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Computational kinetics of a large scale biological process on GPU workstations: DNA bending

Arnold Peter Ruymgaart
The University of Texas at Austin
The University of Texas at Austin, 2013

@article{ruymgaart2013computational,

   title={Computational kinetics of a large scale biological process on GPU workstations: DNA bending},

   author={Ruymgaart, Arnold Peter},

   year={2013}

}

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It has only recently become possible to study the dynamics of large time scale biological processes computationally in explicit solvent and atomic detail. This required a combination of advances in computer hardware, utilization of parallel and special purpose hardware as well as numerical and theoretical approaches. In this work we report advances in these areas contributing to the feasibility of a work of this scope in a reasonable time. We then make use of them to study an interesting model system, the action of the DNA bending protein 1IHF and demonstrate such an effort can now be performed on GPU equipped PC workstations. Many cellular processes require DNA bending. In the crowded compartment of the cell, DNA must be efficiently stored but this is just one example where bending is observed. Other examples include the effects of DNA structural features involved in transcription, gene regulation and recombination. 1IHF is a bacterial protein that binds and kinks DNA at sequence specific sites. The 1IHF binding to DNA is the cause or effect of bending of the double helix by almost 180 degrees. Most sequence specific DNA binding proteins bind in the major groove of the DNA and sequence specificity results from direct readout. 1IHF is an exception; it binds in the minor groove. The final structure of the binding/bending reaction was crystallized and shows the protein arm like features "latched" in place wrapping the DNA in the minor grooves and intercalating the tips between base pairs at the kink sites. This sequence specific, mostly indirect readout protein-DNA binding/bending interaction is therefore an interesting test case to study the mechanism of protein DNA binding and bending in general. Kinetic schemes have been proposed and numerous experimental studies have been carried out to validate these schemes. Experiments have included rapid kinetics laser T jump studies providing unprecedented temporal resolution and time resolved (quench flow) DNA foot-printing. Here we complement and add to those studies by investigating the mechanism and dynamics of the final latching/initial unlatching at an atomic level. This is accomplished with the computational tools of molecular dynamics and the theory of Milestoning. Our investigation begins by generating a reaction coordinate from the crystal structure of the DNA-protein complex and other images generated through modelling based on biochemical intuition. The initial path is generated by steepest descent minimization providing us with over 100 anchor images along the Steepest Descent Path (SDP) reaction coordinate. We then use the tools of Milestoning to sample hypersurfaces (milestones) between reaction coordinate anchors. Launching multiple trajectories from each milestone allowed us to accumulate average passage times to adjacent milestones and obtain transition probabilities. A complete set of rates was obtained this way allowing us to draw important conclusions about the mechanism of DNA bending. We uncover two possible metastable intermediates in the dissociation unkinking process. The first is an unexpected stable intermediate formed by initial unlatching of the IHF arms accompanied by a complete "psi-0" to "psi+140" conformational change of the IHF arm tip prolines. This unlatching (de-intercalation of the IHF tips from the kink sites) is required for any unkinking to occur. The second intermediate is formed by the IHF protein arms sliding over the DNA phosphate backbone and refolding in the next groove. The formation of this intermediate occurs on the millisecond timescale which is within experimental unkinking rate results. We show that our code optimization and parallelization enhancements allow the entire computational process of these millisecond timescale events in about one month on 10 or less GPU equipped workstations/cluster nodes bringing these studies within reach of researchers that do not have access to supercomputer clusters.
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