4.5 Review

Advances in distributed computing with modern drug discovery

期刊

EXPERT OPINION ON DRUG DISCOVERY
卷 14, 期 1, 页码 9-22

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/17460441.2019.1552936

关键词

Cloud computing; computational chemistry; distributed computing; drug discovery; grid computing; high-performance computing; virtual screening

资金

  1. Spanish Ministry of Economy and Competitiveness [CTQ2017-87974-R]
  2. Spanish MEC
  3. European Commission FEDER [AEI/FEDER, UE] [TIN2016-78799-P]
  4. supercomputing infrastructure of Poznan Supercomputing Center
  5. e-infrastructure program of the Research Council of Norway
  6. supercomputer center of UiT -the Arctic University of Norway
  7. Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT)
  8. European Regional Development Fund (ERDF)

向作者/读者索取更多资源

Introduction: Computational chemistry dramatically accelerates the drug discovery process and high-performance computing (HPC) can be used to speed up the most expensive calculations. Supporting a local HPC infrastructure is both costly and time-consuming, and, therefore, many research groups are moving from in-house solutions to remote-distributed computing platforms. Areas covered: The authors focus on the use of distributed technologies, solutions, and infrastructures to gain access to HPC capabilities, software tools, and datasets to run the complex simulations required in computational drug discovery (CDD). Expert opinion: The use of computational tools can decrease the time to market of new drugs. HPC has a crucial role in handling the complex algorithms and large volumes of data required to achieve specificity and avoid undesirable side-effects. Distributed computing environments have clear advantages over in-house solutions in terms of cost and sustainability. The use of infrastructures relying on virtualization reduces set-up costs. Distributed computing resources can be difficult to access, although web-based solutions are becoming increasingly available. There is a trade-off between cost-effectiveness and accessibility in using on-demand computing resources rather than free/academic resources. Graphics processing unit computing, with its outstanding parallel computing power, is becoming increasingly important.

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