The need to implement FAIR principles in biomolecular simulations

Nature Methods. 2025. Vol. 22. P. 641–645.

Amaro R., Åqvist J., Bahar I., Battistini F., Bellaiche A., Beltran D., Biggin P., Alexey K. Shaytan

The communities that embraced data archiving efforts decades ago are now, in the era of data-driven biology, gaining the most from the AI revolution. The structural biology community was a pioneer in this regard, establishing the Protein Data Bank in 1971 and making data accessible using the FAIR principles even before these were articulated1,2. The genomics and bioinformatics community has followed the example, establishing many widely used databases3,4. By contrast, molecular simulation has been anchored in usage paradigms dating back to the seventies, when molecular dynamics (MD) simulation was first applied to study biomacromolecules5. At that time, MD was used by theoretical physicists and chemists in proof-of-concept simulations, but 50 years later, MD has evolved into a cornerstone molecular biology technique that can provide accurate, quantitative analysis and property prediction. MD is now employed by tens of thousands of researchers worldwide, accounting for roughly 15% of global supercomputer usage. Unfortunately, these rich and costly data are not systematically maintained, and when further analyses are required, simulations have to be rerun — an unacceptable situation from scientific, environmental and sustainability standpoints. In this letter, we argue for a collaborative endeavor to archive MD simulation data and describe ongoing efforts to establish cost-effective and sustainable data archiving strategies.

Keywords: acceptance of technology, DNA, biology, SARS-CoV-2

Publication based on the results of: Development of theoretical foundations and methods of generative artificial intelligence and their application to heterogeneous domain area (2025)