Core AutoDock-GPU

• Accelerating AutoDock4 with GPUs and Gradient-Based Local Search. Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas F Tillack, Michel F Sanner, Andreas Koch, Stefano Forli. Journal of Chemical Theory and Computation (JCTC), 2021(https://pubs.acs.org/doi/10.1021/acs.jctc.0c01006), ChemRxiv (preprint), 2019(https://chemrxiv.org/articles/preprint/Accelerating_AutoDock4_with_GPUs_and_Gradient-Based_Local_Search/9702389/1)

Using AutoDock-GPU

• GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research. Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Josh V. Vermaas, Rupesh Agarwal, Jeff Larkin, Duncan Poole, Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas Koch, Stefano Forli, Oscar Hernandez, Jeremy C. Smith, Ada Sedova. 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB), 2020(https://dl.acm.org/doi/10.1145/3388440.3412472)

• Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4. Léa El Khoury, Diogo Santos-Martins, Sukanya Sasmal, Jérôme Eberhardt, Giulia Bianco, Francesca Alessandra Ambrosio, Leonardo Solis-Vasquez, Andreas Koch, Stefano Forli, David L. Mobley. Journal of Computer-Aided Molecular Design (JCAMD), 2019(https://link.springer.com/article/10.1007%2Fs10822-019-00240-w), ChemRxiv (preprint), 2019(https://chemrxiv.org/articles/Comparison_of_Ligand_Affinity_Ranking_Using_AutoDock-GPU_and_MM-GBSA_Scores_in_the_D3R_Grand_Challenge_4/8309690)

• D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU. Diogo Santos-Martins, Jerome Eberhardt, Giulia Bianco, Leonardo Solis-Vasquez, Francesca Alessandra Ambrosio, Andreas Koch, Stefano Forli. Journal of Computer-Aided Molecular Design (JCAMD), 2019(https://link.springer.com/article/10.1007%2Fs10822-019-00241-9)

Performance, computational energy, and other aspects

• Benchmarking the Performance of Irregular Computations in AutoDock-GPU Molecular Docking. Leonardo Solis-Vasquez, Andreas F. Tillack, Diogo Santos-Martins, Andreas Koch, Scott LeGrand, Stefano Forli. Parallel Computing, 2021(https://doi.org/10.1016/j.parco.2021.102861)

• Parallelizing Irregular Computations for Molecular Docking. Leonardo Solis-Vasquez, Diogo Santos-Martins, Andreas F. Tillack, Andreas Koch, Jerome Eberhardt, Stefano Forli. 10th Workshop on Irregular Applications: Architectures and Algorithms (IA3), 2020(https://ieeexplore.ieee.org/document/9407259)

• Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking. Leonardo Solis-Vasquez, Diogo Santos-Martins, Andreas Koch, Stefano Forli. 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 2020(https://ieeexplore.ieee.org/document/9092332)

• Accelerating Molecular Docking by Parallelized Heterogeneous Computing - A Case Study of Performance, Quality of Results, and Energy-Efficiency using CPUs, GPUs, and FPGAs. Leonardo Solis-Vasquez. PhD thesis. TUprints, 2019(https://tuprints.ulb.tu-darmstadt.de/9288/)

Porting to other accelerators

• A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software. Leonardo Solis-Vasquez, Andreas Koch. 5th International Workshop on FPGAs for Software Programmers (FSP), 2018(https://ieeexplore.ieee.org/document/8470463)

Predecessors of AutoDock-GPU

• A Performance and Energy Evaluation of OpenCL-accelerated Molecular Docking. Leonardo Solis-Vasquez, Andreas Koch. 5th International Workshop on OpenCL (IWOCL), 2017(https://dl.acm.org/doi/10.1145/3078155.3078167)
• Molecular Docking on FPGA and GPU Platforms. I. Pechan and B. Feher. 21st International Conference on Field Programmable Logic and Applications, 2011(https://dl.acm.org/doi/10.1109/FPL.2011.93)

Further reading

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