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article · Journal of Parallel and Distributed Computing · 2023

GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis

Emanuele Vitali, Federico Ficarelli, Mauro Bisson, Davide Gadioli, Gianmarco Accordi, Massimiliano Fatica, Andrea R. Beccari, Gianluca Palermo

Cited by 15Open access

Abstract

Finding a novel drug is a very long and complex procedure. Using computer simulations, it is possible to accelerate the preliminary phases by performing a virtual screening that filters a large set of drug candidates to a manageable number. This paper presents the implementations and comparative analysis of two GPU-optimised implementations of a virtual screening algorithm targeting novel GPU architectures. This work focuses on the analysis of parallel computation patterns and their mapping onto the target architecture. The first method adopts a traditional approach that spreads the computation for a single molecule across the entire GPU. The second uses a novel batched approach that exploits the parallel architecture of the GPU to evaluate more molecules in parallel. Experimental results showed a different behavior depending on the size of the database to be screened, either reaching a performance plateau sooner or having a more extended initial transient period to achieve a higher throughput (up to 5x), which is more suitable for extreme-scale virtual screening campaigns.

Cite this paper

APA 7

Vitali, E., Ficarelli, F., Bisson, M., Gadioli, D., Accordi, G., Fatica, M., Beccari, A. R., & Palermo, G. (2023). GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis. Journal of Parallel and Distributed Computing, 186, 104819. https://doi.org/10.1016/j.jpdc.2023.104819

MLA 9

Vitali, Emanuele, et al. “GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis.” Journal of Parallel and Distributed Computing, vol. 186, 2023, p. 104819, https://doi.org/10.1016/j.jpdc.2023.104819.

Chicago

Vitali, Emanuele, Federico Ficarelli, Mauro Bisson, Davide Gadioli, Gianmarco Accordi, Massimiliano Fatica, Andrea R. Beccari, and Gianluca Palermo. 2023. “GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis.” Journal of Parallel and Distributed Computing 186: 104819. https://doi.org/10.1016/j.jpdc.2023.104819.

Harvard

Vitali, E. et al. (2023) ‘GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis’, Journal of Parallel and Distributed Computing, 186, p. 104819. Available at: https://doi.org/10.1016/j.jpdc.2023.104819.

BibTeX
@article{vitali2023optimized,
  title = {{GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis}},
  author = {Vitali, Emanuele and Ficarelli, Federico and Bisson, Mauro and Gadioli, Davide and Accordi, Gianmarco and Fatica, Massimiliano and Beccari, Andrea R. and Palermo, Gianluca},
  journal = {Journal of Parallel and Distributed Computing},
  volume = {186},
  pages = {104819},
  year = {2023},
  doi = {10.1016/j.jpdc.2023.104819}
}

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