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arXiv 2020年

作者： Giberti, F. Tribello, G.A. Ceriotti, Michele Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Atomistic Simulation Centre School of Mathematics and Physics Queen’s University Belfast BelfastBT14 7EN United Kingdom

Enhanced sampling techniques have become an essential tool in computational chemistry and physics, where they are applied to sample activated processes that occur on a time scale that is inaccessible to conventional simulations. Despite their popularity, it is well known that they have constraints that hinder their applications to complex problems. The core issue lies in the need to describe the system using a small number of collective variables (CVs). Any slow degree of freedom that is not properly described by the chosen CVs will hinder sampling efficiency. However, exploration of configuration space is also hampered by including variables that are not relevant to describe the activated process under study. This paper presents the Adaptive Topography of Landscape for Accelerated Sampling (ATLAS), a new biasing method capable of working with many CVs. The root idea of ATLAS is to apply a divide-and-conquer strategy where the high-dimensional CVs space is divided into basins, each of which is described by an automatically-determined, low-dimensional set of variables. A well-tempered metadynamics-like bias is constructed as a function of these local variables. Indicator functions associated with the basins switch on and off the local biases, so that the sampling is performed on a collection of low-dimensional CV spaces, that are smoothly combined to generate an effectively high-dimensional bias. The unbiased Boltzmann distribution is recovered through reweigting, making the evaluation of conformational and thermodynamic properties straightforward. The decomposition of the free-energy landscape in local basins can be updated iteratively as the simulation discovers new (meta)stable states. Copyright © 2020, The Authors. All rights reserved.

关键词： computational chemistry

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A dynamical model for the calcineurin-NFATc signaling pathway and muscle fiber shifting

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PAMM 2021年第1期20卷

作者： Yesid Villota-Narvaez Angélica Ramírez-Martínez Diego Garzón-Alvarado Oliver Röhrle Biomimetics Laboratory and Numerical Methods and Modeling Research Group (GNUM) Instituto de Biotecnología (IBUN) Universidad Nacional de Colombia Bogotá Colombia Stuttgart Centre for Simulation Sciences (SC SimTech) Pfaffenwaldring 5a 70569 Stuttgart Germany Computational modeling of natural systems Research Group (COMMONS) Mechanical Engineering Department Universidad Central Bogota Colombia Institute for Modeling and Simulation of Biomechanical Systems University of Stuttgart Pfaffenwaldring 5a 70569 Stuttgart Germany

Training exercise produces skeletal muscle adaptation: at the organ scale, as anatomical changes; and at the myofiber scale, as mitochondrial and protein type content. The protein content of a myofiber is controlled by the calcineurin-NFATc signaling pathway: exercise triggers the pathway, and its final product is the translocation of dephosphorylated NFATc to the nucleus. Once in the nucleus, NFATc controls the state of the gene program to encode the slow or the fast fiber type characteristics. In the long term, the adaptation of the fiber type characteristics produces a shift in muscle fiber type: an increase in the number of myofibers of the fast type (which means that myofibers of the slow type shift to fast type) is related to force production; and an increase in the number of myofibers of the slow type (myofibers of the fast type shift to slow type) is related to fatigue resistance. These macroscopic features, i.e. force production and fatigue resistance, are the main target of most training protocols; however, little attention is focused on the limitations imposed by the fiber distribution of muscles at the organ scale. Based on the calcineurin-NFATc signaling pathway, we represented an exercise stimulus by a cytosolic calcium signal, and simulated the dynamics of NFATc in the nucleus. In this contribution, we present a dynamical model for the calcineurin-NFATc signaling pathway to describe the time course of dephosphorilated NFATc in the nucleus. We used an experimental report of a continuous stimulation pattern for calibration, and an experimental report of a pulsed stimulation pattern for comparison; we obtained a good agreement between the simulations and the experimental measurements.

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Structure-Based Experimental Datasets for Benchmarking of Protein simulation Force Fields

arXiv

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arXiv 2023年

作者： Cavender, Chapin E. Case, David A. Chen, Julian C.-H. Chong, Lillian T. Keedy, Daniel A. Lindorff-Larsen, Kresten Mobley, David L. Ollila, O.H. Samuli Oostenbrink, Chris Robustelli, Paul Voelz, Vincent A. Wall, Michael E. Wych, David C. Gilson, Michael K. Skaggs School of Pharmacy and Pharmaceutical Sciences UC San Diego 9500 Gilman Drive La Jolla CA92093 United States Dept. of Chemistry & Chemical Biology Rutgers University PiscatawayNJ08854 United States Bioscience Division Los Alamos National Laboratory Los Alamos NM87545 United States Department of Chemistry and Biochemistry The University of Toledo ToledoOH43606 United States University of Pittsburgh 219 Parkman Avenue PittsburghPA15260 United States Structural Biology Initiative CUNY Advanced Science Research Center New YorkNY10031 United States Department of Chemistry and Biochemistry City College of New York New YorkNY10031 United States PhD Programs in Biochemistry Biology and Chemistry CUNY Graduate Center New YorkNY10016 United States Linderstrøm-Lang Centre for Protein Science Department of Biology University of Copenhagen Copenhagen NDK-2200 Denmark Pharmaceutical Sciences Department University of California Irvine IrvineCA United States University of Helsinki Institute of Biotechnology Helsinki Finland Institute for Molecular Modeling and Simulation University of Natural Resources and Life Sciences Muthgasse 11 Vienna1190 Austria Dartmouth College Department of Chemistry HanoverNH03755 United States Department of Chemistry Temple University PhiladelphiaPA United States Computer Computational and Statistical Sciences Division Los Alamos National Laboratory Los AlamosNM87545 United States The Center for Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States

This review article provides an overview of structurally oriented, experimental datasets that can be used to benchmark protein force fields, focusing on data generated by nuclear magnetic resonance (NMR) spectroscopy and room temperature (RT) protein crystallography. We discuss why these observables are useful for assessing force field accuracy, how they can be calculated from simulation trajectories, and statistical issues that arise when comparing simulations with experiment. The target audience for this article is computational researchers and trainees who develop, benchmark, or use protein force fields for molecular simulations. © 2023, CC BY.

关键词： Proteins

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A Mathematical Study to Gout Symptoms

A Mathematical Study to Gout Symptoms

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作者： Shuixian Yan Victor Moreno Sanling Yuan Baojun Song Business School University of Shanghai for Science and Technology Key Laboratory of Jiangxi Province for Numerical Simulation and Emulation Techniques Gannan Normal University Simon A.Levin Mathematical Computational and Modeling Sciences Center Arizona State University College of Science University of Shanghai for Science and Technology Department of Mathematical Sciences Montclair State University

Gout is a form of inflammatory arthritis characterized by sharp pain and severe swelling that often causes severe physical disability. Gout is caused by the chronic elevation of uric acid levels in the blood and is known as the disease of kings due to its strong association with a diet rich in fructose and beer. Recent studies suggest that a high uric acid concentration is the result of a dynamical process that highlights the interactions between leptin production, insulin resistance, low muscle mass and a diet rich in fructose. Once individuals develop hyperuricemia, reach a high uric acid concentration in excess of 7 mg/dL for men and 6 mg/dL for women, they become susceptible to developing gout. We propose a novel dynamic system to analyze and determine the connections between a diet involving different levels of fructose(in both adult men and women in the U.S.) and the concentration of uric acid in the blood. Our model simulations suggest that adult males under a diet containing levels of fructose stimulating a 0.5 uric acid growth rate, could develop hyperuricemia after around 10,000 days, while it only takes women about 5000 days with a diet stimulating a 0.4 growth rate.

关键词： Gout Uric Acid Leptin Insulin Mathematical Models

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Theoretical analysis and simulation of phase separation in a driven bidirectional two-lane system

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Physical Review E 2019年第3期100卷 032133-032133页

作者： Qing-Yi Hao Rui Jiang Mao-Bin Hu Yunxin Zhang Chao-Yun Wu Ning Guo Key Laboratory of Modeling Simulation and Control of Complex Ecosystem in Dabie Mountains of Anhui Higher Education Institutes School of Mathematics and Computational Science Anqing Normal University Anqing 246133 China School of Mathematical Sciences Fudan University Shanghai 200433 China MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing 100044 China School of Engineering Science University of Science and Technology of China Hefei 230026 China School of Automotive and Transportation Engineering Hefei University of Technology Hefei 230009 China

The two-lane driven system is a type of important model to research some transport systems, and also a powerful tool to investigate properties of nonequilibrium state systems. This paper presents a driven bidirectional two-lane model. The dynamic characteristics of the model with periodic boundary are investigated by Monte Carlo simulation, simple mean field, and cluster mean field methods, respectively. By simulations, phase separations are observed in the system with some values of model parameters. When the phase separation does not occur, cluster mean field results are in good agreement with simulation results. According to the cluster mean field analysis and simulations, a conjecture about the condition that the phase separation happens is proposed. Based on the conjecture, the phase boundary distinguishing phase separation state and homogeneous state is determined, and a corresponding phase diagram is drawn. The conjecture is validated through observing directly the spatiotemporal diagram and investigating the coarsening process of the system by simulation, and a possible mechanism causing the phase separation is also discussed. These outcomes maybe contribute to understand deeply transport systems including the congestion and efficiency of the transport, and enrich explorations of nonequilibrium state systems.

关键词： Dynamical phase transitions Phase diagrams Phase separation Phase transitions Transport phenomena

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A general-purpose hierarchical mesh partitioning method with node balancing strategies for large-scale numerical simulations

arXiv

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arXiv 2018年

作者： Kong, Fande Stogner, Roy H. Gaston, Derek R. Peterson, John W. Permann, Cody J. Slaughter, Andrew E. Martineau, Richard C. Department of Modeling and Simulation Idaho National Laboratory Idaho FallsID United States Institute for Computational and Engineering Sciences University of Texas AustinTX United States

Large-scale parallel numerical simulations are essential for a wide range of engineering problems that involve complex, coupled physical processes interacting across a broad range of spatial and temporal scales. The data structures involved in such simulations (meshes, sparse matrices, etc.) are frequently represented as graphs, and these graphs must be optimally partitioned across the available computational resources in order for the underlying calculations to scale efficiently. Partitions which minimize the number of graph edges that are cut (edge-cuts) while simultaneously maintaining a balance in the amount of work (i.e. graph nodes) assigned to each processor core are desirable, and the performance of most existing partitioning software begins to degrade in this metric for partitions with more than than O(103) processor cores. In this work, we consider a general-purpose hierarchical partitioner which takes into account the existence of multiple processor cores and shared memory in a compute node while partitioning a graph into an arbitrary number of subgraphs. We demonstrate that our algorithms significantly improve the preconditioning efficiency and overall performance of realistic numerical simulations running on up to 32,768 processor cores with nearly 109 unknowns. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical models

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Iterative unbiasing of quasi-equilibrium sampling

arXiv

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arXiv 2019年

作者： Giberti, F. Cheng, B. Tribello, G.A. Ceriotti, M. Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Trinity College University of Cambridge CambridgeCB2 1TQ United Kingdom Atomistic Simulation Centre School of Mathematics and Physics Queen's University Belfast BelfastBT14 7EN United Kingdom

Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an appropriately-chosen set of collective variables can significantly accelerate the exploration of phase space, albeit at the price of distorting the distribution of microstates. Efficient re-weighting to recover the unbiased distribution can be nontrivial when employing adaptive sampling techniques such as Metadynamics, Variationally Enhanced Sampling or Parallel Bias Metadynamics, in which the system evolves in a quasi-equilibrium manner under a time-dependent bias. We introduce an iterative unbiasing scheme that makes efficient use of all the trajectory data, and that does not require the distribution to be evaluated on a grid. The method can thus be used even when the bias has a high dimensionality. We benchmark this approach against some of the existing schemes, on models systems with different complexities and dimensionalities. Copyright © 2019, The Authors. All rights reserved.

关键词： Phase space methods

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A diffuse-interface model for smoothed particle hydrodynamics

arXiv

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arXiv 2018年

作者： Xu, Zhijie Meakin, Paul Tartakovsky, Alexandre Idaho National Laboratory Center for Advanced Modeling and Simulation Physics of Geological Processes University of Oslo Multiphase Flow Assurance Innovation Center Institute for Energy Technology Kjeller Computational Mathematics Technical Group Computational & Information Sciences Directorate Pacific Northwest National Laboratory

Diffuse-interface theory provides a foundation for the modeling and simulation of microstructure evolution in a very wide range of materials, and for the tracking/capturing of dynamic interfaces between different materials on larger scales. Smoothed particle hydrodynamics (SPH) is also widely used to simulate fluids and solids that are subjected to large deformations and have complex dynamic boundaries and/or interfaces, but no explicit interface tracking/capturing is required, even when topological changes such as fragmentation and coalescence occur, because of its Lagrangian particle nature. Here we developed an SPH model for single-component two-phase fluids that is based on diffuse-interface theory. In the model, the interface has a finite thickness and a surface tension that depend on the coefficient, k, of the gradient contribution to the Helmholtz free energy functional and the density dependent homogeneous free energy. In this model, there is no need to locate the surface (or interface) or to compute the curvature at and near the interface. One- and two-dimensional SPH simulations were used to validate the model. Copyright © 2018, The Authors. All rights reserved.

关键词： Hydrodynamics

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Screw dislocation structure and mobility in body centered cubic Fe predicted by a Gaussian Approximation Potential

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npj computational Materials 2018年第1期4卷 90-96页

作者： Francesco Maresca Daniele Dragoni Gábor Csányi Nicola Marzari William A.Curtin Laboratory for Multiscale Mechanics Modeling(LAMMM) Institute of Mechanical EngineeringÉcole Polytechnique Fédérale de LausanneLausanne CH-1015Switzerland Theory and Simulation of Materials(THEOS) and National Centre for Computational Design and Discovery of Novel Materials(NCCR MARVEL)École Polytechnique Fédérale de LausanneLausanne CH-1015Switzerland Dipartimento di Scienza dei Materiali Universitàdi Milano-BicoccaVia R.Cozzi 55Milan I-20125Italy Department of Engineering University of CambridgeTrumpington StreetCambridge CB21PZUK

The plastic flow behavior of bcc transition metals up to moderate temperatures is dominated by the thermally activated glide of screw dislocations,which in turn is determined by the atomic-scale screw dislocation core structure and the associated kink-pair nucleation mechanism for *** complex plasticity phenomena requires the simulation of many atoms and interacting dislocations and *** sizes are beyond the scope of first-principles methods and thus require empirical interatomic *** for the technological important case of bcc Fe,existing empirical interatomic potentials yield spurious ***,the structure and motion of the screw dislocations in Fe are studied using a new Gaussian Approximation Potential(GAP)for bcc Fe,which has been shown to reproduce the potential energy surface predicted by density-functional theory(DFT)and many associated *** Fe GAP predicts a compact,non-degenerate core structure,a single-hump Peierls potential,and glide on{110},consistent with DFT *** thermally activated motion at finite temperatures occurs by the expected kink-pair nucleation and propagation *** stress-dependent enthalpy barrier for screw motion,computed using the nudgedelastic-band method,follows closely a form predicted by standard theories with a zero-stress barrier of~1 eV,close to the experimental value of 0.84 eV,and a Peierls stress of~2 GPa consistent with DFT predictions of the Peierls potential.

关键词： structure dislocation cubic

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