J Inherit Metab Dis. 2023 Aug 22. doi: 10.1002/jimd.12674. Online ahead of print.

ABSTRACT

Due to the low number of patients, rare genetic diseases are a special challenge for the development of therapies, especially for diseases that result from numerous, patient-specific pathogenic variants. Precision medicine makes use of various kinds of molecular information about a specific variant, so that the possibilities for an effective therapy based on the molecular features of the variants can be elucidated. The attention to personalized precision therapies has increased among scientists and clinicians, since the "single drug for all patients" approach does not allow the classification of individuals in subgroups according to the differences in the disease genotype or phenotype. This review article summarizes some approaches of personalized precision medicine that can be used for a cost-effective and fast development of therapies, even for single patients. We have focused on specific examples on inborn errors of metabolism, with special attention on drug repurposing. Furthermore, we provide an overview of cell culture models that are suitable for precision medicine approaches. This article is protected by copyright. All rights reserved.

PMID:37606592 | DOI:10.1002/jimd.12674

Curr Pharm Biotechnol. 2023 Aug 21. doi: 10.2174/1389201024666230821103601. Online ahead of print.

ABSTRACT

Drug repositioning is a method of using authorized drugs for other unusually complex diseases. Compared to new drug development, this method is fast, low in cost, and effective. Through the use of outstanding bioinformatics tools, such as computer-aided drug design (CADD), computer strategies play a vital role in the re-transformation of drugs. The use of CADD's special strategy for target-based drug reuse is the most promising method, and its realization rate is high. In this review article, we have particularly focused on understanding the various technologies of CADD and the use of computer-aided drug design for target-based drug reuse, taking COVID-19 and cancer as examples. Finally, it is concluded that CADD technology is accelerating the development of repurposed drugs due to its many advantages, and there are many facts to prove that the new ligand-targeting strategy is a beneficial method and that it will gain momentum with the development of technology.

PMID:37605405 | DOI:10.2174/1389201024666230821103601

Nat Rev Urol. 2023 Aug 21. doi: 10.1038/s41585-023-00805-3. Online ahead of print.

ABSTRACT

The application of bioinformatics has revolutionized the practice of medicine in the past 20 years. From early studies that uncovered subtypes of cancer to broad efforts spearheaded by the Cancer Genome Atlas initiative, the use of bioinformatics strategies to analyse high-dimensional data has provided unprecedented insights into the molecular basis of disease. In addition to the identification of disease subtypes - which enables risk stratification - informatics analysis has facilitated the identification of novel risk factors and drivers of disease, biomarkers of progression and treatment response, as well as possibilities for drug repurposing or repositioning; moreover, bioinformatics has guided research towards precision and personalized medicine. Implementation of specific computational approaches such as artificial intelligence, machine learning and molecular subtyping has yet to become widespread in urology clinical practice for reasons of cost, disruption of clinical workflow and need for prospective validation of informatics approaches in independent patient cohorts. Solving these challenges might accelerate routine integration of bioinformatics into clinical settings.

PMID:37604982 | DOI:10.1038/s41585-023-00805-3

Bioinformatics. 2023 Aug 21:btad506. doi: 10.1093/bioinformatics/btad506. Online ahead of print.

ABSTRACT

MOTIVATION: Antimicrobial peptides (AMPs) are promising molecules to treat infectious diseases caused by multi-drug resistance pathogens, some types of cancer, and other conditions. Computer-aided strategies are efficient tools for the high-throughput screening of AMPs.

RESULTS: This report highlights StarPep Toolbox, an open-source and user-friendly software to study the bioactive chemical space of AMPs using complex network-based representations, clustering, and similarity-searching models. The novelty of this research lies in the combination of network science and similarity-searching techniques, distinguishing it from conventional methods based on machine learning and other computational approaches. The network-based representation of the AMP chemical space presents promising opportunities for peptide drug repurposing, development, and optimization. This approach could serve as a baseline for the discovery of a new generation of therapeutics peptides.

AVAILABILITY: All underlying code and installation files are accessible through GitHub (https://github.com/Grupo-Medicina-Molecular-y-Traslacional/StarPep) under the Apache 2.0 license.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37603724 | DOI:10.1093/bioinformatics/btad506

Cannabis Cannabinoid Res. 2023 Jul 26. doi: 10.1089/can.2022.0336. Online ahead of print.

ABSTRACT

Introduction: Cannabis use is associated with brain functional changes in regions implicated in prominent neuroscientific theories of addiction. Emerging evidence suggests that cannabidiol (CBD) is neuroprotective and may reverse structural brain changes associated with prolonged heavy cannabis use. In this study, we examine how an ∼10-week exposure of CBD in cannabis users affected resting-state functional connectivity in brain regions functionally altered by cannabis use. Materials and Methods: Eighteen people who use cannabis took part in a ∼10 weeks open-label pragmatic trial of self-administered daily 200 mg CBD in capsules. They were not required to change their cannabis exposure patterns. Participants were assessed at baseline and post-CBD exposure with structural magnetic resonance imaging (MRI) and a functional MRI resting-state task (eyes closed). Seed-based connectivity analyses were run to examine changes in the functional connectivity of a priori regions-the hippocampus and the amygdala. We explored if connectivity changes were associated with cannabinoid exposure (i.e., cumulative cannabis dosage over trial, and plasma CBD concentrations and Δ9-tetrahydrocannabinol (THC) plasma metabolites postexposure), and mental health (i.e., severity of anxiety, depression, and positive psychotic symptom scores), accounting for cigarette exposure in the past month, alcohol standard drinks in the past month and cumulative CBD dose during the trial. Results: Functional connectivity significantly decreased pre-to-post the CBD trial between the anterior hippocampus and precentral gyrus, with a strong effect size (d=1.73). Functional connectivity increased between the amygdala and the lingual gyrus pre-to-post the CBD trial, with a strong effect size (d=1.19). There were no correlations with cannabinoids or mental health symptom scores. Discussion: Prolonged CBD exposure may restore/reduce functional connectivity differences reported in cannabis users. These new findings warrant replication in a larger sample, using robust methodologies-double-blind and placebo-controlled-and in the most vulnerable people who use cannabis, including those with more severe forms of Cannabis Use Disorder and experiencing worse mental health outcomes (e.g., psychosis, depression).

PMID:37603080 | DOI:10.1089/can.2022.0336

Gigascience. 2022 Dec 28;12:giad057. doi: 10.1093/gigascience/giad057.

ABSTRACT

BACKGROUND: Computational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approaches. However, the underlying mechanisms of action (MOAs) between repurposed drugs and their target diseases remain largely unknown, which is still a main obstacle for computational drug repurposing methods to be widely adopted in clinical settings.

RESULTS: In this work, we propose KGML-xDTD: a Knowledge Graph-based Machine Learning framework for explainably predicting Drugs Treating Diseases. It is a 2-module framework that not only predicts the treatment probabilities between drugs/compounds and diseases but also biologically explains them via knowledge graph (KG) path-based, testable MOAs. We leverage knowledge-and-publication-based information to extract biologically meaningful "demonstration paths" as the intermediate guidance in the Graph-based Reinforcement Learning (GRL) path-finding process. Comprehensive experiments and case study analyses show that the proposed framework can achieve state-of-the-art performance in both predictions of drug repurposing and recapitulation of human-curated drug MOA paths.

CONCLUSIONS: KGML-xDTD is the first model framework that can offer KG path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations and further accelerate the process of drug discovery for emerging diseases.

PMID:37602759 | DOI:10.1093/gigascience/giad057

Front Pharmacol. 2023 Aug 4;14:1182465. doi: 10.3389/fphar.2023.1182465. eCollection 2023.

ABSTRACT

The emergence of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) posed a serious worldwide threat and emphasized the urgency to find efficient solutions to combat the spread of the virus. Drug repurposing has attracted more attention than traditional approaches due to its potential for a time- and cost-effective discovery of new applications for the existing FDA-approved drugs. Given the reported success of machine learning (ML) in virtual drug screening, it is warranted as a promising approach to identify potential SARS-CoV-2 inhibitors. The implementation of ML in drug repurposing requires the presence of reliable digital databases for the extraction of the data of interest. Numerous databases archive research data from studies so that it can be used for different purposes. This article reviews two aspects: the frequently used databases in ML-based drug repurposing studies for SARS-CoV-2, and the recent ML models that have been developed for the prospective prediction of potential inhibitors against the new virus. Both types of ML models, Deep Learning models and conventional ML models, are reviewed in terms of introduction, methodology, and its recent applications in the prospective predictions of SARS-CoV-2 inhibitors. Furthermore, the features and limitations of the databases are provided to guide researchers in choosing suitable databases according to their research interests.

PMID:37601065 | PMC:PMC10436567 | DOI:10.3389/fphar.2023.1182465

Front Immunol. 2023 Aug 3;14:1225748. doi: 10.3389/fimmu.2023.1225748. eCollection 2023.

ABSTRACT

Graft-versus-host disease (GVHD) remains a major cause of morbidity and mortality after allogeneic stem cell transplantation (SCT). Currently, more patients can receive SCT. This is attributed to the use of reduced intensity regimens and the use of different GVHD prophylaxis that breaks the barrier of human leukocyte antigen, allowing an increase in the donor pool. Once an area with relatively few clinical trial options, there has been an increase in interest in GVHD prophylaxis and treatment, which has led to many US Food and Drug Administration (FDA) approvals. Although there is considerable excitement over novel therapies, many patients may not have access to them due to geographical or other resource constraints. In this review article, we summarize the latest evidence on how we can continue to repurpose drugs for GVHD prophylaxis and treatment. Drugs covered by our review include those that have been FDA approved for other uses for at least 15 years (since 2008); thus, they are likely to have generic equivalents available now or in the near future.

PMID:37600820 | PMC:PMC10435076 | DOI:10.3389/fimmu.2023.1225748

ACS Omega. 2023 Aug 2;8(32):29292-29301. doi: 10.1021/acsomega.3c02691. eCollection 2023 Aug 15.

ABSTRACT

Staphylococcus aureus-mediated infection is a serious threat in this antimicrobial-resistant world. S. aureus has become a "superbug" by challenging conventional as well as modern treatment strategies. Nowadays, drug repurposing has become a new trend for the discovery of new drug molecules. This study focuses on evaluating FDA-approved drugs that can be repurposed against S. aureus infection. Steered molecular dynamics (SMD) has been performed for Lumacaftor and Olaparib against staphylococcal FemX to understand their binding to the active site. A time-dependent external force or rupture force has been applied to the ligands to calculate the force required to dislocate the ligand from the binding pocket. SMD analysis indicates that Lumacaftor has a high affinity for the substrate binding pocket in comparison to Olaparib. Umbrella sampling exhibits that Lumacaftor possesses a higher free energy barrier to displace it from the ligand-binding site. The bactericidal activity of Lumacaftor and Olaparib has been tested, and it shows that Lumacaftor has moderate activity along with biofilm inhibition potential (MIC value with conc. 128 μg/mL). Pharmacokinetic and toxicology evaluations indicate that Lumacaftor has higher pharmacokinetic potential with lower toxicity. This is the first experimental report where staphylococcal FemX has been targeted for the discovery of new drugs. It is suggested that Lumacaftor may be a potential lead molecule against S. aureus.

PMID:37599983 | PMC:PMC10433341 | DOI:10.1021/acsomega.3c02691

J Mol Graph Model. 2023 Aug 16;125:108602. doi: 10.1016/j.jmgm.2023.108602. Online ahead of print.

ABSTRACT

Antiviral drugs are important for the coronavirus disease 2019 (COVID-19) response, as vaccines and antibodies may have reduced efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Antiviral drugs that have been made available for use, albeit with questionable efficacy, include remdesivir (Veklury®), nirmatrelvir-ritonavir (Paxlovid™), and molnupiravir (Lagevrio®). To expand the options available for COVID-19 and prepare for future pandemics, there is a need to investigate new uses for existing drugs and design novel compounds. To support these efforts, we have created a comprehensive library of 750 molecules that have been sourced from in vitro, in vivo, and in silico studies. It is publicly available at our dedicated website (https://epimedlab.org/crl/). The EpiMed Coronabank Chemical Collection consists of compounds that have been divided into 10 main classes based on antiviral properties, as well as the potential to be used for the management, prevention, or treatment of COVID-19 related complications. A detailed description of each compound is provided, along with the molecular formula, canonical SMILES, and U.S. Food and Drug Administration approval status. The chemical structures have been obtained and are available for download. Moreover, the pharmacokinetic properties of the ligands have been characterised. To demonstrate an application of the EpiMed Coronabank Chemical Collection, molecular docking was used to evaluate the binding characteristics of ligands against SARS-CoV-2 nonstructural and accessory proteins. Overall, our database can be used to aid the drug repositioning process, and for gaining further insight into the molecular mechanisms of action of potential compounds of interest.

PMID:37597309 | DOI:10.1016/j.jmgm.2023.108602

Daru. 2023 Aug 19. doi: 10.1007/s40199-023-00471-1. Online ahead of print.

ABSTRACT

PURPOSE: COVID-19 strangely kills some youth with no history of physical weakness, and in addition to the lungs, it may even directly harm other organs. Its complex mechanism has led to the loss of any significantly effective drug, and some patients with severe forms still die daily. Common methods for identifying disease mechanisms and drug design are often time-consuming or reductionist. Here, we use a novel holistic systems biology approach to predict its molecular mechanisms (in vitro), significant molecular relations with SARS, and repurpose drugs.

METHODS: We have utilized its relative phylogenic similarity to SARS. Using the available omics data for SARS and the fewer data for COVID-19 to decode the mechanisms and their significant relations, We applied the Cytoscape analyzer, MCODE, STRING, and DAVID tools to predict the topographically crucial molecules, clusters, protein interaction mappings, and functional analysis. We also applied a novel approach to identify the significant relations between the two infections using the Fischer exact test for MCODE clusters. We then constructed and analyzed a drug-gene network using PharmGKB and DrugBank (retrieved using the dgidb).

RESULTS: Some of the shared identified crucial molecules, BPs and pathways included Kaposi sarcoma-associated herpesvirus infection, Influenza A, and NOD-like receptor signaling pathways. Besides, our identified crucial molecules specific to host response against SARS-CoV-2 included FGA, BMP4, PRPF40A, and IFI16.

CONCLUSION: We also introduced seven new repurposed candidate drugs based on the drug-gene network analysis for the identified crucial molecules. Therefore, we suggest that our newly recommended repurposed drugs be further investigated in Vitro and in Vivo against COVID-19.

PMID:37597114 | DOI:10.1007/s40199-023-00471-1

Nat Prod Bioprospect. 2023 Aug 18;13(1):25. doi: 10.1007/s13659-023-00389-w.

ABSTRACT

Worldwide, fruit is an indispensable treasure house of nutrition for human beings, occupying a vital position of human diet. Postharvest fruit storage requires efficient antifungal agents to control Botrytis cinerea, which is a vital postharvest disease affecting fruit and leading to enormous losses. However, with the enormous abuse of existing antifungal drugs, the problem of drug-resistant fungi is imminent, making the controlling diseases caused by pathogenic fungi even more challenging. Drug repurposing is an efficient alternative method, we evaluated a well-known antifungal chemical, terbinafine, against the agricultural pathogen, B. cinerea in vitro, as a result, terbinafine showed strong antifungal activity. Furthermore, the in vivo antifungal activity of terbinafine was evaluated, the results showed that terbinafine could reduce the decay area on grapes. Terbinafine could disrupt the cell membrane integrity, increase cell membrane permeability, and eventual cell death of B. cinerea. In addition, terbinafine reduced decay incidence, and weight loss and maintained the soluble solids, titratable acidity, ascorbic acid, total phenolic, and malondialdehyde content during the storage period of grapes. Overall, terbinafine could be an antifungal preservative for postharvest table grapes fresh-keeping.

PMID:37594518 | DOI:10.1007/s13659-023-00389-w

Curr Opin Infect Dis. 2023 Aug 21. doi: 10.1097/QCO.0000000000000947. Online ahead of print.

ABSTRACT

PURPOSE OF REVIEW: Cystic echinococcosis is a neglected zoonosis for which humans are dead end hosts. It is not only widely distributed in sheep rearing areas of low-income and middle-income countries but also has a significant presence in wealthy countries, for example, in Europe. It results in considerable morbidity, and its current management is far from optimal. Medical management is with a benzimidazole, with the addition of praziquantel under some circumstances.

RECENT FINDINGS: Interest in mebendazole as an anticancer drug has stimulated research into new drug formulations to improve bioavailability and possibly reduce inter-individual variability in in-vivo drug levels, which may help its activity against cystic echinococcosis. Further evidence to support administration of albendazole with a fatty meal has been provided. GlaxoSmithKilne (GSK) has agreed to extend its albendazole donation programme to include echinococcosis. The search for new drugs has focussed on natural products, such as essential oils and on repurposing of existing drugs licensed for human use against other conditions.

SUMMARY: The medical treatment of cystic echinococcosis remains sorely neglected, with no new drugs for almost 40 years. We need a better understanding of how to use the drugs we do have, whilst seeking new ones. Drug repurposing may be the best pathway.

PMID:37593991 | DOI:10.1097/QCO.0000000000000947

Curr Mol Med. 2023 Aug 17. doi: 10.2174/1566524023666230817115937. Online ahead of print.

ABSTRACT

BACKGROUND: Despite recent progress in drug development, lung cancer remains a complex disease that poses a major public health issue worldwide, and new therapeutic strategies are urgently needed because of the failure of standard treatments. Ion channels play a critical role in various cellular processes that regulate cell proliferation, differentiation, and cell death.

OBJECTIVES: The potential of ion channel modulators as tumor growth suppressors has been highlighted in recent studies. Therefore, we hypothesized that hydroquinidine (HQ), a previously understudied potassium channel modulator, might have anticarcinogenic activity against A549 cells.

METHODS: The anticancer potential of HQ was investigated using various well-established in vitro assays.

RESULTS: HQ significantly decreased colony formation and tumorigenicity and exhibited a significant anti-migratory effect in A549 cells. Our results demonstrated that HQ significantly inhibited the growth of cancer cells by decreasing the proliferation rate while increasing cell death. The altered gene expression profile in response to treatment with HQ was consistent with the observed cellular effects. Incubation of cells with HQ resulted in the downregulation of genes involved in cell division and survival, while genes promoting cell cycle arrest and apoptosis were upregulated.

CONCLUSION: Our findings suggest that HQ has the potential to limit lung cancer growth as a novel potent anticarcinogenic agent. However, more investigations are needed to gain further insight into the mechanism of action of HQ and to evaluate its efficacy in in-vivo models.

PMID:37592773 | DOI:10.2174/1566524023666230817115937

J Intern Med. 2023 Aug 17. doi: 10.1111/joim.13711. Online ahead of print.

ABSTRACT

Ursodeoxycholic acid (UDCA), an off-patent drug used to treat liver disease, is able to block SARS-CoV-2 entry into the cells downregulating ACE2 expression, a promising strategy to protect against infection. In this light, John et al. have recently demonstrated that in patients with cirrhosis, UDCA exposure was associated with both a decrease in SARS-CoV-2 infection and a reduction in COVID-19 severity confirming previous data published by Brevini et al. To investigate the impact of UDCA treatment in SARS-CoV-2 infection and COVID-19 outcomes in an unselected population of COVID-19 patients we used the administrative databases from Lombardy (Northern Italy), the first region of Western world to experience a rapid increase in the number of COVID-19 cases and related deaths and the most populated Italian region. The analysis included patients from the 1st and 2nd pandemic waves, were wild-type and alfa variant were predominant. This article is protected by copyright. All rights reserved.

PMID:37592407 | DOI:10.1111/joim.13711

Genes Dis. 2023 Jan 20;11(1):148-175. doi: 10.1016/j.gendis.2022.12.013. eCollection 2024 Jan.

ABSTRACT

Chemotherapy is an effortless and frequently used approach in cancer therapy. However, in most cases, it can only prolong life expectancy and does not guarantee a complete cure. Furthermore, chemotherapy is associated with severe adverse effects, one of the major complications of effective cancer therapy. In addition, newly published research outputs show that cancer stem cells are involved in cancer disease progression, drug resistance, metastasis, and recurrence and that they are functional in the trans-differentiation capacity of cancer stem cells to cancer cells in response to treatments. Novel strategies are therefore required for better management of cancer therapy. The prime approach would be to synthesize and develop novel drugs that need extensive resources, time, and endurance to be brought into therapeutic use. The subsequent approach would be to screen the anti-cancer activity of available non-cancerous drugs. This concept of repurposing non-cancer drugs as an alternative to current cancer therapy has become popular in recent years because using existing anticancer drugs has several adverse effects. Micronutrients have also been investigated for cancer therapy due to their significant anti-cancer effects with negligible or no side effects and availability in food sources. In this paper, we discuss an ideal hypothesis for screening available non-cancerous drugs with anticancer activity, with a focus on cancer stem cells and their clinical application for cancer treatment. Further, drug repurposing and the combination of micronutrients that can target both cancers and cancer stem cells may result in a better therapeutic approach leading to maximum tumor growth control.

PMID:37588226 | PMC:PMC10425757 | DOI:10.1016/j.gendis.2022.12.013

Methods. 2023 Aug 14:S1046-2023(23)00134-2. doi: 10.1016/j.ymeth.2023.08.006. Online ahead of print.

ABSTRACT

Drug-target interaction (DTI) prediction serves as the foundation of new drug findings and drug repositioning. For drugs/targets, the sequence data contains the biological structural information, while the heterogeneous network contains the biochemical functional information. These two types of information describe different aspects of drugs and targets. Due to the complexity of DTI machinery, it is necessary to learn the representation from multiple perspectives. We hereby try to design a way to leverage information from multi-source data to the maximum extent and find a strategy to fuse them. To address the above challenges, we propose a model, named MOVE (short for integrating multi-source information for predicting DTI via cross-view contrastive learning), for learning comprehensive representations of each drug and target from multi-source data. MOVE extracts information from the sequence view and the network view, then utilizes a fusion module with auxiliary contrastive learning to facilitate the fusion of representations. Experimental results on the benchmark dataset demonstrate that MOVE is effective in DTI prediction.

PMID:37586602 | DOI:10.1016/j.ymeth.2023.08.006

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2023 Jun 28;48(6):868-876. doi: 10.11817/j.issn.1672-7347.2023.220644.

ABSTRACT

OBJECTIVES: Staphylococcus epidermidis (S. epidermidis) is a Gram-positive opportunistic pathogen that often causes hospital infections. With the abuse of antibiotics, the resistance of S. epidermidis gradually increases, and drug repurposing has become a research hotspot in the treating of refractory drug-resistant bacterial infections. This study aims to study the antimicrobial and antibiofilm effects of simeprevir, an antiviral hepatitis drug, on S. epidermidis in vitro.

METHODS: The micro-dilution assay was used to determine the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of simeprevir against S. epidermidis. Crystal violet staining assay was used to detect the biofilm inhibitory effect of simeprevir. The antimicrobial activity of simeprevir against S. epidermidis and its biofilm were explored by SYTO9/PI fluorescent staining. The combined effect between simeprevir and gentamycin was assessed by checkerboard assay and was confirmed by time-inhibition assay.

RESULTS: Simeprevir showed significant antimicrobial effects against S. epidermidis type strains and clinical isolates with the MIC and MBC at 2-16 μg/mL and 4-32 μg/mL, respectively. The antimicrobial effects of simeprevir were confirmed by SYTO9/PI staining. Simeprevir at MIC could significantly inhibit and break the biofilm on cover slides. Similarly, simeprevir also significantly inhibit the biofilm formation on the surface of urine catheters either in TSB [from (0.700±0.020) to (0.050±0.004)] (t=54.03, P<0.001), or horse serum [from (1.00±0.02) to (0.13±0.01)] (t=82.78, P<0.001). Synergistic antimicrobial effect was found between simeprevir and gentamycin against S. epidermidis with the fractional inhibitory concentration index of 0.5.

CONCLUSIONS: Simeprevir shows antimicrobial effect and anti-biofilm activities against S. epidermidis.

PMID:37587072 | DOI:10.11817/j.issn.1672-7347.2023.220644

PLoS One. 2023 Aug 16;18(8):e0287198. doi: 10.1371/journal.pone.0287198. eCollection 2023.

ABSTRACT

Drug repurposing is the finding new activity of the existing drug. Recently, Albendazole's well-known antihelmintic has got the attention of an anticancer drug. Plausible evidence of the interaction of Albendazole with one of the types of tyrosine kinase protein receptor, vascular endothelial growth factor receptor-2 (VEGFR-2) is still not well understood. Inhibition of the VEGFR-2 receptor can prevent tumor growth. The current study investigated the interaction of Albendazole with VEGFR-2.It was found that the said interaction exhibited potent binding energy ΔG = -7.12 kcal/mol, inhibitory concentration (Ki) = 6.04 μM, and as positive control comparison with standard drug (42Q1170A) showed ΔG = -12.35 kcal/mol and Ki = 881 μM. The key residue Asp1046 was formed involved hydrogen bonding with Albendazole. The molecular dynamics simulation study revealed the stable trajectory of the VEGFR-2 receptor with Albendazole bound complex having significant high free energy of binding as calculated from Molecular Mechanics Generalized Born and Surface Area study ΔG = -42.07±2.4 kcal/mol. The binding energy is significantly high for greater stability of the complex. Principal component analysis of molecular docking trajectories exhibited ordered motion at higher modes, implying a high degree of VEGFR-2 and Albendazole complex stability as seen with the standard drug 42Q. Therefore, the current work suggests the role of Albendazole as a potent angiogenesis inhibitor as ascertained by its potential interaction with VEGFR-2. The findings of research will aid in the future development of Albendazole in anticancer therapy.

PMID:37585409 | DOI:10.1371/journal.pone.0287198

Heliyon. 2023 Aug 1;9(8):e18863. doi: 10.1016/j.heliyon.2023.e18863. eCollection 2023 Aug.

ABSTRACT

High malaria mortality coupled with increased emergence of resistant multi-drug resistant strains of Plasmodium parasite, warrants the development of new and effective antimalarial drugs. However, drug design and discovery are costly and time-consuming with many active antimalarial compounds failing to get approved due to safety reasons. To address these challenges, the current study aimed at testing the antiplasmodial activities of approved drugs that were predicted using a target-similarity approach. This approach is based on the fact that if an approved drug used to treat another disease targets a protein similar to Plasmodium falciparum protein, then the drug will have a comparable effect on P. falciparum. In a previous study, in vitro antiplasmodial activities of 10 approved drugs was reported of the total 28 approved drugs. In this study, six out of 18 drugs that were previously not tested, namely epirubicin, irinotecan, venlafaxine, palbociclib, pelitinib, and PD153035 were tested for antiplasmodial activity. The drug susceptibility in vitro assays against five P. falciparum reference strains (D6, 3D7, W2, DD2, and F32 ART) and ex vivo assays against fresh clinical isolates were done using the malaria SYBR Green I assay. Standard antimalarial drugs were included as controls. Epirubicin and irinotecan showed excellent antiplasmodial ex vivo activity against field isolates with mean IC50 values of 0.044 ± 0.033 μM and 0.085 ± 0.055 μM, respectively. Similar activity was observed against W2 strain where epirubicin had an IC50 value of 0.004 ± 0.0009 μM, palbociclib 0.056 ± 0.006 μM, and pelinitib 0.057 ± 0.013 μM. For the DD2 strain, epirubicin, irinotecan and PD 153035 displayed potent antiplasmodial activity (IC50 < 1 μM). Epirubicin and irinotecan showed potent antiplasmodial activities (IC50 < 1 μM) against DD2, D6, 3D7, and F32 ART strains and field isolates. This shows the potential use of these drugs as antimalarials. All the tested drugs showed antiplasmodial activities with IC50 values below 20 μM, which suggests that our target similarity-based strategy is successful at predicting antiplasmodial activity of compounds thereby circumventing challenges in antimalarial drug discovery.

PMID:37583763 | PMC:PMC10424068 | DOI:10.1016/j.heliyon.2023.e18863