Imagine if every time a scientist ran a complex digital simulation of a protein, the results were lost in a messy folder or deleted to save space. This project is like building a giant, organized digital library where all these simulations are stored and labeled correctly. It allows other researchers to reuse old data instead of spending millions of supercomputer hours doing the same work twice.
Companies waste expensive supercomputing time repeating simulations because existing data is stored in incompatible formats or lost entirely. There is no trusted, centralized way to share and verify molecular dynamics trajectories.
A European-scale repository for molecular dynamics simulations. It includes data storage standards, metadata topologies, and quality checking procedures.
If you are a drug discovery firm dealing with high costs of calculating binding affinities for new leads — this project developed a centralized repository that allows you to reuse high-quality simulation data. This reduces the need to waste supercomputer hours on redundant calculations.
If you are a protein engineering SME dealing with unpredictable changes in functional properties of molecules — this project developed interoperable data standards that make it easier to analyze trajectories from different sources. This speeds up the prediction of how a molecule will behave.
If you are a bioinformatics tool provider dealing with fragmented and non-standard simulation data — this project developed a repository with defined metadata topology and quality checking procedures. This provides a reliable data source to test and validate your analysis tools.
Based on available project data, no specific pricing or cost model is mentioned; the project focuses on establishing a European-scale repository for the research community.
The project is designed as a European-scale repository intended to handle a deluge of simulation data from millions of supercomputer hours, suggesting high scalability for large-scale biological data.
Based on available project data, the project emphasizes FAIR principles (Findable, Accessible, Interoperable, and Reusable), which typically align with open access or standardized data sharing, though specific licenses are not listed.
The project aims to streamline the use of supercomputing resources by creating a centralized repository for storage and management of MD trajectories.
The project period runs from 2023-03-01 to 2026-08-31, indicating the full system will be developed by August 2026.
The consortium consists of 7 partners across 5 countries, showing a strong academic lean with 3 universities and 3 research organizations. There is a limited industrial presence with only 1 industry partner (an SME), resulting in an industry ratio of 14%. This suggests the project is currently driven by scientific infrastructure needs rather than immediate commercial product development.
Contact Fundacio Institut de Recerca Biomedica (IRB Barcelona) regarding MDDB data standards.
Contact us to track the release of the MDDB interoperability standards for your drug discovery pipeline.
