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 currently under development with a focus on proteins and differentiable molecular simulation. There are a number of ways that the package could be improved:
Machine learning potentials (duration: 175h, expected difficulty: easy to medium): in the last few years machine learning potentials have been improved significantly. Models such as ANI, ACE, NequIP and Allegro can be added to Molly.
Alchemical simulation features (duration: 175h, expected difficulty: medium): binding free energy methods are now used routinely in drug discovery. Appropriate potentials and protocols could be added to Molly based on software like OpenFE.
Reactant compatibility (duration: 175h, expected difficulty: medium to hard): Reactant.jl allows improved performance and Enzyme support. Molly could be made compatible with Reactant to access these features.
Recommended skills: familiarity with computational chemistry, structural bioinformatics or simulating physical systems.
Expected results: new features added to the package along with tests and relevant documentation.
Mentor: Joe Greener
Contact: feel free to ask questions via email or #juliamolsim on the Julia Slack.