HotSpot Wizard 3.0: Automated design of site-specific mutations and smart libraries

HotSpot Wizard is an interactive web server for prediction of amino acid residues suitable for mutagenesis and construction of libraries of mutants with modified activity, specificity or stability [1]. Positions suitable for mutagenesis are evaluated based on protein structure using a combination of structural, functional and evolutionary information obtained from 7 internet databases and 22 computational tools [2]. The application was designed with an emphasis on an easy usage without the necessity of advanced knowledge of the studied system. This is the reason for the setting of all default values of the parameters based on the extensive analysis to appropriately represent a wide spectrum of input data. Four different strategies are automatically evaluated for every protein structure. Analysis of the results is being run directly in the web interface, which provides user-friendly visualization tool. Moreover, HotSpot Wizard provides a module for the design of a construction of protein mutant library with the support of an automatic detection of suitable target amino acids and corresponding degenerative codons. There are several new features for the version 3.0 to be released early 2018. Stability of single-point or multiple-point mutant can be predicted using the Rosetta scoring function [3]. Users can newly enter also protein sequence as the input for calculation. Then searching for structures or models in the databases of experimental structures or depositories of homology models is performed. The users can also run homology modelling using the programs Modeller [4] and I-Tasser [5]. The current version of the application is freely available for academic users at http://loschmidt.chemi.muni.cz/hotspotwizard. 1. Pavelka, A., Chovancova, E., Damborsky, J., 2009: HotSpot Wizard: a Web Server for Identification of Hot Spots in Protein Engineering. Nucleic Acids Research 37: W376-W383. 2. Bendl, J., Stourac, J., Sebestova, E., Vavra, O., Musil, M., Brezovsky, J., Damborsky, J., 2016: HotSpot Wizard 2: Automated Design of Site-Specific Mutations and Smart Libraries in Protein Engineering. Nucleic Acids Research 44: W479-W487. 3. Kellogg, E.H., Leaver-Fay, A., Baker, D., 2011: Role of Conformational Sampling in Computing Mutation-induced Changes in Protein Structure and Stability. Proteins 79: 830-838. 4. Sali, A., Blundell, T.L., 1993: Comparative Protein Modelling by Satisfaction of Spatial Restraints. Journal of Molecular Biology 234: 779-815. 5. Zhang, Y., 2008: I-TASSER Server for Protein 3D Structure Prediction. BMC Bioinformatics 9: 40

FireProt: Web server for automated design of thermostable proteins

Stable proteins are used in numerous biomedical and biotechnological applications. Unfortunately, naturally occurring proteins cannot usually withstand the harsh industrial environment, since they are mostly evolved to function at mild conditions. Therefore, there is a continuous interest in increasing protein stability to enhance their industrial potential. 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. A much higher degree of stabilization can be achieved by the construction of the multiple-point mutants. Here, we present the FireProt method [1] and the web server [2] for the automated design of multiple-point mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen bioinformatics tools, including several force field calculations. Highly reliable designs of the thermostable proteins are constructed by two distinct protein engineering strategies, based on the energy and evolution approaches and the multiple-point mutants are checked for the potentially antagonistic effects in the designed protein structure. Furthermore, time demands of the FireProt method are radically decreased by the utilization of the smart knowledge-based filters, protocol optimization, and effective parallelization. The server is complemented with an interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable proteins. The server is freely available at http://loschmidt.chemi.muni.cz/fireprot. 1. Bednar, D., Beerens, K., Sebestova, E., Bendl, J., Khare, S., Chaloupkova, R., Prokop, Z., Brezovsky, J., Baker, D., Damborsky, J., 2015: FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants. PLOS Computational Biology 11: e1004556. 2. 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

CAVERDOCK: A new tool for analysis of ligand binding and unbinding based on molecular docking

Understanding the protein-ligand interactions is crucial for engineering improved catalysts. The interaction of a protein and a ligand molecule often takes place in enzymes active site. Such functional sites may be buried inside the protein core, and therefore a transport of a ligand from outside environment to the protein inside needs to be understood. Here we present the CaverDock [1], implementing a novel method for analysis of these important transport processes. Our method is based on a modified molecular docking algorithm. It iteratively places the ligand along the tunnel in such a way that the ligand movement is contiguous and its energy is minimized. The output of the calculation is ligand trajectory and energy profile of transport process. CaverDock uses a modified version of the program AutoDock Vina [2] for molecular docking and implements a parallel heuristic algorithm to search the space of possible trajectories. Our method lies in between of geometrical approaches and molecular dynamics simulations. Contrary to geometrical methods, it provides an evaluation of chemical forces. However, it is not as computationally demanding as the methods based on molecular dynamics. The typical input of CaverDock requires setup for molecular docking and tunnel geometry obtained from Caver [3]. Typical computational time is in dozens of minutes at a single node, allowing virtual screening of a large pool of molecules. We demonstrate CaverDock usability by comparison of a ligand trajectory in different tunnels of wild type and engineered proteins; and computation of energetic profiles for a large set of substrates and inhibitors. CaverDock is available from the web site http://www.caver.cz. 1. Vavra, O., Filipovic, J., Plhak, J., Bednar, D., Marques, S., Brezovsky, J., Matyska, L., Damborsky, J., CAVERDOCK: A New Tool for Analysis of Ligand Binding and Unbinding Based on Molecular Docking. PLOS Computational Biology (submitted). 2. Trott, O., Olson, A.J., AutoDock Vina: Improving the Speed and Accuracy of Docking with a New scoring function, efficient optimization and multithreading, Journal of Computational Chemistry 31: 455-461, 2010. 3. Chovancova, E., Pavelka, A., Benes, P., Strnad, O., Brezovsky, J., Kozlikova, B., Gora, A., Sustr, V., Klvana, M., Medek, P., Biedermannova, L., Sochor, J., Damborsky, J., 2012: CAVER 3.0: A Tool for Analysis of Transport Pathways in Dynamic Protein Structures. PLOS Computational Biology 8: e1002708

Engineering of haloalkane dehalogenase enantioselectivity towards βbromoalkanes: Open-solvated versus occluded-desolvated active sites

Enzymatic catalysis is widely used for preparing optically pure chemicals. Natural catalysts have to be often optimized to exhibit sufficient enantioselectivity towards industrially attractive non-natural substrates. Understanding the molecular basis of enzyme–substrate interactions involved in enantiodiscrimination is essential for rational design of selective catalysts. Haloalkane dehalogenases (EC 3.8.1.5) can convert a broad range of halogenated aliphatic compounds to their corresponding alcohols via SN2 mechanism [1]. The very first haloalkane dehalogenase exhibiting high enantioselectivity towards β-brominated alkanes (E-values of up to 174) was DbjA from Bradyrhizobium japonicum USDA110 [2]. This enzyme has a wide open solvent-accessible active site and its enantioselectivity towards β-brominated alkanes is modulated by a surface loop unique to DbjA [2]. Assuming that the active site geometry is crucial for substrate recognition, it was proposed that DbjA’s enantioselectivity could be transferred to closely related, but non-selective DhaA from Rhodococcus rhodochrous NCIMB13064 [1] by active site transplantation [3]. The unique loop fragment from DbjA together with additional 8-point substitutions was inserted to DhaA. Although the crystal structure of resulting variant DhaA12 exhibited identical geometry of the active site and the access tunnel as DbjA, it did not reach identical level of hydration and flexibility and lacked enantioselectivity towards β-bromoalkanes (E-value = 18) [3]. Interestingly, the variant DhaA31 constructed independently with a goal to enhance enzyme activity towards anthropogenic compound 1,2,3-trichlopropane [4], exhibited high enantioselectivity towards 2-bromopentane (E-value = 179) [5] as DbjA (E-value = 174) [2, 3]. DhaA31 contains five mutations, I135F, C176Y, V245F, L246I and Y273F, located in a main and a slot tunnel. Four of five mutations are large and aromatic residues narrowing two access tunnels and occluding the enzyme active site [4]. The level of DhaA31 active site hydration, so important for DbjA’s enantioselectivity [2, 3] is low, suggesting a different structural basis of enantioselectivity towards 2-bromopentane. A systematic study on the molecular basis of enantioselectivity in DbjA, DhaA, and DhaA31 using thermodynamic and kinetic analyses, site-directed mutagenesis, and molecular modeling was carried out. DhaA31 enantioselectivity arises from the hydrophobic substrate’s interactions with the occluded and desolvated active site [5], while DbjA enantioselectivity results from water-mediated interactions of 2-bromopentane with the active site’s hydrophobic wall [2]. Our data imply that enantioselectivity of haloalkane dehalogenases can be achieved by both occluded-desolvated active site and open-solvated active site. The engineering of “DbjA-like” enantioselectivity by modification of the active site hydration remains challenging. References: 1. Koudelakova, T., et al. 2013. Biotechnol. J. 8: 32–45. Prokop, Z., et al. 2010. Angew. Chem. Int. Ed., 49: 6111-6115. Sykora, J., et al. 2014. Nat. Chem. Biol., 10: 428-430. Pavlova, M., et al. 2009. Nat. Chem. Biol., 5: 727-733. Liskova, V., et al. 2017. Angew. Chem. Int. Ed., DOI: 10.1002/anie.201611193

Rad52 SUMOylation affects the efficiency of the DNA repair

Homologous recombination (HR) plays a vital role in DNA metabolic processes including meiosis, DNA repair, DNA replication and rDNA homeostasis. HR defects can lead to pathological outcomes, including genetic diseases and cancer. Recent studies suggest that the post-translational modification by the small ubiquitin-like modifier (SUMO) protein plays an important role in mitotic and meiotic recombination. However, the precise role of SUMOylation during recombination is still unclear. Here, we characterize the effect of SUMOylation on the biochemical properties of the Saccharomyces cerevisiae recombination mediator protein Rad52. Interestingly, Rad52 SUMOylation is enhanced by single-stranded DNA, and we show that SUMOylation of Rad52 also inhibits its DNA binding and annealing activities. The biochemical effects of SUMO modification in vitro are accompanied by a shorter duration of spontaneous Rad52 foci in vivo and a shift in spontaneous mitotic recombination from single-strand annealing to gene conversion events in the SUMO-deficient Rad52 mutants. Taken together, our results highlight the importance of Rad52 SUMOylation as part of a ‘quality control’ mechanism regulating the efficiency of recombination and DNA repair

Engineering the protein dynamics of an ancestral luciferase.

Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein AncHLD-RLuc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of AncHLD-RLuc challenged the scaffold dynamics. Screening for both activities reveals InDel mutations localized in three distinct regions that lead to altered protein dynamics (based on crystallographic B-factors, hydrogen exchange, and molecular dynamics simulations). An anisotropic network model highlights the importance of the conformational flexibility of a loop-helix fragment of Renilla luciferases for ligand binding. Transplantation of this dynamic fragment leads to lower product inhibition and highly stable glow-type bioluminescence. The success of our approach suggests that a strategy comprising (i) constructing a stable and evolvable template, (ii) mapping functional regions by backbone mutagenesis, and (iii) transplantation of dynamic features, can lead to functionally innovative proteins

Engineering the protein dynamics of an ancestral luciferase

Abstract: Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein AncHLD-RLuc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of AncHLD-RLuc challenged the scaffold dynamics. Screening for both activities reveals InDel mutations localized in three distinct regions that lead to altered protein dynamics (based on crystallographic B-factors, hydrogen exchange, and molecular dynamics simulations). An anisotropic network model highlights the importance of the conformational flexibility of a loop-helix fragment of Renilla luciferases for ligand binding. Transplantation of this dynamic fragment leads to lower product inhibition and highly stable glow-type bioluminescence. The success of our approach suggests that a strategy comprising (i) constructing a stable and evolvable template, (ii) mapping functional regions by backbone mutagenesis, and (iii) transplantation of dynamic features, can lead to functionally innovative proteins

Computer-assisted stabilization of fibroblast growth factor FGF-18

The fibroblast growth factors (FGF) family holds significant potential for addressing chronic diseases. Specifically, recombinant FGF18 shows promise in treating osteoarthritis by stimulating cartilage formation. However, recent phase 2 clinical trial results of sprifermin (recombinant FGF18) indicate insufficient efficacy. Leveraging our expertise in rational protein engineering, we conducted a study to enhance the stability of FGF18. As a result, we obtained a stabilized variant called FGF18-E4, which exhibited improved stability with 16 °C higher melting temperature, resistance to trypsin and a 2.5-fold increase in production yields. Moreover, the FGF18-E4 maintained mitogenic activity after 1-week incubation at 37 °C and 1-day at 50 °C. Additionally, the inserted mutations did not affect its binding to the fibroblast growth factor receptors, making FGF18-E4 a promising candidate for advancing FGF-based osteoarthritis treatment

Strategies for Stabilization of Enzymes in Organic Solvents

One of the major barriers to the use of enzymes in industrial biotechnology is their insufficient stability under processing conditions. The use of organic solvent systems instead of aqueous media for enzymatic reactions offers numerous advantages, such as increased solubility of hydrophobic substrates or suppression of water-dependent side reactions. For example, reverse hydrolysis reactions that form esters from acids and alcohols become thermodynamically favorable. However, organic solvents often inactivate enzymes. Industry and academia have devoted considerable effort into developing effective strategies to enhance the lifetime of enzymes in the presence of organic solvents. The strategies can be grouped into three main categories: (i) isolation of novel enzymes functioning under extreme conditions, (ii) modification of enzyme structures to increase their resistance toward nonconventional media, and (iii) modification of the solvent environment to decrease its denaturing effect on enzymes. Here we discuss successful examples representing each of these categories and summarize their advantages and disadvantages. Finally, we highlight some potential future research directions in the field, such as investigation of novel nanomaterials for immobilization, wider application of computational tools for semirational prediction of stabilizing mutations, knowledge-driven modification of key structural elements learned from successfully engineered proteins, and replacement of volatile organic solvents by ionic liquids and deep eutectic solvents