Vina-GPU 2.1

Vina-GPU 2.1 further improves the virtual screening runtime and accuracy with the noval RILC-BFGS and GCS mthods based on Vina-GPU 2.0. Vina-GPU 2.1 includes AutoDock-Vina-GPU 2.1, QuickVina 2-GPU 2.1 and QuickVina-W-GPU 2.1.

Virtual Screening Results

• Runtime comparison of Vina-GPU 2.1 on Drugbank library (partial)

• Accuracy comparison of Vina-GPU 2.1 on Drugbank library (partial)

Compiling and Running

Windows

Build from source file

Visual Studio 2019 is recommended for build Vina-GPU 2.1 from source 1. install boost library (current version is 1.77.0) 2. install CUDA Toolkit (current version: v12.2) if you are using NVIDIA GPU cards

**Note**: the OpenCL library can be found in CUDA installation path for NVIDIA or in the driver installation path for AMD

1. add $(ONE_OF_VINA_GPU_2_1_METHODS)/lib $(ONE_OF_VINA_GPU_2_1_METHODS)/OpenCL/inc $(YOUR_BOOST_LIBRARY_PATH) $(YOUR_BOOST_LIBRARY_PATH)/boost $(YOUR_CUDA_TOOLKIT_LIBRARY_PATH)/CUDA/v12.2/include in the include directories
2. add $(YOUR_BOOST_LIBRARY_PATH)/stage/lib $(YOUR_CUDA_TOOLKIT_PATH)/CUDA/lib/x64in the addtional library
3. add OpenCL.lib in the additional dependencies
4. add --config=$(ONE_OF_VINA_GPU_2_1_METHODS)/input_file_example/2bm2_config.txt in the command arguments
5. add NVIDIA_PLATFORM OPENCL_3_0 WINDOWS in the preprocessor definitions if necessary
6. if you want to compile the binary kernel file on the fly, add BUILD_KERNEL_FROM_SOURCE in the preprocessor definitions
7. build & run Note: ensure the line ending are CLRF

Linux

Note: At least 8M stack size is needed. To change the stack size, use ulimit -s 8192. 1. install boost library (current version is 1.77.0) 2. install CUDA Toolkit (current version: v12.2) if you are using NVIDIA GPU cards

**Note**: OpenCL library can be usually in `/usr/local/cuda` (for NVIDIA GPU cards)

1. cd into one of the three methods of Vina-GPU 2.1 ($(ONE_OF_VINA_GPU_2_1_METHODS))
2. change the BOOST_LIB_PATH and OPENCL_LIB_PATH accordingly in Makefile

3. set GPU platform GPU_PLATFORM and OpenCL version OPENCL_VERSION in Makefile. some options are given below:

   Note: -DOPENCL_3_0 is highly recommended in Linux, please avoid using -OPENCL_1_2 in the Makefile setting. To check the OpenCL version on a given platform, use clinfo. |Macros|Options|Descriptions| |--|--|--|
   |GPU_PLATFORM|-DNVIDIA_PLATFORM / -DAMD_PLATFORM|NVIDIA / AMD GPU platform | OPENCL_VERSION | -DOPENCL_3_0 / -OPENCL_2_0|OpenCL version 2.1 / 2.0

4. type make clean and make source to build $(ONE_OF_VINA_GPU_2_1_METHODS) that compile the kernel files on the fly (this would take some time at the first use)

5. after a successful compiling, $(ONE_OF_VINA_GPU_2_1_METHODS) can be seen in the directory
6. change --opencl_binary_path in the ./input_file_example/2bm2_config.txt accordingly and type $(ONE_OF_VINA_GPU_2_1_METHODS) --config ./input_file_example/2bm2_config.txt to run one of the Vina-GPU 2.1 method
7. once you successfully run $(ONE_OF_VINA_GPU_2_1_METHODS), its runtime can be further reduced by typing make clean and make to build it without compiling kernel files (but make sure the Kernel1_Opt.bin file and Kernel2_Opt.bin file is located in the dir specified by --opencl_binary_path)
8. other compile options:

Enlarge the docking box

The docking box now can be enlarged by

1. Change -DSMALL_BOX into -DLARGE_BOX in Makefile
2. Type make source and $(ONE_OF_VINA_GPU_2_1_METHODS) --config ./input_file_example/2bm2_config.txt
3. Once the tutorial docking is finished, type make clearn and make
4. Now you can enlarge the docking box --size_x/y/z accordingly (see Limitation below)

Structure Optimization

Usage

Limitation

Citation

• Tang, Shidi, et al. "Vina-GPU 2.1: towards further optimizing docking speed and precision of AutoDock Vina and its derivatives." IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024).
• Ding, Ji, et al. "Vina-GPU 2.0: further accelerating AutoDock Vina and its derivatives with graphics processing units." Journal of chemical information and modeling 63.7 (2023): 1982-1998.
• 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.