A5061322136- Receptor Mechanisms and Signaling
- Protein Structure and Dynamics
- Neuropeptides and Animal Physiology
- Computational Drug Discovery Methods
- Mass Spectrometry Techniques and Applications
- Parallel Computing and Optimization Techniques
- Machine Learning in Materials Science
- RNA and protein synthesis mechanisms
- Enzyme Structure and Function
- Neuroscience and Neuropharmacology Research
- Monoclonal and Polyclonal Antibodies Research
- Photoreceptor and optogenetics research
- Ion channel regulation and function
- Lipid Membrane Structure and Behavior
- Pharmacological Receptor Mechanisms and Effects
- Advanced Data Storage Technologies
- Distributed and Parallel Computing Systems
- Color Science and Applications
- Advanced NMR Techniques and Applications
- Spectroscopy and Quantum Chemical Studies
- Neuroscience and Neural Engineering
- Scientific Computing and Data Management
- Machine Learning in Bioinformatics
- Pharmacological Effects and Assays
- Genomics and Chromatin Dynamics
Stanford University
2016-2025
D. E. Shaw Research
2009-2021
Stanford Medicine
2018-2021
Laboratoire d'Informatique de Paris-Nord
2020
Columbia University
2007-2016
Leiden University
2016
IIT@MIT
2000-2010
Hebrew University of Jerusalem
2007
Massachusetts Institute of Technology
2001-2005
University of Cambridge
2001
Recent advances in hardware and software have enabled increasingly long molecular dynamics (MD) simulations of biomolecules, exposing certain limitations the accuracy force fields used for such spurring efforts to refine these fields. modifications Amber CHARMM protein fields, example, improved backbone torsion potentials, remedying deficiencies earlier versions. Here, we further advance simulation by improving amino acid side-chain potentials ff99SB field. First, model alpha-helical systems...
Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms implementation techniques significantly accelerate parallel MD compared with current state-of-the-art codes. These include a novel decomposition method message-passing reduce communication requirements, as well primitives further time. have...
An outstanding challenge in the field of molecular biology has been to understand process by which proteins fold into their characteristic three-dimensional structures. Here, we report results atomic-level dynamics simulations, over periods ranging between 100 μs and 1 ms, that reveal a set common principles underlying folding 12 structurally diverse proteins. In simulations conducted with single physics-based energy function, proteins, representing all three major structural classes,...
Molecular dynamics (MD) simulations are widely used to study protein motions at an atomic level of detail, but they have been limited time scales shorter than those many biologically critical conformational changes. We examined two fundamental processes in dynamics--protein folding and change within the folded state--by means extremely long all-atom MD conducted on a special-purpose machine. Equilibrium WW domain captured multiple unfolding events that consistently follow well-defined...
Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms implementation techniques significantly accelerate parallel MD compared with current state-of-the-art codes. These include a novel decomposition method message-passing reduce communication requirements, as well primitives further time. have...
The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macro-molecules could in principle provide answers some of the most important currently outstanding questions fields biology, chemistry, medicine. A wide range biologically interesting phenomena, however, occur over timescales on order a millisecond---several orders magnitude beyond duration longest current MD simulations. We describe massively parallel machine called Anton,...
How drugs bind to their receptors--from initial association, through drug entry into the binding pocket, adoption of final bound conformation, or "pose"--has remained unknown, even for G-protein-coupled receptor modulators, which constitute one-third all marketed drugs. We captured this pharmaceutically critical process in atomic detail using first unbiased molecular dynamics simulations molecules spontaneously associate with receptors achieve poses matching those determined...
Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy such simulations, however, is critically dependent on force field--the mathematical model used to approximate atomic-level forces acting simulated molecular system. Here we present systematic extensive evaluation eight different protein fields based comparisons experimental data with that reach previously inaccessible...
Although the thermodynamic principles that control binding of drug molecules to their protein targets are well understood, detailed experimental characterization process by which such occurs has proven challenging. We conducted relatively long, unguided molecular dynamics simulations in a ligand (the cancer dasatinib or kinase inhibitor PP1) was initially placed at random location within box also contained (Src kinase) known bind. In several these simulations, correctly identified its target...
Anton 2 is a second-generation special-purpose supercomputer for molecular dynamics simulations that achieves significant gains in performance, programmability, and capacity compared to its predecessor, 1. The architecture of tailored fine-grained event-driven operation, which improves performance by increasing the overlap computation with communication, also allows wider range algorithms run efficiently, enabling many new software-based optimizations. A 512-node machine, currently up ten...
The mechanism of ion channel voltage gating-how channels open and close in response to changes-has been debated since Hodgkin Huxley's seminal discovery that the crux nerve conduction is flow across cellular membranes. Using all-atom molecular dynamics simulations, we show how a voltage-gated potassium (KV) switches between activated deactivated states. On deactivation, pore hydrophobic collapse rapidly halts flow. Subsequent voltage-sensing domain (VSD) relaxation, including inward,...
A third of marketed drugs act by binding to a G-protein-coupled receptor (GPCR) and either triggering or preventing activation. Although recent crystal structures have provided snapshots both active inactive functional states GPCRs, these do not reveal the mechanism which GPCRs transition between states. Here we propose an activation for β 2 -adrenergic receptor, prototypical GPCR, based on atomic-level simulations in agonist-bound transitions spontaneously from crystallographically observed...
H2O2 and vanadate are known insulinomimetic agents. Together they induce insulin's bioeffects with a potency which exceeds that seen insulin, vanadate, or alone. Employing Western blotting anti-P-Tyr antibodies, we have identified in Fao cells at least four proteins (pp180, 150, 114, 100) whose P-Tyr content is rapidly increased upon treatment of the 3 mM H2O2. Tyrosine phosphorylation these additional was markedly potentiated (6-10-fold) when 100 microM sodium orthovanadate added together...
Under typical viewing conditions, we find it easy to distinguish between different materials, such as metal, plastic, and paper. Recognizing materials from their surface reflectance properties (such lightness gloss) is a nontrivial accomplishment because of confounding effects illumination. However, if subjects have tacit knowledge the statistics illumination encountered in real world, then possible reject unlikely image interpretations, thus estimate even when precise unknown. A matching...
Gaussian split Ewald (GSE) is a versatile mesh method that fast and accurate when used with both real-space k-space Poisson solvers. While methods are known to be asymptotically superior in terms of computational cost parallelization efficiency, such as smooth particle-mesh (SPME) have thus far remained dominant because they been more efficient than existing for simulations typical systems the size range current practical interest. Real-space GSE, however, approximately factor 2 faster...