Eva Sebestova

CAVER Analyst 1.0: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures

UNLABELLED 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. AVAILABILITY AND IMPLEMENTATION CAVER Analyst is a multi-platform software written in JAVA. Binaries and documentation are freely available for non-commercial use at http://www.caver.cz.

Engineering enzyme stability and resistance to an organic cosolvent by modification of residues in the access tunnel.

Mutations targeting as few as four residues lining the access tunnel extended enzyme’s half-life in 40% dimethyl sulfoxide from minutes to weeks (4,000-fold) and increased its melting temperature by 19 Grades C. Protein crystallography and molecular dynamics revealed that the tunnel residue packing is a key determinant of protein stability and the active-site accessibility for co-solvent molecules (red dots). The broad applicability of this concept was verified by analyzing twenty six proteins with buried active sites from all six enzyme classes.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

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 (ΔT m = 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.

HotSpot Wizard 2.0: automated design of site-specific mutations and smart libraries in protein engineering

HotSpot Wizard 2.0 is a web server for automated identification of hot spots and design of smart libraries for engineering proteins’ stability, catalytic activity, substrate specificity and enantioselectivity. The server integrates sequence, structural and evolutionary information obtained from 3 databases and 20 computational tools. Users are guided through the processes of selecting hot spots using four different protein engineering strategies and optimizing the resulting librarys size by narrowing down a set of substitutions at individual randomized positions. The only required input is a query protein structure. The results of the calculations are mapped onto the proteins structure and visualized with a JSmol applet. HotSpot Wizard lists annotated residues suitable for mutagenesis and can automatically design appropriate codons for each implemented strategy. Overall, HotSpot Wizard provides comprehensive annotations of protein structures and assists protein engineers with the rational design of site-specific mutations and focused libraries. It is freely available at http://loschmidt.chemi.muni.cz/hotspotwizard.

CAVER: algorithms for analyzing dynamics of tunnels in macromolecules

The biological function of a macromolecule often requires that a small molecule or ion is transported through its structure. The transport pathway often leads through void spaces in the structure. The properties of transport pathways change significantly in time; therefore, the analysis of a trajectory from molecular dynamics rather than of a single static structure is needed for understanding the function of pathways. The identification and analysis of transport pathways are challenging because of the high complexity and diversity of macromolecular shapes, the thermal motion of their atoms, and the large amount of conformations needed to properly describe conformational space of protein structure. In this paper, we describe the principles of the CAVER 3.0 algorithms for the identification and analysis of properties of transport pathways both in static and dynamic structures. Moreover, we introduce the improved clustering solution for finding tunnels in macromolecules, which is included in the latest CAVER 3.02 version. Voronoi diagrams are used to identify potential pathways in each snapshot of a molecular dynamics trajectory and clustering is then used to find the correspondence between tunnels from different snapshots. Furthermore, the geometrical properties of pathways and their evolution in time are computed and visualized.

Balancing the Stability-Activity Trade-off by Fine-Tuning Dehalogenase Access Tunnels.

A variant of the haloalkane dehalogenase DhaA with greatly enhanced stability and tolerance of organic solvents but reduced activity was created by mutating four residues in the access tunnel. To create a stabilised enzyme with superior catalytic activity, two of the four originally modified residues were randomised. The resulting mutant F 176 G exhibited 32‐ and 10‐times enhanced activity towards 1,2‐dibromoethane in buffer and 40 % DMSO, respectively, upon retaining high stability. Structural and molecular dynamics analyses demonstrated that the new variant exhibited superior activity because the F 176 G mutation increased the radius of the tunnel’s mouth and the mobility of α‐helices lining the tunnel. The new variant’s tunnel was open in 48 % of trajectories, compared to 58 % for the wild‐type, but only 0.02 % for the original four‐point variant. Delicate balance between activity and stability of enzymes can be manipulated by fine‐tuning the diameter and dynamics of their access tunnels.

DspA from Strongylocentrotus purpuratus: The first biochemically characterized haloalkane dehalogenase of non-microbial origin

Haloalkane dehalogenases are known as bacterial enzymes cleaving a carbon-halogen bond in halogenated compounds. Here we report the first biochemically characterized non-microbial haloalkane dehalogenase DspA from Strongylocentrotus purpuratus. The enzyme shows a preference for terminally brominated hydrocarbons and enantioselectivity towards β-brominated alkanes. Moreover, we identified other putative haloalkane dehalogenases of eukaryotic origin, representing targets for future experiments to discover dehalogenases with novel catalytic properties.

Ancestral Haloalkane Dehalogenases Show Robustness and Unique Substrate Specificity

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), as well as 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. This is extremely difficult to achieve by rational protein engineering. The study highlights that ASR is an efficient approach for the development of novel biocatalysts and robust templates for directed evolution.

Computer-assisted engineering of hyperstable fibroblast growth factor 2

Fibroblast growth factors (FGFs) serve numerous regulatory functions in complex organisms, and their corresponding therapeutic potential is of growing interest to academics and industrial researchers alike. However, applications of these proteins are limited due to their low stability. Here we tackle this problem using a generalizable computer‐assisted protein engineering strategy to create a unique modified FGF2 with nine mutations displaying unprecedented stability and uncompromised biological function. The data from the characterization of stabilized FGF2 showed a remarkable prediction potential of in silico methods and provided insight into the unfolding mechanism of the protein. The molecule holds a considerable promise for stem cell research and medical or pharmaceutical applications.