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Potential Therapeutic Agents and Associated Bioassay Data for COVID-19 and Related Human Coronavirus Infections.

ABSTRACT: The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has led to several million confirmed cases and hundreds of thousands of deaths worldwide. To support the ongoing research and development of COVID-19 therapeutics, this report provides an overview of protein targets and corresponding potential drug candidates with bioassay and structure-activity relationship data found in the scientific literature and patents for COVID-19 or related virus infections. Highlighted are several sets of small molecules and biologics that act on specific targets, including 3CLpro, PLpro, RdRp, S-protein-ACE2 interaction, helicase/NTPase, TMPRSS2, and furin, which are involved in the viral life cycle or in other aspects of the disease pathophysiology. We hope this report will be valuable to the ongoing drug repurposing efforts and the discovery of new therapeutics with the potential for treating COVID-19.

SUBMITTER: Zhou QA

PROVIDER: S-EPMC7447080 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Potential Therapeutic Agents and Associated Bioassay Data for COVID-19 and Related Human Coronavirus Infections.

Zhou Qiongqiong Angela QA Kato-Weinstein Junko J Li Yingzhu Y Deng Yi Y Granet Roger R Garner Linda L Liu Cynthia C Polshakov Dmitrii D Gessner Chris C Watkins Steven S

ACS pharmacology & translational science 20200730 5

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has led to several million confirmed cases and hundreds of thousands of deaths worldwide. To support the ongoing research and development of COVID-19 therapeutics, this report provides an overview of protein targets and corresponding potential drug candidates with bioassay and structure-activity relationship data found in the scientific literature and patents for COVID-19 or related virus infections. Highlighted are several sets ...[more]

PMID: 33062950

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Project description:Focused screening on target-prioritized compound sets can be an efficient alternative to high throughput screening (HTS). For most biomolecular targets, compound prioritization models depend on prior screening data or a target structure. For phenotypic or multi-protein pathway targets, it may not be clear which public assay records provide relevant data. The question also arises as to whether data collected from disparate assays might be usefully consolidated. Here, we report on the development and application of a data mining pipeline to examine these issues. To illustrate, we focus on identifying inhibitors of oxidative phosphorylation, a druggable metabolic process in epithelial ovarian tumors. The pipeline compiled 8415 available OXPHOS-related bioassays in the PubChem data repository involving 312,093 unique compound records. Application of PubChem assay activity annotations, PAINS (Pan Assay Interference Compounds), and Lipinski-like bioavailability filters yields 1852 putative OXPHOS-active compounds that fall into 464 clusters. These chemotypes are diverse but have relatively high hydrophobicity and molecular weight but lower complexity and drug-likeness. These chemotypes show a high abundance of bicyclic ring systems and oxygen containing functional groups including ketones, allylic oxides (alpha/beta unsaturated carbonyls), hydroxyl groups, and ethers. In contrast, amide and primary amine functional groups have a notably lower than random prevalence. UMAP representation of the chemical space shows strong divergence in the regions occupied by OXPHOS-inactive and -active compounds. Of the six compounds selected for biological testing, 4 showed statistically significant inhibition of electron transport in bioenergetics assays. Two of these four compounds, lacidipine and esbiothrin, increased in intracellular oxygen radicals (a major hallmark of most OXPHOS inhibitors) and decreased the viability of two ovarian cancer cell lines, ID8 and OVCAR5. Finally, data from the pipeline were used to train random forest and support vector classifiers that effectively prioritized OXPHOS inhibitory compounds within a held-out test set (ROCAUC 0.962 and 0.927, respectively) and on another set containing 44 documented OXPHOS inhibitors outside of the training set (ROCAUC 0.900 and 0.823). This prototype pipeline is extensible and could be adapted for focus screening on other phenotypic targets for which sufficient public data are available.Scientific contributionHere, we describe and apply an assay data mining pipeline to compile, process, filter, and mine public bioassay data. We believe the procedure may be more broadly applied to guide compound selection in early-stage hit finding on novel multi-protein mechanistic or phenotypic targets. To demonstrate the utility of our approach, we apply a data mining strategy on a large set of public assay data to find drug-like molecules that inhibit oxidative phosphorylation (OXPHOS) as candidates for ovarian cancer therapies.

Project description:The ongoing pandemic coronavirus disease 19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a matter of global concern. Environmental factors such as air pollution and smoking and comorbid conditions (hypertension, diabetes mellitus and underlying cardio-respiratory illness) likely increase the severity of COVID-19. Rheumatic manifestations such as arthralgias and arthritis may be prevalent in about a seventh of individuals. COVID-19 can result in acute interstitial pneumonia, myocarditis, leucopenia (with lymphopenia) and thrombocytopenia, also seen in rheumatic diseases like lupus and Sjogren's syndrome. Severe disease in a subset of patients may be driven by cytokine storm, possibly due to secondary hemophagocytic lymphohistiocytosis (HLH), akin to that in systemic onset juvenile idiopathic arthritis or adult-onset Still's disease. In the absence of high-quality evidence in this emerging disease, understanding of pathogenesis may help postulate potential therapies. Angiotensin converting enzyme 2 (ACE2) appears important for viral entry into pneumocytes; dysbalance in ACE2 as caused by ACE inhibitors or ibuprofen may predispose to severe disease. Preliminary evidence suggests potential benefit with chloroquine or hydroxychloroquine. Antiviral drugs like lopinavir/ritonavir, favipiravir and remdesivir are also being explored. Cytokine storm and secondary HLH might require heightened immunosuppressive regimens. Current international society recommendations suggest that patients with rheumatic diseases on immunosuppressive therapy should not stop glucocorticoids during COVID-19 infection, although minimum possible doses may be used. Disease-modifying drugs should be continued; cessation may be considered during infection episodes as per standard practices. Development of a vaccine may be the only effective long-term protection against this disease.Key Points• Patients with coronavirus disease 19 (COVID-19) may have features mimicking rheumatic diseases, such as arthralgias, acute interstitial pneumonia, myocarditis, leucopenia, lymphopenia, thrombocytopenia and cytokine storm with features akin to secondary hemophagocytic lymphohistiocytosis.• Although preliminary results may be encouraging, high-quality clinical trials are needed to better understand the role of drugs commonly used in rheumatology like hydroxychloroquine and tocilizumab in COVID-19.• Until further evidence emerges, it may be cautiously recommended to continue glucocorticoids and other disease-modifying antirheumatic drugs (DMARDs) in patients receiving these therapies, with discontinuation of DMARDs during infections as per standard practice.

Dataset Information

Potential Therapeutic Agents and Associated Bioassay Data for COVID-19 and Related Human Coronavirus Infections.

Publications

Potential Therapeutic Agents and Associated Bioassay Data for COVID-19 and Related Human Coronavirus Infections.

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