The Molecular Simulation Design Framework (MoSDeF)
1 was developed as a suite of tools to mitigate challenges associated with initializing and conducting molecular simulations, with a focus on facilitating reproducibility.
2 By providing standardized, open-source libraries, MoSDeF can automate steps in the preparation of chemical/biological systems for simulation, thereby minimizing unnecessary human involvement and associated errors. Furthermore, the automation of workflows enables easier setup of high-throughput screening processes, through integration with workflow management tools such as signac and signac-flow.
3 To further leverage and extend these types of workflows, a new package, genGrouper, has been developed for generalized chemical representation of simulation inputs, utilizing the PyTorch deep learning library.
4 Additionally, progress has been made in supporting features necessary for more complex water models, such as TIP4P/2005f and TIP5P models, and a standard screening workflow centered around MoSDeF software has been performed and made available for facile extension to more sophisticated high-throughput active learning approaches.
References
- “MoSDeF” [Online]. Available: https://mosdef.org
- Cummings, P. T. et al. (2021). Open‐source molecular modeling software in chemical engineering focusing on the Molecular Simulation Design Framework. In AIChE Journal (Vol. 67, Issue 3). Wiley.
- Adorf, C. S., et al. Simple data and workflow management with the signac framework. Comput. Mater. Sci., 146(C):220–229, 2018.
- Ansel, J., et al., (2024) PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation. In ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2. ACM.
