TY - JOUR
T1 - Drug repurposing based on a quantum-inspired method versus classical fingerprinting uncovers potential antivirals against SARS-CoV-2
T2 - Quantum-inspired identification of SARS-CoV-2 antivirals
AU - Jimenez Guardeno, Jose
AU - Ortega Prieto, Ana
AU - Menendez Moreno, Borja
AU - Maguire, Thomas
AU - Richardson, Adam
AU - Diaz-Hernandez, Juan Ignacio
AU - Diez Perez, Javier
AU - Zuckerman, Mark
AU - Mercadal Playa, Albert
AU - Cordero Deline, Carlos
AU - Malim, Michael
AU - Martinez Nunez, Rocio
N1 - Funding Information:
This work was funded by a King’s Together Rapid COVID-19 Call award to RTMN, the Huo Family Foundation (MHM and RTMN), the Wellcome Trust (213984/Z/18/Z to RTMN; 106223/ Z/14/Z and 222433/Z/21/Z to MHM), the MRC Genotype-to-Phenotype UK National Virology Consortium (MR/W005611/1 to MHM), the National Institutes of Health (AI076119 to MHM) and the Department of Health via a National Institute for Health Research comprehensive Biomedical Research Centre award to Guy’s and St. Thomas’ NHS Foundation Trust in partnership with King’s College London and King’s College Hospital NHS Foundation Trust.(MHM). JMJG is a long-term fellow of the European Molecular Biology Organization (ALTF 663-2016). TJAM PhD studentship was funded by Asthma UK Centre in Allergic Mechanisms of Asthma. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Links to funders: King’s Together: https://www.kcl.ac.uk/research/ funding-opportunities/seedfund Huo Family Foundation: https://huofamilyfoundation.org/ Wellcome Trust: https://wellcome.org/ MRC: https://mrc.ukri.org/ NIAID: https://www.niaid.nih. gov/ Asthma UK: https://www.asthma-allergy.ac. uk/ NIHR-GSTT: https://www. guysandstthomasbrc.nihr.ac.uk/ EMBO: https:// www.embo.org/funding/fellowships-grants-andcareer-support/. The authors thank Fujitsu Limited for providing access to Digital Annealer and Fujitsu Spain for all the support and commitment.
Publisher Copyright:
Copyright: © 2022 Jimenez-Guardeño et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2022/7/18
Y1 - 2022/7/18
N2 - The COVID-19 pandemic has accelerated the need to identify new antiviral therapeutics at pace, including through drug repurposing. We employed a Quadratic Unbounded Binary Optimization (QUBO) model, to search for compounds similar to Remdesivir, the first antiviral against SARS-CoV-2 approved for human use, using a quantum-inspired device. We modelled Remdesivir and compounds present in the DrugBank database as graphs, established the optimal parameters in our algorithm and resolved the Maximum Weighted Independent Set problem within the conflict graph generated. We also employed a traditional Tanimoto fingerprint model. The two methods yielded different lists of lead compounds, with some overlap. While GS-6620 was the top compound predicted by both models, the QUBO model predicted BMS-986094 as second best. The Tanimoto model predicted different forms of cobalamin, also known as vitamin B12. We then determined the half maximal inhibitory concentration (IC50) values in cell culture models of SARS-CoV-2 infection and assessed cytotoxicity. We also demonstrated efficacy against several variants including SARS-CoV-2 Strain England 2 (England 02/2020/407073), B.1.1.7 (Alpha), B.1.351 (Beta) and B.1.617.2 (Delta). Lastly, we employed an in vitro polymerization assay to demonstrate that these compounds directly inhibit the RNA-dependent RNA polymerase (RdRP) of SARS-CoV-2. Together, our data reveal that our QUBO model performs accurate comparisons (BMS-986094) that differed from those predicted by Tanimoto (different forms of vitamin B12); all compounds inhibited replication of SARS-CoV-2 via direct action on RdRP, with both models being useful. While Tanimoto may be employed when performing relatively small comparisons, QUBO is also accurate and may be well suited for very complex problems where computational resources may limit the number and/or complexity of possible combinations to evaluate. Our quantum-inspired screening method can therefore be employed in future searches for novel pharmacologic inhibitors, thus providing an approach for accelerating drug deployment.
AB - The COVID-19 pandemic has accelerated the need to identify new antiviral therapeutics at pace, including through drug repurposing. We employed a Quadratic Unbounded Binary Optimization (QUBO) model, to search for compounds similar to Remdesivir, the first antiviral against SARS-CoV-2 approved for human use, using a quantum-inspired device. We modelled Remdesivir and compounds present in the DrugBank database as graphs, established the optimal parameters in our algorithm and resolved the Maximum Weighted Independent Set problem within the conflict graph generated. We also employed a traditional Tanimoto fingerprint model. The two methods yielded different lists of lead compounds, with some overlap. While GS-6620 was the top compound predicted by both models, the QUBO model predicted BMS-986094 as second best. The Tanimoto model predicted different forms of cobalamin, also known as vitamin B12. We then determined the half maximal inhibitory concentration (IC50) values in cell culture models of SARS-CoV-2 infection and assessed cytotoxicity. We also demonstrated efficacy against several variants including SARS-CoV-2 Strain England 2 (England 02/2020/407073), B.1.1.7 (Alpha), B.1.351 (Beta) and B.1.617.2 (Delta). Lastly, we employed an in vitro polymerization assay to demonstrate that these compounds directly inhibit the RNA-dependent RNA polymerase (RdRP) of SARS-CoV-2. Together, our data reveal that our QUBO model performs accurate comparisons (BMS-986094) that differed from those predicted by Tanimoto (different forms of vitamin B12); all compounds inhibited replication of SARS-CoV-2 via direct action on RdRP, with both models being useful. While Tanimoto may be employed when performing relatively small comparisons, QUBO is also accurate and may be well suited for very complex problems where computational resources may limit the number and/or complexity of possible combinations to evaluate. Our quantum-inspired screening method can therefore be employed in future searches for novel pharmacologic inhibitors, thus providing an approach for accelerating drug deployment.
UR - http://www.scopus.com/inward/record.url?scp=85135381323&partnerID=8YFLogxK
U2 - https://doi.org/10.1371/journal.pcbi.1010330
DO - https://doi.org/10.1371/journal.pcbi.1010330
M3 - Article
SN - 1553-734X
VL - 18
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 7
M1 - e1010330
ER -