Pharma Focus Asia

Repurposed Drugs against the Latest Variants of Concerns of SARS-CoV-2

Sinosh Skariyachan, Department of Microbiology, St. Pius X College

The present concern of COVID-19 is the rapid emergence of variants of concern of SARS-CoV-2 such as Omicron that showed high transmission potential. Thus, discovering potential drug candidates is one of the utmost concerns. Repurposing FDA-approved drugs that are already in use is probably one of the promising strategies, however, such applications require extensive studies and research.


The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) affected all areas of life and the economy by causing COVID-19 and created alarming caution in the form of variants of concerns (VoC). The latest VoC that are of public health relevance are Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). Due to the emerging spread of these VoCs, several vaccines that are already approved by the World Health Organisation showed limited activities against VoC and even those who have already been vaccinated with repeated and multiple doses are susceptible to the infection. Thus, identifying potential solutions and probable therapeutics have high scope and relevance in pharmaceutical sectors. While conventional drug discovery pipelines against any new infections are a tedious task with complexity, initial investments, manpower, and time, computational drug discovery with the aid of data sciences is gaining attention in the pharmaceutical sectors. The latest developments in computational biology have led to the enhanced scope of drug repurposing via the approaches such as structure-based screening techniques like molecular profiling and target identification, molecular docking, molecular dynamic simulations, quantitative structure-activity relationships, network-based approaches, and artificial intelligence and machine and deep learning algorithms.

Drug repurposing: A new paradigm shift of old strategies

The concept of drug repurposing attains attention in clinical trials that substantially reduce the time and cost in new drug developments. Drug repurposing, otherwise known as drug repositioning, is the approach of utilising existing and FDA-approved drugs for treating infections and diseases including several emerging infections. Drug repurposing is rational and fascinating approach, providing less time and cost requirements for specific drug screening and development. Several potential drugs do not enter clinical trials, and less than 15% of the lead candidates get approval. There are several examples of repurposed drugs are in practice that included aspirin, the cyclooxygenase inhibitor for coronary heart disease, sildenafil, a phosphodiesterase inhibitor for erectile dysfunction, antibiotic erythromycin for gastric motility and thalidomide, an antiemetic against multiple myeloma. At present, there is considerable scope in the repurposing of drugs to enhance the identification of lead molecules that can prevent or treat COVID-19. The major aspects of drug repositioning are to enhance the traditional drug development approaches by searching for safe, novel, and effective drugs in humans. The primary focus for these aspects is the application of drugs that have the same molecular pathways but are involved in various diseases. The major mechanism of drug repurposing is depending on the type and nature of the molecular targets to which the drugs are delivered. One of the major drivers of drug repurposing has been the accidental discovery of the pharmacological properties of new molecular targets, indicating an innovative use of drugs. For example, FDA-approved drugs such as ritonavir and lopinavir have been extensively used against Human Immunodeficiency Virus-1 and 2 (HIV). These drugs were also suggested repurposed for the treatment of COVID-19. This is due to the fact of the likeness of the SARS-CoV and MERS-CoV (beta coronavirus) genome sequences to SARS-CoV-2. Therefore, the drugs that have been utilised for the treatment of MERS-CoV and SARS-CoV-2 were probably employed for the treatment of the VoC causing COVID-19, which implies that the action mechanism of repurposed drugs toward their targets must be like their family target members. The administration of such drugs to patients with moderate COVID-19 infections showed a substantial response which confirms the concept of drug repurposing. The major aspects of drug repurposing depend on two scientific facts: the screening of drugs based on the interpretation of the human genome which share the common targets in cases of several diseases, and the idea of pleiotropic drugs.

The main road map of computational drug repurposing started with the mining of primary drug data, their target, and the disease. A drug-disease pathway is constructed and their features will be extracted and filtered thoroughly. A computer-aided analysis is performed via the approaches such as machine learning that involve the structural analysis of the drug compounds.The repurposing of the drug is known to reduce the costs required for the development of a new lead candidate, with extra savings in pre-clinical phases I and II. Furthermore, concerning COVID-19 research, the scope of repurposing also has applications in several areas such as precision medicine, rapid therapeutic options, screening of multiple purposes for existing drugs, and identification of direct-acting and host-targeting antivirals.

The elucidation of detailed molecular mechanisms between the interaction of drugs and their molecular targets is a critical component in the discovery of drugs. Though various biophysical and biochemical approaches are available to study the molecular interactions of the small compounds with their targets, the powerful approach is structure-based computational biology aspects which can assist in predicting the molecular basis of the interaction between the complexes. Thus, repurposing the drug is an attractive and alternative approach to identifying the appropriate lead candidates from the existing diverse and focused libraries, to combat diseases. When concerning the developments in multiplex assays, data mining, cell-based screening, bioinformatics, and chem-informatics approaches, and the utilisation of their databases, pharmaceutical industries have demonstrated greater interest in screening molecules that showed failures due to several reasons. Three major steps are essential before the process of repurposing drugs. Firstly, the identification of drug molecules for the specific disease. Secondly, evaluation and assessment of the selected drug compounds in pre-clinical models. Thirdly, evaluation of safety in phase II clinical trials. The repurposing of the drugs can be classified into experimental and computational techniques. With the aid of combinatorial approaches to these aspects, better outcomes can be achieved than when they are used individually.  The computational approaches are highly data-driven approaches that necessitate the utilisation of genetic expressions, structural analysis of lead compounds, and the proteomic data of drug candidates. The computational medicinal chemistry approaches provide a pivotal role in the drug repurposing process.

Structure‑based drug discovery

The structure-based approach namely virtual screening helps to identify small molecules from currently available repositories that can be utilised for repurposing. The studies have utilised molecular docking approaches for virtual screening against the potential targets of SARS-CoV-2, such as the main protease for the repurposing of probable drugs such as β-eudesmol, digitoxigenin, ritonavir, hesperidin, rutin, indinavir, crocin, and emetine. In addition, the other virtual screening approaches such as combinations of molecular docking with molecular dynamic (MD) simulations and free energy binding calculations by MM-GBSA studies and two-way molecular docking with computational ADMET prediction studies for COVID-19 drug repurposing. The major strategies used for the structure-based screening of drug repurposing are molecular docking, MD simulations, and quantitative structure-activity relationship analysis

Network‑based drug discovery

Network-based strategies are used in drug repurposing due to the potential of merging and integrating several data sources. The latest developments in high-throughput and computational screening techniques permit the network modelling of biological systems that enables structure-guided pharmaceutical research with the scope of identification of novel molecular targets. The major aspects used for repurposing drugs are the analysis of drug-target networks, drug-drug networks, and drug-disease networks. Though there are several approaches in practice, two major types of computational network-based approaches are network-based propagation and network-based clustering approaches. Previous studies have successfully employed PPI networkclustering and disease-gene network propagation to predict the disease-gene relationships for the repurposing of various drugs.

Artificial intelligence-driven techniques

Artificial intelligence (AI) technology was recently employed for drug repurposing for COVID-19 research. A deep-learning approach was used to screen several repurposed molecules with anti-SARS-CoV-2- activities and validated experimentally. The previously trained deep-learning prediction model was used for the study of drug-target interactions. This model is termed Molecule Transformer-Drug Target Interaction (MT-DTI) which is used to screen commercially available antiviral drugs that target the major targets of SARS-CoV-2 such as proteinase, helicase, and RNA-dependent RNA polymerase (RDRP). AI-based strategies provide support rapidly by accessing COVID-19 resources including databases, web servers, computational tools, and mathematical and predictive models which decrease the period required for drug development.

Major repurposed drugs suggested for COVID-19

The FDA-approved drugs such as ritonavir, lopinavir, carmofur, boceprevir, and doxycycline target the SARS-CoV-2 main protease or 3-chymotrypsin-like proteins and 16 non-structural proteins. Platycodin and Fostamatinib disodium bind with Nsp3 proteins. The drugs such as remdesivir, ribavirin, and favipiravir interact with RNA-dependent RNA polymerases (RdRp, Nsp12) of SARS-CoV-2. The drugs namely vapreotide, daclatasvir, atazanavir, and bismuth potassium citrate inhibit the helicase (Nsp13) of SARS-CoV-2. Similarly, dinucleoside 123 and raltegravir affect methyltransferases (Guanine-N7-methyltransferase, 2’-O-methyltransferase), while memantine and gliclazide inhibit the envelope protein SARS-CoV-2. It was suggested that chloroquine and arbidolntarget the spike protein of SARS CoV-2.  Losartan and captopril block the activity of ACE receptors and camostat mesylate blocked the transmembrane protease serine 2 (TMPRSS2), hydroxychloroquine inhibit the specific proteinase called cathepsin L. Further, oseltamivir and sitagliptin block the activity of DPP4 cell receptors and viral neuraminidases. The drugs such as nitrofurantoin, ergoloid pemirolast, hypericin, isoniazid pyruvate, eridictoyl, and cepharanthine block the ACE2 receptor of human and the S protein of SARS-CoV-2. baricitinib is inhibited the Janus kinase pathway, efavirenz has inhibited the enzymes such as helicase, RdRp, exo-nuclease, and methyltransferase of SARS-CoV-2. Mefuparib hydrochloride blocks the activity of poly [ADP-ribose] polymerase 1 (PARP-1). The drugs such as sirolimus, mercaptopurine toremifene, dactinomycin, irbesartan, emodin, and melatonin block the activity of glycogen synthase kinase 3 (GSK-3), and NF-kappa B signalling pathways.The drugs such as ivermectin, nitazoxanide, and azithromycin also inhibit various virulent factors of SARS-CoV-2. Further, paritaprevir is active against 3 chymotrypsin-like proteins/SARS-CoV-2 main protease. Ledipasvir,sirolimus, and vancomycin target the ACE2-SARS-CoV-2-RBD complex. FDA-approved abemaciclib, olaparib, capmatinib, irinotecan, estradiol benzoate, lumacaftor, and pazopanib block various activities of CD147with SARS-CoV spike protein. Furthermore, rifabutin, nilotinib, dihydroergotamine, dactinomycin, bromocriptine, entrectinib, elbasvir, selinexor, rifapentine, quinupristin, rutin, diosmin, digitoxin, and antrafenine interact with 3-chymotrypsin-like proteins/SARS-CoV-2 main protease and demonstrated the therapeutic effect. Although these drugs are being suggested as a potential treatment against COVID-19 variants, several ethical concerns ascend regarding the application of such drugs without adequate clinical trials that are approved by the FDA.

According to the latest reports from the US National Library of Medicine Clinical trial application programming interface, several repurposed drugs have enteredvarious phases of clinical trials. The FDA drugs such as pioglitazone completed the phase four clinical trials, while, remdesivir, lopinavir/ ritonavir, interferon beta-1A, hydroxychloroquine, and AZD7442 have entered phase 3 clinical trials. Silmitasertib, leronlimab, duvelisib, ruconest, and infliximab completed the phase two clinical trials. L-ascorbic acid and aerosolised hydroxychloroquine sulfate have completed the phase -1 clinical trials, these repurposed drugs are expected to have a profound therapeutic impact against the latest variants of SARS-CoV-2.  

The latest studies suggested that main protease (3CLpro, papain-like proteases (PLpro), and RNA-dependent RNA polymerase (RdRp) and helicase are the potential molecular targets of these repurposed drugs, several of these proteins involved in the functions such as protein synthesis, replication, RNA transcription, translation, processing, and infection. majority of the proteins are non-structural proteins (nsps) for coronaviruses.

Impact of variants in molecular targets of SARS-CoV and immune escape mechanism

The mutations in the spike protein of the SARS-CoV-2 and the emergence of the VoC have received much attention and this mutation resulted in spike variations that inclined the recognition of polyclonal antibodies and caused immune escape. The substitution mutation in the receptor-binding domains (RBD) affected the recognition by certain convalescent serums in which E484 with changes to amino acids K, P, or Q demonstrated potential impact.  This mutation is recognised as an escape mutation that is caused when exposed to monoclonal antibodies C144 and C121. E484K mutation was identified to minimise the neutralisation capacity of MAbs REGN10934 and REGN10989. The mutations such as K444E, G446V, L452R, and F490S also escaped several convalescent sera and resulted that SARS-CoV-2 VoC becoming more robust for survival in the human body. Further, the N439K substitution enhanced the ACE2 receptor binding affinity to SARS-CoV-2. This mutation reduced the neutralisation potential of the plasma. However, some mutations did not show a profound impact, for example, N439K has not affected the use of polyclonal antibodies. This variation is probably due to the immune escape caused by the mutation via ACE2 binding affinity than the identification of antibody epitope directly, making the variant important for further studies. The mutation inn-terminal domain (NTD) of the spike protein also caused immune escape. The mutations such as K150T, K150R, S151P,K150E, N148S, and K150Q were identified to be escape mutations. Similarly, Δ140 mutant in the spike protein acquired E484K mutation and directly resulted in the escape of the antibody responses.

Studies clearly showed that the mutation causes changes in the structural antigenicity of SARS-CoV-2 proteins and evades the immune systems. The amino acid changes in the spike glycoprotein that is resulted due to the mutation may adversely affect the binding of the small molecules and repurposed drugs. Thus, more studies are essential to understand the mechanism of the impact of structural and non-structural proteins that are affected by the mutations. These mutations in spike proteins certainly affect the antibodies that probably lead to increased viral resistance at the global level. Thorough knowledge of the sequence data of the viral genome and the impact of variants on the binding pockets of the drug influence the action of the repurposed drugs.

Applications, merits, and demerits of repurposing approaches

Repurposed drugs have several merits and demerits in their direct applications. The major advantages can be at the translational research level, the target level, and the disease level. In addition, the major merits of the repurposed drugs are lower cost of production, the limited period requirement for identifying, effective use, and safe drugs for rapid use, utilisation of bioinformatics and chemoinformatics resources at initial stages that provide a profound breakthrough for future experimental studies. The major chem-bioinformatic approaches to drug repurposing are molecular docking, signature matching, pathway mapping, and genome-wide association studies.

There are several limitations while using repurposed drugs that need to be understood properly. The major limitations are weak intellectual property rights available for repurposed drugs, larger computational operations are required to perform molecular docking studies with existing drugs, the correctly used network-based approaches promote limited promising results, the data-deepened approaches are inaccurate due to the limited volume of existing COVID-19 data, lack of strong solid evidence of the success of the repurposed drugs against COVID-19, lack of experimental outcome for the validation of the modelling and prediction data, the low success rate in new disease settings, extensive data requirement before the repurposing studies, dosing and safety issues are some of the major concerns. In addition, robust, accurate toxicological analysis of repurposed drugs is required before the delivery and testing of the repurposed drugs. Furthermore, it is tedious to find ideal and unique receptor-drug interactions within the restraints of the currently accepted therapeutic systems.


Drug repurposing can be one of the potential futuristic applications for identifying novel therapeutic strategies against the latest VoC of SARS-CoV-2.  It is, of course, one of the new-generation research strategies for treating several emerging and re-emerging infectious diseases, however, their efficacy in comparison with several standard conventional viral vaccines or other small molecules needs to be investigated. Computational biology and data science-driven approaches coupled with a chem-bioinformatics provide significant breakthrough to study the scope and applications of repurposed drugs against the VoC of SARS-CoV. These techniques also contribute substantial foundations and breakthroughs for experimental studies and clinical trials in the future.


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Sinosh Skariyachan

Sinosh Skariyachan, Ph.D. is presently working as Assistant Professor in Microbiology at St. Pius X College, Rajapuram (Aided by Govt. of Kerala, India), Kasaragod, Kerala, India with more than 17 years of experience in teaching and research. One of his key areas of research is computational drug discovery and medicinal chemistry. He has published more than 75 international papers, book chapters, and text books. He is the editor of prestigious journals such as Computers in Biology and Medicine (Elsevier), Frontiers in Microbiology and a referee for more than 125 international journals. He received several awards and grants.

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