DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding

  title={DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding},
  author={Hyungro Lee and H. Ma and Matteo Turilli and D. Bhowmik and S. Jha and A. Ramanathan},
  journal={2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS)},
  • Hyungro Lee, H. Ma, +3 authors A. Ramanathan
  • Published 2019
  • Computer Science
  • 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS)
  • Simulations of biological macromolecules are important in understanding the physical basis of complex processes such as protein folding. However, even with increasing computational capacity and specialized architectures, the ability to simulate protein folding at atomistic scales still remains challenging. This stems from the dual aspects of high dimensionality of protein conformational landscapes, and the inability of atomistic molecular dynamics (MD) simulations to sufficiently sample these… CONTINUE READING
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