Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries

Masoudi-Sobhanzadeh, Yosef; Salemi, Aysan; Pourseif, Mohammad M.; Jafari, Behzad; Omidi, Yadollah; Masoudi‐Nejad, Ali

doi:10.1093/bib/bbab113

Cited by 16 publications

(13 citation statements)

References 98 publications

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“…Naturally, this causes problems when using a rigid docking method in the drug repurposing workflow. [27] False-positives that are identified through virtual screening and sent forth for assay or clinical testing can potentially waste valuable time and resources. [28] Potential hits from a rigid docking screening method require additional validation (e.g., with MD) before consideration with experimental analysis.…”

Section: Strategymentioning

confidence: 99%

“…This is a feature unqiue to flexible docking methods, and is an important component when considering using molecular docking in drug design and drug repurposing. [27] Modern antiviral compounds are often very large molecules, and without "opening" up the active site, a rigid docking method will struggle to accomodate a large antiviral in a confined active site. Consequently, a rigid docking method may reject that particular protein-ligand docking outright if atoms overlap or steric clashes are too high to find an energy minimum.…”

Section: Cifdockmentioning

confidence: 99%

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Identification of Potential SARS-CoV-2 Inhibitors Using Flexible Docking Based Drug Repurposing of Antivirals

Warrensford

Pittman

Kearns

et al. 2022

Preprint

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A selection of antiviral compounds from the Drug Repurposing Hub were screened as potential inhibitors against SARS-CoV-2 protein targets using CIFDock, a flexible docking method. CIFDock allows for a fully flexible active site of the protein-ligand complex and retaining of explicit water molecules throughout docking simulations. This method provides a more thorough conformational space search than is attainable by rigid docking methods, and thus a more accurate representation of the binding interactions between these antiviral compounds and the SARS-CoV-2 protein targets. Four proteins critical to viral function were selected as targets of the study: the main protease (Mpro), the papain-like protease (PLpro), the transmembrane protease (TMPRSS2), and the RNA-dependent RNA-polymerase (RdRp). The results reveal potential SARS-CoV-2 viral inhibitors from this library of antivirals, based on favorable Glide scores of the docked protein-ligand poses. The antiviral compounds brecanavir, mozenavir, palinavir, sovaprevir, and telinavir yielded excellent binding scores across all protease targets. Additionally, these particular antivirals have not yet been investigated in clinical trials nor in vitro studies regarding COVID-19. Therefore, these compounds can be recommended for further research against SARS-CoV-2, based on extensive docking analysis with relevant protein targets.

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Section: Strategymentioning

confidence: 99%

Section: Cifdockmentioning

confidence: 99%

Identification of Potential SARS-CoV-2 Inhibitors Using Flexible Docking Based Drug Repurposing of Antivirals

Warrensford

Pittman

Kearns

et al. 2022

Preprint

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“…For the repurposing of drugs, researchers have proposed various approaches such as in silico, in vitro, and in vivo techniques. 13 Computational methods are at the center of the attention for researchers since they reduce time and produce helpful solutions. 14,15 In this study, the computational techniques have been divided into several categories as follows: i) Molecular docking techniques: most of the carried out studies fall into this class of computational methods and consider the 3D structure of SARS-CoV-2's proteins and existing drugs.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A fuzzy logic-based computational method for the repurposing of drugs against COVID-19

2021

Self Cite

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Introduction: COVID-19 has spread out all around the world and seriously interrupted human activities. Being a newfound disease, not only many aspects of the disease are unknown, but also there is not an effective medication to cure the disease. Besides, designing a drug is a time-consuming process and needs large investment. Hence, drug repurposing techniques, employed to discover the hidden benefits of the existing drugs, maybe a useful option for treating COVID-19. Methods: The present study exploits the drug repositioning concepts and introduces some candidate drugs which may be effective in controlling COVID-19. The suggested method consists of three main steps. First, the required data such as the amino acid sequences of targets and drug-target interactions are extracted from the public databases. Second, the similarity score between the targets (protein/enzymes) and genome of SARS-COV-2 is computed using the proposed fuzzy logic-based method. Since the classical approaches yield outcomes which may not be useful for the real-world applications, the fuzzy technique can address the issue. Third, after ranking targets based on the obtained scores, the usefulness of drugs affecting them is examined for managing COVID-19. Results: The results indicate that antiviral medicines, designed for curing hepatitis C, may also cure COVID-19. According to the findings, ribavirin, simeprevir, danoprevir, and XTL-6865 may be helpful in controlling the disease. Conclusion: It can be concluded that the similarity-based drug repurposing techniques may be the most suitable option for managing emerging diseases such as COVID-19 and can be applied to a wide range of data. Also, fuzzy logic-based scoring methods can produce outcomes which are more consistent with the real-world biological applications than others.

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“…For instance, one widely used methodology is the network-based approach, which can integrate different data sources, including omics data and drug–protein–disease interaction networks [ 16 , 19 , 20 , 21 ]. Another methodology is the structure-based approach, which enables a large number of compounds to be screened for their ability to bind to known or predicted molecular targets for COVID-19 treatment [ 16 , 22 , 23 , 24 , 25 ]. These methodologies are promising but may have their limitations.…”

Section: Introductionmentioning

confidence: 99%

Exploring Drugs and Vaccines Associated with Altered Risks and Severity of COVID-19: A UK Biobank Cohort Study of All ATC Level-4 Drug Categories Reveals Repositioning Opportunities

Xiang

Wong

2021

Pharmaceutics

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Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of prior use of all level-4 ATC drug categories (N = 819, including vaccines) with COVID-19 diagnosis and severity. Effects of drugs on the risk of infection, disease severity, and mortality were investigated separately. Logistic regression was conducted, controlling for main confounders. We observed strong and highly consistent protective associations with statins. Many top-listed protective drugs were also cardiovascular medications, such as angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), calcium channel blocker (CCB), and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones, proton pump inhibitors, and testosterone-5-alpha reductase inhibitors, among others. We also observed protective associations by influenza, pneumococcal, and several other vaccines. Subgroup and interaction analyses were also conducted, which revealed differences in protective effects in various subgroups. For example, protective effects of flu/pneumococcal vaccines were weaker in obese individuals, while protection by statins was stronger in cardiovascular patients. To conclude, our analysis revealed many drug repositioning candidates, for example several cardiovascular medications. Further studies are required for validation.

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Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries

Cited by 16 publications

References 98 publications

Identification of Potential SARS-CoV-2 Inhibitors Using Flexible Docking Based Drug Repurposing of Antivirals

Identification of Potential SARS-CoV-2 Inhibitors Using Flexible Docking Based Drug Repurposing of Antivirals

A fuzzy logic-based computational method for the repurposing of drugs against COVID-19

Exploring Drugs and Vaccines Associated with Altered Risks and Severity of COVID-19: A UK Biobank Cohort Study of All ATC Level-4 Drug Categories Reveals Repositioning Opportunities

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