Predictive and Scalable MacroMolecular Modeling
Abstract
Most biomolecular complexes involve three or more molecules, forming macromolecules
consisting of thousands to a million atoms. We consider fast molecular modeling algorithms and
data structures to support automated prediction of bimolecular structure assemblies formulating
it as the approximate solution of a nonconvex geometric optimization problem. The conformation
of the macromolecules with respect to each other are optimized with respect to a hierarchical
interface matching score based on molecular energetic potentials ((Lennard-Jones, Coulombic,
generalized Born, Poisson Boltzmann ). The assembly prediction decision procedure involves
both search and scoring over very high dimensional spaces, (O(6^n) for n rigid molecules) , and
moreover is provably NP-hard. To make things even more complicated, predicting biomolecular
complexes requires search optimization to include molecular flexibility and induced conformational
changes as the assembly interfaces complementarily align. I shall also briefly present fast
computation methods which run on commodity multicore CPUs and manycore GPUs. The key
idea is to trade off accuracy of pairwise, long-range atomistic energetics for a higher speed of
execution. Our CUDA kernel for GPU acceleration uses a cache-friendly, recursive and linear-
space octree data structure to handle very large molecular structures with up to several million
atoms. Based on this CUDA kernel, we utilize a hybrid method which simultaneously exploits both
CPU and GPU cores to provide the best performance based on selected parameters of the
approximation scheme.
Bio
Chandrajit Bajaj is a Professor of Computer Science, and the director of the
Center for Computational Visualization in the Institute for Computational and
Engineering Sciences (ICES) at the University of Texas at Austin. Bajaj holds the
Computational Applied Mathematics Chair in Visualization. He is also an affiliate
faculty member of Mathematics, Biomedical Engineering, the Institute of Cell and
Molecular Biology and Neurosciences. He currently serves on the editorial boards
for the International Journal of Computational Geometry and Applications, and the
ACM Computing Surveys. He is a fellow of the American Association for the
Advancement of Science (AAAS), the Association of Computing Machinery (ACM),
and the Institute of Electrical and Electronic Engineers (IEEE).
Date: 2015-Sep-11 Time: 11:00:00 Room: 02.2 Centro de Congressos IST
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