A5052048127- Protein Structure and Dynamics
- Mass Spectrometry Techniques and Applications
- Spectroscopy and Quantum Chemical Studies
- Quantum Information and Cryptography
- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Photonic and Optical Devices
- Advanced Chemical Physics Studies
- Chronic Lymphocytic Leukemia Research
- Chronic Myeloid Leukemia Treatments
- Quantum optics and atomic interactions
- Quantum Computing Algorithms and Architecture
- Genetic Neurodegenerative Diseases
- Parkinson's Disease Mechanisms and Treatments
- DNA and Nucleic Acid Chemistry
- Analytical Chemistry and Chromatography
- Neurological disorders and treatments
- Cold Atom Physics and Bose-Einstein Condensates
- Enzyme Structure and Function
- Optical and Acousto-Optic Technologies
- Laser-Matter Interactions and Applications
- Avian ecology and behavior
- Magnetic Bearings and Levitation Dynamics
- Quantum, superfluid, helium dynamics
- Mechanical and Optical Resonators
Schrodinger (United States)
2025
University of Maryland, College Park
2018-2024
Hope Center for Neurological Disorders
2023-2024
University of Mary
2020
United States Air Force Research Laboratory
2020
Center for Physical Sciences and Technology
2019
National Institute of Standards and Technology
2019
Joint Quantum Institute
2019
University of California, Davis
2012
Abstract The defining feature of Parkinson disease (PD) and Lewy body dementia (LBD) is the accumulation alpha-synuclein (Asyn) fibrils in bodies neurites. Here we develop validate a method to amplify Asyn extracted from LBD postmortem tissue samples use solid state nuclear magnetic resonance (SSNMR) studies determine atomic resolution structure. Amplified comprise mixture single protofilament two with very low twist. fold highly similar determined by recent cryo-electron microscopy study...
Identifying and discovering druggable protein binding sites is an important early step in computer-aided drug discovery, but it remains a difficult task where most campaigns rely on priori knowledge of from experiments. Here, we present site prediction method called Graph Attention Site Prediction (GrASP) re-evaluate assumptions nearly every the workflow data set preparation to model evaluation. GrASP able achieve state-of-the-art performance at recovering PDB structures while maintaining...
AMINO uses techniques from information theory to generate new order parameters for molecular dyanmics simulations.
Abstract Understanding how mutations render a drug ineffective is problem of immense relevance. Often the mechanism through which cause resistance can be explained purely thermodynamics. However, more perplexing situation when two proteins have same binding affinities but different residence times. In this work, we demonstrate all‐atom molecular dynamics simulations using recent developments grounded in statistical mechanics provide detailed mechanistic rationale for such variances. We...
Spectral gap optimization of order parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)] is a method for constructing the reaction coordinate (RC) in molecular systems, especially when they are plagued with hard to sample rare events, given larger dictionary or basis functions limited static dynamic information about system. In its original formulation, SGOOP designed construct 1-dimensional RC. Here we extend scope by introducing simple but...
Understanding ligand dissociation mechanisms at an atomic resolution is a highly desired but difficult to achieve objective in experiments as well computer simulations. Structural details of the process are general hard capture experiments, while relevant time scales far beyond molecular dynamics (MD) simulations even with most powerful supercomputers. As such, many different specialized enhanced sampling methods have been proposed that make it possible efficiently calculate protein-ligand...
Understanding kinetics including reaction pathways and associated transition rates is an important yet difficult problem in numerous chemical biological systems, especially situations with multiple competing pathways. When these high-dimensional systems are projected on low-dimensional coordinates, which often needed for enhanced sampling or interpretation of simulations experiments, one can end up losing the kinetic connectivity underlying landscape. Thus, projection, metastable states...
The residence time (τ) of a drug bound to receptor target is increasingly recognized as key property control during ligand-optimization campaigns and provides useful dimension for modulating compound profiles in addition binding affinity. For this reason, many computational approaches have been developed predict quantity. Several methods employ an empirical correlation between the measured simulation ligand escape pocket biased molecular dynamics (MD), while others rely on more formal that...
Proteins sample a variety of conformations distinct from their crystal structure. These structures, propensities, and the pathways for moving between them contain an enormous amount information about protein function that is hidden purely structural perspective. Molecular dynamics simulations can uncover these alternative but often at prohibitively high computational cost. Here we apply our recent statistical mechanics artificial intelligence-based molecular framework enhanced sampling...
ABSTRACT Identifying and discovering druggable protein binding sites is an important early step in computer-aided drug discovery but remains a difficult task where most campaigns rely on priori knowledge of from experiments. Here we present novel site prediction method called Graph Attention Site Prediction (GrASP) re-evaluate assumptions nearly every the workflow dataset preparation to model evaluation. GrASP able achieve state-of-the-art performance at recovering PDB structures while...
Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through ability to extract relevant information from raw data. Recently, AI has also found use in enhancing efficiency of molecular simulations, wherein derived slow modes are used accelerate simulation targeted ways. However, while typical fields where is characterized by a plethora data, per construction, suffer limited sampling and thus As such, simulations can dangerous situation AI-optimization...
The defining feature of Parkinson disease (PD) and Lewy body dementia (LBD) is the accumulation alpha-synuclein (Asyn) fibrils in bodies neurites. We developed validated a novel method to amplify Asyn extracted from LBD postmortem tissue samples used solid state nuclear magnetic resonance (SSNMR) studies determine atomic resolution structure. Amplified comprise two protofilaments with pseudo-2
In this work we revisit the classic problem of homogeneous nucleation a liquid droplet in supersaturated vapor phase. We consider at different extents driving force, which here is extent supersaturation, and calculate reaction coordinate (RC) for as force varied. The RC constructed linear combination three order parameters, where one accounts number liquid-like atoms, other two local density fluctuations. calculated from all-atom biased unbiased molecular dynamics (MD) simulations using...
Abstract Understanding how point mutations can render a ligand or drug ineffective against given biological target is problem of immense fundamental and practical relevance. Often the efficacy such resistance be explained purely on thermo-dynamic basis wherein mutated system displays reduced binding affinity for ligand. However, more perplexing harder to explain situation when two protein sequences have same drug. In this work, we demonstrate all-atom molecular dynamics simulations,...
Molecular dynamics (MD) simulations generate valuable all-atom resolution trajectories of complex systems, but analyzing this high-dimensional data as well reaching practical timescales even with powerful super-computers remain open problems. As such, many specialized sampling and reaction coordinate construction methods exist that alleviate these However, typically don’t work directly on all atomic coordinates, still require previous knowledge the important distinguishing features system,...
Abstract Obtaining atomistic resolution of ligand dissociation from a protein is much sought after experimental and computational challenge. Structural details the process are in general hard to capture experiments, while relevant timescales far beyond molecular dynamics (MD) simulations even with most powerful super-computers. As such many different specialized enhanced sampling methods have been proposed that make it possible efficiently calculate mechanisms protein-ligand systems....
Abstract Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through ability to extract relevant information from raw data. Recently AI has also seen use for enhancing efficiency of molecular simulations, wherein derived slow modes are used accelerate simulation in targeted ways. However, while typical fields where is characterized by a plethora data, simulations per-construction suffer limited sampling and thus As such can dangerous situation...
Reliable control of quantum information in matter-based qubits requires precisely applied external fields, and unaccounted for spatial cross-talk these fields between adjacent leads to loss fidelity. We report a CMOS foundry-produced, micro-fabricated silicon nitride (Si3N4) optical waveguide addressing chain eight, unequally-spaced trapped barium ions with crosstalk compatible scalable processing. The mitigation techniques incorporated into the chip design result reduction measured field by...
Spectral gap optimization of order parameters (SGOOP) (Tiwary and Berne, Proc. Natl. Acad. Sci. 113 2839 (2016)) is a method for constructing the reaction coordinate (RC) in molecular systems, especially when they are plagued with hard to sample rare events, given larger dictionary or basis functions, limited static dynamic information about system. In its original formulation, SGOOP designed construct 1-dimensional RC. Here we extend scope by introducing simple but powerful extension based...
Proteins sample a variety of conformations distinct from their crystal structure. These structures, propensities, and pathways for moving between them contain enormous information about protein function that is hidden purely structural perspective. Molecular dynamics simulations can uncover these higher energy states but often at prohibitively high computational cost. Here we apply our recent statistical mechanics artificial intelligence based molecular framework enhanced sampling loops in...