Identification of oral therapeutics using an AI platform against the virus responsible for COVID-19, SARS-CoV-2
Adam Bess, Frej Berglind, Supratik Mukhopadhyay, Michal Brylinski, Chris Alvin, Fanan Fattah, Kishor M Wasan
Frontiers in Pharmacology, doi:10.3389/fphar.2023.1297924
Purpose: This study introduces a sophisticated computational pipeline, eVir, designed for the discovery of antiviral drugs based on their interactions within the human protein network. There is a pressing need for cost-effective therapeutics for infectious diseases (e.g., , particularly in resourcelimited countries. Therefore, our team devised an Artificial Intelligence (AI) system to explore repurposing opportunities for currently used oral therapies. The eVir system operates by identifying pharmaceutical compounds that mirror the effects of antiviral peptides (AVPs)-fragments of human proteins known to interfere with fundamental phases of the viral life cycle: entry, fusion, and replication. eVir extrapolates the probable antiviral efficacy of a given compound by analyzing its established and predicted impacts on the human protein-protein interaction network. This innovative approach provides a promising platform for drug repurposing against SARS-CoV-2 or any virus for which peptide data is available.
Methods: The eVir AI software pipeline processes drug-protein and proteinprotein interaction networks generated from open-source datasets. eVir uses Node2Vec, a graph embedding technique, to understand the nuanced connections among drugs and proteins. The embeddings are input a Siamese Network (SNet) and MLPs, each tailored for the specific mechanisms of entry, fusion, and replication, to evaluate the similarity between drugs and AVPs. Scores generated from the SNet and MLPs undergo a Platt probability calibration and are combined into a unified score that gauges the potential antiviral efficacy of a drug. This integrated approach seeks to boost drug identification confidence, offering a potential solution for detecting therapeutic candidates with pronounced antiviral potency. Once identified a number of compounds were tested for efficacy and toxicity in lung carcinoma cells (Calu-3) infected with SARS-CoV-2. A lead compound was further identified to determine its efficacy and toxicity in K18-hACE2 mice infected with SARS-CoV-2. Computational Predictions: The SNet confidently differentiated between similar and dissimilar drug pairs with an accuracy of 97.28% and AUC of 99.47%.
Ethics statement Ethical approval was not required for the studies on humans in accordance with the local legislation and institutional requirements because only commercially available established cell lines were used. The animal study was approved by This animal work was done at IITRI CRO which has appropriate ethics approval. The study was conducted in accordance with the local legislation and institutional requirements.
Author contributions
Conflict of interest Author KW has stock options in Skymount Medical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Abou Dalle, Kantarjian, Burger, Estrov, Ohanian et al., Efficacy and safety of generic imatinib after switching from original imatinib in patients treated for chronic myeloid leukemia in the United States, Cancer Med,
doi:10.1002/cam4.2545Ariey-Bonnet, Carrasco, Le Grand, Hoffer, Betzi et al., In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor, Mol. Oncol,
doi:10.1002/1878-0261.12810Assaad, Assaad-Khalil, Imatinib a Tyrosine Kinase Inhibitor: a potential treatment for SARS-COV-2 induced pneumonia, Alexandria J. Med,
doi:10.1080/20905068.2020.1778417Bess, Berglind, Mukhopadhyay, Brylinski, Griggs et al., Artificial intelligence for the discovery of novel antimicrobial agents for emerging infectious diseases, Drug Discov. Today,
doi:10.1016/j.drudis.2021.10.022Bess, None
Bess, None
Bess, None
Dalziel, Round, Garside, Stein, Cost effectiveness of imatinib compared with interferon-alpha or hydroxycarbamide for first-line treatment of chronic myeloid leukaemia, Pharmacoeconomics,
doi:10.2165/00019053-200523050-00010Dittmar, Lee, Whig, Segrist, Li et al., Drug repurposing screens reveal cell-type-specific entry pathways and FDA-approved drugs active against SARS-Cov-2, Cell Rep,
doi:10.1016/j.celrep.2021.108959Drew, Wallingford, Marcotte, MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies, Mol. Syst. Biol,
doi:10.15252/msb.202010016Gancheva, Virchis, Howard-Reeves, Cross, Brazma et al., Myeloproliferative neoplasm with ETV6-ABL1 fusion: a case report and literature review, Mol. Cytogenet,
doi:10.1186/1755-8166-6-39García, Cooper, Shi, Bornmann, Carrion et al., Productive replication of ebola virus is regulated by the c-Abl1 tyrosine kinase, Sci. Transl. Med,
doi:10.1126/scitranslmed.3003500Gargouri, Alzwi, Abobaker, Cyclin dependent kinase inhibitors as a new potential therapeutic option in management of COVID-19, Med. Hypotheses,
doi:10.1016/j.mehy.2020.110380Gassen, Papies, Bajaj, Emanuel, Dethloff et al., SARS-CoV-2-mediated dysregulation of metabolism and autophagy uncovers host-targeting antivirals, Nat. Commun,
doi:10.1038/s41467-021-24007-wGilson, Liu, Baitaluk, Nicola, Hwang et al., BindingDB in 2015: a public database for medicinal chemistry, computational chemistry and systems pharmacology, Nucleic Acids Res,
doi:10.1093/nar/gkv1072Giurgiu, Reinhard, Brauner, Dunger-Kaltenbach, Fobo et al., CORUM: the comprehensive resource of mammalian protein complexes-2019, Nucleic Acids Res,
doi:10.1093/nar/gky973Grover, Leskovec, Node2vec: scalable feature learning for networks
Hancock, Haney, Gill, The immunology of host defence peptides: beyond antimicrobial activity, Nat. Rev. Immunol,
doi:10.1038/nri.2016.29Kantarjian, Larson, Guilhot, O'brien, Mone et al., Efficacy of imatinib dose escalation in patients with chronic myeloid leukemia in chronic phase, Cancer,
doi:10.1002/cncr.24066Klann, Bojkova, Tascher, Ciesek, Münch et al., Growth factor receptor signaling inhibition prevents SARS-CoV-2 replication, Mol. Cell,
doi:10.1016/j.molcel.2020.08.006Koch, Siamese neural networks for one-shot image recognition
Kuhlmann, Fleckenstein, Antiparasitic agents, Infectious diseases
Lazebnik, Cell fusion as a link between the SARS-CoV-2 spike protein, COVID-19 complications, and vaccine side effects, Oncotarget,
doi:10.18632/oncotarget.28088Liu, Lin, Wen, Jorissen, Gilson, BindingDB: a webaccessible database of experimentally determined protein-ligand binding affinities, Nucleic Acids Res,
doi:10.1093/nar/gkl999Liu, Naderi, Alvin, Mukhopadhyay, Brylinski, Break down in order to build up: decomposing small molecules for fragment-based drug design with eMolFrag, J. Chem. Inf. Model,
doi:10.1021/acs.jcim.6b00596Maxwell, Sanders, Sabot, Hachem, Llanos-Cuentas et al., COVID-19 therapeutics for low-and middle-income countries: a review of candidate agents with potential for near-term use and impact, Am. J. Trop. Med. Hyg,
doi:10.4269/ajtmh.21-0200Mering, Huynen, Jaeggi, Schmidt, Bork et al., STRING: a database of predicted functional associations between proteins, Nucleic Acids Res,
doi:10.1093/nar/gkg034Mikolov, Chen, Corrado, Dean, Efficient estimation of Word representations in vector space
Mikolov, Sutskever, Chen, Corrado, Dean, Distributed representations of words and phrases and their compositionality
Naderi, Alvin, Ding, Mukhopadhyay, Brylinski, A graphbased approach to construct target-focused libraries for virtual screening, J. Cheminform,
doi:10.1186/s13321-016-0126-6Niculescu-Mizil, Caruana, Obtaining calibrated probabilities from boosting
Niculescu-Mizil, Caruana, Predicting good probabilities with supervised learning
Pickard, Calverley, Chang, Garva, Gago et al., Discovery of re-purposed drugs that slow SARS-CoV-2 replication in human cells, PLoS Pathog,
doi:10.1371/journal.ppat.1009840Pu, Naderi, Liu, Wu, Mukhopadhyay et al., eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates, BMC Pharmacol. Toxicol,
doi:10.1186/s40360-018-0282-6Qureshi, Thakur, Tandon, Kumar, AVPdb: a database of experimentally validated antiviral peptides targeting medically important viruses, Nucleic Acids Res,
doi:10.1093/nar/gkt1191Reeves, Smith, Olson, Thorne, Bornmann et al., Variola and monkeypox viruses utilize conserved mechanisms of virion motility and release that depend on abl and Src family tyrosine kinases, J. Virol,
doi:10.1128/jvi.01814-10Sasaki, Ramesh, Chada, Gomyo, Roth et al., The anthelmintic drug mebendazole induces mitotic arrest and apoptosis by depolymerizing tubulin in non-small cell lung cancer cells, Mol. Cancer Ther
Shcherbakov, Ei, Firsova, The mebendazole treatment of patients with alveolar echinococcosis, Med. Parazitol. Mosk
Simbulan-Rosenthal, Dakshanamurthy, Gaur, Chen, Fang et al., The repurposed anthelmintic mebendazole in combination with trametinib suppresses refractory NRASQ61K melanoma, Oncotarget,
doi:10.18632/oncotarget.14990Snel, Lehmann, Bork, Huynen, STRING: a web-server to retrieve and display the repeatedly occurring neighbourhood of a gene, Nucleic Acids Res,
doi:10.1093/nar/28.18.3442Szklarczyk, Gable, Lyon, Junge, Wyder et al., STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets, Nucleic Acids Res,
doi:10.1093/nar/gky1131Szklarczyk, Kirsch, Koutrouli, Nastou, Mehryary et al., The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest, Nucleic Acids Res,
doi:10.1093/nar/gkac1000Talarico, Pignatti, Pazdur, Registration by the European Agency for the Evaluation of Medicinal products (EMEA) of oncology products approved by the Food and Drug Administration (FDA) under accelerated approval (AA) regulations, J. Clin. Oncol,
doi:10.1200/jco.2005.23.16_suppl.6054Wang, Yang, The therapeutic potential of natural dietary flavonoids against SARS-CoV-2 infection, Nutrients,
doi:10.3390/nu15153443Weston, Coleman, Haupt, Logue, Matthews et al., Broad anti-coronavirus activity of food and drug administration-approved drugs against SARS-CoV-2 in vitro and SARS-CoV in vivo, J. Virol,
doi:10.1128/JVI.01218-20Wishart, Feunang, Guo, Lo, Marcu et al., DrugBank 5.0: a major update to the DrugBank database for 2018, Nucleic Acids Res,
doi:10.1093/nar/gkx1037Wishart, Knox, Guo, Cheng, Shrivastava et al., DrugBank: a knowledgebase for drugs, drug actions and drug targets, Nucleic Acids Res,
doi:10.1093/nar/gkm958Wishart, Knox, Guo, Shrivastava, Hassanali et al., DrugBank: a comprehensive resource for in silico drug discovery and exploration, Nucleic Acids Res,
doi:10.1093/nar/gkj067
