TCBG Seminar

Dissolving proteins with continuum models: a Poisson-Boltzmann solver in Python, with GPUs and boundary integrals

Dr. Christopher Cooper
Mechanical Engineering
Universidad Tecnica Federico Santa Maria
Valparaiso, Chile

Monday, March 6, 2017
3:00 pm (CT)
3269 Beckman Institute


The implicit-solvent model uses continuum theory to compute the electrostatic potential around dissolved biomolecules, which yields a system of partial differential equations where the Poisson- Boltzmann and Poisson equations are coupled on the molecular surface. To solve the resulting system of PDEs efficiently, we wrote a fast boundary-element method (with a multipole-based treecode) in Python and CUDA (for exploiting GPUs). We call our code PyGBe — a Python-based GPU code with boundary elements. In this talk, I will detail the implicit-solvent model and our implementation in PyGBe, to then present results in the context of protein solvation, binding, and adsorption. Results will include detailed evidence of verification and validation of the code, and practical applications which are relevant in nanoscale biosensor design. Despite Poisson- Boltzmann-based solvers are widely used in computational biophysics, the model has well-known limitations. Towards the end of this talk, I will discuss current developments that try to overcome some of those limitations from a boundary integral framework.

Christopher Cooper is an Academic Instructor at the Department of Mechanical Engineering in Universidad Técnica Federico Santa María, in Valparaíso, Chile. He obtained a PhD and MS in mechanical engineering from Boston University in 2015 and 2012, respectively, and an Engineer's Degree and BSc in mechanical engineering from Universidad Técnica Federico Santa María in 2009 and 2007. He is also an Associate Researcher at the Centro Científico Tecnológico de Valparaíso (CCTVal), and is currently a Visiting Assistant Research Scientist at the Department of Mathematics in the University of Michigan. His research interests are in the interface of mathematics, biophysics, and computer science. More specifically, he works on the development of fast and accurate numerical software for the simulation of protein electrostatics, with applications in solvation, binding, and nanoscale biosensors. He is also interested in algorithms relevant to boundary-integral equations on modern hardware, such as GPUs.

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