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Vina-GPU 2.0 accelerates AutoDock Vina and its related commonly derived docking methods, such as QuickVina 2 and QuickVina-W with GPUs.

License: Apache License 2.0

C++ 90.70% C 9.13% Batchfile 0.01% Makefile 0.18%

vina-gpu-2.0's Introduction

Vina-GPU 2.0

Vina-GPU 2.0 accelerates AutoDock Vina and its related commonly derived docking methods, such as QuickVina 2 and QuickVina-W with GPUs. Vina-GPU 2.0 includes the following three docking methods,including Vina-GPU+,QuickVina 2-GPU and QuickVina-W-GPU.

Vina-GPU+

Vina-GPU+ further accelerates Vina-GPU and facilitates single receptor-multi-ligand docking. The compile and run process is described in here.

If you would like to develop and build Vina-GPU+ from source please look at README.md(https://github.com/DeltaGroupNJUPT/Vina-GPU-2.0/blob/main/Vina-GPU%2B/README.md).

QuickVina 2-GPU

The compile and run process is described in here.

QuickVina-W-GPU

The compile and run process is described in here.

Graphic User Interface (GUI)

A graphic user interface (GUI) is provided for users on Windows OS

  1. first make sure that Vina-GPU2.0.exe can run on a terminal
  2. put the Vina-GPU2.0.exe and all .bin formatted files in ./Vina-GPU-2.0/GUI/exec and overwrite the original files
  3. run the Vina-GPU2.0.exefile within ./Vina-GPU-2.0/GUI to start up the Vina-GPU 2.0 GUI
  4. select docking methods
  5. select the input and output files
  6. set the box center, the box size, thread and search_depth
  7. click the start button to run Vina-GPU 2.o
  8. click score button to get docking scores

Citation

  • Tang, Shidi et al. “Accelerating AutoDock Vina with GPUs.” Molecules (Basel, Switzerland) vol. 27,9 3041. 9 May. 2022, doi:10.3390/molecules27093041
  • Trott, Oleg, and Arthur J. Olson. "AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading." Journal of computational chemistry 31.2 (2010): 455-461.
  • Hassan, N. M. , et al. "Protein-Ligand Blind Docking Using QuickVina-W With Inter-Process Spatio-Temporal Integration." Scientific Reports 7.1(2017):15451.
  • Amr Alhossary, Stephanus Daniel Handoko, Yuguang Mu, and Chee-Keong Kwoh. "Fast, accurate, and reliable molecular docking with QuickVina 2. " Bioinformatics (2015): 2214–2216.

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