MoSGrid: efficient data management and a standardized data exchange format for molecular simulations in a grid environment

Blunk, Dirk; Breuers, Sebastian; Brinkmann, André; Vieira, Inês dos Santos; Fels, Gregor; Gesing, Sandra; Grunzke, Richard; Herres‐Pawlis, Sonja; Kohlbacher, Oliver; Krüger, Jens; Lang, Ulrich; Packschies, Lars; Müller-Pfefferkorn, R.; Schäfer, Patrick; Steinke, Thomas; Warzecha, Klaus‐Dieter; Wewior, Martin

doi:10.1186/1758-2946-4-s1-p21

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the virtual research community WeNMR has a large collection of portals providing production services for different applications in structural biology [ 49 ], including molecular dynamics simulations with Gromacs [ 50 ]. Data exchange in multi-step molecular simulations and analysis has been treated in several works previously [ 51 – 54 ]. Within the MoSGrid project the molecular simulation markup language (MSML) [ 51 , 52 ] has been developed employing the concept of Chemical Markup Language (CML) dictionaries and used in quantum chemistry, molecular dynamics and docking simulations on the MoSGrid portal [ 55 ].…”

Section: Introductionmentioning

confidence: 99%

“…Data exchange in multi-step molecular simulations and analysis has been treated in several works previously [ 51 – 54 ]. Within the MoSGrid project the molecular simulation markup language (MSML) [ 51 , 52 ] has been developed employing the concept of Chemical Markup Language (CML) dictionaries and used in quantum chemistry, molecular dynamics and docking simulations on the MoSGrid portal [ 55 ]. The Collaborative Computing Project for NMR (CCPN) [ 53 ] has provided a software framework that consists of a data model [ 54 ], the CcpNmr Analysis program, and a collection of additional tools, including the CcpNmr FormatConverter.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Native structure-based modeling and simulation of biomolecular systems per mouse click

et al. 2014

View full text Add to dashboard Cite

BackgroundMolecular dynamics (MD) simulations provide valuable insight into biomolecular systems at the atomic level. Notwithstanding the ever-increasing power of high performance computers current MD simulations face several challenges: the fastest atomic movements require time steps of a few femtoseconds which are small compared to biomolecular relevant timescales of milliseconds or even seconds for large conformational motions. At the same time, scalability to a large number of cores is limited mostly due to long-range interactions. An appealing alternative to atomic-level simulations is coarse-graining the resolution of the system or reducing the complexity of the Hamiltonian to improve sampling while decreasing computational costs. Native structure-based models, also called Gō-type models, are based on energy landscape theory and the principle of minimal frustration. They have been tremendously successful in explaining fundamental questions of, e.g., protein folding, RNA folding or protein function. At the same time, they are computationally sufficiently inexpensive to run complex simulations on smaller computing systems or even commodity hardware. Still, their setup and evaluation is quite complex even though sophisticated software packages support their realization.ResultsHere, we establish an efficient infrastructure for native structure-based models to support the community and enable high-throughput simulations on remote computing resources via GridBeans and UNICORE middleware. This infrastructure organizes the setup of such simulations resulting in increased comparability of simulation results. At the same time, complete workflows for advanced simulation protocols can be established and managed on remote resources by a graphical interface which increases reusability of protocols and additionally lowers the entry barrier into such simulations for, e.g., experimental scientists who want to compare their results against simulations. We demonstrate the power of this approach by illustrating it for protein folding simulations for a range of proteins.ConclusionsWe present software enhancing the entire workflow for native structure-based simulations including exception-handling and evaluations. Extending the capability and improving the accessibility of existing simulation packages the software goes beyond the state of the art in the domain of biomolecular simulations. Thus we expect that it will stimulate more individuals from the community to employ more confidently modeling in their research.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-292) contains supplementary material, which is available to authorized users.

show abstract