David van der Spoel
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View article: Bayesian three-point water models
Bayesian three-point water models Open
We introduce a Bayesian framework leveraging synthetic likelihoods to enable uncertainty quantification and robust inference of non-bonded force parameters in three-point water models. The approach integrates multiple experimental observab…
View article: Accurate Electrostatics for Biomolecular Systems through Machine Learning
Accurate Electrostatics for Biomolecular Systems through Machine Learning Open
Accurate models for electrostatic interactions are fundamental for force field calculations in drug and material design. Given good mod- els of the entire charge distributions, e.g. from the quantum-chemical electron density, the electrost…
View article: Evolutionary Machine Learning of Physics-Based Force Fields in High-Dimensional Parameter-Space
Evolutionary Machine Learning of Physics-Based Force Fields in High-Dimensional Parameter-Space Open
This work presents the Alexandria Chemistry Toolkit (ACT), an open-source software for machine learning of physics-based force fields (FFs) from scratch, based on user-specified potential functions. In this approach, a set of FF parameters…
View article: Point + Gaussian charge model for electrostatic interactions derived by machine learning
Point + Gaussian charge model for electrostatic interactions derived by machine learning Open
At short distances between atoms, point charges are a poor approximation of the electrostatic interaction. The combination of a point charge and a Gaussian distributed charge yields a much more accurate model.
View article: Quantitative evaluation of anharmonic bond potentials for molecular simulations
Quantitative evaluation of anharmonic bond potentials for molecular simulations Open
Most general force fields only implement a harmonic potential to model covalent bonds. Here we evaluate 28 different potentials on 76 diatomics to find more realistic ones.
View article: Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space Open
This work presents the Alexandria Chemistry Toolkit (ACT), an open-source software for machine learning of physics-based force fields (FFs) from scratch, based on user-specified potential functions.
View article: Assessment of Climate Impact of Sustainable Forestry Based on Landscape Structure
Assessment of Climate Impact of Sustainable Forestry Based on Landscape Structure Open
This article presents an evaluation of the environmental impact of forestry based on landscape theory. It has been argued that this type of forestry offers a positive impact on the climate because there is a balance between the amount of g…
View article: Carbon-Neutral Forestry Contributes to Global Warming due to Carbon Debt
Carbon-Neutral Forestry Contributes to Global Warming due to Carbon Debt Open
This article presents an evaluation of the environmental impact of forestry based on landscape theory. It has been argued that this type of forestry offers a positive impact on the climate because there is a balance between the amount of g…
View article: Quantification of Anisotropy in Exchange and Dispersion Interactions: A Simple Model for Physics-Based Force Fields
Quantification of Anisotropy in Exchange and Dispersion Interactions: A Simple Model for Physics-Based Force Fields Open
In some compounds, exchange repulsion is orientation dependent. However, in contrast to quantum chemical methods that treat exchange explicitly, empirical models assume exchange to be spherically symmetric, yielding an average description …
View article: Impact of Combination Rules, Level of Theory, and Potential Function on the Modeling of Gas- and Condensed-Phase Properties of Noble Gases
Impact of Combination Rules, Level of Theory, and Potential Function on the Modeling of Gas- and Condensed-Phase Properties of Noble Gases Open
The systems of noble gases are particularly instructive for molecular modeling due to the elemental nature of their interactions. They do not normally form bonds nor possess a (permanent) dipole moment, and the only forces determining thei…
View article: Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals?
Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals? Open
Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scal…
View article: Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals?
Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals? Open
Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery, chemical reaction design, materials science, and structural biology. Coarse-grained models offer a simplified representation of mole…
View article: Can molecular dynamics be used to simulate biomolecular recognition?
Can molecular dynamics be used to simulate biomolecular recognition? Open
There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challeng…
View article: Simulations of Amyloid-Forming Peptides in the Crystal State
Simulations of Amyloid-Forming Peptides in the Crystal State Open
There still is little treatment available for amyloid diseases, despite their significant impact on individuals and the social and economic implications for society. One reason for this is that the physical nature of amyloid formation is n…
View article: Can molecular dynamics be used to simulate biomolecular recognition?
Can molecular dynamics be used to simulate biomolecular recognition? Open
There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challeng…
View article: An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation Open
Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets…
View article: Probing Phase Transitions in Organic Crystals Using Atomistic MD Simulations
Probing Phase Transitions in Organic Crystals Using Atomistic MD Simulations Open
A profound understanding of the physicochemical properties of organic crystals is crucial for topics from material science to drug discovery. Using molecular dynamics (MD) simulations with a sufficiently accurate force field, microscopic i…
View article: An Imbalance in the Force: The Need for Standardised Benchmarks for Molecular Simulation
An Imbalance in the Force: The Need for Standardised Benchmarks for Molecular Simulation Open
Force fields (FF) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized datasets a…
View article: Binding Networks Identify Targetable Protein Pockets for Mechanism-Based Drug Design
Binding Networks Identify Targetable Protein Pockets for Mechanism-Based Drug Design Open
The human genome codes only a few thousand druggable proteins, mainly receptors and enzymes. While this pool of available drug targets is limited, there is an untapped potential for discovering new drug-binding mechanisms and modes. For ex…
View article: Binding networks identify targetable protein pockets for mechanism-based drug design
Binding networks identify targetable protein pockets for mechanism-based drug design Open
This repository contains supporting files for the manuscript entitled: Binding networks identify targetable protein pockets for mechanism-based drug design.
View article: Binding networks identify targetable protein pockets for mechanism-based drug design
Binding networks identify targetable protein pockets for mechanism-based drug design Open
This repository contains supporting files for the manuscript entitled: Binding networks identify targetable protein pockets for mechanism-based drug design.
View article: Quantitative predictions from molecular simulations using explicit or implicit interactions
Quantitative predictions from molecular simulations using explicit or implicit interactions Open
Equilibrium simulations of molecular systems allow to extract many physicochemical properties. Given an “accurate enough” model, a “large enough” simulation system and “long enough” simulations, such calculations should yield accurate pred…
View article: Accurate absolute free energies for ligand–protein binding based on non-equilibrium approaches
Accurate absolute free energies for ligand–protein binding based on non-equilibrium approaches Open
View article: clinfo/gromacs: Hypersound–accelerated molecular dynamics simulation
clinfo/gromacs: Hypersound–accelerated molecular dynamics simulation Open
Public/backup repository of the GROMACS molecular simulation toolkit. Please do not mine the metadata blindly; we use https://gitlab.com/gromacs/gromacs for code review and issue tracking.
View article: NMR refinement and peptide folding using the GROMACS software
NMR refinement and peptide folding using the GROMACS software Open
Nuclear magnetic resonance spectroscopy is used routinely for studying the three-dimensional structures and dynamics of proteins and nucleic acids. Structure determination is usually done by adding restraints based upon NMR data to a class…
View article: Comment on acp-2020-1329
Comment on acp-2020-1329 Open
Size-dependent solubility is prevalent in atmospheric nanoparticles, but a molecular level understanding is still insufficient, especially for organic compounds. Here, we performed molecular dynamics simulations to investigate the size dep…
View article: Energetic analysis of succinic acid in water droplets: insight into the size-dependent solubility of atmospheric nanoparticles
Energetic analysis of succinic acid in water droplets: insight into the size-dependent solubility of atmospheric nanoparticles Open
<p>Size-dependent solubility is prevalent in atmospheric nanoparticles, but a molecular level understanding is still insufficient, especially for organic compounds. Here, we performed molecular dynamics simulations to investigate the…
View article: Energetic analysis of succinic acid in water droplets: insight into thesize-dependent solubility of atmospheric nanoparticles
Energetic analysis of succinic acid in water droplets: insight into thesize-dependent solubility of atmospheric nanoparticles Open
Size-dependent solubility is prevalent in atmospheric nanoparticles, but a molecular level understanding is still insufficient, especially for organic compounds. Here, we performed molecular dynamics simulations to investigate the size dep…
View article: Supplementary material to &quot;Energetic analysis of succinic acid in water droplets: insight into thesize-dependent solubility of atmospheric nanoparticles&quot;
Supplementary material to "Energetic analysis of succinic acid in water droplets: insight into thesize-dependent solubility of atmospheric nanoparticles" Open
View article: NMR Refinement and Peptide Folding Using the GROMACS Software
NMR Refinement and Peptide Folding Using the GROMACS Software Open
Nuclear magnetic resonance spectroscopy is used routinely for studying the three-dimensional structures and dynamics of proteins. Structure determination is usually done by adding restraints based upon NMR data to a classical energy functi…