Testing for Physical Validity in Molecular Simulations

10.26434/chemrxiv.6005279 ◽

2018 ◽

Author(s):

Pascal T. Merz ◽

Michael R. Shirts

Keyword(s):

Molecular Dynamics ◽

Open Source ◽

Lipid Bilayers ◽

Software Package ◽

Degrees Of Freedom ◽

Molecular Simulations ◽

Polymeric Materials ◽

Md Simulations ◽

Time Step ◽

Software Packages

Advances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations powerful tools in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. However, the quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions. Unphysical behavior of simulations can have significant influence on the results and reproducibility of these simulations, such as folding of proteins and DNA or properties of lipid bilayers determined by cutoff treatment, dynamics of peptides and polymers affected by the choice of thermostat, or liquid properties depending on the simulation time step. Motivated by such examples, we propose a two-fold approach to increase the robustness of molecular simulations. The first part of this approach involves tests which can be performed by the users of MD programs on their respective systems and setups. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviations from the Boltzmann ensemble, and lack of ergodicity between degrees of freedom. To make the usage as easy as possible, we have developed an open-source and platform-independent Python library (https://physical-validation.readthedocs.io) implementing these tests. The second part of the approach involves testing for code correctness. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. We have implemented such a validation for the GROMACS software package, ensuring that every major releases passes a number of physical sanity checks performed on selected representative systems before shipping. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. The tests are, as the rest of the package, open source software, and can be adapted for other software packages.

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Testing for Physical Validity in Molecular Simulations

10.26434/chemrxiv.6005279.v1 ◽

2018 ◽

Author(s):

Pascal T. Merz ◽

Michael R. Shirts

Keyword(s):

Molecular Dynamics ◽

Open Source ◽

Lipid Bilayers ◽

Software Package ◽

Degrees Of Freedom ◽

Molecular Simulations ◽

Polymeric Materials ◽

Md Simulations ◽

Time Step ◽

Software Packages

Advances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations powerful tools in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. However, the quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions. Unphysical behavior of simulations can have significant influence on the results and reproducibility of these simulations, such as folding of proteins and DNA or properties of lipid bilayers determined by cutoff treatment, dynamics of peptides and polymers affected by the choice of thermostat, or liquid properties depending on the simulation time step. Motivated by such examples, we propose a two-fold approach to increase the robustness of molecular simulations. The first part of this approach involves tests which can be performed by the users of MD programs on their respective systems and setups. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviations from the Boltzmann ensemble, and lack of ergodicity between degrees of freedom. To make the usage as easy as possible, we have developed an open-source and platform-independent Python library (https://physical-validation.readthedocs.io) implementing these tests. The second part of the approach involves testing for code correctness. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. We have implemented such a validation for the GROMACS software package, ensuring that every major releases passes a number of physical sanity checks performed on selected representative systems before shipping. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. The tests are, as the rest of the package, open source software, and can be adapted for other software packages.

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Sharing Data from Molecular Simulations

10.26434/chemrxiv.9775493 ◽

2019 ◽

Author(s):

Mark J. Abraham ◽

Rossen Apostolov ◽

Jonathan Barnoud ◽

Paul Bauer ◽

Christian Blau ◽

...

Keyword(s):

Molecular Dynamics ◽

Best Practices ◽

Molecular Dynamics Simulations ◽

Software Package ◽

Molecular Simulations ◽

Md Simulations ◽

Scientific Output ◽

Level Of Detail ◽

Simulation Data ◽

Dynamics Simulations

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations have become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, and each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( <a href="https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/">https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/</a>). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way towards more open, interoperable and reproducible outputs coming from research studies using MD simulations.

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Sharing Data from Molecular Simulations

10.26434/chemrxiv.9775493.v1 ◽

2019 ◽

Author(s):

Mark J. Abraham ◽

Rossen Apostolov ◽

Jonathan Barnoud ◽

Paul Bauer ◽

Christian Blau ◽

...

Keyword(s):

Molecular Dynamics ◽

Best Practices ◽

Molecular Dynamics Simulations ◽

Software Package ◽

Molecular Simulations ◽

Md Simulations ◽

Scientific Output ◽

Level Of Detail ◽

Simulation Data ◽

Dynamics Simulations

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations have become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, and each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( <a href="https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/">https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/</a>). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way towards more open, interoperable and reproducible outputs coming from research studies using MD simulations.

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Efficient Treatment of Fixed and Induced Dipolar Interactions

MRS Proceedings ◽

10.1557/proc-653-z7.22 ◽

2000 ◽

Vol 653 ◽

Author(s):

Celeste Sagui ◽

Thoma Darden

Keyword(s):

Molecular Dynamics ◽

Md Simulations ◽

Lagrangian Formalism ◽

Dipolar Interactions ◽

Time Step ◽

Efficient Treatment ◽

Particle Mesh Ewald ◽

Fixed Charges ◽

Self Consistency ◽

Induced Dipoles

AbstractFixed and induced point dipoles have been implemented in the Ewald and Particle-Mesh Ewald (PME) formalisms. During molecular dynamics (MD) the induced dipoles can be propagated along with the atomic positions either by interation to self-consistency at each time step, or by a Car-Parrinello (CP) technique using an extended Lagrangian formalism. The use of PME for electrostatics of fixed charges and induced dipoles together with a CP treatment of dipole propagation in MD simulations leads to a cost overhead of only 33% above that of MD simulations using standard PME with fixed charges, allowing the study of polarizability in largemacromolecular systems.

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Split the Charge Difference in Two! a Rule of Thumb for Adding Proper Amounts of Ions in MD Simulations

10.26434/chemrxiv.9783155.v2 ◽

2020 ◽

Author(s):

Matías R. Machado ◽

Sergio Pantano

Keyword(s):

Molecular Dynamics ◽

Ionic Strength ◽

Molecular Simulations ◽

Md Simulations ◽

Good Practices ◽

Rule Of Thumb ◽

Ionic Concentrations

Despite the relevance of properly setting ionic concentrations in Molecular Dynamics (MD) simulations, methods or practical rules to set ionic strength are scarce and rarely documented. Based on a recently proposed thermodynamics method we provide an accurate rule of thumb to define the electrolytic content in simulation boxes. Extending the use of good practices in setting up MD systems is promptly needed to ensure reproducibility and consistency in molecular simulations.

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Raf promotes dimerization of the Ras G-domain with increased allosteric connections

10.1101/2020.07.15.205070 ◽

2020 ◽

Author(s):

Morgan Packer ◽

Jillian A. Parker ◽

Jean K. Chung ◽

Zhenlu Li ◽

Young Kwang Lee ◽

...

Keyword(s):

Molecular Dynamics ◽

Lipid Bilayers ◽

Md Simulations ◽

Size Exclusion ◽

Supported Lipid Bilayers ◽

Erk Pathway ◽

Signaling Complex ◽

Macromolecular Assembly ◽

High Affinity ◽

Exclusion Chromatography

AbstractRas dimerization is critical for Raf activation, yet Ras alone does not dimerize. Here we show that the Ras binding domain of Raf (Raf-RBD) induces robust Ras dimerization at low surface densities on supported lipid bilayers and, to a lesser extent, in solution as observed by size exclusion chromatography and confirmed by SAXS. Community network analysis based on molecular dynamics (MD) simulations show robust allosteric connections linking the two Raf-RBD D113 residues, located in the Galectin scaffold protein binding site of each Raf-RBD molecule and 85 Å apart on opposite ends of the dimer complex. Our results suggest that Raf-RBD binding and Ras dimerization are concerted events that lead to a high-affinity signaling complex at the membrane that we propose is an essential unit in the macromolecular assembly of higher order Ras/Raf/Galectin complexes important for signaling through the Ras/Raf/MEK/ERK pathway.

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Structure and Dynamics of Glycosphingolipids in Lipid Bilayers: Insights from Molecular Dynamics Simulations

International Journal of Carbohydrate Chemistry ◽

10.1155/2011/950256 ◽

2011 ◽

Vol 2011 ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

Ronak Y. Patel ◽

Petety V. Balaji

Keyword(s):

Molecular Dynamics ◽

Lipid Bilayers ◽

Membrane Structure ◽

Lipid Membrane ◽

Biological Membranes ◽

Md Simulations ◽

Atomic Level ◽

Structure And Dynamics ◽

Hydrogen Bonding Interactions ◽

Dynamics Simulations

Glycolipids are important constituents of biological membranes, and understanding their structure and dynamics in lipid bilayers provides insights into their physiological and pathological roles. Experimental techniques have provided details into their behavior at model and biological membranes; however, computer simulations are needed to gain atomic level insights. This paper summarizes the insights obtained from MD simulations into the conformational and orientational dynamics of glycosphingolipids and their exposure, hydration, and hydrogen-bonding interactions in membrane environment. The organization of glycosphingolipids in raft-like membranes and their modulation of lipid membrane structure are also reviewed.

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Binding of Ca2+-Independent C2 Domains to Lipid Membranes: a Multi-Scale Molecular Dynamics Study

10.1101/2020.10.30.361964 ◽

2020 ◽

Author(s):

Andreas Haahr Larsen ◽

Mark S.P. Sansom

Keyword(s):

Molecular Dynamics ◽

Lipid Bilayers ◽

Md Simulations ◽

Multiscale Simulation ◽

Coarse Grained ◽

Type I ◽

Type Ii ◽

Binding Modes ◽

C2 Domains ◽

Anionic Lipids

AbstractC2 domains facilitate protein-lipid interaction in cellular recognition and signalling processes. They possess a β-sandwich structure, with either type I or type II topology. C2 domains can interact with anionic lipid bilayers in either a Ca2+-dependent or a Ca2+-independent manner. The mechanism of recognition of anionic lipids by Ca2+-independent C2 domains is incompletely understood. We have used molecular dynamics (MD) simulations to explore the membrane interactions of six Ca2+– independent C2 domains, from KIBRA, PI3KC2α, RIM2, PTEN, SHIP2, and Smurf2. In coarse grained MD simulations these C2 domains bound to lipid bilayers, forming transient interactions with zwitterionic (phosphatidylcholine, PC) bilayers compared to long lived interactions with anionic bilayers also containing either phosphatidylserine (PS) or PS and phosphatidylinositol bisphosphate (PIP2). Type I C2 domains bound non-canonically via the front, back or side of the β sandwich, whereas type II C2 domains bound canonically, via the top loops (as is typically the case for Ca2+-dependent C2 domains). C2 domains interacted strongly (up to 120 kJ/mol) with membranes containing PIP2 causing the bound anionic lipids to clustered around the protein. The C2 domains bound less strongly to anionic membranes without PIP2 (<50 kJ/mol), and most weakly to neutral membranes (<33 kJ/mol). Productive binding modes were identified and further analysed in atomistic simulations. For PTEN and SHIP2, CG simulations were also performed of the intact enzymes (i.e. phosphatase domain plus C2 domain) with PIP2-contating bilayers and the roles of the two domains in membrane localization were compared. From a methodological perspective, these studies establish a multiscale simulation protocol for studying membrane binding/recognition proteins, capable of revealing binding modes alongside details of lipid binding affinity and specificity.

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MasterMSM: A Package for Constructing Master Equation Models of Molecular Dynamics

10.26434/chemrxiv.8234147.v1 ◽

2019 ◽

Author(s):

David De Sancho ◽

Anne Aguirre

Keyword(s):

Molecular Dynamics ◽

Master Equation ◽

Md Simulations ◽

Distinctive Features ◽

Markov State Models ◽

Software Packages ◽

Long Time ◽

State Models ◽

Definition Of ◽

Kinetics Of

<div>Markov state models (MSMs) have become one of the most important techniques for understanding biomolecular transitions from classical molecular dynamics (MD) simulations. MSMs provide a systematized way of accessing the long time kinetics of the system of interest from the short-timescale microscopic transitions observed in simulation trajectories. At the same time, they provide a consistent description of the equilibrium and dynamical properties of the system of interest, and they are ideally suited for comparisons against experiment. A few software packages exist for building MSMs, which have been widely adopted. Here we introduce MasterMSM, a new Python package that uses the master equation formulation of MSMs and provides a number of new algorithms for building and analyzing these models. We demonstrate some of the most distinctive features of the package, including the estimation of rates, definition of core-sets for transition based assignment of states, the estimation of committors and fluxes, and the sensitivity analysis of the emerging networks. The package is available at https://github.com/daviddesancho/MasterMSM.</div>

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