Strategies and software tools for engineering protein tunnels and dynamical gates

Improvements in the catalytic activity, substrate specificity or enantioselectivity of enzymes are traditionally achieved by modification of enzymes’ active sites. We have recently proposed that the enzyme engineering endeavors should target both the active sites and the access tunnels/channels [1,2]. Using the model enzymes haloalkane dehalogenases, we have demonstrated that engineering of access tunnels provides enzymes with significantly improved catalytic properties [3] and stability [4]. User-friendly software tools Caver [5], Caver Analyst [6], CaverDock [7] and Caver Web [8], have been developed for the computational design of protein tunnels/channels; FireProt [9] and HotSpot Wizard [10] for automated design of stabilizing mutations and smart libraries. Using these tools we were able to introduce a new tunnel to a protein structure and tweak its conformational dynamics. This engineering strategy has led to improved catalytic efficiency [2], enhanced promiscuity or even a functional switch (unpublished). Our concepts and software tools are widely applicable to various enzymes with known structures and buried active sites. 1. Damborsky, J., et al., 2009: Computational Tools for Designing and Engineering Biocatalysts. Current Opinion in Chemical Biology 13: 26-34. 2. Prokop, Z., et al., 2012: Engineering of Protein Tunnels: Keyhole-lock-key Model for Catalysis by the Enzymes with Buried Active Sites. Protein Engineering Handbook, Wiley-VCH, Weinheim, pp. 421-464. 3. Brezovsky, J., et al., 2016: Engineering a de Novo Transport Tunnel. ACS Catalysis 6: 7597-7610. 4. Koudelakova, T., et al., 2013: Engineering Enzyme Stability and Resistance to an Organic Cosolvent by Modification of Residues in the Access Tunnel. Angewandte Chemie 52: 1959-1963. 5. Chovancova, E., et al., 2012: CAVER 3.0: A Tool for Analysis of Transport Pathways in Dynamic Protein Structures. PLOS Computational Biology 8: e1002708. 6. Jurcik, A., et al., 2018: CAVER Analyst 2.0: Analysis and Visualization of Channels and Tunnels in Protein Structures and Molecular Dynamics Trajectories. Bioinformatics 34: 3586-3588. 7. Vavra, O., et al., 2019: CaverDock 1.0: A New Tool for Analysis of Ligand Binding and Unbinding Based on Molecular Docking. Bioinformatics (under review). 8. Stourac, J., et al. 2019: Caver Web 1.0: Identification of Tunnels and Channels in Proteins and Analysis of Ligand Transport. Nucleic Acids Research (under review). 9. Musil, M., et al., 2017: FireProt: Web Server for Automated Design of Thermostable Proteins. Nucleic Acids Research 45: W393-W399. 10. Sumbalova, L. et al., 2018: HotSpot Wizard 3.0: Automated Design of Site-Specific Mutations and Smart Libraries in Protein Engineering. Nucleic Acids Research 46: W356-W362

Establishment of computational biology in Greece and Cyprus: Past, present, and future.

We review the establishment of computational biology in Greece and Cyprus from its inception to date and issue recommendations for future development. We compare output to other countries of similar geography, economy, and size—based on publication counts recorded in the literature—and predict future growth based on those counts as well as national priority areas. Our analysis may be pertinent to wider national or regional communities with challenges and opportunities emerging from the rapid expansion of the field and related industries. Our recommendations suggest a 2-fold growth margin for the 2 countries, as a realistic expectation for further expansion of the field and the development of a credible roadmap of national priorities, both in terms of research and infrastructure funding

When do correlations increase with firing rates in recurrent networks?

A central question in neuroscience is to understand how noisy firing patterns are used to transmit information. Because neural spiking is noisy, spiking patterns are often quantified via pairwise correlations, or the probability that two cells will spike coincidentally, above and beyond their baseline firing rate. One observation frequently made in experiments, is that correlations can increase systematically with firing rate. Theoretical studies have determined that stimulus-dependent correlations that increase with firing rate can have beneficial effects on information coding; however, we still have an incomplete understanding of what circuit mechanisms do, or do not, produce this correlation-firing rate relationship. Here, we studied the relationship between pairwise correlations and firing rates in recurrently coupled excitatory-inhibitory spiking networks with conductance-based synapses. We found that with stronger excitatory coupling, a positive relationship emerged between pairwise correlations and firing rates. To explain these findings, we used linear response theory to predict the full correlation matrix and to decompose correlations in terms of graph motifs. We then used this decomposition to explain why covariation of correlations with firing rate—a relationship previously explained in feedforward networks driven by correlated input—emerges in some recurrent networks but not in others. Furthermore, when correlations covary with firing rate, this relationship is reflected in low-rank structure in the correlation matrix

Metallochaperones regulate intracellular copper levels.

Copper (Cu) is an important enzyme co-factor that is also extremely toxic at high intracellular concentrations, making active efflux mechanisms essential for preventing Cu accumulation. Here, we have investigated the mechanistic role of metallochaperones in regulating Cu efflux. We have constructed a computational model of Cu trafficking and efflux based on systems analysis of the Cu stress response of Halobacterium salinarum. We have validated several model predictions via assays of transcriptional dynamics and intracellular Cu levels, discovering a completely novel function for metallochaperones. We demonstrate that in addition to trafficking Cu ions, metallochaperones also function as buffers to modulate the transcriptional responsiveness and efficacy of Cu efflux. This buffering function of metallochaperones ultimately sets the upper limit for intracellular Cu levels and provides a mechanistic explanation for previously observed Cu metallochaperone mutation phenotypes

What makes or breaks a campaign to stop an invading plant pathogen?

Diseases in humans, animals and plants remain an important challenge in our society. Effective control of invasive pathogens often requires coordinated concerted action of a large group of stakeholders. Both epidemiological and human behavioural factors influence the outcome of a disease control campaign. In mathematical models that are frequently used to guide such campaigns, human behaviour is often ill-represented, if at all. Existing models of human, animal and plant disease that do incorporate participation or compliance are often driven by pay-offs or direct observations of the disease state. It is however very well known that opinion is an important driving factor of human decision making. Here we consider the case study of Citrus Huanglongbing disease (HLB), which is an acute bacterial disease that threatens the sustainability of citrus production across the world. We show how by coupling an epidemiological model of this invasive disease with an opinion dynamics model we are able to answer the question: What makes or breaks the effectiveness of a disease control campaign? Frequent contact between stakeholders and advisors is shown to increase the probability of successful control. More surprisingly, we show that informing stakeholders about the effectiveness of control methods is of much greater importance than prematurely increasing their perceptions of the risk of infection. We discuss the overarching consequences of this finding and the effect on human as well as plant disease epidemics