Drug Discov Today. 2021 Oct 16:S1359-6446(21)00438-4. doi: 10.1016/j.drudis.2021.10.002. Online ahead of print.

ABSTRACT

In the COVID-19 pandemic, drug repositioning has presented itself as an alternative to the time-consuming process of generating new drugs. This review describes a drug repurposing process that is based on a new data-driven approach: we put forward five information paths that associate COVID-19-related genes and COVID-19 symptoms with drugs that directly target these gene products, that target the symptoms or that treat diseases that are symptomatically or genetically similar to COVID-19. The intersection of the five information paths results in a list of 13 drugs that we suggest as potential candidates against COVID-19. In addition, we have found information in published studies and in clinical trials that support the therapeutic potential of the drugs in our final list.

PMID:34666181 | DOI:10.1016/j.drudis.2021.10.002

Free Radic Biol Med. 2021 Oct 16:S0891-5849(21)00762-0. doi: 10.1016/j.freeradbiomed.2021.08.245. Online ahead of print.

ABSTRACT

As hypoxia is a major driver for the pathophysiology of COVID-19, it is crucial to characterize the hypoxic response at the cellular and molecular levels. In order to augment drug repurposing with the identification of appropriate molecular targets, investigations on therapeutics preventing hypoxic cell damage is required. In this work, we propose a hypoxia model based on alveolar lung epithelial cells line using chemical inducer, CoCl2 that can be used for testing calcium channel blockers (CCBs). Since recent studies suggested that CCBs may reduce the infectivity of SARS-Cov-2, we specifically select FDA approved calcium channel blocker, nifedipine for the study. First, we examined hypoxia-induced cell morphology and found a significant increase in cytosolic calcium levels, mitochondrial calcium overload as well as ROS production in hypoxic A549 cells. Secondly, we demonstrate the protective behaviour of nifedipine for cells that are already subjected to hypoxia through measurement of cell viability as well as 4D imaging of cellular morphology and nuclear condensation. Thirdly, we show that the protective effect of nifedipine is achieved through the reduction of cytosolic calcium, mitochondrial calcium, and ROS generation. Overall, we outline a framework for quantitative analysis of mitochondrial calcium and ROS using 3D imaging in laser scanning confocal microscopy and the open-source image analysis platform ImageJ. The proposed pipeline was used to visualize mitochondrial calcium and ROS level in individual cells that provide an understanding of molecular targets. Our findings suggest that the therapeutic value of nifedipine may potentially be evaluated in the context of COVID-19 therapeutic trials.

PMID:34666149 | DOI:10.1016/j.freeradbiomed.2021.08.245

IEEE J Biomed Health Inform. 2021 Oct 19;PP. doi: 10.1109/JBHI.2021.3120933. Online ahead of print.

ABSTRACT

Disease signature-based drug repositioning approaches typically first identify a disease signature from gene expression profiles of disease samples to represent a particular disease. Then such a disease signature is connected with the drug-induced gene expression profiles to find potential drugs for the particular disease. In order to obtain reliable disease signatures, the size of disease samples should be large enough, which is not always a single case in practice, especially for personalized medicine. On the other hand, the sample sizes of drug-induced gene expression profiles are generally large. In this study, we propose a new drug repositioning approach (HDgS), in which the drug signature is first identified from drug-induced gene expression profiles, and then connected to the gene expression profiles of disease samples to find the potential drugs for patients. In order to take the dependencies among genes into account, the human protein complexes (HPC) are used to define the drug signature. The proposed HDgS is applied to the drug-induced gene expression profiles in LINCS and several types of cancer samples. The results indicate that the HPC-based drug signature can effectively find drug candidates for patients and that the proposed HDgS can be applied for personalized medicine with even one patient sample.

PMID:34665747 | DOI:10.1109/JBHI.2021.3120933

Bioinformatics. 2021 Oct 19:btab715. doi: 10.1093/bioinformatics/btab715. Online ahead of print.

ABSTRACT

MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. Accurately identifying DTIs in silico can significantly shorten development time and reduce costs. Recently, many sequence-based methods are proposed for DTI prediction and improve performance by introducing the attention mechanism. However, these methods only model single non-covalent inter-molecular interactions among drugs and proteins and ignore the complex interaction between atoms and amino acids.

RESULTS: In this paper, we propose an end-to-end bio-inspired model based on the convolutional neural network (CNN) and attention mechanism, named HyperAttentionDTI, for predicting DTIs. We use deep CNNs to learn the feature matrices of drugs and proteins. To model complex non-covalent inter-molecular interactions among atoms and amino acids, we utilize the attention mechanism on the feature matrices and assign an attention vector to each atom or amino acid. We evaluate HpyerAttentionDTI on three benchmark datasets and the results show that our model achieves significantly improved performance compared to the state-of-the-art baselines. Moreover, a case study on the human Gamma-aminobutyric acid receptors confirm that our model can be used as a powerful tool to predict DTIs.

AVAILABILITY: The codes of our model are available at https://github.com/zhaoqichang/HpyerAttentionDTI and https://zenodo.org/record/5039589.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34664614 | DOI:10.1093/bioinformatics/btab715

J Biomol Struct Dyn. 2021 Oct 18:1-17. doi: 10.1080/07391102.2021.1990131. Online ahead of print.

ABSTRACT

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma.

PMID:34662258 | DOI:10.1080/07391102.2021.1990131

Front Med (Lausanne). 2021 Sep 30;8:704256. doi: 10.3389/fmed.2021.704256. eCollection 2021.

ABSTRACT

Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead to enormous losses. This study systematically reviews the application of Artificial Intelligence (AI) techniques in COVID-19, especially for diagnosis, estimation of epidemic trends, prognosis, and exploration of effective and safe drugs and vaccines; and discusses the potential limitations. Methods: We report this systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed, Embase and the Cochrane Library from inception to 19 September 2020 for published studies of AI applications in COVID-19. We used PROBAST (prediction model risk of bias assessment tool) to assess the quality of literature related to the diagnosis and prognosis of COVID-19. We registered the protocol (PROSPERO CRD42020211555). Results: We included 78 studies: 46 articles discussed AI-assisted diagnosis for COVID-19 with total accuracy of 70.00 to 99.92%, sensitivity of 73.00 to 100.00%, specificity of 25 to 100.00%, and area under the curve of 0.732 to 1.000. Fourteen articles evaluated prognosis based on clinical characteristics at hospital admission, such as clinical, laboratory and radiological characteristics, reaching accuracy of 74.4 to 95.20%, sensitivity of 72.8 to 98.00%, specificity of 55 to 96.87% and AUC of 0.66 to 0.997 in predicting critical COVID-19. Nine articles used AI models to predict the epidemic of the COVID-19, such as epidemic peak, infection rate, number of infected cases, transmission laws, and development trend. Eight articles used AI to explore potential effective drugs, primarily through drug repurposing and drug development. Finally, 1 article predicted vaccine targets that have the potential to develop COVID-19 vaccines. Conclusions: In this review, we have shown that AI achieved high performance in diagnosis, prognosis evaluation, epidemic prediction and drug discovery for COVID-19. AI has the potential to enhance significantly existing medical and healthcare system efficiency during the COVID-19 pandemic.

PMID:34660623 | PMC:PMC8514781 | DOI:10.3389/fmed.2021.704256

Front Pharmacol. 2021 Sep 30;12:720694. doi: 10.3389/fphar.2021.720694. eCollection 2021.

ABSTRACT

In the past decade, the emergence of machine learning (ML) applications has led to significant advances towards implementation of personalised medicine approaches for improved health care, due to the exceptional performance of ML models when utilising complex big data. The immune-mediated chronic inflammatory diseases are a group of complex disorders associated with dysregulated immune responses resulting in inflammation affecting various organs and systems. The heterogeneous nature of these diseases poses great challenges for tailored disease management and addressing unmet patient needs. Applying novel ML techniques to the clinical study of chronic inflammatory diseases shows promising results and great potential for precision medicine applications in clinical research and practice. In this review, we highlight the clinical applications of various ML techniques for prediction, diagnosis and prognosis of autoimmune rheumatic diseases, inflammatory bowel disease, autoimmune chronic kidney disease, and multiple sclerosis, as well as ML applications for patient stratification and treatment selection. We highlight the use of ML in drug development, including target identification, validation and drug repurposing, as well as challenges related to data interpretation and validation, and ethical concerns related to the use of artificial intelligence in clinical research.

PMID:34658859 | PMC:PMC8514674 | DOI:10.3389/fphar.2021.720694

Front Neurosci. 2021 Sep 29;15:736786. doi: 10.3389/fnins.2021.736786. eCollection 2021.

ABSTRACT

Ceftriaxone (CEF) is a safe and multipotent antimicrobial agent that possesses neuroprotective properties. Earlier, we revealed the restoration of cognitive function in OXYS rats with signs of Alzheimer's disease (AD)-like pathology by CEF along with its modulating the expression of genes related to the system of amyloid beta (Aβ) metabolism in the brain. The aim of this study was to determine the effects of CEF on behavior, Aβ deposition, and associated neuroinflammation using another model of an early AD-like pathology induced by Aβ. Mice were injected bilaterally i.c.v. with Aβ fragment 25-35 to produce the AD model, while the CEF treatment (100 mg/kg/day, i.p., 36 days) started the next day after the surgery. The open field test, T-maze, Barnes test, IntelliCage, and passive avoidance test were used for behavioral phenotyping. Neuronal density, amyloid accumulation, and the expression of neuroinflammatory markers were measured in the frontal cortex and hippocampus. CEF exhibited beneficial effects on some cognitive features impaired by Aβ neurotoxicity including complete restoration of the fear-induced memory and learning in the passive avoidance test and improved place learning in the IntelliCage. CEF significantly attenuated amyloid deposition and neuroinflammatory response. Thus, CEF could be positioned as a potent multipurpose drug as it simultaneously targets proteostasis network and neuroinflammation, as well as glutamate excitotoxicity, oxidative pathways, and neurotrophic function as reported earlier. Together with previous reports on the positive effects of CEF in AD models, the results confirm the potential of CEF as a promising treatment against cognitive decline from the early stages of AD progression.

PMID:34658774 | PMC:PMC8511453 | DOI:10.3389/fnins.2021.736786

ACS Infect Dis. 2021 Oct 18. doi: 10.1021/acsinfecdis.1c00278. Online ahead of print.

ABSTRACT

The antimicrobial medication malarone (atovaquone/proguanil) is used as a fixed-dose combination for treating children and adults with uncomplicated malaria or as chemoprophylaxis for preventing malaria in travelers. It is an inexpensive, efficacious, and safe drug frequently prescribed around the world. Following anecdotal evidence from 17 patients in the provinces of Quebec and Ontario, Canada, suggesting that malarone/atovaquone may present some benefits in protecting against COVID-19, we sought to examine its antiviral potential in limiting the replication of SARS-CoV-2 in cellular models of infection. In VeroE6 expressing human TMPRSS2 and human lung Calu-3 epithelial cells, we show that the active compound atovaquone at micromolar concentrations potently inhibits the replication of SARS-CoV-2 and other variants of concern including the alpha, beta, and delta variants. Importantly, atovaquone retained its full antiviral activity in a primary human airway epithelium cell culture model. Mechanistically, we demonstrate that the atovaquone antiviral activity against SARS-CoV-2 is partially dependent on the expression of TMPRSS2 and that the drug can disrupt the interaction of the spike protein with the viral receptor, ACE2. Additionally, spike-mediated membrane fusion was also reduced in the presence of atovaquone. In the United States, two clinical trials of atovaquone administered alone or in combination with azithromycin were initiated in 2020. While we await the results of these trials, our findings in cellular infection models demonstrate that atovaquone is a potent antiviral FDA-approved drug against SARS-CoV-2 and other variants of concern in vitro.

PMID:34658235 | DOI:10.1021/acsinfecdis.1c00278

Expert Rev Hematol. 2021 Oct 16. doi: 10.1080/17474086.2021.1995348. Online ahead of print.

ABSTRACT

INTRODUCTION: Drug repositioning (DR) is defined as determining new therapeutic applications for existing drugs. This approach is advantageous over de novo drug discovery in accelerating clinical development, in terms of lower costs, a shortened development period, a well-known action mechanism, a feasible dosage, and an acceptable safety profile.

AREAS COVERED: This work was aimed at reviewing agents with successful DR in hematology.

EXPERT OPINION: Thalidomide and plerixafor have been successfully repositioned for treating multiple myeloma and harvesting peripheral blood stem cells, respectively. The former was originally developed as a sedative and the latter as an anti-HIV drug. Currently, the feasibility of repositioning various agents is being explored (e.g., an anti-influenza virus drug oseltamivir for primary immune thrombocytopenia, an anti-HIV drug abacavir for adult T-cell leukemia, and a macrolide antibiotic clarithromycin for multiple myeloma). Furthermore, bosutinib for chronic myeloid leukemia or the antiplatelet drug cilostazol have been suggested to have clinical benefits for the management of amyotrophic lateral sclerosis and ischemic stroke, respectively. To promote DR, effective application of artificial intelligence or stem cell models, comprehensive database construction shared between academia and pharmaceutical companies, suitable handling of drug patents, and wide cooperation in the area of specialty are warranted.

PMID:34657533 | DOI:10.1080/17474086.2021.1995348

Biotechnol J. 2021 Oct 17:e2100417. doi: 10.1002/biot.202100417. Online ahead of print.

ABSTRACT

The use of anticancer peptides (ACPs) as an alternative/complementary strategy to conventional chemotherapy treatments has been shown to decrease drug resistance and/or severe side effects. However, the efficacy of the positively-charged ACP is inhibited by elevated levels of negatively-charged cell-surface components which trap the peptides and prevent their contact with the cell membrane. Consequently, this decreases ACP-mediated membrane pore formation and cell lysis. Negatively-charged heparan sulphate (HS) and chondroitin sulphate (CS) have been shown to inhibit the cytotoxic effect of ACPs. In this study, we propose a strategy to promote the broad utilization of ACPs. In this context, we developed a drug repositioning pipeline to analyse transcriptomics data generated for four different cancer cell lines (A549, HEPG2, HT29, and MCF7) treated with hundreds of drugs in the LINCS L1000 project. Based on previous studies identifying genes modulating levels of the glycosaminoglycans (GAGs) HS and CS at the cell surface, our analysis aimed at identifying drugs inhibiting genes correlated with high HS and CS levels. As a result, we identified six chemicals as likely repositionable drugs with the potential to enhance the performance of ACPs. The codes in R and Python programming languages are publicly available in https://github.com/ElyasMo/ACPs_HS_HSPGs_CS. As a conclusion, these six drugs are highlighted as excellent targets for synergistic studies with ACPs aimed at lowering the costs associated with ACP-treatment. This article is protected by copyright. All rights reserved.

PMID:34657375 | DOI:10.1002/biot.202100417

EBioMedicine. 2021 Oct 13;72:103629. doi: 10.1016/j.ebiom.2021.103629. Online ahead of print.

ABSTRACT

The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) poses an unprecedented challenge to humanity. SARS-CoV-2 infections range from asymptomatic to severe courses of COVID-19 with acute respiratory distress syndrome (ARDS), multiorgan involvement and death. Risk factors for disease severity include older age, male sex, increased BMI and pre-existing comorbidities. Ethnicity is also relevant to COVID-19 susceptibility and severity. Host genetic predisposition to COVID-19 is now increasingly recognized and whole genome and candidate gene association studies regarding COVID-19 susceptibility have been performed. Several common and rare variants in genes related to inflammation or immune responses have been identified. We summarize research on COVID-19 host genetics and compile genetic variants associated with susceptibility to COVID-19 and disease severity. We discuss candidate genes that should be investigated further to understand such associations and provide insights relevant to pathogenesis, risk classification, therapy response, precision medicine, and drug repurposing.

PMID:34655949 | DOI:10.1016/j.ebiom.2021.103629

Biomed Pharmacother. 2021 Oct 12;144:112274. doi: 10.1016/j.biopha.2021.112274. Online ahead of print.

ABSTRACT

Sex differences in immune-mediated diseases are linked to the activity of estrogens on innate immunity cells, including macrophages. Tamoxifen (TAM) is a selective estrogen receptor modulator (SERM) used in estrogen receptor-alpha (ERα)-dependent breast cancers and off-target indications such as infections, although the immune activity of TAM and its active metabolite, 4-OH tamoxifen (4HT), is poorly characterized. Here, we aimed at investigating the endocrine and immune activity of these SERMs in macrophages. Using primary cultures of female mouse macrophages, we analyzed the expression of immune mediators and activation of effector functions in competition experiments with SERMs and 17β-estradiol (E2) or the bacterial endotoxin LPS. We observed that 4HT and TAM induce estrogen antagonist effects when used at nanomolar concentrations, while pharmacological concentrations that are reached by TAM in clinical settings regulate the expression of VEGFα and other immune activation genes by ERα- and G protein-coupled receptor 1 (GPER1)-independent mechanisms that involve NRF2 through PI3K/Akt-dependent mechanisms. Importantly, we observed that SERMs potentiate cell phagocytosis and modify the effects of LPS on the expression of inflammatory cytokines, such as TNFα and IL1β, with an overall increase in cell inflammatory phenotype, further sustained by potentiation of IL1β secretion through caspase-1 activation. Altogether, our data unravel a novel molecular mechanism and immune functions for TAM and 4HT, sustaining their repurposing in infective and other estrogen receptors-unrelated pathologies.

PMID:34653752 | DOI:10.1016/j.biopha.2021.112274

Eur J Pharmacol. 2021 Oct 12:174569. doi: 10.1016/j.ejphar.2021.174569. Online ahead of print.

ABSTRACT

Drug repurposing or studying existing drugs for potential therapeutic utility in newer indications has been identified as an attractive option for treating a number of diseases. Various strategies of drug repurposing include serendipitous observation of drug's unexpected effects, directing the failed investigational drugs to new indications and currently adopted systematic approach to identify, screen and develop existing drug molecules for new off-label indications. Drug repurposing is able to constructively overcome the bottleneck restraints encountered during traditional de novo drug development process in grounds of timelines, cost and resources. However, success rates of drug repurposing programs are not very impressive. Through a meticulous examination of some failed repurposing attempts we aimed to identify key factors leading to high attrition rate in such studies. Based on the fundamental elements of knowledge and evaluation, we have defined four pillars toward improving success rate in drug repurposing programs viz. sound knowledge of the repurposed drug's pharmacological characteristics (pillar 1: drug pharmacology); drug formulation considerations in new indication (pillar 2: drug formulation); evaluation in representative biological assays with translational potential (pillar 3: evaluation in biological assays); and robust clinical trial methodologies including biomarker driven approach to provide conclusive evidence of repurposed drug's efficacy in new indication (pillar 4: clinical evaluation). In addition to the pharmacological challenges, certain regulatory concerns, including lack of clear guidelines for evaluation and market exclusivity pose hurdles in the application of drug repurposing, which may however be overcome to a great extent by adopting some strategies as discussed in this review.

PMID:34653378 | DOI:10.1016/j.ejphar.2021.174569

Per Med. 2021 Oct 15. doi: 10.2217/pme-2021-0077. Online ahead of print.

ABSTRACT

SARS-CoV-2, a recently emerged zoonotic virus, has resulted in unstoppable high morbidity and mortality rates worldwide. However, due to a limited knowledge of the dynamics of the SARS-CoV-2 infection, it has been observed that the current COVID-2019 therapy has led to some clinical repercussions. We discuss the adverse effects of drugs for COVID-2019 primarily based on some clinical trials. As therapeutic efficacy and toxicity of therapy may vary due to different, genetic determinants, sex, age and the ethnic background of test subjects, hence biomarker-based personalized therapy could be more appropriate. We will share our thoughts on the current landscape of personalized therapy as a roadmap to fight against SARS-CoV-2 or another emerging pathogen.

PMID:34649460 | DOI:10.2217/pme-2021-0077

Curr Opin Struct Biol. 2021 Oct 11;72:114-126. doi: 10.1016/j.sbi.2021.09.003. Online ahead of print.

ABSTRACT

Drug discovery is the process of new drug identification. This process is driven by the increasing data from existing chemical libraries and data banks. The knowledge graph is introduced to the domain of drug discovery for imposing an explicit structure to integrate heterogeneous biomedical data. The graph can provide structured relations among multiple entities and unstructured semantic relations associated with entities. In this review, we summarize knowledge graph-based works that implement drug repurposing and adverse drug reaction prediction for drug discovery. As knowledge representation learning is a common way to explore knowledge graphs for prediction problems, we introduce several representative embedding models to provide a comprehensive understanding of knowledge representation learning.

PMID:34649044 | DOI:10.1016/j.sbi.2021.09.003

J Thorac Oncol. 2021 Oct 11:S1556-0864(21)03205-6. doi: 10.1016/j.jtho.2021.09.008. Online ahead of print.

ABSTRACT

INTRODUCTION: Mutations in BRAF occur in 2-4% of lung adenocarcinoma (LUAD) patients. Combination dabrafenib/trametinib or single-agent vemurafenib is approved only for patients with cancers driven by the V600E BRAF mutation. Targeted therapy is not currently available for patients harboring non-V600 BRAF mutations.

METHODS: An LUAD patient-derived xenograft (PDX) model (PHLC12) with wild-type and non-amplified epidermal growth factor receptor (EGFR) was tested for response to EGFR tyrosine kinase inhibitors (TKI). A cell line derived from this model (X12CL) was also used to evaluate drug sensitivity and to identify potential drivers by siRNA knockdown. Kinase assays were used to test direct targeting of the candidate driver by the EGFR TKIs. Structural modeling including, molecular dynamics (MD) simulations, and binding assays were conducted to explore the mechanism of off-target inhibition by EGFR TKIs on the model 12 driver.

RESULTS: Both PDX PHLC12 and the X12CL cell line were sensitive to multiple EGFR TKIs. The BRAFG469V mutation was found to be the only known oncogenic mutation in this model. siRNA knockdown of BRAF, but not the EGFR, killed X12CL, confirming BRAFG469V as the oncogenic driver. Kinase activity of the BRAF protein isolated from X12CL was inhibited by treatment with the EGFR TKIs gefitinib and osimertinib, and expression of BRAFG469V in non-EGFR-expressing NR6 cells promoted growth in low serum, which was also sensitive to EGFR TKIs. . Structural modeling, MD simulations, and in vitro binding assays support BRAFG469V being a direct target of the TKIs.

CONCLUSION: Clinically approved EGFR TKIs can be repurposed to treat NSCLC patients harboring the BRAFG469V mutation.

PMID:34648945 | DOI:10.1016/j.jtho.2021.09.008

Klin Mikrobiol Infekc Lek. 2020 Dec;26(4):138-139.

ABSTRACT

Antibiotics are considered to be one of the most important discoveries of medicine, which has significantly affected the mortality due to infectious diseases. Given their increasing use, certain problems arise over time, resulting from non-indicated and inadequate - administration of antibiotics. This results in increasing antibiotic resistance as well as a higher risk of side/adverse effects. Recently, these side effects of drugs have been used for indications other than those originally intended and approved. Such a process is called drug repositioning. Due to the recent increase in the cost of developing novel drugs and the high risk of failure in clinical trials, the pharmaceutical industry is trying to find new indications for existing drugs.

PMID:34648651

Curr Mol Pharmacol. 2021 Oct 13. doi: 10.2174/1874467214666211013122528. Online ahead of print.

ABSTRACT

BACKGROUND: The currently circulating novel SARS-CoV-2 coronavirus disease (COVID-19) has brought the whole world to a standstill. Recent studies have deciphered the viral genome structure, epidemiology and are in the process of unveiling multiple mechanisms of pathogenesis. Apart from atypical pneumonia and lung disease manifestations, this disease has also been found to be associated with neurological symptoms, which include dizziness, headache, stroke, or seizures, among others. However, a possible direct or indirect association between SARS-CoV-2 and seizures is still not clear. In any manner, it may be of interest to analyze the drugs being used for viral infection in the background of epilepsy or vice versa.

OBJECTIVE: To identify the most credible drug candidate for COVID-19 in persons with epilepsy or COVID-19 patients experiencing seizures.

METHODS: A literature search for original and review articles was performed, and further, the Comparative Toxicogenomics Database was used to unearth the most credible drug candidate.

RESULTS: Our search based on common mechanistic targets affecting SARS-CoV-2 and seizures revealed ivermectin, dexamethasone, anakinra, and tocilizumab for protection against both COVID-19 and seizures. Amongst the antiseizure medications, we found valproic acid as the most probable pharmacotherapy for COVID-19 patients experiencing seizures.

CONCLUSION: These findings would hopefully provide the basis for initiating further studies on the pathogenesis and drug targeting strategies for this emerging infection accompanied with seizures or in people with epilepsy.

PMID:34645381 | DOI:10.2174/1874467214666211013122528

Curr Mol Med. 2021 Oct 13. doi: 10.2174/1566524021666211013121831. Online ahead of print.

ABSTRACT

The coronavirus disease emerged in December 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome-related coronavirus 2 (SARS-CoV-2) and its rapid global spread has brought an international health emergency and urgent responses for seeking efficient prevention and therapeutic treatment. This has led to imperative needs for illustration of the molecular pathogenesis of SARS-CoV-2, identification of molecular targets or receptors, and development of antiviral drugs, antibodies, and vaccines. In this study, we investigated the current research progress in combating SARS-CoV-2 infection. Based on the published research findings, we first elucidated, at the molecular level, SARS-CoV-2 viral structures, potential viral host-cell-invasion and pathogenic mechanisms, main virus-induced immune responses, and emerging SARS-CoV-2 variants. We then focused on the main virus- and host-based potential targets, summarized and categorized effective inhibitory molecules based on drug development strategies for COVID-19, that can guide efforts for the identification of new drugs and treatment for this problematic disease. Current research and development of antibodies and vaccines were also introduced and discussed. We concluded that the main virus entry route- SARS-CoV-2 spike protein interaction with ACE2 receptors has played a key role in guiding the development of therapeutic treatments against COVID-19, four main therapeutic strategies may be considered in developing molecular therapeutics, and drug repurposing is likely to be an easy, fast and low-cost approach in such a short period of time with urgent need of antiviral drugs. Additionally, the quick development of antibody and vaccine candidates has yielded promising results, but the wide-scale deployment of safe and effective COVID-19 vaccines remains paramount in solving the pandemic crisis. As new variants of the virus begun to emerge, the efficacy of these vaccines and treatments must be closely evaluated. Finally, we discussed the possible challenges of developing molecular therapeutics for COVID-19 and suggested some potential future efforts. Despite the limited availability of literatures, our attempt in this work to provide a relatively comprehensive overview of current SARS-CoV-2 studies can be helpful for quickly acquiring the key information of COVID-19 and further promoting this important research to control and diminish the pandemic.

PMID:34645374 | DOI:10.2174/1566524021666211013121831