VirtualFlow Project

VirtualFlowIntroduction

VirtualFlow is a versatile, parallel workflow platform for carrying out virtual screening related tasks on Linux-based computer clusters of any type and size which are managed by a batchsystem (such as SLURM).

VirtualFlow is an open source project with over 20 contributors distributed around the globe. I am the creator and lead developer of this project. 

Currently, there exist two versions of VirtualFlow, which are tailored to different types of tasks:

  • VFLP: VirtualFlow for Ligand Preparation
  • VFVS : VirtualFlow for Virtual Screenings

They use the same core technology regarding the workflow management and parallelization, and they can be used individually or in concert with each other. Additional versions are expected to arrive in the future. Pre-built ready-to-dock ligand libraries for VFVS are available for free.


Project Homepage


How to Cite

If you are using VirtualFlow, please cite the following papers in relevant publications: 

  • Christoph Gorgulla, Andras Boeszoermenyi, Zi-Fu Wang, Patrick D. Fischer, Paul W. Coote, Krishna M. Padmanabha Das, Yehor S. Malets, Dmytro S. Radchenko, Yurii S. Moroz, David A. Scott, Konstantin Fackeldey, Moritz Hoffmann, Iryna Iavniuk, Gerhard Wagner, Haribabu Arthanari An open-source drug discovery platform enables ultra-large virtual screens. Nature 580, 663–668 (2020). https://doi.org/10.1038/s41586-020-2117-z
  • Gorgulla, C., Fackeldey, K., Wagner, G., & Arthanari, H. (2020). Accounting of Receptor Flexibility in Ultra-Large Virtual Screens with VirtualFlow Using a Grey Wolf Optimization Method. Supercomputing Frontiers and Innovations, 7(3), 4–12. https://doi.org/10.14529/jsfi200301
  • Gorgulla, C., Çınaroğlu, S.S., Fischer, P.D., Fackeldey, K., Wagner, G. and Arthanari, H., 2021. VirtualFlow Ants—Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization. International Journal of Molecular Sciences, 22(11), p.5807. https://doi.org/10.3390/ijms22115807
  • Gorgulla, C., Fackeldey, K., Wagner, G. and Arthanari, H., 2020. Accounting of receptor flexibility in ultra-large virtual screens with VirtualFlow using a grey wolf optimization method. Supercomputing frontiers and innovations, 7(3), p.4. https://dx.doi.org/10.14529%2Fjsfi200301
     

Team

Contributors and team members of the project (as for June 2022): 

VirtualFlow Team