ESPResSo++ 2.0: Advanced methods for multiscale molecular simulation

[1]  J. Kirkwood.  Statistical Mechanics of Fluid Mixtures , 1935 .

[2]  R. Feynman,et al.  Quantum Mechanics and Path Integrals , 1965 .

[3]  P. Gennes.  Reptation of a Polymer Chain in the Presence of Fixed Obstacles , 1971 .

[4]  S. Edwards,et al.  Dynamics of concentrated polymer systems. Part 1.—Brownian motion in the equilibrium state , 1978 .

[5]  S. Edwards,et al.  The Theory of Polymer Dynamics , 1986 .

[6]  G. Grest,et al.  Dynamics of entangled linear polymer melts: A molecular‐dynamics simulation , 1990 .

[7]  Grady Booch,et al.  Object-Oriented Design with Applications , 1990 .

[8]  D. C. Rapaport,et al.  Multi-million particle molecular dynamics I. Design considerations for vector processing , 1991 .

[9]  R. Benzi,et al.  The lattice Boltzmann equation: theory and applications , 1992 .

[10]  Y. Qian,et al.  Lattice BGK Models for Navier-Stokes Equation , 1992 .

[11]  Mark E. Tuckerman,et al.  Reversible multiple time scale molecular dynamics , 1992 .

[12]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[13]  P. Ahlrichs,et al.  Simulation of a single polymer chain in solution by combining lattice Boltzmann and molecular dynamics , 1999, cond-mat/9905183.

[14]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[15]  D. d'Humières,et al.  Multiple–relaxation–time lattice Boltzmann models in three dimensions , 2002, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[16]  A. Louis.  Beware of density dependent pair potentials , 2002, cond-mat/0205110.

[17]  Salvatore Torquato,et al.  Statistical mechanical models with effective potentials: Definitions, applications, and thermodynamic consequences , 2002 .

[18]  K. Kremer,et al.  Multiscale simulation in polymer science , 2002 .

[19]  Steven J. Plimpton,et al.  Equilibration of long chain polymer melts in computer simulations , 2003, cond-mat/0306026.

[20]  E Weinan,et al.  Heterogeneous multiscale method: A general methodology for multiscale modeling , 2003 .

[21]  J. Boon.  The Lattice Boltzmann Equation for Fluid Dynamics and Beyond , 2003 .

[22]  Kurt Binder,et al.  Computational Soft Matter: from Synthetic Polymers to Proteins ; NIC Winter School, 29 February - 6 March 2004, Gustav-Stresemann-Institut, Bonn, Germany - Poster Abstracts , 2004 .

[23]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[24]  K. Kremer,et al.  Adaptive resolution molecular-dynamics simulation: changing the degrees of freedom on the fly. , 2005, The Journal of chemical physics.

[25]  David E. Shaw,et al.  A fast, scalable method for the parallel evaluation of distance‐limited pairwise particle interactions , 2005, J. Comput. Chem..

[26]  Björn Karlsson,et al.  Beyond the C++ Standard Library: An Introduction to Boost , 2005 .

[27]  Matej Praprotnik,et al.  Adaptive resolution scheme for efficient hybrid atomistic-mesoscale molecular dynamics simulations of dense liquids. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Ulf D. Schiller,et al.  Statistical mechanics of the fluctuating lattice Boltzmann equation. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  Matej Praprotnik,et al.  Adaptive resolution simulation of liquid water , 2007 .

[30]  Matej Praprotnik,et al.  Adaptive molecular resolution via a continuous change of the phase space dimensionality. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  Matej Praprotnik,et al.  FAST TRACK COMMUNICATION: Fractional dimensions of phase space variables: a tool for varying the degrees of freedom of a system in a multiscale treatment , 2007 .

[32]  Brian E. Granger,et al.  IPython: A System for Interactive Scientific Computing , 2007, Computing in Science & Engineering.

[33]  L.Delle Site,et al.  Some fundamental problems for an energy-conserving adaptive-resolution molecular dynamics scheme. , 2007, 0709.2579.

[34]  G. Voth.  Coarse-Graining of Condensed Phase and Biomolecular Systems , 2008 .

[35]  Matej Praprotnik,et al.  Multiscale simulation of soft matter: from scale bridging to adaptive resolution. , 2008, Annual review of physical chemistry.

[36]  Matej Praprotnik,et al.  Concurrent triple-scale simulation of molecular liquids. , 2008, The Journal of chemical physics.

[37]  Matej Praprotnik,et al.  Simulation approaches to soft matter: Generic statistical properties vs. chemical details , 2008, Comput. Phys. Commun..

[38]  Matej Praprotnik,et al.  Coupling atomistic and continuum hydrodynamics through a mesoscopic model: application to liquid water. , 2009, The Journal of chemical physics.

[39]  Kurt Kremer,et al.  Comparative atomistic and coarse-grained study of water: What do we lose by coarse-graining? , 2009, The European physical journal. E, Soft matter.

[40]  A. Ladd,et al.  Lattice Boltzmann Simulations of Soft Matter Systems , 2008, 0803.2826.

[41]  John L. Klepeis,et al.  Millisecond-scale molecular dynamics simulations on Anton , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[42]  Cecilia Clementi,et al.  Communication: On the locality of hydrogen bond networks at hydrophobic interfaces. , 2010, The Journal of chemical physics.

[43]  M. Tuckerman.  Statistical Mechanics: Theory and Molecular Simulation , 2010 .

[44]  K. Kremer,et al.  Fluctuating soft-sphere approach to coarse-graining of polymer models , 2010 .

[45]  Matej Praprotnik,et al.  Coupling different levels of resolution in molecular simulations. , 2009, The Journal of chemical physics.

[46]  Kurt Kremer,et al.  Multiscale simulation of soft matter systems. , 2010, Faraday discussions.

[47]  A. Alavi,et al.  Quantum nature of the proton in water-hydroxyl overlayers on metal surfaces. , 2010, Physical review letters.

[48]  Alejandro Pérez,et al.  Enol tautomers of Watson-Crick base pair models are metastable because of nuclear quantum effects. , 2010, Journal of the American Chemical Society.

[49]  L Delle Site,et al.  Classical to path-integral adaptive resolution in molecular simulation: towards a smooth quantum-classical coupling. , 2010, Physical review letters.

[50]  Cyrus K. Aidun,et al.  Lattice-Boltzmann Method for Complex Flows , 2010 .

[51]  Wes McKinney,et al.  Data Structures for Statistical Computing in Python , 2010, SciPy.

[52]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[53]  L Delle Site,et al.  Comment on "Adaptive multiscale molecular dynamics of macromolecular fluids". , 2011, Physical review letters.

[54]  Matej Praprotnik,et al.  Statistical Physics Problems in Adaptive Resolution Computer Simulations of Complex Fluids , 2011 .

[55]  L Delle Site,et al.  Adaptive resolution simulation of liquid para-hydrogen: testing the robustness of the quantum-classical adaptive coupling. , 2011, Physical chemistry chemical physics : PCCP.

[56]  Mischa Bonn,et al.  Nuclear quantum effects affect bond orientation of water at the water-vapor interface. , 2012, Physical review letters.

[57]  C P Herrero,et al.  Anomalous nuclear quantum effects in ice. , 2011, Physical review letters.

[58]  Kurt Kremer,et al.  Kirkwood-Buff Analysis of Liquid Mixtures in an Open Boundary Simulation. , 2012, Journal of chemical theory and computation.

[59]  Kurt Kremer,et al.  Structure Formation of Toluene around C60: Implementation of the Adaptive Resolution Scheme (AdResS) into GROMACS. , 2012, Journal of chemical theory and computation.

[60]  L Delle Site,et al.  Quantum locality and equilibrium properties in low-temperature parahydrogen: a multiscale simulation study. , 2012, The Journal of chemical physics.

[61]  Wilfred F van Gunsteren,et al.  Multi-resolution simulation of biomolecular systems: a review of methodological issues. , 2013, Angewandte Chemie.

[62]  Thomas Brandes,et al.  ESPResSo++: A modern multiscale simulation package for soft matter systems , 2013, Comput. Phys. Commun..

[63]  Carlo Pierleoni,et al.  Predicting the thermodynamics by using state-dependent interactions. , 2012, The Journal of chemical physics.

[64]  Kurt Kremer,et al.  Coil–Globule–Coil Transition of PNIPAm in Aqueous Methanol: Coupling All-Atom Simulations to Semi-Grand Canonical Coarse-Grained Reservoir , 2013 .

[65]  Pep Español,et al.  Hamiltonian adaptive resolution simulation for molecular liquids. , 2012, Physical review letters.

[66]  Pep Español,et al.  Monte carlo adaptive resolution simulation of multicomponent molecular liquids. , 2013, Physical review letters.

[67]  Matej Praprotnik,et al.  Adaptive resolution simulation of an atomistic protein in MARTINI water. , 2014, The Journal of chemical physics.

[68]  Pierre de Buyl,et al.  H5MD: A structured, efficient, and portable file format for molecular data , 2013, Comput. Phys. Commun..

[69]  Karsten Kreis,et al.  A unified framework for force-based and energy-based adaptive resolution simulations , 2014, EPL (Europhysics Letters).

[70]  Lu Wang,et al.  Quantum delocalization of protons in the hydrogen-bond network of an enzyme active site , 2014, Proceedings of the National Academy of Sciences.

[71]  Kurt Kremer,et al.  Equilibration of High Molecular Weight Polymer Melts: A Hierarchical Strategy. , 2014, ACS macro letters.

[72]  N. Aluru,et al.  Relative Entropy and Optimization-Driven Coarse-Graining Methods in VOTCA , 2015, PloS one.

[73]  Travis E. Oliphant,et al.  Guide to NumPy , 2015 .

[74]  P Español,et al.  Statistical mechanics of Hamiltonian adaptive resolution simulations. , 2014, The Journal of chemical physics.

[75]  Frank Noé,et al.  PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models. , 2015, Journal of chemical theory and computation.

[76]  K. Kremer,et al.  Direct Equilibration and Characterization of Polymer Melts for Computer Simulations , 2015 .

[77]  Michael Rubinstein,et al.  Opportunities in theoretical and computational polymeric materials and soft matter. , 2015, Soft matter.

[78]  Kurt Kremer,et al.  Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties. , 2015, The Journal of chemical physics.

[79]  K. Daoulas,et al.  Communication: One size fits all: Equilibrating chemically different polymer liquids through universal long-wavelength description. , 2015, The Journal of chemical physics.

[80]  Kipton Barros,et al.  Distributed Database Kriging for Adaptive Sampling (D2KAS) , 2015, Comput. Phys. Commun..

[81]  K. Kremer,et al.  Advantages and challenges in coupling an ideal gas to atomistic models in adaptive resolution simulations , 2014, 1412.6810.

[82]  E. Nies,et al.  A parallel algorithm for step- and chain-growth polymerization in molecular dynamics. , 2014, The Journal of chemical physics.

[83]  Matej Praprotnik,et al.  Adaptive resolution simulation of a DNA molecule in salt solution. , 2015, Journal of chemical theory and computation.

[84]  Karsten Kreis,et al.  The relative entropy is fundamental to adaptive resolution simulations. , 2016, The Journal of chemical physics.

[85]  G. Samaey,et al.  Generic Adaptive Resolution Method for Reverse Mapping of Polymers from Coarse-Grained to Atomistic Descriptions. , 2016, Journal of chemical theory and computation.

[86]  Karsten Kreis,et al.  Adaptive Resolution Simulations with Self-Adjusting High-Resolution Regions. , 2016, Journal of chemical theory and computation.

[87]  J H Peters,et al.  Simulation of macromolecular liquids with the adaptive resolution molecular dynamics technique. , 2016, Physical review. E.

[88]  K. Kremer,et al.  Adaptive resolution simulation of oligonucleotides. , 2016, The Journal of chemical physics.

[89]  Matej Praprotnik,et al.  Open boundary molecular dynamics of sheared star-polymer melts. , 2016, Soft matter.

[90]  Karsten Kreis,et al.  From Classical to Quantum and Back: A Hamiltonian Scheme for Adaptive Multiresolution Classical/Path-Integral Simulations. , 2016, Journal of chemical theory and computation.

[91]  Kurt Kremer,et al.  A multi‐resolution model to capture both global fluctuations of an enzyme and molecular recognition in the ligand‐binding site , 2016, Proteins.

[92]  Nikita Tretyakov,et al.  An improved dissipative coupling scheme for a system of Molecular Dynamics particles interacting with a Lattice Boltzmann fluid , 2016, Comput. Phys. Commun..

[93]  K. Kremer,et al.  Using force-based adaptive resolution simulations to calculate solvation free energies of amino acid sidechain analogues. , 2017, The Journal of chemical physics.

[94]  M. Tuckerman,et al.  From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics. , 2017, The Journal of chemical physics.

[95]  Horacio V. Guzman.  Scaling law to determine peak forces in tapping-mode AFM experiments on finite elastic soft matter systems , 2017, Beilstein journal of nanotechnology.

[96]  Matej Praprotnik,et al.  Molecular systems with open boundaries: Theory and simulation , 2017 .

[97]  Kurt Kremer,et al.  Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes. , 2017, Physical review. E.

[98]  Giovanni Samaey,et al.  Coarse‐grained molecular dynamics simulations of polymerization with forward and backward reactions , 2018, J. Comput. Chem..

[99]  Giovanni Samaey,et al.  Reverse mapping method for complex polymer systems , 2018, J. Comput. Chem..

[100]  M. Nadeau,et al.  Proteins : Structure , Function , and Bioinformatics , 2022 .