AmberTools
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Kurt A. O'Hearn | Maria C. Nagan | D. York | H. Aktulga | C. Simmerling | Tai-Sung Lee | K. Merz | Koushik Kasavajhala | T. Luchko | A. Rahnamoun | Negin Forouzesh | V. Cruzeiro | Stephan N. Schott-Verdugo | M. Manathunga | Haixin Wei | T. Giese | Holger Gohlke | T. Kurtzman | Pengfei Li | Ali Risheh | Qiang Zhu | F. Pan | Kellon Belfon | Akhil Shajan | David A Case | Davide Cerutti | G. A. Cisneros | Andreas W Götz | Saeed Izadi | M. C. Kaymak | Edward King | Jian Liu | Ray Luo | Matias R Machado | H. Nguyen | Alexey V Onufriev | S. Pantano | Ruxi Qi | Jason M. Swails | Junmei Wang | Xiong Wu | Yongxian Wu | Shigong Zhang | Shiji Zhao | Thomas E Cheatham | Dan Roe | Adrian Roitberg
[1] R. Luo,et al. Streamlining and Optimizing Strategies of Electrostatic Parameterization. , 2023, Journal of chemical theory and computation.
[2] Y. Duan,et al. Optimal Scheme to Achieve Energy Conservation in Induced Dipole Models. , 2023, Journal of chemical theory and computation.
[3] S. Pantano,et al. The SIRAH force field: a suite for simulations of complex biological systems at the coarse-grained and multiscale levels. , 2023, Journal of structural biology.
[4] Russell B. Davidson,et al. tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking , 2023, J. Chem. Inf. Model..
[5] H. Aktulga,et al. Quantum Mechanics/Molecular Mechanics Simulations on NVIDIA and AMD Graphics Processing Units , 2023, J. Chem. Inf. Model..
[6] Y. Duan,et al. Transferability of the Electrostatic Parameters of the Polarizable Gaussian Multipole Model. , 2023, Journal of chemical theory and computation.
[7] D. York,et al. ACES: Optimized Alchemically Enhanced Sampling. , 2023, Journal of chemical theory and computation.
[8] Timothy J. Giese,et al. AMBER Free Energy Tools: A New Framework for the Design of Optimized Alchemical Transformation Pathways. , 2023, Journal of chemical theory and computation.
[9] Timothy J. Giese,et al. AMBER Drug Discovery Boost Tools: Automated Workflow for Production Free-Energy Simulation Setup and Analysis (ProFESSA) , 2022, J. Chem. Inf. Model..
[10] Timothy J. Giese,et al. Multireference Generalization of the Weighted Thermodynamic Perturbation Method. , 2022, The journal of physical chemistry. A.
[11] Y. Duan,et al. Accurate Reproduction of Quantum Mechanical Many-Body Interactions in Peptide Main-Chain Hydrogen-Bonding Oligomers by the Polarizable Gaussian Multipole Model. , 2022, Journal of chemical theory and computation.
[12] R. Krasny,et al. Accelerating the 3D reference interaction site model theory of molecular solvation with treecode summation and cut‐offs , 2022, J. Comput. Chem..
[13] Y. Duan,et al. PyRESP: A Program for Electrostatic Parameterizations of Additive and Induced Dipole Polarizable Force Fields. , 2022, Journal of chemical theory and computation.
[14] Y. Duan,et al. Stress tensor and constant pressure simulation for polarizable Gaussian multipole model. , 2022, The Journal of chemical physics.
[15] Callum J. Dickson,et al. Lipid21: Complex Lipid Membrane Simulations with AMBER , 2022, Journal of chemical theory and computation.
[16] D. Case,et al. Integral equation models for solvent in macromolecular crystals , 2021, The Journal of chemical physics.
[17] R. Luo,et al. Machine-Learned Molecular Surface and Its Application to Implicit Solvent Simulations. , 2021, Journal of chemical theory and computation.
[18] D. York,et al. Extension of the Variational Free Energy Profile and Multistate Bennett Acceptance Ratio Methods for High-Dimensional Potential of Mean Force Profile Analysis. , 2021, The journal of physical chemistry. A.
[19] R. Luo,et al. Estimating the Roles of Protonation and Electronic Polarization in Absolute Binding Affinity Simulations. , 2021, Journal of chemical theory and computation.
[20] Andreas W. Götz,et al. Open-Source Multi-GPU-Accelerated QM/MM Simulations with AMBER and QUICK , 2021, J. Chem. Inf. Model..
[21] H. Aktulga,et al. Harnessing the Power of Multi-GPU Acceleration into the Quantum Interaction Computational Kernel Program. , 2021, Journal of chemical theory and computation.
[22] D. York,et al. Variational Method for Networkwide Analysis of Relative Ligand Binding Free Energies with Loop Closure and Experimental Constraints. , 2021, Journal of chemical theory and computation.
[23] Richard North,et al. Andreas , 2020, The Longman Anthology of Old English, Old Icelandic and Anglo-Norman Literatures.
[24] Lin Frank Song,et al. Evolution of Alchemical Free Energy Methods in Drug Discovery , 2020, J. Chem. Inf. Model..
[25] Y. Duan,et al. Efficient formulation of polarizable Gaussian multipole electrostatics for biomolecular simulations. , 2020, The Journal of chemical physics.
[26] L. Watson,et al. Multidimensional Global Optimization and Robustness Analysis in the Context of Protein-Ligand Binding. , 2020, Journal of chemical theory and computation.
[27] Per Larsson,et al. MkVsites: A tool for creating GROMACS virtual sites parameters to increase performance in all‐atom molecular dynamics simulations , 2020, J. Comput. Chem..
[28] K. Merz,et al. Parallel Implementation of Density Functional Theory Methods in the Quantum Interaction Computational Kernel Program. , 2020, Journal of chemical theory and computation.
[29] Timothy J. Giese,et al. Confluence of Theory and Experiment Reveal the Catalytic Mechanism of the Varkud Satellite Ribozyme , 2019, Nature Chemistry.
[30] Timothy J. Giese,et al. Development of a Robust Indirect Approach for MM→QM Free Energy Calculations that Combines Force-matched Reference Potential and Bennett's Acceptance Ratio Methods. , 2019, Journal of chemical theory and computation.
[31] Junmei Wang,et al. End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design. , 2019, Chemical reviews.
[32] He Huang,et al. ff19SB: Amino-acid specific protein backbone parameters trained against quantum mechanics energy surfaces in solution. , 2019, Journal of chemical theory and computation.
[33] Holger Gohlke,et al. PACKMOL-Memgen: A Simple-To-Use, Generalized Workflow for Membrane-Protein-Lipid-Bilayer System Building , 2019, J. Chem. Inf. Model..
[34] Timothy J. Giese,et al. Cleaning Up Mechanistic Debris Generated by Twister Ribozymes Using Computational RNA Enzymology. , 2019, ACS catalysis.
[35] Ray Luo,et al. An efficient second‐order poisson–boltzmann method , 2019, J. Comput. Chem..
[36] Y. Duan,et al. Development of Polarizable Gaussian Model for Molecular Mechanical Calculations I: Atomic Polarizability Parameterization To Reproduce ab Initio Anisotropy. , 2019, Journal of chemical theory and computation.
[37] Ray Luo,et al. Robustness and Efficiency of Poisson-Boltzmann Modeling on Graphics Processing Units. , 2018, Journal of chemical information and modeling.
[38] Ye Mei,et al. Accelerated Computation of Free Energy Profile at ab Initio Quantum Mechanical/Molecular Mechanics Accuracy via a Semi-Empirical Reference Potential. I. Weighted Thermodynamics Perturbation. , 2018, Journal of chemical theory and computation.
[39] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[40] A. Onufriev,et al. Grid-Based Surface Generalized Born Model for Calculation of Electrostatic Binding Free Energies , 2017, J. Chem. Inf. Model..
[41] B. Brooks,et al. Efficient Strategy for the Calculation of Solvation Free Energies in Water and Chloroform at the Quantum Mechanical/Molecular Mechanical Level , 2017, J. Chem. Inf. Model..
[42] Ray Luo,et al. Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units. , 2017, Journal of chemical theory and computation.
[43] Timothy J. Giese,et al. Ambient-Potential Composite Ewald Method for ab Initio Quantum Mechanical/Molecular Mechanical Molecular Dynamics Simulation. , 2016, Journal of chemical theory and computation.
[44] C. Bannwarth,et al. Dispersion-Corrected Mean-Field Electronic Structure Methods. , 2016, Chemical reviews.
[45] C. Simmerling,et al. ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. , 2015, Journal of chemical theory and computation.
[46] R. Walker,et al. An extensible interface for QM/MM molecular dynamics simulations with AMBER , 2014, J. Comput. Chem..
[47] Tai-Sung Lee,et al. Roadmaps through free energy landscapes calculated using the multi-dimensional vFEP approach. , 2014, Journal of chemical theory and computation.
[48] D. Case,et al. Twenty-five years of nucleic acid simulations. , 2013, Biopolymers.
[49] Holger Gohlke,et al. FEW: A workflow tool for free energy calculations of ligand binding , 2013, J. Comput. Chem..
[50] Ross C. Walker,et al. An overview of the Amber biomolecular simulation package , 2013 .
[51] Tai-Sung Lee,et al. A New Maximum Likelihood Approach for Free Energy Profile Construction from Molecular Simulations. , 2013, Journal of chemical theory and computation.
[52] Holger Gohlke,et al. MMPBSA.py: An Efficient Program for End-State Free Energy Calculations. , 2012, Journal of chemical theory and computation.
[53] R. Luo,et al. Reducing grid-dependence in finite-difference Poisson-Boltzmann calculations. , 2012, Journal of chemical theory and computation.
[54] Mehmet Gonullu,et al. Department of Computer Science and Engineering , 2011 .
[55] Ray Luo,et al. Assessment of linear finite‐difference Poisson–Boltzmann solvers , 2010, J. Comput. Chem..
[56] Carlos Simmerling,et al. Three-dimensional molecular theory of solvation coupled with molecular dynamics in Amber. , 2010, Journal of chemical theory and computation.
[57] Ray Luo,et al. Performance of Nonlinear Finite-Difference Poisson-Boltzmann Solvers. , 2010, Journal of chemical theory and computation.
[58] Austin B. Yongye,et al. Extension of the GLYCAM06 biomolecular force field to lipids, lipid bilayers and glycolipids , 2008, Molecular simulation.
[59] Karl Nicholas Kirschner,et al. GLYCAM06: A generalizable biomolecular force field. Carbohydrates , 2008, J. Comput. Chem..
[60] Michael R. Shirts,et al. Statistically optimal analysis of samples from multiple equilibrium states. , 2008, The Journal of chemical physics.
[61] V. Hornak,et al. Comparison of multiple Amber force fields and development of improved protein backbone parameters , 2006, Proteins.
[62] Holger Gohlke,et al. The Amber biomolecular simulation programs , 2005, J. Comput. Chem..
[63] Fumio Hirata,et al. A molecular theory of liquid interfaces. , 2005, Physical chemistry chemical physics : PCCP.
[64] Junmei Wang,et al. Development and testing of a general amber force field , 2004, J. Comput. Chem..
[65] D. Case,et al. Exploring protein native states and large‐scale conformational changes with a modified generalized born model , 2004, Proteins.
[66] Ray Luo,et al. Accelerated Poisson–Boltzmann calculations for static and dynamic systems , 2002, J. Comput. Chem..
[67] D. Case,et al. Modification of the Generalized Born Model Suitable for Macromolecules , 2000 .
[68] Ghazi Rabihavi. David , 1997 .
[69] Gregory D. Hawkins,et al. Parametrized Models of Aqueous Free Energies of Solvation Based on Pairwise Descreening of Solute Atomic Charges from a Dielectric Medium , 1996 .
[70] P. Kollman,et al. A second generation force field for the simulation of proteins , 1995 .
[71] Peter A. Kollman,et al. FREE ENERGY CALCULATIONS : APPLICATIONS TO CHEMICAL AND BIOCHEMICAL PHENOMENA , 1993 .
[72] P. Kollman,et al. A well-behaved electrostatic potential-based method using charge restraints for deriving atomic char , 1993 .
[73] P. Kollman,et al. An all atom force field for simulations of proteins and nucleic acids , 1986, Journal of computational chemistry.
[74] U. Singh,et al. A NEW FORCE FIELD FOR MOLECULAR MECHANICAL SIMULATION OF NUCLEIC ACIDS AND PROTEINS , 1984 .
[75] C. Smith,et al. Adrian. , 1983, British medical journal.
[76] Peter A. Kollman,et al. AMBER: Assisted model building with energy refinement. A general program for modeling molecules and their interactions , 1981 .
[77] Charles H. Bennett,et al. Efficient estimation of free energy differences from Monte Carlo data , 1976 .
[78] R. Zwanzig. High‐Temperature Equation of State by a Perturbation Method. I. Nonpolar Gases , 1954 .
[79] J. Kirkwood. Statistical Mechanics of Fluid Mixtures , 1935 .
[80] J Andrew McCammon,et al. Generalized Born model with a simple, robust molecular volume correction. , 2007, Journal of chemical theory and computation.
[81] Machine-Learned Molecular Surface and Its Application to Implicit Solvent Simulations , 2022 .