Surpeta B, Sequeiros-Borja CE, Brezovsky J, 2020: Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering. International Journal of Molecular Sciences 21: 2713. full text

Computational prediction has become an indispensable aid in the processes of engineering and designing proteins for various biotechnological applications. With the tremendous progress in more powerful computer hardware and more efficient algorithms, some of in silico tools and methods have started to apply the more realistic description of proteins as their conformational ensembles, making protein dynamics an integral part of their prediction workflows. To help protein engineers to harness benefits of considering dynamics in their designs, we surveyed new tools developed for analyses of conformational ensembles in order to select engineering hotspots and design mutations. Next, we discussed the collective evolution towards more flexible protein design methods, including ensemble-based approaches, knowledge-assisted methods, and provable algorithms. Finally, we highlighted apparent challenges that current approaches are facing and provided our perspectives on their further development.

Stourac J, Vavra O, Kokkonen P, Filipovic J, Pinto G, Brezovsky J, Damborsky J, Bednar D, 2019: Caver Web 1.0: Identification of Tunnels and Channels in Proteins and Analysis of Ligand Transport. Nucleid Acids Research (advance article DOI: 10.1093/nar/gkz378). full text

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands’ transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface. The server is built on top of the abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling the study of the ligand transport. The program is easy-to-use as the only required inputs are a protein structure for a tunnel identification and a list of ligands for the transport analysis. The automated guidance procedures assist the users to set up the calculation in a way to obtain biologically relevant results. The identified tunnels, their properties, energy profiles and trajectories for ligands’ passages can be calculated and visualized. The tool is very fast (2-20 min per job) and is applicable even for virtual screening purposes. Its simple setup and comprehensive graphical user interface make the tool accessible for a broad scientific community. The server is freely available at https://loschmidt.chemi.muni.cz/caverweb.

Filipovic J, Vavra O, Plhak J, Bednar D, Marques  SM, Brezovsky J, Matyska L, Damborsky J, 2019: CaverDock: A Novel Method for the Fast Analysis of Ligand Transport. IEEE Transactions on Computational Biology and Bioinformatics (early access DOI:10.1109/TCBB.2019.2907492). full text

Here we present a novel method for the analysis of transport processes in proteins and its implementation called CaverDock. Our method is based on a modified molecular docking algorithm. It iteratively places the ligand along the access tunnel in such a way that the ligand movement is contiguous and the energy is minimized. The result of CaverDock calculation is a ligand trajectory and an energy profile of the transport process. CaverDock uses the modified docking program Autodock Vina for molecular docking and implements a parallel heuristic algorithm for searching the space of possible trajectories. Our method lies in between the geometrical approaches and molecular dynamics simulations. Contrary to the geometrical methods, it provides an evaluation of chemical forces. However, it is far less computationally demanding and easier to set up compared to molecular dynamics simulations. CaverDock will find broad use in the fields of computational enzymology, drug design and protein engineering. The software is available free of charge to the academic users at https://loschmidt.chemi.muni.cz/caverdock/.

Vavra O, Filipovic J, Plhak J, Bednar D, Marques SM, Brezovsky J, Stourac J, Matyska L, Damborsky J, 2019: CaverDock: A Molecular Docking-Based Tool to Analyse Ligand Transport through Protein Tunnels and Channels. Bioinformatics (accepted manuscript DOI: 10.1093/bioinformatics/btz386). full text

Motivation: Protein tunnels and channels are key transport pathways that allow ligands to pass between proteins’ external and internal environments. These functionally important structural features warrant detailed attention. It is difficult to study the ligand binding and unbinding process experimentally, while molecular dynamics simulations can be time-consuming and computationally demanding.
Results: CaverDock is a new software tool for analysing the ligand passage through the biomolecules. The method uses the optimised docking algorithm of AutoDock Vina for ligand placement docking and implements a parallel heuristic algorithm to search the space of possible trajectories. The duration of the simulations takes from minutes to a few hours. Here we describe the implementation of the method and demonstrate CaverDock’s usability by i) comparison of the results with other available tools, ii) determination of the robustness with large ensembles of ligands and iii) the analysis and comparison of the ligand trajectories in engineered tunnels. Thorough testing confirms that CaverDock is applicable for the fast analysis of ligand binding and unbinding in fundamental enzymology and protein engineering.
Availability: User guide and binaries for Ubuntu are freely available for non-commercial use at https://loschmidt.chemi.muni.cz/caverdock/. The web implementation is available at https://loschmidt.chemi.muni.cz/caverweb/. The source code is available on request.

Kokkonen P, Sykora J, Prokop Z, Ghose A, Bednar D, Amaro M, Beerens K, Bidmanova S, Slanska M, Brezovsky J, Damborsky J, Hof M, 2018: Molecular Gating of an Engineered Enzyme Captured in Real Time. Journal of the American Chemical Society (just accepted), doi: 10.1021/jacs.8b09848. full text

Engineering dynamical molecular gates represents a widely applicable strategy for designing efficient biocatalysts. Here we analyzed the dynamics of a molecular gate artificially introduced into an access tunnel of the most efficient haloalkane dehalogenase using pre-steady-state kinetics, a single-molecule fluorescence spectroscopy and molecular dynamics. Photoinduced electron-transfer – fluorescence correlation spectroscopy (PET-FCS) has enabled real-time observation of molecular gating at single molecule level with the rate constants (k_on = 1822 s^-1, k_off = 60 s^-1) corresponding well with those from the pre-steady-state kinetics (k_-1 = 1100 s^-1, k₁ = 20 s^-1).