Git Product home page Git Product logo

molly.jl's Introduction

Molly logo

Build status Coverage status Latest release License Documentation stable Documentation dev

Much of science can be explained by the movement and interaction of molecules. Molecular dynamics (MD) is a computational technique used to explore these phenomena, from noble gases to biological macromolecules. Molly.jl is a pure Julia package for MD, and for the simulation of physical systems more broadly.

The package is described in a talk at Enzyme Conference 2023 and an earlier talk at the JuliaMolSim minisymposium at JuliaCon 2022. Slides are also available for a tutorial in September 2023.

Implemented features include:

  • Non-bonded interactions - Lennard-Jones Van der Waals/repulsion force, electrostatic Coulomb potential and reaction field, gravitational potential, soft sphere potential, Mie potential, Buckingham potential, soft core variants.
  • Bonded interactions - harmonic and Morse bonds, bond angles, torsion angles, harmonic position restraints, FENE bonds.
  • Interface to allow definition of new interactions, simulators, thermostats, neighbor finders, loggers etc.
  • Read in OpenMM force field files and coordinate files supported by Chemfiles.jl. There is also experimental support for Gromacs files.
  • Verlet, velocity Verlet, Störmer-Verlet, flexible Langevin and Nosé-Hoover integrators.
  • Andersen, Berendsen and velocity rescaling thermostats.
  • Monte Carlo barostat and variants.
  • Steepest descent energy minimization.
  • Replica exchange molecular dynamics.
  • Monte Carlo simulation.
  • Periodic, triclinic and infinite boundary conditions.
  • Constraints with SHAKE and RATTLE
  • Flexible loggers to track arbitrary properties throughout simulations.
  • Cutoff algorithms for non-bonded interactions.
  • Various neighbor list implementations to speed up the calculation of non-bonded forces, including the use of CellListMap.jl.
  • Implicit solvent GBSA methods.
  • Unitful.jl compatibility so numbers have physical meaning.
  • Set up crystal systems using SimpleCrystals.jl.
  • Automatic multithreading.
  • GPU acceleration on CUDA-enabled devices.
  • Run with Float64, Float32 or other float types.
  • Some analysis functions, e.g. RDF.
  • Visualise simulations as animations with Makie.jl.
  • Compatibility with AtomsBase.jl and AtomsCalculators.jl.
  • Differentiable molecular simulation. This is a unique feature of the package and the focus of its current development.

Features not yet implemented include:

  • High GPU performance.
  • Ewald or particle mesh Ewald summation.
  • Full support for constrained bonds and angles.
  • Protein preparation - solvent box, add hydrogens etc.
  • Simulators such as metadynamics.
  • Quantum mechanical modelling.
  • Domain decomposition algorithms.
  • Alchemical free energy calculations.
  • High test coverage.
  • API stability.

Installation

Julia is required, with Julia v1.7 or later required to get the latest version of Molly. It is recommended to run on the current stable Julia release for the best performance. Install Molly from the Julia REPL. Enter the package mode by pressing ] and run add Molly.

Usage

Some examples are given here, see the documentation for more on how to use the package.

Simulation of a Lennard-Jones fluid:

using Molly

n_atoms = 100
boundary = CubicBoundary(2.0u"nm")
temp = 298.0u"K"
atom_mass = 10.0u"g/mol"

atoms = [Atom(mass=atom_mass, σ=0.3u"nm", ϵ=0.2u"kJ * mol^-1") for i in 1:n_atoms]
coords = place_atoms(n_atoms, boundary; min_dist=0.3u"nm")
velocities = [random_velocity(atom_mass, temp) for i in 1:n_atoms]
pairwise_inters = (LennardJones(),)
simulator = VelocityVerlet(
    dt=0.002u"ps",
    coupling=AndersenThermostat(temp, 1.0u"ps"),
)

sys = System(
    atoms=atoms,
    coords=coords,
    boundary=boundary,
    velocities=velocities,
    pairwise_inters=pairwise_inters,
    loggers=(temp=TemperatureLogger(100),),
)

simulate!(sys, simulator, 10_000)

Simulation of a protein:

using Molly

sys = System(
    joinpath(dirname(pathof(Molly)), "..", "data", "5XER", "gmx_coords.gro"),
    joinpath(dirname(pathof(Molly)), "..", "data", "5XER", "gmx_top_ff.top");
    loggers=(
        temp=TemperatureLogger(10),
        writer=StructureWriter(10, "traj_5XER_1ps.pdb"),
    ),
)

temp = 298.0u"K"
random_velocities!(sys, temp)
simulator = VelocityVerlet(
    dt=0.0002u"ps",
    coupling=AndersenThermostat(temp, 1.0u"ps"),
)

simulate!(sys, simulator, 5_000)

The above 1 ps simulation looks something like this when you view it in VMD: MD simulation

Contributing

Contributions are very welcome including reporting bugs, fixing bugs, adding new features, improving performance, adding tests and improving documentation. Feel free to open an issue or use the channels below to discuss your contribution. New features will generally require tests to be added as well. See the roadmap issue for some discussion of recent progress and future plans.

Join the #juliamolsim channel on the Julia Slack, the #molly channel on the JuliaMolSim Zulip or post on the Julia Discourse to discuss the usage and development of Molly.jl.

Molly.jl follows the Contributor Covenant code of conduct.

Citation

If you use Molly, please cite the following paper (bib entry here):

  • Greener JG. Differentiable simulation to develop molecular dynamics force fields for disordered proteins, Chemical Science 15, 4897-4909 (2024)

A paper involving more contributors with further details on the software will be written at some point.

Interested?

There is the possibility of a postdoc position involving the development and use of Molly. Contact Joe Greener with informal enquiries.

molly.jl's People

Contributors

jgreener64 avatar ejmeitz avatar jaydevsr avatar noeblassel avatar sebastianm-c avatar chemicalfiend avatar lmiq avatar bondrewd avatar exaclior avatar leios avatar github-actions[bot] avatar axsk avatar maxscheurer avatar longemen3000 avatar goggle avatar ehsanirani avatar ellipse0934 avatar hsugawa8651 avatar jrdegreeff avatar ehgus avatar ruibin-liu avatar tjjarvinen avatar ederag avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.