Dr. Gareth Tribello

Lecturer in Atomistic Simulation

Gareth

DBB.01.022
+44 (0) 28 9097 6010
g.tribello@qub.ac.uk

Atomistic Simulation Centre School of Mathematics and Physics Queen's University Belfast University Road Belfast BT7 1NN Northern Ireland

Degrees, Awards and Honours

    Interests

      Most Recent Publications

      1. Probing the Unfolded Configurations of a β-Hairpin Using Sketch-Map, Journal of Chemical Theory and Computation, 2015, 11, No. 3, pp. 1086
        doi: 10.1021/ct500950z Abstract
        This work examines the conformational ensemble involved in β-hairpin folding by means of advanced molecular dynamics simulations and dimensionality reduction. A fully atomistic description of the protein and the surrounding solvent molecules is used, and this complex energy landscape is sampled by means of parallel tempering metadynamics simulations. The ensemble of configurations explored is analyzed using the recently proposed sketch-map algorithm. Further simulations allow us to probe how mutations affect the structures adopted by this protein. We find that many of the configurations adopted by a mutant are the same as those adopted by the wild-type protein. Furthermore, certain mutations destabilize secondary-structure-containing configurations by preventing the formation of hydrogen bonds or by promoting the formation of new intramolecular contacts. Our analysis demonstrates that machine-learning techniques can be used to study the energy landscapes of complex molecules and that the visualizations that are generated in this way provide a natural basis for examining how the stabilities of particular configurations of the molecule are affected by factors such as temperature or structural mutations.

      2. Understanding the Interaction between Low-Energy Electrons and DNA Nucleotides in Aqueous Solutionhttp://dx.doi.org/10.1021/ct500950z, Journal of Physical Chemistry Letters, 2015, 6, No. 15, pp. 3091
        doi: 10.1021/acs.jpclett.5b01011 Abstract Full Text

        Reactions that can damage DNA have been simulated using a combination of molecular dynamics and density functional theory. In particular, the damage caused by the attachment of a low energy electron to the nucleobase. Simulations of anionic single nucleotides of DNA in an aqueous environment that was modeled explicitly have been performed. This has allowed us to examine the role played by the water molecules that surround the DNA in radiation damage mechanisms. Our simulations show that hydrogen bonding and protonation of the nucleotide by the water can have a significant effect on the barriers to strand breaking reactions. Furthermore, these effects are not the same for all four of the bases.

      3. Demonstrating the Transferability and the Descriptive Power of Sketch-Maphttp://dx.doi.org/10.1021/acs.jpclett.5b01011, J. Chem. Theory Comput. , 2013, 9, pp. 1521Abstract

      All of Gareth's publications

      Sketch-map

      How does does the pathway through which a protein folds change as it is mutated? What happens to the structures adopted by a cluster of material as temperature is increased? We can examine these problems using molecular dynamics simulations. However, the output from any such simulation is inherently high-dimensional because MD tell us how the positions of all the atoms are change as a function of time. To help interpret MD simulations and to thus help solve problem like those above we recently introduced the sketch-map algorithm. Sketch-map generates a low-dimensional represetation of an MD trajectory and thus allows one to see details that would be difficult to visualize by other means. More information on the sketch-map algorithm can be found at the website.

      Relevant Papers

      1. Title: Simplifying the representation of complex free-energy landscapes using sketch-map

        Author(s): Ceriotti M., Tribello G. Parrinello M.

        Proc. Natl. Acad Sci. U.S.A , 108, pp. 13023-13028 (2011)

      2. Title: Demonstrating the Transferability and the Descriptive Power of Sketch-Map

        Author(s): Ceriotti M., Tribello G., Parrinello M.,

        J. Chem. Theory Comput. , 9, pp. 1521- (2013)

      The free energy surface for Lennard Jones 38 shown as a function of a set of sketch-map coordinates at three different temperatures. In this representation you can clearly see how the volume of phase space that is sampled changes with temperature.

      Enhanced sampling

      A figure showing how the self-learning, reconnaissance metadynamics algorithm works. A clustering algorithm is used to find regions of configuration space where the system is getting trapped. A bias is then added to force the system away from these kinetic traps.

      Chemical reactions, phase transitions and the self assembly of molecules take place over timescales that are often far longer than what is accesible in an atomistic molecular dynamics simulation. At first sight it would thus seem that these processes are not amenable to study using molecular dynamics. This is not the case, however. We can study these long-time-scale processes by changing the potential so as to make rare events occur more frequently. From these sorts of simulation we can extract relative free energies and can thus begin to say something about reaction mechanisms for even the slowest processes. More information on the algorithms that I use and have developed for enhancing sampling in this way can be found here.

      Relevant Papers

      1. Title: Using sketch-map coordinates to analyze and bias molecular dynamics simulations

        Author(s): Tribello G., Ceriotti M., Parrinello M.

        Proc. Natl. Acad. Sci. U.S.A., 109, pp. 5196-5201 (2012)

      2. Title: A self-learning algorithm for biased molecular dynamics

        Author(s): Tribello G., Ceriotti M., Parrinello M.

        Proc. Natl. Acad Sci U.S.A. , 107, pp. 17509-17514 (2010)

      Nucleation of crystals

      When we encouter chemicals in our daily life, be they pharmaceutical drugs, the rocks in the earth or the condiments we add to our food, they are often in a crystalline form. As such understanding how and why particular crystals form is enormously important. The crystalline form of a substance affects its processibility and in some cases its performance. There is thus a strong desire amongst industrial chemists to control crystallization. Furthermore, nucleation - the first step in the formation of a crystal - is an increadibly rare event, which makes it very difficult (and thus interesting) to simulate.

      Relevant Papers

      1. Title: A molecular dynamics study of the early states of calcium carbonate growth

        Author(s): Tribello G., Bruneval F., Liew C.C., Parrinello M.

        J. Phys. Chem. B,, 113, pp. 11680-11687 (2009)

      The earliest formed clusters of sodium chloride that form in solution. Contrary to what one would expect small clusters of sodium chloride can have a structure that resembles Wurtzite as well as the familiar rock salt structure.

      Self assembly in biomolecules

      The free energy landscape for a short protein as a function of a set of sketch-map coordinates.

      Many biomolecules spontaneously self-assemble into their biologically active form. This process of folding can be observed ex-vivo so the energy landscape must be shaped so as to encourage the system into its biologically active state. There has been an enormous effort to simulate this process over the past few years so as to better understand how these molecules evolved to have such exquisit functionalities. Currently, I have a project that uses sketch-map to understand how sampling of configuration space changes when proteins are mutated and when proteins are denatured at high temperatures or in the presence of a denaturants like urea.

      Relevant Papers

      1. Title: Using sketch-map coordinates to analyze and bias molecular dynamics simulations

        Author(s): Tribello G., Ceriotti M., Parrinello M.

        Proc. Natl. Acad. Sci. U.S.A., 109, pp. 5196-5201 (2012)

      2. Title: Locating binding poses in protein-ligand systems using reconnaissance metadynamics

        Author(s): Soderhjelm P., Tribello G., Parrinello M.

        Proc. Natl. Acad. Sci. U.S.A. , 109, pp. 5170-5175 (2012)