Saadi, AA;
Alfe, D;
Babuji, Y;
Bhati, A;
Blaiszik, B;
Brace, A;
Brettin, T;
... Yin, J; + view all
(2021)
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads.
In:
Proceedings of ICPP 2021: 50th International Conference on Parallel Processing.
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2–3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can deliver this combination of higher quality and speed. Here, we describe an Integrated Modeling PipEline for COVID Cure by Assessing Better LEads (IMPECCABLE) that employs multiple methodological innovations to overcome this fundamental limitation. We also describe the computational framework that we have developed to support these innovations at scale, and characterize the performance of this framework in terms of throughput, peak performance, and scientific results. We show that individual workflow components deliver 100 × to 1000 × improvement over traditional methods, and that the integration of methods, supported by scalable infrastructure, speeds up drug discovery by orders of magnitudes. IMPECCABLE has screened ∼ 1011 ligands and has been used to discover a promising drug candidate. These capabilities have been used by the US DOE National Virtual Biotechnology Laboratory and the EU Centre of Excellence in Computational Biomedicine.
| Type: | Proceedings paper |
|---|---|
| Title: | IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads |
| Event: | ICPP 2021: 50th International Conference on Parallel Processing |
| ISBN-13: | 9781450390682 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3472456.3473524 |
| Publisher version: | https://doi.org/10.1145/3472456.3473524 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Chemistry UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Earth Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10140536 |
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