From January 10, 2019 release of PLOS Computational Biology (v. 15 pp. 1-4)
Ten simple rules on how to create open access and reproducible molecular simulations of biological systems
All PLOS journals have an open data policy that, amongst other things, states that all data and related metadata underlying the findings reported in a submitted manuscript should be deposited in an appropriate public repository, or for smaller datasets, as supporting information. This should obviously apply to computational methods as well, but unfortunately this is not always applied in practice, although it is of greatest importance for the scientific quality of simulations and other modeling projects.
Molecular dynamics and other type of simulations have become a fundamental part of life sciences. The simulations are dependent on a number of parameters such as force fields, initial configurations, simulation protocols, and software. Researchers have different opinions about the types of software they prefer, and in general, we believe authors should be free to choose the tools that best fit their needs. However, as scientists, we also have a common obligation to critically test each other’s statements to find mistakes (including errors in the algorithms and bugs in the code), which can be exemplified by a heated debate over simulations of supercooled water that ended up being due to a subtle algorithmic issue, and we believe PLOS has a particularly strong responsibility to lead this development even if it might cause some short-term grief.
In particular, all published results should, in principle, be possible to reproduce independently by scientists in other labs using different tools. To ensure this, we propose a set of standards that any publication in PLOS Computational Biology, and hopefully, publications in other journals as well, should follow. We do believe that the sooner such policies are widely adapted, the more open and collaborative science will flourish.
These 10 simple rules should not be limited to molecular dynamics but also include Monte Carlo simulations, quantum mechanics calculations, molecular docking, and any other computational methods involving computations on biological molecules.
Read the full publication here.