantum chemical modelling of the process of lithium insertion into WO(3) films,” Catal. Today, vol. 101, pp. 155–162, 2005. ARTICLE
J. Polanski, R. Gieleciak, T. Magdziarz, and A. Bak, “GRID formalism for the comparative molecular surface analysis: application to the CoMFA benchmark steroids, azo dyes, and HEPT derivatives,” J. Chem. Inf. Comput. Sci., vol. 44, no. 4, pp. 1423–1435, 2004.
J. Polanski, A. Bak, R. Gieleciak, and T. Magdziarz, “Self-organizing neural networks for Modeling robust 3D and 4D QSAR: Application to dihydrofolate reductase inhibitors,” Molecules, vol. 9, no. 12, pp. 1148–1159, 2004.
J. Polański, H. Niedba\la, R. Musio\l, D. Tabak, B. Podeszwa, R. Gieleciak, A. Bak, A. Pa\lka, and T. Magdziarz, “Analogues of the styrylquinoline and styrylquinazoline HIV-1 integrase inhibitors: design and synthetic problems.,” Acta Pol. Pharm., vol. 61, pp. 3–4, 2004.
A. Gora and E. Broclawik, “Theoretical estimation of acid-base properties of Lewis and Bronsted centres at the V-W-O catalyst surface: water molecule as the probe in DFT calculations,” J. Mol. Catal. -Chem., vol. 215, pp. 187–193, 2004.ARTICLE
A. Eilmes, R. W. Munn, V. G. Mavrantzas, D. N. Theodorou, and A. Gora, “Microscopic calculation of the static electric susceptibility of polyethylene,” J. Chem. Phys., vol. 119, pp. 11458–11466, 2003.
A. Eilmes, R. W. Munn, and A. Gora, “Microscopic calculation of the energetics of ions in polyethylene,” J. Chem. Phys., vol. 119, pp. 11467–11474, 2003.
E. Broclawik, A. Gora, and M. Najbar, “The role of tungsten in formation of active sites for no SCR on the V-W-O catalyst surface – quantum chemical modeling (DFT),” J. Mol. Catal. -Chem., vol. 166, pp. 31–38, 2001.ARTICLE
M. Najbar, A. Gora, A. Bialas, and A. Weselucha-Birczynska, “Low-temperature reactivity of the surface species of vanadia-tungsta catalyst,” Solid State Ion., vol. 141, pp. 499–506, 2001.ARTICLE
A. Gora, E. Broclawik, and M. Najbar, “Quantum chemical modeling (DFT) of active species on the V-W-O catalyst surface in various redox conditions,” Comput. Chem., vol. 24, pp. 405–410, 2000.ARTICLE
M. Najbar, E. Broclawik, A. Gora, J. Camra, A. Bialas, and A. Weselucha-Birczynska, “Evolution of the surface species of the V2O5-WO3 catalysts,” Chem. Phys. Lett., vol. 325, pp. 330–339, 2000.ARTICLE
M. Najbar, F. Mizukami, A. Bialas, J. Camra, A. Weselucha-Birczynska, H. Izutsu, and A. Gora, “Evolution of Ti-Sn-rutile-supported V2O5-WO3 catalyst during its use in nitric oxide reduction by ammonia,” Top. Catal., vol. 11, pp. 131–138, 2000.ARTICLE
PREECIDINGS AND OTHER PAPERS
Gora, A., Brezovsky, J. & Damborsky, J., Computer-assisted enzyme engineering by modification of tunnels, channels and gates. Current Opinion in Biotechnology vol 22, supplement 1 September 2011.
Gora, A., Pacheco Tanaka, D. A., Mizukami, F. & Suzuki, T. M., Low temperature hydrogen recovering from organic storage compounds – application of pore fill type palladium membrane. Proceedings of International Conference and Exhibition on Green Chemistry, 18-21 IX 2006 Kuala Lumpur, Malaysia, 2006.
Gora, A. & Brocławik E. Dissociation of the Water Molecule on the V-W-O Catalyst Surface – Quantum Chemical Modeling. Polish Journal of Environmental Studies, 9(1), 31-34, 2000.
Najbar M., Białas A., Mizukami F., Wesełucha-Birczyńska A., Bielańska E. & Gora A. Vanadia-Tungsta DENOX Catalysts on High Surface Area Rutile. Polish Journal of Environmental Studies, 6, 83-8, 1997.
Prokop Z, Gora A, Brezovsky J, Chalupkova R, Stepankova V & Damborsky J Protein Engineering Handbook, Volume 3: Book chapter: Engineering of protein tunnels: Keyhole-lock-key model for catalysis by the enzymes with buried active sites – ISBN 978-3-527-33123-9 – Wiley-VCH, Weinheim.
US Patent No 13/604,094 “Method of thermostabilization of a protein and/or stabilization towards organic solvents” Jiri Damborsky, Zbynek Prokop, Tana Koudelakova, Veronika Stepankova, Radka Chaloupkova, Eva Chovancova, Artur Wiktor Gora, Jan Brezovsky.