Biomolecular simulations are important technique for our understanding and design of biological molecules and their interactions. Simulation methods are demonstrating rapidly growing impact in areas as diverse as biocatalysis, drug delivery, biomaterials, biotechnology, and drug or protein design. Simulations offer the potential of uniquely detailed, atomic‐level insight into mechanisms, dynamics, and processes, as well as increasingly accurate predictions of molecular properties. Yet the field only relatively recently started to store and share (bio)simulation data to be reused for new, unexpected projects, and started discussions about their biomolecular simulation data FAIRification (i.e. to make them Findable, Accessible, Interoperable and Reusable). Here we show several current possibilities moving in this direction, but we should stress that these guidelines are not carved to stone and the biomolecular simulation community still needs to address challenges to FAIRify their data.

Storing and sharing the data from biomolecular simulations


The biomolecular simulation data comes in several forms and multiple formats, which unfortunately are not completely interoperable. Different methods also require slightly different metadata description.


  • What type of data do you have?
    • Molecular dynamics data - by far the most typical and largest biomolecular simulation data. Each molecular dynamics simulation is driven by the used engine, force-field, and multiple other and often hidden simulation parameters to produce trajectories that are further analysed.
    • Molecular docking data - docking provides the structures of the complex (e.g. ligand-protein, protein-protein, protein-nucleic acid, etc) and its score/energy.
    • Virtual screening data - virtual screening is used for selection of active compounds from the pool of others and is usually in the form of ID and its score/energy.
    • Free energies and other analysis data - data calculatable from the analysis of the simulations.
  • Where should you store this data?
    • Since there is no common community repository that would be able to gather the often spatious simulation data, the field did not systematically store them. Recently, there’s multiple possibilities where the data can be stored. The repositories can be divided in two main branches:
      • Generic: Repositories that can be used to store any kind of data.
      • Specific: Repositories designed to store specific data (e.g. MD data).
    • Are you looking for a long-term or short-term storage? Repositories have different options (and sometimes prices) for the storage time of your data.
    • Do you need a static reference for your data? A code (identifier) that can uniquely identify and refer to your data?
  • What data should you store?
  • What type of data should you store from the whole bunch of data generated in our project. Again, the type of data might vary depending on the biomolecular simulation field.
  • Consider what is essential (absolutely needed to reproduce the simulated experiment) versus what can be extracted from this data (analyses).

  • How do you want your data to be shared?
    • You should consider the terms in which other scientists can use your data for other projects, access, modify, or redistribute them.


  • Deposit your data to a suitable repository for sharing. There’s a long (and incomplete) list of repositories available for data sharing. Repositories are divided into two main categories, general-purpose and discipline-specific, and both categories are utilised in the domain of biomolecular modeling and simulation. For a general introduction to repositories, you are advised to read the data publication page.
  • Based on the type of data to be shared, pay attention to what should be included and the data and metadata that will be deposited to repositories. Below listed are some suggested examples of types of essential and optional data describing the biomolecular simulation data:
    • Molecular Dynamics:
      • Essentials:
        • Metadata (Temperature, pressure, program, version, …)
        • Complete set of input files that were used in the simulations
        • Trajectory(ies)
        • Topology(ies)
      • Optionals:
        • Analysis data (Free energy, snapshots, clusterization)
    • Docking poses:
      • Essentials:
        • The complete set of molecules tested as well as the scoring functions used and the high-ranking, final poses (3D-structures)
        • Metadata (Identifiers (SMILES, InChI-Key), target (PDBID), energies/scores, program, version, box definition)
      • Optionals:
        • Complete ensemble of poses
    • Virtual Screening:
      • Essentials:
        • List of molecules sorted
        • Metadata (identifiers of ligands and decoy molecules, target, program+version, type of VS (QSAR, ML, Docking,…))
      • Optionals:
        • Details of the method, scores, …
    • Free energies and other analyses:
      • Essentials:
        • Metadata (model, method, program, version, force field(s), etc.)
        • Values (Free energy values, channels, etc.)
      • Optionals:
        • Link to Trajectory (Dynamic PDB?)
  • Associate a license with the data and/or source code e.g. models. Licenses mainly differ on openness vs restrictiveness, and it is crucial to understand the differences among licenses before sharing your research outputs. The RDMkit licensing page lists resources that can help you understand licensing and choose an appropriate license.
  • File formats Biomolecular simulation field has a tendency to produce a multitude of input/output formats, each of them mainly related to one software package. That makes interoperability and reproducibility really difficult. You can share your data but this data will only be useful if the scientist interested in it has access to the tool that has generated it. The field is working on possible standards (e.g. TNG trajectory).

  • Metadata standards There is no existing standard defining the type and format of the metadata needed to describe a particular project and its associated data. How to store the program, version, parameters used, input files, etc. is still an open question, which has been addressed in many ways and using many formats (json, xml, txt, etc.). Again, different initiatives exist trying to address this issue (see further references).

  • Data size Data generated in the biomolecular simulation field is growing at an alarming pace. Making this data available to the scientific community sometimes means transferring them to a long-term storage, and even this a priori straightforward process can be cumbersome because of the large data size.

Relevant tools and resources

Tool or resource Description Tags Registry
BigNASim Repository for Nucleic Acids MD simulations biomol sim
BindingDB Public, web-accessible database of measured binding affinities biomol sim
Bioactive Conformational Ensemble Platform designed to efficiently generate bioactive conformers and speed up the drug discovery process. biomol sim
BioExcel COVID-19 Platform designed to provide web-access to atomistic-MD trajectories for macromolecules involved in the COVID-19 disease. biomol sim
COVID-19 Molecular Structure and Therapeutics Hub COVID-19 Molecular Structure and Therapeutics Hub biomol sim Data License list Overview of typical licenses used for data resources licensing biomol sim
Dryad Open-source, community-led data curation, publishing, and preservation platform for CC0 publicly available research data data publication biomol sim
Dynameomics Database of folding / unfolding pathway of representatives from all known protein folds by MD simulation biomol sim
FigShare Data publishing platform data publication biomol sim
GPCRmd Repository of GPCR protein simulations biomol sim
MemProtMD Database of over 5000 intrinsic membrane protein structures biomol sim
Mendeley data Multidisciplinary, free-to-use open repository specialized for research data data publication biomol sim
MoDEL Database of Protein Molecular Dynamics simulations representing different structural clusters of the PDB biomol sim
MoDEL Covid19 Database of COVID-19 related atomistic Molecular Dynamic Trajectories biomol sim
MoDEL-CNS Repository for Central Nervous System-related mainly membrane protein MD simulations biomol sim
ModelArchive Repository for molecular models - providing doi of models biomol sim
MolMeDB Database about interactions of molecules with membranes biomol sim
NMRlipids Repository for lipid MD simulations to validate force fields with NMR data biomol sim
OpenScienceFramework free and open source project management tool that supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery data publication biomol sim
PDB-Dev Prototype archiving system for structural models obtained using integrative or hybrid modeling biomol sim
Zenodo Generalist research data repository built and developed by OpenAIRE and CERN data publication biomol sim

Where can training materials and events about biomolecular simulations be found?

BioExcel Knowledge Resource Center