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Simulation Foundry: Automated and F.A.I.R. Molecular Modeling.

Gudrun Gygli¹, Juergen Pleiss¹

¹Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany.

Journal of Chemical Information and Modeling

|April 3, 2020

Summary

This summary is machine-generated.

The Simulation Foundry (SF) automates molecular modeling (MM) data creation, enhancing reproducibility and data sharing. This workflow ensures molecular modeling data is findable, accessible, interoperable, and reusable (F.A.I.R.).

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Area of Science:

Computational chemistry and materials science.
Development of automated workflows for scientific simulations.

Background:

Molecular modeling (MM) is crucial for predicting properties of complex systems.
Current MM data creation can be challenging to repeat, replicate, and share effectively.
Need for standardized, automated workflows to manage increasing simulation demands.

Purpose of the Study:

To introduce the Simulation Foundry (SF), a modular workflow for automated MM data generation.
To enhance the reproducibility, replicability, and F.A.I.R. principles of MM data.
To facilitate high-throughput simulations and data integration for multicomponent systems.

Main Methods:

Developed a modular workflow based on widely used scripting languages (bash, Python).
Implemented standardized data structures and file naming conventions for cross-platform compatibility.
Ensured reusability and re-editability of the workflow for expert users.

Main Results:

Demonstrated SF's usability through simulations of thermophysical properties of binary mixtures.
Established a standardized data exchange format for integrating simulated and experimental data.
Provided complete documentation for result provenance and transparency.

Conclusions:

The SF enhances the automation, modularity, and efficiency of molecular modeling.
SF promotes reproducible, transparent, and F.A.I.R. data creation within the scientific community.
SF serves as a platform for integrating new methods and fostering collaborative research.