Evid Based Complement Alternat Med. 2022 Jul 14;2022:3827933. doi: 10.1155/2022/3827933. eCollection 2022.

ABSTRACT

Drug repositioning and drug reuse are the heated topics in the field of oncology in recent years. These two concepts refer to seeking effective drugs for cancer that are not originally intended to treat cancer. The survival benefits are then analyzed by combining the re-positioned drugs with conventional cancer treatment methods. Simvastatin is a clinically commonly used hyperlipidemia drug and exerts the effect of preventing cardiovascular diseases. Recent studies have found that simvastatin has great potential in the treatment of colorectal cancer, and a large number of clinical studies have used simvastatin as an adjuvant drug to help treat metastatic colorectal cancer.

PMID:35873646 | PMC:PMC9303163 | DOI:10.1155/2022/3827933

Front Pharmacol. 2022 Jul 6;13:908549. doi: 10.3389/fphar.2022.908549. eCollection 2022.

ABSTRACT

Drug repurposing is the process of discovering new indications (i.e., diseases or conditions) for already approved drugs. Many computational methods have been proposed for predicting new associations between drugs and diseases. In this article, we proposed a new method, called DR-HGNN, an integrative heterogeneous graph neural network-based method for multi-labeled drug repurposing, to discover new indications for existing drugs. For this purpose, we first used the DTINet dataset to construct a heterogeneous drug-protein-disease (DPD) network, which is a graph composed of four types of nodes (drugs, proteins, diseases, and drug side effects) and eight types of edges. Second, we labeled each drug-protein edge, dp i,j = (d i , p j ), of the DPD network with a set of diseases, {δ i,j,1, … , δ i,j,k } associated with both d i and p j and then devised multi-label ranking approaches which incorporate neural network architecture that operates on the heterogeneous graph-structured data and which leverages both the interaction patterns and the features of drug and protein nodes. We used a derivative of the GraphSAGE algorithm, HinSAGE, on the heterogeneous DPD network to learn low-dimensional vector representation of features of drugs and proteins. Finally, we used the drug-protein network to learn the embeddings of the drug-protein edges and then predict the disease labels that act as bridges between drugs and proteins. The proposed method shows better results than existing methods applied to the DTINet dataset, with an AUC of 0.964.

PMID:35873597 | PMC:PMC9298882 | DOI:10.3389/fphar.2022.908549

Cancer Sci. 2022 Jul 24. doi: 10.1111/cas.15502. Online ahead of print.

ABSTRACT

Cancer-associated fibroblasts (CAFs) are a major component of the tumor microenvironment that mediate resistance of cancer cells to anticancer drugs. Tranilast is an antiallergic drug that suppresses the release of cytokines from various inflammatory cells. In this study, we investigated the inhibitory effect of tranilast on the interactions between non-small cell lung cancer (NSCLC) cells and the CAFs in the tumor microenvironment. Three EGFR-mutant NSCLC cell lines, two KRAS-mutant cell lines and three CAFs derived from NSCLC patients were used. To mimic the tumor microenvironment, the NSCLC cells were co-cultured with the CAFs in vitro, and the molecular profiles and sensitivity to molecular targeted therapy were assessed. Crosstalk between NSCLC cells and CAFs induced multiple biological effects on the NSCLC cells both in vivo and in vitro, including activation of the STAT3 signaling pathway, promotion of xenograft tumor growth, induction of epithelial-mesenchymal transition (EMT), and acquisition of resistance to molecular-targeted therapy, including of EGFR-mutant NSCLC cells to osimertinib and of KRAS-mutant NSCLC cells to selumetinib. Treatment with tranilast led to inhibition of IL-6 secretion from the CAFs, which, in turn, resulted in inhibition of CAF-induced phospho-STAT3 upregulation. Tranilast also inhibited CAF-induced EMT in the NSCLC cells. Finally, combined administration of tranilast with molecular-targeted therapy reversed the CAF-mediated resistance of the NSCLC cells to the molecular-targeted drugs, both in vitro and in vivo. Our results showed that combined administration of tranilast with molecular-targeted therapy is a possible new treatment strategy to overcome drug resistance caused by cancer- CAF interaction.

PMID:35871750 | DOI:10.1111/cas.15502

Methods Mol Biol. 2022;2535:221-240. doi: 10.1007/978-1-0716-2513-2_17.

ABSTRACT

Metabolic modeling is a powerful computational tool to analyze metabolism. It has not only been used to identify metabolic rewiring strategies in cancer but also to predict drug targets and candidate drugs for repurposing. Here, we will elaborate on the reconstruction of context-specific metabolic models of cancer using rFASTCORMICS and the subsequent prediction of drugs for repurposing using our drug prediction workflow.

PMID:35867234 | DOI:10.1007/978-1-0716-2513-2_17

Front Cell Infect Microbiol. 2022 Jul 5;12:855119. doi: 10.3389/fcimb.2022.855119. eCollection 2022.

ABSTRACT

Drug repurposing and combination therapy have been proposed as cost-effective strategies to improve Chagas disease treatment. Miltefosine (MLT), a synthetic alkylphospholipid initially developed for breast cancer and repositioned for leishmaniasis, is a promising candidate against Trypanosoma cruzi infection. This study evaluates the efficacy of MLT as a monodrug and combined with benznidazole (BZ) in both in vitro and in vivo models of infection with T. cruzi (VD strain, DTU TcVI). MLT exhibited in vitro activity on amastigotes and trypomastigotes with values of IC50 = 0.51 µM (0.48 µM; 0,55 µM) and LC50 = 31.17 µM (29.56 µM; 32.87 µM), respectively. Drug interaction was studied with the fixed-ration method. The sum of the fractional inhibitory concentrations (ΣFICs) resulted in ∑FIC= 0.45 for trypomastigotes and ∑FIC= 0.71 for amastigotes, suggesting in vitro synergistic and additive effects, respectively. No cytotoxic effects on host cells were observed. MLT efficacy was also evaluated in a murine model of acute infection alone or combined with BZ. Treatment was well tolerated with few adverse effects, and all treated animals displayed significantly lower mean peak parasitemia and mortality than infected non-treated controls (p<0.05). The in vivo studies showed that MLT led to a dose-dependent parasitostatic effect as monotherapy which could be improved by combining with BZ, preventing parasitemia rebound after a stringent immunosuppression protocol. These results support MLT activity in clinically relevant stages from T. cruzi, and it is the first report of positive interaction with BZ, providing further support for evaluating combined schemes using MLT and exploring synthetic alkylphospholipids as drug candidates.

PMID:35865815 | PMC:PMC9294734 | DOI:10.3389/fcimb.2022.855119

Indian J Med Res. 2022 Jan;155(1):83-85. doi: 10.4103/ijmr.ijmr_2798_21.

NO ABSTRACT

PMID:35859434 | DOI:10.4103/ijmr.ijmr_2798_21

Cell Mol Life Sci. 2022 Jul 22;79(8):441. doi: 10.1007/s00018-022-04450-8.

ABSTRACT

Spinal muscular atrophy (SMA) is a genetic disease resulting in the loss of α-motoneurons followed by muscle atrophy. It is caused by knock-out mutations in the survival of motor neuron 1 (SMN1) gene, which has an unaffected, but due to preferential exon 7 skipping, only partially functional human-specific SMN2 copy. We previously described a Drosophila-based screening of FDA-approved drugs that led us to discover moxifloxacin. We showed its positive effect on the SMN2 exon 7 splicing in SMA patient-derived skin cells and its ability to increase the SMN protein level. Here, we focus on moxifloxacin's therapeutic potential in additional SMA cellular and animal models. We demonstrate that moxifloxacin rescues the SMA-related molecular and phenotypical defects in muscle cells and motoneurons by improving the SMN2 splicing. The consequent increase of SMN levels was higher than in case of risdiplam, a potent exon 7 splicing modifier, and exceeded the threshold necessary for a survival improvement. We also demonstrate that daily subcutaneous injections of moxifloxacin in a severe SMA murine model reduces its characteristic neuroinflammation and increases the SMN levels in various tissues, leading to improved motor skills and extended lifespan. We show that moxifloxacin, originally used as an antibiotic, can be potentially repositioned for the SMA treatment.

PMID:35864358 | DOI:10.1007/s00018-022-04450-8

PLoS One. 2022 Jul 21;17(7):e0270852. doi: 10.1371/journal.pone.0270852. eCollection 2022.

ABSTRACT

Computational drug repositioning aims to identify potential applications of existing drugs for the treatment of diseases for which they were not designed. This approach can considerably accelerate the traditional drug discovery process by decreasing the required time and costs of drug development. Tensor decomposition enables us to integrate multiple drug- and disease-related data to boost the performance of prediction. In this study, a nonnegative tensor decomposition for drug repositioning, NTD-DR, is proposed. In order to capture the hidden information in drug-target, drug-disease, and target-disease networks, NTD-DR uses these pairwise associations to construct a three-dimensional tensor representing drug-target-disease triplet associations and integrates them with similarity information of drugs, targets, and disease to make a prediction. We compare NTD-DR with recent state-of-the-art methods in terms of the area under the receiver operating characteristic (ROC) curve (AUC) and the area under the precision and recall curve (AUPR) and find that our method outperforms competing methods. Moreover, case studies with five diseases also confirm the reliability of predictions made by NTD-DR. Our proposed method identifies more known associations among the top 50 predictions than other methods. In addition, novel associations identified by NTD-DR are validated by literature analyses.

PMID:35862409 | DOI:10.1371/journal.pone.0270852

Front Mol Biosci. 2022 Jul 4;9:860525. doi: 10.3389/fmolb.2022.860525. eCollection 2022.

ABSTRACT

Gastric cancer remains one of the major contributors to global cancer mortality, although there is no promising target drug in clinics. Hence, the identification of novel targeted drugs for gastric cancer is urgent. As a promising strategy for inducing ferroptosis for gastric cancer treatment, the ferroptosis inducer is a potential drug. Nevertheless, no ferroptosis inducer has entered clinics. So, our purpose was to identify a novel ferroptosis inducer for gastric cancer treatment using a drug repurposing strategy. Firstly, using a drug repurposing strategy with the aid of a commercialized compound library, HC-056456, a small molecule bioactive CatSper channel blocker, was characterized to inhibit the growth of gastric cancer line MGC-803. At the same time, this anti-proliferation effect can be blocked by ferrostatin-1, a ferroptosis inhibitor, indicating that HC-056456 is a ferroptosis inducer. Then, HC-056456 was identified to decrease GSH content via p53/SLC7A11 signaling pathway. Then Fe2+ and lipid peroxide were accumulated when cells were exposed to HC-056456. Finally, HC-056456 was found to suppress the growth of gastric cancer cells by increasing p53 and repressing SLC7A11 in vivo but not in the presence of ferrostatin-1. In sum, we systematically elucidate that HC-056456 exerts anti-gastric cancer effect by provoking ferroptosis in vitro and in vivo, suggesting its potential role in gastric cancer treatment.

PMID:35860356 | PMC:PMC9289365 | DOI:10.3389/fmolb.2022.860525

Database (Oxford). 2022 Jul 19;2022:baac058. doi: 10.1093/database/baac058.

ABSTRACT

Automatic extracting interactions between chemical compound/drug and gene/protein are significantly beneficial to drug discovery, drug repurposing, drug design and biomedical knowledge graph construction. To promote the development of the relation extraction between drug and protein, the BioCreative VII challenge organized the DrugProt track. This paper describes the approach we developed for this task. In addition to the conventional text classification framework that has been widely used in relation extraction tasks, we propose a sequence labeling framework to drug-protein relation extraction. We first comprehensively compared the cutting-edge biomedical pre-trained language models for both frameworks. Then, we explored several ensemble methods to further improve the final performance. In the evaluation of the challenge, our best submission (i.e. the ensemble of models in two frameworks via major voting) achieved the F1-score of 0.795 on the official test set. Further, we realized the sequence labeling framework is more efficient and achieves better performance than the text classification framework. Finally, our ensemble of the sequence labeling models with majority voting achieves the best F1-score of 0.800 on the test set.

DATABASE URL: https://github.com/lingluodlut/BioCreativeVII_DrugProt.

PMID:35856889 | DOI:10.1093/database/baac058

Bioinorg Chem Appl. 2022 Jul 9;2022:2260083. doi: 10.1155/2022/2260083. eCollection 2022.

ABSTRACT

The present study reports the synthesis, characterization, and antibacterial properties of silver trimolybdate (Ag2Mo3O10.2H2O) nanorods. The synthesis was performed using a conventional hydrothermal method. The sample was characterised by scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, UV-Vis-NIR diffuse reflectance, thermogravimetric analysis (TGA), and differential scanning calorimeter (DSC). The direct antibacterial activity was evaluated using the microdilution method to determine the minimum inhibitory concentration (MIC). To assess the ability of Ag2Mo3O10.2H2O nanorods to modulate antibacterial resistance, the MIC of aminoglycosides was established in the presence of a subinhibitory concentration of this substance alone and associated with LED light exposure. The characterization of the sample indicated that the synthesis of silver trimolybdate generated nanometric crystals with rod-like morphology, without secondary phases. The treatment with Ag2Mo3O10.2H2O nanorods alone or combined with visible LED lights exhibited clinically relevant antibacterial activity against both Gram-negative and Gram-positive bacteria. This nanostructure presented a variable antibiotic-modulating action, which was not improved by visible LED light exposure. Nevertheless, LED lights showed promising antibiotic-enhancing activities in the absence of Ag2Mo3O10.2H2O nanorods. In conclusion, silver trimolybdate dihydrate nanorods have antibacterial properties that can be photocatalysed by visible-light exposure. While showing the potential use to combat antibacterial resistance, the simultaneous combination of silver trimolybdate, visible LED lights, and antibacterial drugs should be carefully analysed to avoid antagonist effects that could impair the effectiveness of antibiotic therapy.

PMID:35855788 | PMC:PMC9288309 | DOI:10.1155/2022/2260083

J Hematol Oncol. 2022 Jul 18;15(1):97. doi: 10.1186/s13045-022-01313-4.

ABSTRACT

Drug resistance represents a major obstacle in cancer management, and the mechanisms underlying stress adaptation of cancer cells in response to therapy-induced hostile environment are largely unknown. As the central organelle for cellular energy supply, mitochondria can rapidly undergo dynamic changes and integrate cellular signaling pathways to provide bioenergetic and biosynthetic flexibility for cancer cells, which contributes to multiple aspects of tumor characteristics, including drug resistance. Therefore, targeting mitochondria for cancer therapy and overcoming drug resistance has attracted increasing attention for various types of cancer. Multiple mitochondrial adaptation processes, including mitochondrial dynamics, mitochondrial metabolism, and mitochondrial apoptotic regulatory machinery, have been demonstrated to be potential targets. However, recent increasing insights into mitochondria have revealed the complexity of mitochondrial structure and functions, the elusive functions of mitochondria in tumor biology, and the targeting inaccessibility of mitochondria, which have posed challenges for the clinical application of mitochondrial-based cancer therapeutic strategies. Therefore, discovery of both novel mitochondria-targeting agents and innovative mitochondria-targeting approaches is urgently required. Here, we review the most recent literature to summarize the molecular mechanisms underlying mitochondrial stress adaptation and their intricate connection with cancer drug resistance. In addition, an overview of the emerging strategies to target mitochondria for effectively overcoming chemoresistance is highlighted, with an emphasis on drug repositioning and mitochondrial drug delivery approaches, which may accelerate the application of mitochondria-targeting compounds for cancer therapy.

PMID:35851420 | DOI:10.1186/s13045-022-01313-4

ESMO Open. 2022 Jul 15;7(4):100540. doi: 10.1016/j.esmoop.2022.100540. Online ahead of print.

ABSTRACT

BACKGROUND: Next-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance.

PATIENTS AND METHODS: We used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel.

RESULTS: We reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent.

CONCLUSIONS: There is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.

PMID:35849877 | DOI:10.1016/j.esmoop.2022.100540

PLoS Comput Biol. 2022 Jul 18;18(7):e1010330. doi: 10.1371/journal.pcbi.1010330. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has accelerated the need to identify new antiviral therapeutics at pace, including through drug repurposing. We employed a Quadratic Unbounded Binary Optimization (QUBO) model, to search for compounds similar to Remdesivir, the first antiviral against SARS-CoV-2 approved for human use, using a quantum-inspired device. We modelled Remdesivir and compounds present in the DrugBank database as graphs, established the optimal parameters in our algorithm and resolved the Maximum Weighted Independent Set problem within the conflict graph generated. We also employed a traditional Tanimoto fingerprint model. The two methods yielded different lists of lead compounds, with some overlap. While GS-6620 was the top compound predicted by both models, the QUBO model predicted BMS-986094 as second best. The Tanimoto model predicted different forms of cobalamin, also known as vitamin B12. We then determined the half maximal inhibitory concentration (IC50) values in cell culture models of SARS-CoV-2 infection and assessed cytotoxicity. We also demonstrated efficacy against several variants including SARS-CoV-2 Strain England 2 (England 02/2020/407073), B.1.1.7 (Alpha), B.1.351 (Beta) and B.1.617.2 (Delta). Lastly, we employed an in vitro polymerization assay to demonstrate that these compounds directly inhibit the RNA-dependent RNA polymerase (RdRP) of SARS-CoV-2. Together, our data reveal that our QUBO model performs accurate comparisons (BMS-986094) that differed from those predicted by Tanimoto (different forms of vitamin B12); all compounds inhibited replication of SARS-CoV-2 via direct action on RdRP, with both models being useful. While Tanimoto may be employed when performing relatively small comparisons, QUBO is also accurate and may be well suited for very complex problems where computational resources may limit the number and/or complexity of possible combinations to evaluate. Our quantum-inspired screening method can therefore be employed in future searches for novel pharmacologic inhibitors, thus providing an approach for accelerating drug deployment.

PMID:35849631 | DOI:10.1371/journal.pcbi.1010330

PLoS Comput Biol. 2022 Jul 18;18(7):e1010287. doi: 10.1371/journal.pcbi.1010287. Online ahead of print.

ABSTRACT

Dysregulation of gene expression in Alzheimer's disease (AD) remains elusive, especially at the cell type level. Gene regulatory network, a key molecular mechanism linking transcription factors (TFs) and regulatory elements to govern gene expression, can change across cell types in the human brain and thus serve as a model for studying gene dysregulation in AD. However, AD-induced regulatory changes across brain cell types remains uncharted. To address this, we integrated single-cell multi-omics datasets to predict the gene regulatory networks of four major cell types, excitatory and inhibitory neurons, microglia and oligodendrocytes, in control and AD brains. Importantly, we analyzed and compared the structural and topological features of networks across cell types and examined changes in AD. Our analysis shows that hub TFs are largely common across cell types and AD-related changes are relatively more prominent in some cell types (e.g., microglia). The regulatory logics of enriched network motifs (e.g., feed-forward loops) further uncover cell type-specific TF-TF cooperativities in gene regulation. The cell type networks are also highly modular and several network modules with cell-type-specific expression changes in AD pathology are enriched with AD-risk genes. The further disease-module-drug association analysis suggests cell-type candidate drugs and their potential target genes. Finally, our network-based machine learning analysis systematically prioritized cell type risk genes likely involved in AD. Our strategy is validated using an independent dataset which showed that top ranked genes can predict clinical phenotypes (e.g., cognitive impairment) of AD with reasonable accuracy. Overall, this single-cell network biology analysis provides a comprehensive map linking genes, regulatory networks, cell types and drug targets and reveals cell-type gene dysregulation in AD.

PMID:35849618 | DOI:10.1371/journal.pcbi.1010287

Heliyon. 2022 Jul;8(7):e09910. doi: 10.1016/j.heliyon.2022.e09910. Epub 2022 Jul 11.

ABSTRACT

The first cases of the novel coronavirus, SARS-CoV-2, were detected in December 2019 in Wuhan, China. Nucleotide substitutions and mutations in the SARS-CoV-2 sequence can result in the evolution of the virus and its rapid spread across the world. Therefore, understanding genetic variants of SARS-CoV-2 and targeting the conserved elements responsible for viral replication have great benefits for detecting its infection sources and diagnosing and treating COVID-19. In this study, we used the SARS-CoV-2 sequence isolated from a 59-year-old man in Ardabil, Iran, in April 2020 and sequenced using Oxford Nanopore technology. A meta-analysis comparing the sequence under study with other sequences from Iran indicated long nucleotide insertions/deletions (indels) that code for NSP15, the NSP14-NSP10 complex, open reading frame ORF9b, and ORF1ab polyproteins. In addition, replicating the NSP8 protein in the study sequence is another topic that can affect viral replication. Then using the DNA structure of NSP8, NSP15, NSP14-NSP10 complex, and ORF1ab as a genetic target can help find drug-like compounds for COVID-19. Potential drug-like compounds reported in this study for their mechanism of action and interactions with SARS-CoV-2 genes using drug repurposing are resveratrol, erythromycin, chloramphenicol, indomethacin, ciclesonide, and PDE4 inhibitor. Ciclesonide appears to show the best results when docked with chosen viral proteins. Therefore, different proteins isolated from nucleotide mutations in the virus sequence can indicate distinct inducers for antibodies and are important in vaccine design.

PMID:35847618 | PMC:PMC9271419 | DOI:10.1016/j.heliyon.2022.e09910

Front Pharmacol. 2022 Jun 30;13:861295. doi: 10.3389/fphar.2022.861295. eCollection 2022.

ABSTRACT

Background and purpose: The COVID-19 pandemic continues to pose challenges, especially with the emergence of new SARS-CoV-2 variants that are associated with higher infectivity and/or compromised protection afforded by the current vaccines. There is a high demand for additional preventive and therapeutic strategies effective against this changing virus. Repurposing of approved or clinically tested drugs can provide an immediate solution. Experimental Approach: We applied a novel computational approach to search among approved and commercially available drugs. Antiviral activity of a predicted drug, azelastine, was tested in vitro in SARS-CoV-2 infection assays with Vero E6 cells, Vero cells stably overexpressing the human TMPRSS2 and ACE2 proteins as well as on reconstituted human nasal tissue using the predominant variant circulating in Europe in summer 2020, B.1.177 (D614G variant), and its emerging variants of concern; B.1.1.7 (alpha), B.1.351 (beta) and B.1.617.2 (delta) variants. The effect of azelastine on viral replication was assessed by quantification of viral genomes by droplet digital PCR or qPCR. Key results: The computational approach identified major drug families, such as anti-infective, anti-inflammatory, anti-hypertensive, antihistamine, and neuroactive drugs. Based on its attractive safety profile and availability in nasal formulation, azelastine, a histamine 1 receptor-blocker was selected for experimental testing. Azelastine reduced the virus-induced cytopathic effect and SARS-CoV-2 copy numbers both in preventive and treatment settings upon infection of Vero cells with an EC50 of 2.2-6.5 µM. Comparable potency was observed with the alpha, beta and delta variants. Furthermore, five-fold dilution (containing 0.02% azelastine) of the commercially available nasal spray formulation was highly potent in inhibiting viral propagation in reconstituted human nasal tissue. Conclusion and Implications: Azelastine, an antihistamine available as nasal sprays developed against allergic rhinitis may be considered as a topical prevention or treatment of nasal colonization by SARS-CoV-2. A Phase 2 efficacy indicator study with azelastine-containing nasal spray that was designed based on the findings reported here has been concluded recently, confirming accelerated viral clearance in SARS-CoV-2 positive subjects.

PMID:35846988 | PMC:PMC9280057 | DOI:10.3389/fphar.2022.861295

Bioessays. 2022 Jul 17:e2200060. doi: 10.1002/bies.202200060. Online ahead of print.

ABSTRACT

The SARS-CoV-2 virus is responsible for the COVID-19 pandemic the world experience since 2019. The protein responsible for the first steps of cell invasion, the spike protein, has probably received the most attention in light of its central role during infection. Computational approaches are among the tools employed by the scientific community in the enormous effort to study this new affliction. One of these methods, namely molecular dynamics (MD), has been used to characterize the function of the spike protein at the atomic level and unveil its structural features from a dynamic perspective. In this review, we focus on these main findings, including spike protein flexibility, rare S protein conformational changes, cryptic epitopes, the role of glycans, drug repurposing, and the effect of spike protein variants.

PMID:35843871 | DOI:10.1002/bies.202200060

EBioMedicine. 2022 Jul 14;82:104177. doi: 10.1016/j.ebiom.2022.104177. Online ahead of print.

ABSTRACT

BACKGROUND: Alveolar echinococcosis (AE), which is caused by larval Echinococcus multilocularis, is one of the world's most dangerous neglected diseases. Currently, no fully effective treatments are available to cure this disease.

METHODS: In vitro protoscolicidal assay along with in vivo murine models was applied in repurposing drugs against AE. Genome-wide identification and homology-based modeling were used for predicting drug targets. RNAi, enzyme assay, and RNA-Seq analyses were utilized for investigating the roles in parasite survival and validations for the drug target.

FINDINGS: We identified nelfinavir as the most effective HIV protease inhibitor against larval E. multilocularis. Once-daily oral administration of nelfinavir for 28 days resulted in a remarkable reduction in parasite infection in either immune-competent or immunocompromised mice. E. multilocularis DNA damage-inducible 1 protein (EmuDdi1) is predicted as a target candidate for nelfinavir. We proved that EmuDdi1 is essential for parasite survival and protein excretion and acts as a functionally active protease for this helminth. We found nelfinavir is able to inhibit the proteolytic activity of recombinant EmuDdi1 and block the EmuDdi1-related pathways for protein export. With other evidence of drug efficacy comparison, our results suggest that inhibition of EmuDdi1 is a mechanism by which this HIV proteinase inhibitor mediates its antiparasitic action on echinococcosis.

INTERPRETATION: This study demonstrates that nelfinavir is a promising candidate for treating echinococcosis. This drug repurposing study proves that the widely prescribed drug for AIDS treatment is potent in combating E. multilocularis infection and thus provides valuable insights into the development of single-drug therapy for highly prevalent co-infection between HIV and helminth diseases.

FUNDING: This work was supported by the National Natural Science Foundation of China (31802179), the Natural Science Foundation of Gansu Province, China (No. 21JR7RA027), and the State Key Laboratory of Veterinary Etiological Biology (No. SKLVEB2021YQRC01).

PMID:35843171 | DOI:10.1016/j.ebiom.2022.104177

Bioorg Chem. 2022 Jul 6;127:106009. doi: 10.1016/j.bioorg.2022.106009. Online ahead of print.

ABSTRACT

Leishmaniases have a broad spectrum of clinical manifestations, ranging from a cutaneous to a progressive and fatal visceral disease. Chemotherapy is nowadays the almost exclusive way to fight the disease but limited by its scarce therapeutic arsenal, on its own compromised by adverse side effects and clinical resistance. Cyclobenzaprine (CBP), an FDA-approved oral muscle relaxant drug has previously demonstrated in vitro and in vivo activity against Leishmania sp., but its targets were not fully unveiled. This study aimed to define the role of energy metabolism as a target for the leishmanicidal mechanisms of CBP. Methodology to assess CBP leishmanicidal mechanism variation of intracellular ATP levels using living Leishmania transfected with a cytoplasmic luciferase. Induction of plasma membrane permeability by assessing depolarization with DiSBAC(2)3 and entrance of the vital dye SYTOX® Green. Mitochondrial depolarization by rhodamine 123 accumulation. Mapping target site within the respiratory chain by oxygen consumption rate. Reactive oxygen species (ROS) production using MitoSOX. Morphological changes by transmission electron microscopy. CBP caused on L. infantum promastigotes a decrease of intracellular ATP levels, with irreversible depolarization of plasma membrane, the collapse of the mitochondrial electrochemical potential, mild uncoupling of the respiratory chain, and ROS production, with ensuing intracellular Ca2+ imbalance and DNA fragmentation. Electron microscopy supported autophagic features but not a massive plasma membrane disruption. The severe and irreversible mitochondrial damage induced by CBP endorsed the bioenergetics metabolism as a relevant target within the lethal programme induced by CBP in Leishmania. This, together with the mild-side effects of this oral drug, endorses CBP as an appealing novel candidate as a leishmanicidal drug under a drug repurposing strategy.

PMID:35841672 | DOI:10.1016/j.bioorg.2022.106009