Support is requested for the development and implementation of novel computational methods for simulating the long timestep dynamics of proteins and the application of these methods to study the relation between motions and biological functions in flexible proteins. This will satisfy an urgent need for high-fidelity methos that reach biologically relevant timescales of microseconds to milliseconds of simulation, rather than the nanoseconds to microseconds simulations that are commonly available. While conformational change has itself been studied computationally for many years, our proposed work differs from other approaches in (1) the high-performance implementation of novel methods for long timestep dynamics and enhanced sampling at all-atom resolution and (2) the application of these detailed methods to address questions of flexibility and function in biomolecules of biomedical relevance. Since a quantitative comparison to experiment is critical for both the testing and greater impact of our computational methods, experimental collaborations are proposed. These are documented by letters of support. This project will have a widespread impact on NIH-funded researchers because the target parallel software packages already have a large user base and have an open code source. Longer MD simulations will allow previously impossible studies to be carried out in the fields of protein folding, protein engineering, enzyme design, drug design to flexible targets, and interactions among protein and nucleic acid complexes.

Public Health Relevance

This proposal seeks support for numerical methods that allow the simulation of protein conformational changes in the millisecond timescale, which already allow hundred-fold speedups over traditional molecular dynamics for proteins. With proposed improvements to the methods, implementation in GPUs and parallel CPUs and public dissemination in widely used software, more complex and powerful studies of protein folding, allostery, and protein engineering will be possible. These developments will be guided by the combined experimental - simulation study of the engineering of mutants of a protein of importance in regulating the cell cycle that is a potential target for Alzheimer's disease and cancer.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Notre Dame
Biostatistics & Other Math Sci
Schools of Engineering
Notre Dame
United States
Zip Code
Kastner, Kevin W; Izaguirre, Jesús A (2016) Accelerated molecular dynamics simulations of the octopamine receptor using GPUs: discovery of an alternate agonist-binding position. Proteins 84:1480-9
Feng, Haoyun; Costaouec, Ronan; Darve, Eric et al. (2015) A comparison of weighted ensemble and Markov state model methodologies. J Chem Phys 142:214113
Kim, Yong Hwan; Kastner, Kevin; Abdul-Wahid, Badi et al. (2015) Evaluation of conformational changes in diabetes-associated mutation in insulin a chain: a molecular dynamics study. Proteins 83:662-9
Abdul-Wahid, Badi'; Feng, Haoyun; Rajan, Dinesh et al. (2014) AWE-WQ: fast-forwarding molecular dynamics using the accelerated weighted ensemble. J Chem Inf Model 54:3033-43
Kastner, Kevin W; Shoue, Douglas A; Estiu, Guillermina L et al. (2014) Characterization of the Anopheles gambiae octopamine receptor and discovery of potential agonists and antagonists using a combined computational-experimental approach. Malar J 13:434
Schwantes, Christian R; Pande, Vijay S (2013) Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9. J Chem Theory Comput 9:2000-2009
Sweet, James C; Nowling, Ronald J; Cickovski, Trevor et al. (2013) Long Timestep Molecular Dynamics on the Graphical Processing Unit. J Chem Theory Comput 9:3267-3281
Nowling, Ronald J; Abrudan, Jenica L; Shoue, Douglas A et al. (2013) Identification of novel arthropod vector G protein-coupled receptors. Parasit Vectors 6:150
Abdul-Wahid, Badi'; Yu, Li; Rajan, Dinesh et al. (2012) Folding Proteins at 500 ns/hour with Work Queue. Proc IEEE Int Conf Escience 2012:1-8