University of Calgary
Research Themes
Broadly, the Engel Lab employs a multidisciplinary toolkit containing non-equilibrium physics, differentiable programming, and molecular simulation to elucidate living systems and inform the design of bio-inspired nanotechnology.
ML-inspired biomolecular model development
Over the past decade, the success of machine learning models has exploded. Transparent fitting routines and a suite of optimized software and hardware has enabled community-driven iterative improvement that has culminated in the successes of modern LLMs and image generators. My collaborators and I envision transposing this toolkit from ML to biomolecular modelling and hope to catalyze a revolution in the accuracy of molecular simulation.
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We've started by creating a framework for fitting a physics-based DNA model, oxDNA, using routines from the ML community. Our preprint is here.
Investigating the efficiency of molecular motors and designing de novo nanomachines
Billions of years of evolution have crafted a remarkable suite of cellular machinery, from transport motors that “walk” along cellular tightropes to the rotary motor F0F1 ATP synthase, which harnesses proton concentration gradients to produce ATP, the energetic currency of life. F0F1 ATP synthase operates far from equilibrium, rotating up to 10,000 nm/s, and achieves an unbelievable efficiency of up to nearly 100%. This almost-perfect engine has attracted a collection of experimental and theoretical investigations, most recently into what aspects of the rotor’s design lead to its optimal efficiency. Crucially, however, these attempts have had to use an assumption of near-equilibrium operation to make progress. We're using differentiable simulations to determine thermodynamically optimal protocols for ATP synthase in the far-from-equilibrium regime, shedding light on whether the true biological protocol is the theoretically optimal one. Relevant publication here.
Simulations for DNA nanotechnology
Our group uses the oxDNA model to simulate a range of nanotechnological systems in close collaboration with experimentalists. Contact us if you have a system you would like to understand better!
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Relevant publications:
Engel et al. 2019
