J Biomol Struct Dyn. 2021 Jun 1:1-25. doi: 10.1080/07391102.2021.1931451. Online ahead of print.

ABSTRACT

In view of many European countries and the USA leading to the second wave of COVID-19 pandemic, winter season, the evolution of new mutations in the spike protein, and no registered drugs and vaccines for COVID-19 treatment, the discovery of effective and novel therapeutic agents is urgently required. The degrees and frequencies of COVID-19 clinical complications are related to uncontrolled immune responses, secondary bacterial infections, diabetes, cardiovascular disease, hypertension, and chronic pulmonary diseases. It is essential to recognize that the drug repurposing strategy so far remains the only means to manage the disease burden of COVID-19. Despite some success of using single-target drugs in treating the disease, it is beyond suspicion that the virus will acquire drug resistance by acquiring mutations in the drug target. The possible synergistic inhibition of drug efficacy due to drug-drug interaction cannot be avoided while treating COVID-19 and allied clinical complications. Hence, to avoid the unintended development drug resistance and loss of efficacy due to drug-drug interaction, multi-target drugs can be promising tools for the most challenging disease. In the present work, we have carried out molecular docking studies of compounds from the FDA approved drug library, and the FDA approved and passed phase -1 drug libraries with ten therapeutic targets of COVID-19. Results showed that known drugs, including nine anti-inflammatory compounds, four antibiotics, six antidiabetic compounds, and one cardioprotective compound, could effectively inhibit multiple therapeutic targets of COVID-19. Further in-vitro, in vivo, and clinical studies will guide these drugs' proper allocation to treat COVID-19.Communicated by Ramaswamy H. Sarma.

PMID:34062110 | DOI:10.1080/07391102.2021.1931451

Biomed Pharmacother. 2021 May 28;140:111769. doi: 10.1016/j.biopha.2021.111769. Online ahead of print.

ABSTRACT

Traumatic brain injury (TBI) is characterized by a complex network of signals mediating inflammatory, proliferative and apoptotic processes during its acute and chronic phases. Current therapies mitigate damage and are mainly for palliative care and there are currently no effective therapies for secondary damage. This suggests a need to discover a compound with a greater spectrum of action that can control various pathological aspects of TBI. Here we used a network pharmacology approach to explore the benefits of tibolone, an estrogen and androgen receptor agonist with broader actions in cells, as a possible repurposing drug for TBI therapy. Using different databases we retrieved the targets significantly associated to TBI and tibolone, obtaining 2700 and 652, respectively. The top 10 GO enriched terms were mostly related to cell proliferation, apoptosis and inflammation. Following protein-protein functional analysis, the top connected proteins were related to kinase activity (MAPK1/14/3, AKT1 PIK3R1), apoptosis (TP53, CASP3), growth factors (EGFR), estrogen signalling (ESR1) and inflammation (IL6, TNF), with IL6 as an important signalling hub belonging to the top GO categories. Thus, we identified IL6 as a cellular node which we then validated using molecular mechanics-generalized born surface area (MMGBSA) and docking to explore which tibolone metabolite might interact with this protein. Both 3α and 3β-OH tibolone seemed to bind better to IL6 at important sites responsible for its binding to IL6R. In conclusion, our study demonstrates key hubs involved in TBI pathology which indicates IL6 as a target molecule of tibolone as drug repurposing for TBI therapy.

PMID:34058440 | DOI:10.1016/j.biopha.2021.111769

Immunopharmacol Immunotoxicol. 2021 May 31:1-15. doi: 10.1080/08923973.2021.1931302. Online ahead of print.

ABSTRACT

A global threat has emerged in 2019 due to the rapid spread of Coronavirus disease (COVID-19). As of January 2021, the number of cases worldwide reached 103 million cases and 2.22 million deaths which were confirmed as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This global pandemic galvanized the scientific community to study the causative virus (SARS-CoV2) pathogenesis, transmission, and clinical symptoms. Remarkably, the most common complication associated with this disease is the cytokine storm which is responsible for COVID-19 mortality. Thus, targeting the cytokine storm with new medications is needed to hamper COVID-19 complications where the most prominent strategy for the treatment is drug repurposing. Through this strategy, several steps are skipped especially those required for testing drug safety and thus may help in reducing the dissemination of this pandemic. Accordingly, the aim of this review is to outline the pathogenesis, clinical features, and immune complications of SARS-CoV2 in addition to suggesting several repurposed drugs with their plausible mechanism of action for possible management of severe COVID-19 cases.

PMID:34057871 | DOI:10.1080/08923973.2021.1931302

Cell Oncol (Dordr). 2021 May 31. doi: 10.1007/s13402-021-00613-0. Online ahead of print.

ABSTRACT

BACKGROUND: The aggressive, invasive and treatment resistant nature of glioblastoma makes it one of the most lethal cancers in humans. Total surgical resection is difficult, and a combination of radiation and chemotherapy is used to treat the remaining invasive cells beyond the tumour border by inducing DNA damage and activating cell death pathways in glioblastoma cells. Unfortunately, recurrence is common and a major hurdle in treatment, often met with a more aggressive and treatment resistant tumour. A mechanism of resistance is the response of DNA repair pathways upon treatment-induced DNA damage, which enact cell-cycle arrest and repair of DNA damage that would otherwise cause cell death in tumour cells.

CONCLUSIONS: In this review, we discuss the significance of DNA repair mechanisms in tumour formation, aggression and treatment resistance. We identify an underlying trend in the literature, wherein alterations in DNA repair pathways facilitate glioma progression, while established high-grade gliomas benefit from constitutively active DNA repair pathways in the repair of treatment-induced DNA damage. We also consider the clinical feasibility of inhibiting DNA repair in glioblastoma and current strategies of using DNA repair inhibitors as agents in combination with chemotherapy, radiation or immunotherapy. Finally, the importance of blood-brain barrier penetrance when designing novel small-molecule inhibitors is discussed.

PMID:34057732 | DOI:10.1007/s13402-021-00613-0

Front Oncol. 2021 May 13;11:688755. doi: 10.3389/fonc.2021.688755. eCollection 2021.

ABSTRACT

Vaccines used to prevent infections have long been known to stimulate immune responses to cancer as illustrated by the approval of the Bacillus Calmette-Guérin (BCG) vaccine to treat bladder cancer since the 1970s. The recent approval of immunotherapies has rejuvenated this research area with reports of anti-tumor responses with existing infectious diseases vaccines used as such, either alone or in combination with immune checkpoint inhibitors. Here, we have reviewed and summarized research activities using approved vaccines to treat cancer. Data supporting a cancer therapeutic use was found for 16 vaccines. For 10 (BCG, diphtheria, tetanus, human papillomavirus, influenza, measles, pneumococcus, smallpox, typhoid and varicella-zoster), clinical trials have been conducted or are ongoing. Within the remaining 6, preclinical evidence supports further evaluation of the rotavirus, yellow fever and pertussis vaccine in carefully designed clinical trials. The mechanistic evidence for the cholera vaccine, combined with the observational data in colorectal cancer, is also supportive of clinical translation. There is limited data for the hepatitis B and mumps vaccine (without measles vaccine). Four findings are worth highlighting: the superiority of intravesical typhoid vaccine instillations over BCG in a preclinical bladder cancer model, which is now the subject of a phase I trial; the perioperative use of the influenza vaccine to limit and prevent the natural killer cell dysfunction induced by cancer surgery; objective responses following intratumoral injections of measles vaccine in cutaneous T-cell lymphoma; objective responses induced by human papillomavirus vaccine in cutaneous squamous cell carcinoma. All vaccines are intended to induce or improve an anti-tumor (immune) response. In addition to the biological and immunological mechanisms that vary between vaccines, the mode of administration and sequence with other (immuno-)therapies warrant more attention in future research.

PMID:34055652 | PMC:PMC8155725 | DOI:10.3389/fonc.2021.688755

Comput Struct Biotechnol J. 2021 May 24. doi: 10.1016/j.csbj.2021.05.037. Online ahead of print.

ABSTRACT

The world is facing the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were responsible for causing epidemics earlier. To tackle these viruses, there is a lack of approved antiviral drugs. Therefore, we have developed robust computational methods to predict the repurposed drugs using machine learning techniques namely Support Vector Machine, Random Forest, k-Nearest Neighbour, Artificial Neural Network, and Deep Learning. We used the experimentally validated drugs/chemicals with anti-corona activity and their inhibition efficiencies (IC50/EC50) from 'DrugRepV' repository. The unique entries of SARS-CoV-2 (142), SARS (221), MERS (123), and overall Coronaviruses (414) were subdivided into the training/testing and independent validation datasets, followed by the extraction of chemical/structural descriptors and fingerprints (17968). The highly relevant features were filtered using the recursive feature selection algorithm. The selected chemical descriptors were used to develop prediction models with Pearson's correlation coefficients ranging from 0.60-0.90 on training/testing. The robustness of the predictive models was further ensured using external independent validation datasets, decoy datasets, applicability domain, and chemical analyses. The developed models were used to predict promising repurposed drug candidates against coronaviruses after scanning the DrugBank. Top predicted molecules for SARS-CoV-2 were further validated by molecular docking against the spike protein complex with ACE receptor. We found potential repurposed drugs namely, Verteporfin, Alatrofloxacin, Metergoline, Rescinnamine, Leuprolide, and Telotristat ethyl with high binding affinity. These computational methods would assist in antiviral drug discovery against SARS-CoV-2 and other Coronaviruses.

PMID:34055238 | PMC:PMC8141697 | DOI:10.1016/j.csbj.2021.05.037

Front Genet. 2021 Apr 8;12:657182. doi: 10.3389/fgene.2021.657182. eCollection 2021.

ABSTRACT

Drug repositioning is an application-based solution based on mining existing drugs to find new targets, quickly discovering new drug-disease associations, and reducing the risk of drug discovery in traditional medicine and biology. Therefore, it is of great significance to design a computational model with high efficiency and accuracy. In this paper, we propose a novel computational method MGRL to predict drug-disease associations based on multi-graph representation learning. More specifically, MGRL first uses the graph convolution network to learn the graph representation of drugs and diseases from their self-attributes. Then, the graph embedding algorithm is used to represent the relationships between drugs and diseases. Finally, the two kinds of graph representation learning features were put into the random forest classifier for training. To the best of our knowledge, this is the first work to construct a multi-graph to extract the characteristics of drugs and diseases to predict drug-disease associations. The experiments show that the MGRL can achieve a higher AUC of 0.8506 based on five-fold cross-validation, which is significantly better than other existing methods. Case study results show the reliability of the proposed method, which is of great significance for practical applications.

PMID:34054920 | PMC:PMC8153989 | DOI:10.3389/fgene.2021.657182

Virology. 2021 May 25;560:110-115. doi: 10.1016/j.virol.2021.05.009. Online ahead of print.

ABSTRACT

A recent study have reported that pre-use of azelastine is associated with a decrease in COVID-19 positive test results among susceptible elderly people. Besides, it has been reported that antihistamine drugs could prevent viruses from entering cells. The purpose of this study is to investigate whether azelastine have antiviral activity against SARS-CoV-2 in vitro and the possible mechanism. Here, we discovered antihistamine azelastine has an affinity to ACE2 by cell membrane chromatography (CMC); Then we determined the equilibrium dissociation constant (KD) of azelastine-ACE2 as (2.58 ± 0.48) × 10-7 M by surface plasmon resonance (SPR). The results of molecular docking showed that azelastine could form an obvious hydrogen bond with Lys353. The pseudovirus infection experiments showed that azelastine effectively inhibited viral entry (EC50 = 3.834 μM). Our work provides a new perspective for the screening method of drug repositioning for COVID-19, and an attractive and promising drug candidate for anti-SARS-CoV-2.

PMID:34052578 | DOI:10.1016/j.virol.2021.05.009

Biomed Pharmacother. 2021 May 18;140:111742. doi: 10.1016/j.biopha.2021.111742. Online ahead of print.

ABSTRACT

Here, drug repurposing and molecular docking were employed to screen approved MPP inhibitors and their derivatives to suggest a specific therapeutic agent for the treatment of COVID-19. The approved MPP inhibitors against HIV and HCV were prioritized, while RNA dependent RNA Polymerase (RdRp) inhibitor remdesivir including Favipiravir, alpha-ketoamide were studied as control groups. The target drug surface hotspot was also investigated through the molecular docking technique. Molecular dynamics was performed to determine the binding stability of docked complexes. Absorption, distribution, metabolism, and excretion analysis was conducted to understand the pharmacokinetics and drug-likeness of the screened MPP inhibitors. The results of the study revealed that Paritaprevir (-10.9 kcal/mol) and its analog (CID 131982844) (-16.3 kcal/mol) showed better binding affinity than the approved MPP inhibitors compared in this study, including remdesivir, Favipiravir, and alpha-ketoamide. A comparative study among the screened putative MPP inhibitors revealed that the amino acids T25, T26, H41, M49, L141, N142, G143, C145, H164, M165, E166, D187, R188, and Q189 are at potentially critical positions for being surface hotspots in the MPP of SARS-CoV-2. The top 5 predicted drugs (Paritaprevir, Glecaprevir, Nelfinavir, and Lopinavir) and the topmost analog showed conformational stability in the active site of the SARS-CoV-2 MP protein. The study also suggested that Paritaprevir and its analog (CID 131982844) might be effective against SARS-CoV-2. The current findings are limited to in silico analysis and lack in vivo efficacy testing; thus, we strongly recommend a quick assessment of Paritaprevir and its analog (CID 131982844) in a clinical trial.

PMID:34052565 | DOI:10.1016/j.biopha.2021.111742

J Biomed Inform. 2021 May 27:103821. doi: 10.1016/j.jbi.2021.103821. Online ahead of print.

ABSTRACT

AIM: Rapidly developing AI and machine learning (ML) technologies can expedite therapeutic development and in the time of current pandemic their merits are particularly in focus. The purpose of this study was to explore various ML approaches for molecular property prediction and illustrate their utility for identifying potential SARS-CoV-2 3CLpro inhibitors.

MATERIALS AND METHODS: We perform a series of drug discovery screenings based on supervised ML models operating in different ways on molecular representations, encompassing shallow learning methods based on fixed molecular fingerprints, Graph Convolutional Neural Network (Graph-CNN) with its self-learned molecular representations, as well as ML methods based on combining fixed and Graph-CNN learned representations.

RESULTS: Results of our ML models are compared both with respect to the aggregated predictive performance in terms of ROC-AUC based on the scaffold splits, as well as on the granular level of individual predictions, corresponding to the top ranked repurposing candidates. This comparison reveals both certain characteristic homogeneity regarding chemical and pharmacological classification, with a prevalence of sulfonamides and anticancer drugs, as well as identifies novel groups of potential drug candidates against COVID-19.

CONCLUSIONS: A series of ML approaches for molecular property prediction enables drug discovery screenings, illustrating the utility for COVID-19. We show that the obtained results correspond well with the already published research on COVID-19 treatment, as well as provide novel insights on potential antiviral characteristics inferred from in vitro data.

PMID:34052441 | DOI:10.1016/j.jbi.2021.103821

Bioorg Chem. 2021 May 7;113:104971. doi: 10.1016/j.bioorg.2021.104971. Online ahead of print.

ABSTRACT

Drug repurposing has gained much attention as a cost-effective strategy that plays an exquisite role in identifying undescribed biological activities in clinical drugs. In the present work, we report the repurposing of the antibacterial drug nitrofurazone (NFZ) as a potential anticancer agent against CaCo-2, MDA-MB 231 and HepG-2 cancer cell lines. Novel series of nitrofurazone analogs were then designed considering the important pharmacologic features present in NFZ. Synthesis and biological evaluation of the target compounds revealed their promising anticancer activities endowed with antimicrobial potential and possessing better lipophilicity than NFZ. Compound 7, exclusively, inhibited the growth of all tested cancer cells more potently than NFZ with the least cytotoxicity against normal cells, displaying anti Gram-positive bacterial activities and antifungal potential. Analysis of the stereo-electronic properties of compound 7 via investigating the energies of HOMO, LUMO, HOMO-LUMO energy gap and MEP maps demonstrated its high reactivity and the expected molecular mechanism of action through reduction of the 5-nitrofuryl moiety. Data of the bioactivity studies indicated that the potent anticancer activity of 7 is mainly through increasing intracellular ROS levels and induction of apoptosis via significantly down-regulating the expression of Bcl-2 while up-regulating BAX, p53 and caspase 3 expression levels. Compound 7 potently inhibited the cellular expression levels of antioxidant enzymes GPx1 and GR compared to NFZ. Antioxidant enzymes kinetic studies and blind molecular docking simulations disclosed the mechanistic and structural aspects of the interaction between 7 and both GR and GPx1. Thus, the successful discovery of 7 as a potential dual anticancer-antimicrobial nitrofurazone analog might validate the applicability of drug repurposing strategy in unravelling the unrecognized bioactivity of the present conventional drugs, besides furnishing the way towards more optimization and development studies.

PMID:34051413 | DOI:10.1016/j.bioorg.2021.104971

Int J Pharm. 2021 May 26:120750. doi: 10.1016/j.ijpharm.2021.120750. Online ahead of print.

ABSTRACT

The development of molecules for topical dermatology has primarily relied on drug repurposing or on combination therapies, leading to an average of only one New Chemical Entity (NCE) approved per year by the FDA. Topical products offer benefits to patients by enabling localized treatment, while minimizing systemic exposure and the likelihood of adverse events. New therapies are further justified by the burden skin diseases cause on patients' quality of life. Notwithstanding the opportunities, the selection of a topical NCE presents challenges, primarily derived from a target product profile uncommon to oral drugs. Beyond a more stringent range of physicochemical properties, the molecule must display adequate solubility and chemical stability in topical-relevant excipients; must effectively cross the stratum corneum, considerably less permeable than the intestinal epithelium, and elicit a local therapeutic response; and must enable a formulation with robust physical stability. A novel framework intended to de-risk NCE selection is presented and based on four calculated physicochemical properties: molecular weight, clog P, topological polar surface area, and aromatic ring count. The use of topical-relevant solvents to assess the molecule's solubility profile, and a 2-day accelerated chemical stability methodology, are also described as critical steps in early dermal development.

PMID:34051321 | DOI:10.1016/j.ijpharm.2021.120750

Nucleic Acids Res. 2021 May 28:gkab405. doi: 10.1093/nar/gkab405. Online ahead of print.

ABSTRACT

The Mergeomics web server is a flexible online tool for multi-omics data integration to derive biological pathways, networks, and key drivers important to disease pathogenesis and is based on the open source Mergeomics R package. The web server takes summary statistics of multi-omics disease association studies (GWAS, EWAS, TWAS, PWAS, etc.) as input and features four functions: Marker Dependency Filtering (MDF) to correct for known dependency between omics markers, Marker Set Enrichment Analysis (MSEA) to detect disease relevant biological processes, Meta-MSEA to examine the consistency of biological processes informed by various omics datasets, and Key Driver Analysis (KDA) to identify essential regulators of disease-associated pathways and networks. The web server has been extensively updated and streamlined in version 2.0 including an overhauled user interface, improved tutorials and results interpretation for each analytical step, inclusion of numerous disease GWAS, functional genomics datasets, and molecular networks to allow for comprehensive omics integrations, increased functionality to decrease user workload, and increased flexibility to cater to user-specific needs. Finally, we have incorporated our newly developed drug repositioning pipeline PharmOmics for prediction of potential drugs targeting disease processes that were identified by Mergeomics. Mergeomics is freely accessible at http://mergeomics.research.idre.ucla.edu and does not require login.

PMID:34048577 | DOI:10.1093/nar/gkab405

Sci Rep. 2021 May 27;11(1):11234. doi: 10.1038/s41598-021-90701-w.

ABSTRACT

Understanding the molecular basis of fibrosis, the lethal complication of COVID-19, is urgent. By the analysis of RNA-sequencing data of SARS-CoV-2-infected cells combined with data mining we identified genes involved in COVID-19 progression. To characterize their implication in the fibrosis development we established a correlation matrix based on the transcriptomic data of patients with idiopathic pulmonary fibrosis. With this method, we have identified a cluster of genes responsible for SARS-CoV-2-fibrosis including its entry receptor ACE2 and epidermal growth factor EGF. Then, we developed Vi-Fi scoring-a novel drug repurposing approach and simultaneously quantified antiviral and antifibrotic activities of the drugs based on their transcriptomic signatures. We revealed the strong dual antifibrotic and antiviral activity of EGFR/ErbB inhibitors. Before the in vitro validation, we have clustered 277 cell lines and revealed distinct COVID-19 transcriptomic signatures of the cells with similar phenotypes that defines their suitability for COVID-19 research. By ERK activity monitoring in living lung cells, we show that the drugs with predicted antifibrotic activity downregulate ERK in the host lung cells. Overall, our study provides novel insights on SARS-CoV-2 dependence on EGFR/ERK signaling and demonstrates the utility of EGFR/ErbB inhibitors for COVID-19 treatment.

PMID:34045585 | DOI:10.1038/s41598-021-90701-w

Methods Appl Fluoresc. 2021 May 27. doi: 10.1088/2050-6120/ac0619. Online ahead of print.

ABSTRACT

Optical biopsies bring the microscope to the patient rather than the tissue to the microscope, and may complement or replace the tissue-harvesting component of the traditional biopsy process with its associated risks. In general, optical biopsies are limited by the lack of endogenous tissue contrast and the small number of clinically approved in vivo dyes. This study tests multiple FDA-approved drugs that have structural similarity to research dyes, as off-label in situ fluorescent alternatives to standard ex vivo hematoxylin & eosin tissue stain. Numerous drug-dye combinations shown here may facilitate relatively safe and fast in situ or possibly in vivo staining of tissue, enabling real-time optical biopsies and other advanced microscopy technologies, which have implications for the speed and performance of tissue- and cellular-level diagnostics.

PMID:34044380 | DOI:10.1088/2050-6120/ac0619

RSC Med Chem. 2020 Dec 21;12(3):370-379. doi: 10.1039/d0md00367k.

ABSTRACT

The rapid growth of COVID-19 cases is causing an increasing death toll and also paralyzing the world economy. De novo drug discovery takes years to move from idea and/or pre-clinic to market, and it is not a short-term solution for the current SARS-CoV-2 pandemic. Drug repurposing is perhaps the only short-term solution, while vaccination is a middle-term solution. Here, we describe the discovery path of the HCV NS3-4A protease inhibitors boceprevir and telaprevir as SARS-CoV-2 main protease (3CLpro) inhibitors. Based on our hypothesis that α-ketoamide drugs can covalently bind to the active site cysteine of the SARS-CoV-2 3CLpro, we performed docking studies, enzyme inhibition and co-crystal structure analyses and finally established that boceprevir, but not telaprevir, inhibits replication of SARS-CoV-2 and mouse hepatitis virus (MHV), another coronavirus, in cell culture. Based on our studies, the HCV drug boceprevir deserves further attention as a repurposed drug for COVID-19 and potentially other coronaviral infections as well.

PMID:34041486 | PMC:PMC8130630 | DOI:10.1039/d0md00367k

Front Chem. 2021 May 10;9:636362. doi: 10.3389/fchem.2021.636362. eCollection 2021.

ABSTRACT

The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a devastating effect globally with no effective treatment. The swift strategy to find effective treatment against coronavirus disease 2019 (COVID-19) is to repurpose the approved drugs. In this pursuit, an exhaustive computational method has been used on the DrugBank compounds targeting nsp16/nsp10 complex (PDB code: 6W4H). A structure-based pharmacophore model was generated, and the selected model was escalated to screen DrugBank database, resulting in three compounds. These compounds were subjected to molecular docking studies at the protein-binding pocket employing the CDOCKER module available with the Discovery Studio v18. In order to discover potential candidate compounds, the co-crystallized compound S-adenosyl methionine (SAM) was used as the reference compound. Additionally, the compounds remdesivir and hydroxycholoroquine were employed for comparative docking. The results have shown that the three compounds have demonstrated a higher dock score than the reference compounds and were upgraded to molecular dynamics simulation (MDS) studies. The MDS results demonstrated that the three compounds, framycetin, kanamycin, and tobramycin, are promising candidate compounds. They have represented a stable binding mode at the targets binding pocket with an average protein backbone root mean square deviation below 0.3 nm. Additionally, they have prompted the hydrogen bonds during the entire simulations, inferring that the compounds have occupied the active site firmly. Taken together, our findings propose framycetin, kanamycin, and tobramycin as potent putative inhibitors for COVID-19 therapeutics.

PMID:34041221 | PMC:PMC8141588 | DOI:10.3389/fchem.2021.636362

Front Oncol. 2021 May 10;11:653621. doi: 10.3389/fonc.2021.653621. eCollection 2021.

ABSTRACT

To meet the anabolic demands of the proliferative potential of tumor cells, malignant cells tend to rewire their metabolic pathways. Although different types of malignant cells share this phenomenon, there is a large intracellular variability how these metabolic patterns are altered. Fortunately, differences in metabolic patterns between normal tissue and malignant cells can be exploited to increase the therapeutic ratio. Modulation of cellular metabolism to improve treatment outcome is an emerging field proposing a variety of promising strategies in primary tumor and metastatic lesion treatment. These strategies, capable of either sensitizing or protecting tissues, target either tumor or normal tissue and are often focused on modulating of tissue oxygenation, hypoxia-inducible factor (HIF) stabilization, glucose metabolism, mitochondrial function and the redox balance. Several compounds or therapies are still in under (pre-)clinical development, while others are already used in clinical practice. Here, we describe different strategies from bench to bedside to optimize the therapeutic ratio through modulation of the cellular metabolism. This review gives an overview of the current state on development and the mechanism of action of modulators affecting cellular metabolism with the aim to improve the radiotherapy response on tumors or to protect the normal tissue and therefore contribute to an improved therapeutic ratio.

PMID:34041023 | PMC:PMC8143268 | DOI:10.3389/fonc.2021.653621

Front Pharmacol. 2021 May 10;12:624844. doi: 10.3389/fphar.2021.624844. eCollection 2021.

ABSTRACT

The increasing risks of radiological or nuclear attacks or associated accidents have served to renew interest in developing radiation medical countermeasures. The development of prospective countermeasures and the subsequent gain of Food and Drug Administration (FDA) approval are invariably time consuming and expensive processes, especially in terms of generating essential human data. Due to the limited resources for drug development and the need for expedited drug approval, drug developers have turned, in part, to the strategy of repurposing agents for which safety and clinical data are already available. Approval of drugs that are already in clinical use for one indication and are being repurposed for another indication is inherently faster and more cost effective than for new agents that lack regulatory approval of any sort. There are four known growth factors which have been repurposed in the recent past as radiomitigators following the FDA Animal Rule: Neupogen, Neulasta, Leukine, and Nplate. These four drugs were in clinic for several decades for other indications and were repurposed. A large number of additional agents approved by various regulatory authorities for given indications are currently under investigation for dual use for acute radiation syndrome or for delayed pathological effects of acute radiation exposure. The process of drug repurposing, however, is not without its own set of challenges and limitations.

PMID:34040517 | PMC:PMC8141805 | DOI:10.3389/fphar.2021.624844

Sci Rep. 2021 May 26;11(1):11049. doi: 10.1038/s41598-021-90296-2.

ABSTRACT

The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific community's massive response has resulted in a flood of experiments, analyses, hypotheses, and publications, especially in the field of drug repurposing. However, many of the proposed therapeutic compounds obtained from SARS-CoV-2 specific assays are not in agreement and thus demonstrate the need for a singular source of COVID-19 related information from which a rational selection of drug repurposing candidates can be made. In this paper, we present the COVID-19 PHARMACOME, a comprehensive drug-target-mechanism graph generated from a compilation of 10 separate disease maps and sources of experimental data focused on SARS-CoV-2/COVID-19 pathophysiology. By applying our systematic approach, we were able to predict the synergistic effect of specific drug pairs, such as Remdesivir and Thioguanosine or Nelfinavir and Raloxifene, on SARS-CoV-2 infection. Experimental validation of our results demonstrate that our graph can be used to not only explore the involved mechanistic pathways, but also to identify novel combinations of drug repurposing candidates.

PMID:34040048 | DOI:10.1038/s41598-021-90296-2