Abstract
High-performance and high-throughput computing play an important role in drug development and, in particular, in solving the computationally intensive problem of virtual screening. The variety and complexity of tools require technical knowledge for selection, setup and usage of the computational platform. There is need for ready solutions and services to simplify the process. With low cost and high scalability, Desktop Grid systems can significantly expand the computational capacity available for a virtual screening. This paper describes High-Throughput Virtual Screening as a Service (HiTViSc): we present three logical levels of operation (computational, virtual screening and user level), the user workflows related to virtual screening, resource administration and visualization and analysis of results, and the multi-user access. The novelty of the work is related to implementation of the Desktop Grid as a Service concept. In particular, comparing to other cloud-based virtual screening services, we use Desktop Grid resources to implement computationally intensive work. Comparing to umbrella Desktop Grid projects, the users of HiTViSc can be both consumers and providers of computing resources at the same time, and employ additional steps of virtual screening based on supportive utilities provided by HiTViSc.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Blaze Cloud from Cresset. https://www.cresset-group.com/products/blaze/#blaze-cloud. Accessed 31 Jan 2023
Anderson, D.P.: BOINC: a platform for volunteer computing. J. Grid Comput. 18(1), 99–122 (2020)
Berman, H.M., et al.: The protein data bank. Nucl. Acids Res. 28(1), 235–242 (2000). https://doi.org/10.1093/nar/28.1.235
Chernov, I.: Effective scanning of parameter space in a desktop grid for identification of a hydride decomposition model. Program Syst. Theory Appl. 9(4(39)), 53–68 (2018). https://doi.org/10.25209/2079-3316-2018-9-4-53-68
Climateprediction.net | the world’s largest climate modelling experiment for the 21st century. https://www.climateprediction.net. Accessed 31 Mar 2023
Glaser, J., et al.: High-throughput virtual laboratory for drug discovery using massive datasets. Int. J. High Perform. Comput. Appl. 35(5), 452–468 (2021)
Hawkins, P.: Virtual Screening At Ultra-Large Scale: 1.5 Billion And Counting - Webinars. https://www.healthtech.com/openeye-scientific-virtual-screening-at-ultra-large-scale/. Accessed 31 Jan 2023
Home | LHC@home. https://lhcathome.web.cern.ch. Accessed 31 Mar 2023
Irwin, J.J., Sterling, T., Mysinger, M.M., Bolstad, E.S., Coleman, R.G.: Zinc: a free tool to discover chemistry for biology. J. Chem. Inf. Model. 52(7), 1757–1768 (2012). https://doi.org/10.1021/ci3001277
Ivashko, E.: Desktop Grid as a service concept. In: Voevodin, V., Sobolev, S., Yakobovskiy, M., Shagaliev, R. (eds.) Supercomputing: 8th Russian Supercomputing Days, RuSCDays 2022. LNCS, vol. 13708, pp. 632–643. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-22941-1_46
Ivashko, E.E., Nikitina, N.N., Möller, S.: High-performance virtual screening in a BOINC-based Enterprise Desktop Grid. Vestnik Yuzhno-Ural’skogo Gosudarstvennogo Universiteta. Seriya Vychislitelnaya Matematika i Informatika 4(1), 57–63 (2015)
Jaghoori, M.M., Bleijlevens, B., Olabarriaga, S.D.: 1001 ways to run AutoDock Vina for virtual screening. J. Comput. Aided Mol. Des. 30, 237–249 (2016)
Krasoulis, A., Antonopoulos, N., Pitsikalis, V., Theodorakis, S.: DENVIS: scalable and high-throughput virtual screening using graph neural networks with atomic and surface protein pocket features. J. Chem. Inf. Model. 62(19), 4642–4659 (2022)
Liu, T., et al.: Applying high-performance computing in drug discovery and molecular simulation. Natl. Sci. Rev. 3(1), 49–63 (2016)
Mo, Q., Xu, Z., Yan, H., Chen, P., Lu, Y.: VSTH: a user-friendly web server for structure-based virtual screening on Tianhe-2. Bioinformatics 39(1), btac740 (2023)
Murugan, N.A., Podobas, A., Gadioli, D., Vitali, E., Palermo, G., Markidis, S.: A review on parallel virtual screening softwares for high-performance computers. Pharmaceuticals 15(1), 63 (2022)
Nikitina, N., Ivashko, E.: Optimization of the workflow in a BOINC-based Desktop Grid for virtual drug screening. In: Voevodin, V., Sobolev, S., Yakobovskiy, M., Shagaliev, R. (eds.) Supercomputing, RuSCDays 2022. LNCS, vol. 13708, pp. 686–698. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-22941-1_50
Nikitina, N., Ivashko, E., Tchernykh, A.: Congestion game scheduling implementation for high-throughput virtual drug screening using BOINC-based Desktop Grid. In: Malyshkin, V. (ed.) PaCT 2017. LNCS, vol. 10421, pp. 480–491. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62932-2_46
Nikitina, N., Manzyuk, M., Podlipnik, Č, Jukić, M.: Volunteer computing project SiDock@home for virtual drug screening against SARS-CoV-2. In: Byrski, A., Czachórski, T., Gelenbe, E., Grochla, K., Murayama, Y. (eds.) ANTICOVID 2021. IAICT, vol. 616, pp. 23–34. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-86582-5_3
Olğaç, A., Türe, A., Olğaç, S., Möller, S.: Cloud-based high throughput virtual screening in novel drug discovery. In: Kołodziej, J., González-Vélez, H. (eds.) High-Performance Modelling and Simulation for Big Data Applications. LNCS, vol. 11400, pp. 250–278. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-16272-6_9
Prieto-Martínez, F.D., López-López, E., Juárez-Mercado, K.E., Medina-Franco, J.L.: Computational drug design methods-current and future perspectives. In: Silico Drug Design, pp. 19–44 (2019)
Rosetta@home. https://boinc.bakerlab.org. Accessed 31 Mar 2023
Sabe, V.T., et al.: Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: a review. Eur. J. Med. Chem. 224, 113705 (2021)
Singh, N., Chaput, L., Villoutreix, B.O.: Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace. Brief. Bioinform. 22(2), 1790–1818 (2021)
Sulimov, A.V., Kutov, D.C., Sulimov, V.B.: Supercomputer docking. Supercomput. Front. Innov. 6(3), 26–50 (2019)
Together We Are Powerful - Folding@home. https://foldingathome.org. Accessed 31 Mar 2023
Zhang, B., D’Erasmo, M.P., Murelli, R.P., Gallicchio, E.: Free energy-based virtual screening and optimization of RNase H inhibitors of HIV-1 reverse transcriptase. ACS Omega 1(3), 435–447 (2016)
Zhang, B., Li, H., Yu, K., Jin, Z.: Molecular docking-based computational platform for high-throughput virtual screening. CCF Trans. High Perform. Comput. 1–12 (2022)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Nikitina, N., Ivashko, E. (2023). HiTViSc: High-Throughput Virtual Screening as a Service. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2023. Lecture Notes in Computer Science, vol 14098. Springer, Cham. https://doi.org/10.1007/978-3-031-41673-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-41673-6_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-41672-9
Online ISBN: 978-3-031-41673-6
eBook Packages: Computer ScienceComputer Science (R0)