HPC & Life Sciences

By Thomas Cheatham

Department of Medicinal Chemistry College of Pharmacy, University of Utah

Published on

Abstract

Biomolecular simulation provides a means to explore biomolecular structure, dynamics and interactions on timescales from femptoseconds to milliseconds on available high performance computing computational resources. Since the first protein simulations in ~1975, atomistic molecular dynamics (MD) simulations with crude force field representations have increasingly provided insight into structure-function relationships in biomolecules like proteins and nucleic acids. The common "MD codes" have always tried to take advantage of the latest advances in high performance computing and special-purpose hardware (for example GPUs). As computer power has improved, we not only are doing a much better job of describing and understanding biomolecules, but also becoming better at exposing and overcoming limitations in the underlying methodologies and representations. One area where we still have trouble is data overload, workflow and process management. These challenges are becoming particularly acute as we strive to make efficient use of machines like Blue Waters and try to facilitate dissemination of the resulting data. Challenges in code performance and development, and data management, analysis, and dissemination, will be highlighted in this overview.

Bio

Thomas Cheatham, Associate Professor of Medicinal Chemistry in the L.S. Skaggs Pharmacy Research Institute in the College of Pharmacy at the University of Utah, received his B.A. degrees in Chemistry (honors) and in Mathematics and Computer Science from Middlebury College in 1988, worked as a Programmer/Analyst at the Aiken Computational Lab at Harvard, then in 1990 joined the Pharmaceutical Chemistry PhD Program at the University of California San Francisco working with the late Peter Kollman. After receiving his PhD in 1997, Cheatham was a NRC postdoctoral fellow with Bernie Brooks at the National Institutes of Health before moving to Utah in 2000 where he managed the mine fields of multiple departments and research track professor positions to ultimately get tenure. Currently Cheatham serves as the Chair of the XSDEDE User Advisory Committee and is also on the XSEDE Science Advisory Board and NICS User Advisory Committee.

Cheatham's research centers on the development, application and validation of biomolecular simulation methods to provide insight into biomolecular structure, dynamics, energetics and interactions. This involves extensive use of high performance computing computational resources. He is one of the core AMBER developers and primary author of the "ptraj" molecular dynamics trajectory analysis software. Current resources supporting the Cheatham lab include funding from three NIH grants (R01 GM-081411, GM-098102 and GM-074249), a NSF PRAC travel award (OCI-1036208), and a large allocation of HPC resources from both the NSF XSEDE (MCA-01S027) and NCSA / U Illinois Blue Waters computational resource, in addition to robust facilities in the Center for High Performance Computing at the University of Utah. For more information, see http://www.chpc.utah.edu/~cheatham

Cite this work

Researchers should cite this work as follows:

  • Thomas Cheatham (2013), "HPC & Life Sciences," https://nanohub.org/resources/19412.

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Location

Eisner-Lubin Room 401, New York University, New York, NY

Submitter

NanoBio Node

University of Illinois at Urbana-Champaign

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