Michael P. Eastwood
D. E. Shaw Research
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Featured researches published by Michael P. Eastwood.
Science | 2010
David E. Shaw; Paul Maragakis; Kresten Lindorff-Larsen; Stefano Piana; Ron O. Dror; Michael P. Eastwood; Joseph A. Bank; John M. Jumper; John K. Salmon; Yibing Shan; Willy Wriggers
Following Folding Fast Many protein functions involve conformational changes that occur on time-scales between tens of microseconds and milliseconds. This has limited the usefulness of all-atom molecular dynamics simulations, which are performed over shorter time-scales. Shaw et al. (p. 341) now report millisecond-scale, all-atom molecular dynamics simulations in an explicitly represented solvent environment. Simulation of the folding of a WW domain showed a well-defined folding pathway and simulation of the dynamics of bovine pancreatic trypsin inhibitor showed interconversion between distinct conformational states. Millisecond-scale simulations capture biologically relevant structural transitions during protein folding. Molecular dynamics (MD) simulations are widely used to study protein motions at an atomic level of detail, but they have been limited to time scales shorter than those of many biologically critical conformational changes. We examined two fundamental processes in protein dynamics—protein folding and conformational change within the folded state—by means of extremely long all-atom MD simulations conducted on a special-purpose machine. Equilibrium simulations of a WW protein domain captured multiple folding and unfolding events that consistently follow a well-defined folding pathway; separate simulations of the protein’s constituent substructures shed light on possible determinants of this pathway. A 1-millisecond simulation of the folded protein BPTI reveals a small number of structurally distinct conformational states whose reversible interconversion is slower than local relaxations within those states by a factor of more than 1000.
conference on high performance computing (supercomputing) | 2006
Kevin J. Bowers; Edmond Chow; Huafeng Xu; Ron O. Dror; Michael P. Eastwood; Brent A. Gregersen; John L. Klepeis; István Kolossváry; Mark A. Moraes; Federico D. Sacerdoti; John K. Salmon; Yibing Shan; David E. Shaw
Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events of great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms and implementation techniques that significantly accelerate parallel MD simulations compared with current state-of-the-art codes. These include a novel parallel decomposition method and message-passing techniques that reduce communication requirements, as well as novel communication primitives that further reduce communication time. We have also developed numerical techniques that maintain high accuracy while using single precision computation in order to exploit processor-level vector instructions. These methods are embodied in a newly developed MD code called Desmond that achieves unprecedented simulation throughput and parallel scalability on commodity clusters. Our results suggest that Desmonds parallel performance substantially surpasses that of any previously described code. For example, on a standard benchmark, Desmonds performance on a conventional Opteron cluster with 2K processors slightly exceeded the reported performance of IBMs Blue Gene/L machine with 32K processors running its Blue Matter MD code
Journal of the American Chemical Society | 2011
Yibing Shan; Eric T. Kim; Michael P. Eastwood; Ron O. Dror; Markus A. Seeliger; David E. Shaw
Although the thermodynamic principles that control the binding of drug molecules to their protein targets are well understood, detailed experimental characterization of the process by which such binding occurs has proven challenging. We conducted relatively long, unguided molecular dynamics simulations in which a ligand (the cancer drug dasatinib or the kinase inhibitor PP1) was initially placed at a random location within a box that also contained a protein (Src kinase) to which that ligand was known to bind. In several of these simulations, the ligand correctly identified its target binding site, forming a complex virtually identical to the crystallographically determined bound structure. The simulated trajectories provide a continuous, atomic-level view of the entire binding process, revealing persistent and noteworthy intermediate conformations and shedding light on the role of water molecules. The technique we employed, which does not assume any prior knowledge of the binding sites location, may prove particularly useful in the development of allosteric inhibitors that target previously undiscovered binding sites.
Cell | 2013
Anton Arkhipov; Yibing Shan; Rahul Das; Nicholas F. Endres; Michael P. Eastwood; David E. Wemmer; John Kuriyan; David E. Shaw
Dimerization-driven activation of the intracellular kinase domains of the epidermal growth factor receptor (EGFR) upon extracellular ligand binding is crucial to cellular pathways regulating proliferation, migration, and differentiation. Inactive EGFR can exist as both monomers and dimers, suggesting that the mechanism regulating EGFR activity may be subtle. The membrane itself may play a role but creates substantial difficulties for structural studies. Our molecular dynamics simulations of membrane-embedded EGFR suggest that, in ligand-bound dimers, the extracellular domains assume conformations favoring dimerization of the transmembrane helices near their N termini, dimerization of the juxtamembrane segments, and formation of asymmetric (active) kinase dimers. In ligand-free dimers, by holding apart the N termini of the transmembrane helices, the extracellular domains instead favor C-terminal dimerization of the transmembrane helices, juxtamembrane segment dissociation and membrane burial, and formation of symmetric (inactive) kinase dimers. Electrostatic interactions of EGFRs intracellular module with the membrane are critical in maintaining this coupling.
ieee international conference on high performance computing data and analytics | 2009
David E. Shaw; Ron O. Dror; John K. Salmon; J. P. Grossman; Kenneth M. Mackenzie; Joseph A. Bank; Cliff Young; Martin M. Deneroff; Brannon Batson; Kevin J. Bowers; Edmond Chow; Michael P. Eastwood; Douglas J. Ierardi; John L. Klepeis; Jeffrey S. Kuskin; Richard H. Larson; Kresten Lindorff-Larsen; Paul Maragakis; Mark A. Moraes; Stefano Piana; Yibing Shan; Brian Towles
Anton is a recently completed special-purpose supercomputer designed for molecular dynamics (MD) simulations of biomolecular systems. The machines specialized hardware dramatically increases the speed of MD calculations, making possible for the first time the simulation of biological molecules at an atomic level of detail for periods on the order of a millisecond-about two orders of magnitude beyond the previous state of the art. Anton is now running simulations on a timescale at which many critically important, but poorly understood phenomena are known to occur, allowing the observation of aspects of protein dynamics that were previously inaccessible to both computational and experimental study. Here, we report Antons performance when executing actual MD simulations whose accuracy has been validated against both existing MD software and experimental observations. We also discuss the manner in which novel algorithms have been coordinated with Antons co-designed, application-specific hardware to achieve these results.
Journal of Chemical Physics | 2005
Yibing Shan; John L. Klepeis; Michael P. Eastwood; Ron O. Dror; David E. Shaw
Gaussian split Ewald (GSE) is a versatile Ewald mesh method that is fast and accurate when used with both real-space and k-space Poisson solvers. While real-space methods are known to be asymptotically superior to k-space methods in terms of both computational cost and parallelization efficiency, k-space methods such as smooth particle-mesh Ewald (SPME) have thus far remained dominant because they have been more efficient than existing real-space methods for simulations of typical systems in the size range of current practical interest. Real-space GSE, however, is approximately a factor of 2 faster than previously described real-space Ewald methods for the level of force accuracy typically required in biomolecular simulations, and is competitive with leading k-space methods even for systems of moderate size. Alternatively, GSE may be combined with a k-space Poisson solver, providing a conveniently tunable k-space method that performs comparably to SPME. The GSE method follows naturally from a uniform framework that we introduce to concisely describe the differences between existing Ewald mesh methods.
Proceedings of the National Academy of Sciences of the United States of America | 2010
Morten Ø. Jensen; David W. Borhani; Kresten Lindorff-Larsen; Paul Maragakis; Vishwanath Jogini; Michael P. Eastwood; Ron O. Dror; David E. Shaw
We present the first atomic-resolution observations of permeation and gating in a K+ channel, based on molecular dynamics simulations of the Kv1.2 pore domain. Analysis of hundreds of simulated permeation events revealed a detailed conduction mechanism, resembling the Hodgkin–Keynes “knock-on” model, in which translocation of two selectivity filter–bound ions is driven by a third ion; formation of this knock-on intermediate is rate determining. In addition, at reverse or zero voltages, we observed pore closure by a novel “hydrophobic gating” mechanism: A dewetting transition of the hydrophobic pore cavity—fastest when K+ was not bound in selectivity filter sites nearest the cavity—caused the open, conducting pore to collapse into a closed, nonconducting conformation. Such pore closure corroborates the idea that voltage sensors can act to prevent pore collapse into the intrinsically more stable, closed conformation, and it further suggests that molecular-scale dewetting facilitates a specific biological function: K+ channel gating. Existing experimental data support our hypothesis that hydrophobic gating may be a fundamental principle underlying the gating of voltage-sensitive K+ channels. We suggest that hydrophobic gating explains, in part, why diverse ion channels conserve hydrophobic pore cavities, and we speculate that modulation of cavity hydration could enable structural determination of both open and closed channels.
Cell | 2012
Yibing Shan; Michael P. Eastwood; Xuewu Zhang; Eric T. Kim; Anton Arkhipov; Ron O. Dror; John M. Jumper; John Kuriyan; David E. Shaw
The mutation and overexpression of the epidermal growth factor receptor (EGFR) are associated with the development of a variety of cancers, making this prototypical dimerization-activated receptor tyrosine kinase a prominent target of cancer drugs. Using long-timescale molecular dynamics simulations, we find that the N lobe dimerization interface of the wild-type EGFR kinase domain is intrinsically disordered and that it becomes ordered only upon dimerization. Our simulations suggest, moreover, that some cancer-linked mutations distal to the dimerization interface, particularly the widespread L834R mutation (also referred to as L858R), facilitate EGFR dimerization by suppressing this local disorder. Corroborating these findings, our biophysical experiments and kinase enzymatic assays indicate that the L834R mutation causes abnormally high activity primarily by promoting EGFR dimerization rather than by allowing activation without dimerization. We also find that phosphorylation of EGFR kinase domain at Tyr845 may suppress the intrinsic disorder, suggesting a molecular mechanism for autonomous EGFR signaling.
international symposium on computer architecture | 2007
David E. Shaw; Martin M. Deneroff; Ron O. Dror; Jeffrey S. Kuskin; Richard H. Larson; John K. Salmon; Cliff Young; Brannon Batson; Kevin J. Bowers; Jack C. Chao; Michael P. Eastwood; Joseph Gagliardo; J. P. Grossman; C. Richard Ho; Douglas J. Ierardi; István Kolossváry; John L. Klepeis; Timothy Layman; Christine McLeavey; Mark A. Moraes; Rolf Mueller; Edward C. Priest; Yibing Shan; Jochen Spengler; Michael Theobald; Brian Towles; Stanley C. Wang
The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macro-molecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry and medicine. A wide range of biologically interesting phenomena, however, occur over time scales on the order of a millisecond--about three orders of magnitude beyond the duration of the longest current MD simulations. In this paper, we describe a massively parallel machine called Anton, which should be capable of executing millisecond-scale classical MD simulations of such biomolecular systems. The machine, which is scheduled for completion by the end of 2008, is based on 512 identical MD-specific ASICs that interact in a tightly coupled manner using a specialized high-speed communication network. Anton has been designed to use both novel parallel algorithms and special-purpose logic to dramatically accelerate those calculations that dominate the time required for a typical MD simulation. The remainder of the simulation algorithm is executed by a programmable portion of each chip that achieves a substantial degree of parallelism while preserving the flexibility necessary to accommodate anticipated advances in physical models and simulation methods.
Proceedings of the National Academy of Sciences of the United States of America | 2009
Yibing Shan; Markus A. Seeliger; Michael P. Eastwood; Filipp Frank; Huafeng Xu; Morten Ø. Jensen; Ron O. Dror; John Kuriyan; David E. Shaw
In many protein kinases, a characteristic conformational change (the “DFG flip”) connects catalytically active and inactive conformations. Many kinase inhibitors—including the cancer drug imatinib—selectively target a specific DFG conformation, but the function and mechanism of the flip remain unclear. Using long molecular dynamics simulations of the Abl kinase, we visualized the DFG flip in atomic-level detail and formulated an energetic model predicting that protonation of the DFG aspartate controls the flip. Consistent with our models predictions, we demonstrated experimentally that the kinetics of imatinib binding to Abl kinase have a pH dependence that disappears when the DFG aspartate is mutated. Our model suggests a possible explanation for the high degree of conservation of the DFG motif: that the flip, modulated by electrostatic changes inherent to the catalytic cycle, allows the kinase to access flexible conformations facilitating nucleotide binding and release.