Cardiovasc Hematol Agents Med Chem. 2023 Oct 27. doi: 10.2174/0118715257259037231012182741. Online ahead of print.

ABSTRACT

INTRODUCTION: The repurposing of drugs for their anticancer potential is gaining a lot of importance in drug discovery.

AIMS: The present study aims to explore the potential of Simvastatin (SIM), a drug used in the treatment of high cholesterol, and thymoquinone (Nigella Sativa) (THY) for its anti-cancer activity on breast cancer cell lines. Thymoquinone is reported to have many potential medicinal properties exhibiting antioxidant, antiinflammatory, anti-cancer, and activities like tissue growth and division, hormone regulation, immune response and development, and cell signaling.

METHODS: In this analysis, we explored the inhibitory effects of the combination of simvastatin ad thymoquinone on two breast cancer cell lines viz MCF-7 and MDA-MB-231 cells. The combined effect of simvastatin ad thymoquinone on cell viability, colony formation, cell migration, and orientation of more programmed cell death in vitro was studied. Cell cycle arrest in the G2/M phase was concomitant with the combined effect of SIM and THY persuading apoptosis and generating reactive oxygen species (ROS).

RESULTS: The cell cycle arrest in combined treatment was 8.1% on MCF-7 cells and 3.8 % for MDA-MB-231 cells an increased apoptosis was observed when cells were treated in combination which was about 76.20% and 58.15 % respectively for MCF-7 and MDA-MB-231 cells.

CONCLUSION: It was concluded that the combined effect of simvastatin and thymoquinone stimulates apoptosis in breast cancer cells.

PMID:37907488 | DOI:10.2174/0118715257259037231012182741

J Chem Inf Model. 2023 Oct 31. doi: 10.1021/acs.jcim.3c01090. Online ahead of print.

ABSTRACT

Machine learning algorithms have been increasingly applied in drug development due to their efficiency and effectiveness. Machine learning-based drug repurposing can contribute to the identification of novel therapeutic applications for drugs with other indications. The current study used a trained machine learning model to screen a vast chemical library for new JAK2 inhibitors, the biological activities of which were reported. Reference JAK2 inhibitors, comprising 1911 compounds, have experimentally determined IC50 values. To generate the input to the machine learning model, reference compounds were subjected to RDKit, a cheminformatic toolkit, to extract molecular descriptors. A Random Forest Regression model from the Scikit-learn machine learning library was applied to obtain a predictive regression model and to analyze each molecular descriptor's role in determining IC50 values in the reference data set. Then, IC50 values of the library compounds, comprised of 1,576,903 compounds, were predicted using the generated regression model. Interestingly, some compounds that exhibit high IC50 values from the prediction were reported to possess JAK inhibition activity, which indicates the limitations of the prediction model. To confirm the JAK2 inhibition activity of predicted compounds, molecular docking and molecular dynamics simulation were carried out with the JAK inhibitor reference compound, tofacitinib. The binding affinity of docked compounds in the active region of JAK2 was also analyzed by the gmxMMPBSA approach. Furthermore, experimental validation confirmed the results from the computational analysis. Results showed highly comparable outcomes concerning tofacitinib. Conclusively, the machine learning model can efficiently improve the virtual screening of drugs and drug development.

PMID:37906702 | DOI:10.1021/acs.jcim.3c01090

Circulation. 2023 Oct 31. doi: 10.1161/CIRCULATIONAHA.123.064734. Online ahead of print.

ABSTRACT

BACKGROUND: Kawasaki disease (KD) and multisystem inflammatory syndrome in children (MIS-C) share similar clinical manifestations, including cardiovascular complications, suggesting similar underlying immunopathogenic processes. Aberrant neutrophil activation may play a crucial role in the shared pathologies of KD and MIS-C; however, the associated pathogenic mechanisms and molecular drivers remain unknown.

METHODS: We performed a single-cell meta-analysis of neutrophil activation with 103 pediatric single-cell transcriptomic peripheral blood mononuclear cell data across 9 cohorts, including healthy controls, KD, MIS-C, compared with dengue virus infection, juvenile idiopathic arthritis, and pediatric celiac disease. We used a series of computational analyses to investigate the shared neutrophil transcriptional programs of KD and MIS-C that are linked to systemic damage and cardiac pathologies, and suggested Food and Drug Administration-approved drugs to consider as KD and MIS-C treatment.

RESULTS: We meta-analyzed 521 950 high-quality cells. We found that blood signatures associated with risks of cardiovascular events are enriched in neutrophils of KD and MIS-C. We revealed the expansion of CD177+ neutrophils harboring hyperactivated effector functions in both KD and MIS-C, but not in healthy controls or in other viral-, inflammatory-, or immune-related pediatric diseases. KD and MIS-C CD177+ neutrophils had highly similar transcriptomes, marked by conserved signatures and pathways related to molecular damage. We found the induction of a shared neutrophil expression program, potentially regulated by SPI1 (Spi-1 proto-oncogene), which confers enhanced effector functions, especially neutrophil degranulation. CD177 and shared neutrophil expression program expressions were associated with acute stages and attenuated during KD intravenous immunoglobulin treatment and MIS-C recovery. Network analysis identified hub genes that correlated with the high activation of CD177+ neutrophils. Disease-gene association analysis revealed that the CD177+ neutrophil shared neutrophil expression program was associated with the development of coronary and myocardial disorders. Last, we identified and validated TSPO (translocator protein) and S100A12 (S100 calcium-binding protein A12) as main molecular targets, for which the Food and Drug Administration-approved drugs methotrexate, zaleplon, metronidazole, lorazepam, clonazepam, temazepam, and zolpidem, among others, are primary candidates for drug repurposing.

CONCLUSIONS: Our findings indicate that CD177+ neutrophils may exert systemic pathological damage contributing to the shared morbidities in KD and MIS-C. We uncovered potential regulatory drivers of CD177+ neutrophil hyperactivation and pathogenicity that may be targeted as a single therapeutic strategy for either KD or MIS-C.

PMID:37905415 | DOI:10.1161/CIRCULATIONAHA.123.064734

medRxiv. 2023 Oct 16:2023.10.16.23297073. doi: 10.1101/2023.10.16.23297073. Preprint.

ABSTRACT

Multimorbidity represents an increasingly important public health challenge with far-reaching implications for health management and policy. Mental health and metabolic diseases have a well-established epidemiological association. In this study, we investigate the genetic intersection between type 2 diabetes and schizophrenia. We use Mendelian randomization to examine potential causal relationships between the two conditions and related endophenotypes. We report no compelling evidence that type 2 diabetes genetic liability potentially causally influences schizophrenia risk and vice versa . Our findings show that increased body mass index (BMI) has a protective effect against schizophrenia, in contrast to the well-known risk-increasing effect of BMI on type 2 diabetes risk. We identify evidence of colocalization of association signals for these two conditions at 11 genomic loci, six of which have opposing directions of effect for type 2 diabetes and schizophrenia. To elucidate these colocalizing signals, we integrate multi-omics data from bulk and single-cell gene expression studies, along with functional information. We identify high-confidence effector genes and find that they are enriched for homeostasis and lipid-related pathways. We also highlight drug repurposing opportunities including N-methyl-D-aspartate (NMDA) receptor antagonists. Our findings provide insights into shared biological mechanisms for type 2 diabetes and schizophrenia, highlighting common factors that influence the risk of the two conditions in opposite directions and shedding light on the complex nature of this comorbidity.

PMID:37905000 | PMC:PMC10615007 | DOI:10.1101/2023.10.16.23297073

bioRxiv. 2023 Oct 17:2023.10.15.562423. doi: 10.1101/2023.10.15.562423. Preprint.

ABSTRACT

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting fundamental bioinformatics data analyses. The recent feature of accepting image-inputs by ChatGPT motivated us to explore its efficacy in deciphering bioinformatics illustrations. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when quantitative analysis of visual elements was involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

PMID:37904927 | PMC:PMC10614796 | DOI:10.1101/2023.10.15.562423

Sci Rep. 2023 Oct 30;13(1):18571. doi: 10.1038/s41598-023-41374-0.

ABSTRACT

External factors such as exposure to a chemical, drug, or toxicant (CDT), or conversely, the lack of certain chemicals can cause many diseases. The ability to identify such causal CDTs based on changes in the gene expression profile is extremely important in many studies. Furthermore, the ability to correctly infer CDTs that can revert the gene expression changes induced by a given disease phenotype is a crucial step in drug repurposing. We present an approach for Predicting Upstream REgulators (PURE) designed to tackle this challenge. PURE can correctly infer a CDT from the measured expression changes in a given phenotype, as well as correctly identify drugs that could revert disease-induced gene expression changes. We compared the proposed approach with four classical approaches as well as with the causal analysis used in Ingenuity Pathway Analysis (IPA) on 16 data sets (1 rat, 5 mouse, and 10 human data sets), involving 8 chemicals or drugs. We assessed the results based on the ability to correctly identify the CDT as indicated by its rank. We also considered the number of false positives, i.e. CDTs other than the correct CDT that were reported to be significant by each method. The proposed approach performed best in 11 out of the 16 experiments, reporting the correct CDT at the very top 7 times. IPA was the second best, reporting the correct CDT at the top 5 times, but was unable to identify the correct CDT at all in 5 out of the 16 experiments. The validation results showed that our approach, PURE, outperformed some of the most popular methods in the field. PURE could effectively infer the true CDTs responsible for the observed gene expression changes and could also be useful in drug repurposing applications.

PMID:37903768 | DOI:10.1038/s41598-023-41374-0

In Silico Pharmacol. 2023 Oct 25;11(1):27. doi: 10.1007/s40203-023-00164-2. eCollection 2023.

ABSTRACT

Cardiovascular diseases are the primary factor for increased mortality rates around the world. Atherosclerosis brought on by high serum cholesterol can result in coronary heart disease (CHD). The risk of CHD is markedly reduced by lowering serum cholesterol levels. Scientists across the world are inventing new treatment regimens for lowering blood lipid levels. In this work, we repurposed the already established drugs, i.e., cyclizine derivatives as antihyperlipidemic agents. The repurposing was done based on the similarity of the selected cyclizine derivatives with the already established antihyperlipidemic drug, fenofibrate. Computational studies were performed and the 16 cyclizine derivatives docked against PPAR. alpha scored higher than fenofibrate. Lifarizine and medibazine outperform fenofibrate inmmgbsa. Fenofibrate, etodroxizine, meclizine, and cinnarizine had similar mmgbsa scores. The ADME properties of these compounds were performed and from that etodroxizine and levocetirizine were found to have better properties. The computational studies were performed using the Schrodinger software, maestro 12.8. The "Protein Preparation Wizard" module in the Maestro panel was used to create the protein structure and OPLS4 force field was used for energy minimization. The maestro builder panel's "Ligprep", "Receptor Grid Generation" and "Ligand Docking" modules were then used to prepare ligands, receptor grids and to perform docking respectively. MMGBSA was performed on the "prime MMGBSA" segment. Using the "Qikprop" setting in the maestro panel, a number of ADMET properties were predicted, and the program was run in default mode using vsgb as the solvation model.

PMID:37899967 | PMC:PMC10600089 | DOI:10.1007/s40203-023-00164-2

Pharmaceuticals (Basel). 2023 Oct 15;16(10):1465. doi: 10.3390/ph16101465.

ABSTRACT

Oxaliplatin is a chemotherapy drug that can induce severe acute neuropathy in patients within hours of treatment. In our previous study, 10 mg/kg [6]-shogaol (i.p.) significantly alleviated cold and mechanical allodynia induced by a 6 mg/kg oxaliplatin injection (i.p.); however, the precise serotonin-modulatory effect has not been investigated. In this study, we showed that intrathecal injections of NAN-190 (5-HT1A receptor antagonist, 1 µg) and MDL-72222 (5-HT3 receptor antagonist, 15 µg), but not ketanserin (5-HT2A receptor antagonist, 1 µg), significantly blocked the analgesic effect of [6]-shogaol (10 mg/kg, i.p.). Furthermore, the gene expression of the serotonin-synthesizing enzyme tryptophan hydroxylase 2 (TPH2) and serotonin levels in the spinal cord and serum were significantly downregulated (p < 0.0001 and p = 0.0002) and upregulated (p = 0.0298 and p = 0.0099) after oxaliplatin and [6]-shogaol administration, respectively. Moreover, both the gene and protein expression of the spinal serotonin receptors 5-HT1A and 5-HT3 significantly increased after [6]-shogaol injections (p < 0.0001). Finally, intrathecal injections of both receptor agonists (8-OH-DPAT; 5-HT1A receptor agonist, 10 µg and m-CPBG; 5-HT3 receptor agonist, 15 µg) mimicked the effects of [6]-shogaol in oxaliplatin-injected mice. Taken together, these results demonstrate that [6]-shogaol attenuates oxaliplatin-induced neuropathic pain by modulating the spinal serotoninergic system.

PMID:37895936 | DOI:10.3390/ph16101465

Genes (Basel). 2023 Oct 11;14(10):1927. doi: 10.3390/genes14101927.

ABSTRACT

The anticancer drug mithramycin (MTH), has been proposed for drug repurposing after the finding that it is a potent inducer of fetal hemoglobin (HbF) production in erythroid precursor cells (ErPCs) from β-thalassemia patients. In this respect, previously published studies indicate that MTH is very active in inducing increased expression of γ-globin genes in erythroid cells. This is clinically relevant, as it is firmly established that HbF induction is a valuable approach for the therapy of β-thalassemia and for ameliorating the clinical parameters of sickle-cell disease (SCD). Therefore, the identification of MTH biochemical/molecular targets is of great interest. This study is inspired by recent robust evidence indicating that the expression of γ-globin genes is controlled in adult erythroid cells by different transcriptional repressors, including Oct4, MYB, BCL11A, Sp1, KLF3 and others. Among these, BCL11A is very important. In the present paper we report evidence indicating that alterations of BCL11A gene expression and biological functions occur during MTH-mediated erythroid differentiation. Our study demonstrates that one of the mechanisms of action of MTH is a down-regulation of the transcription of the BCL11A gene, while a second mechanism of action is the inhibition of the molecular interactions between the BCL11A complex and specific sequences of the γ-globin gene promoter.

PMID:37895276 | DOI:10.3390/genes14101927

Int J Mol Sci. 2023 Oct 16;24(20):15236. doi: 10.3390/ijms242015236.

ABSTRACT

Pancreatic cancer (PC) is currently recognized as the seventh most prevalent cause of cancer-related mortality among individuals of both genders. It is projected that a significant number of individuals will succumb to this disease in the forthcoming years. Extensive research and validation have been conducted on both gemcitabine and 5-fluorouracil as viable therapeutic options for PC. Nevertheless, despite concerted attempts to enhance treatment outcomes, PC continues to pose significant challenges in terms of achieving effective treatment alone through chemotherapy. Gallic acid, an endogenous chemical present in various botanical preparations, has attracted considerable attention due to its potential as an anticancer agent. The results of the study demonstrated that gallic acid exerted a decline in cell viability that was dependent on its concentration. Furthermore, it efficiently suppressed cell proliferation in PC cells. This study observed a positive correlation between gallic acid and the production of reactive oxygen species (ROS). Additionally, it confirmed the upregulation of proteins associated with the protein kinase-like endoplasmic reticulum kinase (PERK) pathway, which is one of the pathways involved in endoplasmic reticulum (ER) stress. Moreover, the administration of gallic acid resulted in verified alterations in the transmission of mitogen-activated protein kinase (MAPK) signals. Notably, an elevation in the levels of p-p38, which represents the phosphorylated state of p38 MAPK was detected. The scavenger of reactive oxygen species (ROS), N-Acetyl-L-cysteine (NAC), has shown inhibitory effects on phosphorylated p38 (p-p38), whereas the p38 inhibitor SB203580 inhibited C/EBP homologous protein (CHOP). In both instances, the levels of PARP have been successfully reinstated. In other words, the study discovered a correlation between endoplasmic reticulum stress and the p38 signaling pathway. Consequently, gallic acid induces the activation of both the p38 pathway and the ER stress pathway through the generation of ROS, ultimately resulting in apoptosis. The outcomes of this study provide compelling evidence to support the notion that gallic acid possesses considerable promise as a viable therapeutic intervention for pancreatic cancer.

PMID:37894916 | DOI:10.3390/ijms242015236

Molecules. 2023 Oct 11;28(20):7037. doi: 10.3390/molecules28207037.

ABSTRACT

Coffee became a beverage that was in demand in the world and consequently produced millions of tons of coffee byproducts namely coffee silverskin (CS). Unutilized CS will be waste and cause environmental pollution such as greenhouse gas emissions, landfill waste, and groundwater contamination. This is a research concern at this time, although many studies have been conducted to find newer applications of CS, exploration of its benefits in the health sector is still limited. Therefore, exploring the benefits of CS to prevent or delay aging will be very interesting to develop in functional food industry technology. Therefore, this study aims to report profiling metabolites or phytochemicals, biological activities in terms of antioxidant activity, and potential anti-aging of CS via molecular docking simulation and in vitro modulation of the mTOR/AMPK/SIRT1 pathway. Something new has been obtained from this work, the profile of phytocompounds, and biological activities both in molecular docking simulation and in vitro studies. Some of the compounds observed in Robusta CS extract (rCSE) such as Epicatechin, Kaempferol, and Quercitrin, and Arabica CS extract (aCSE) such as (+)-Catechin dan Naringin have promising potential as inhibitors of iNOS, mTOR, and HIF-1α via molecular docking simulation. Interestingly, the in vitro biological activity assay of antioxidant and anti-aging activity, rCSE showed the same promising potential as the results of a molecular docking simulation. More interestingly, AMPK/SIRT1/mTOR expressions are well modulated by rCSE compared to aCSE significantly (p < 0.05). This makes the rCSE have promising biological activity as a candidate for functional food development and/or treatment agent in combating free radicals that cause the aging process. In vivo studies and human trials are certainly needed to see the further efficacy of the rCSE in the future.

PMID:37894516 | DOI:10.3390/molecules28207037

Nucleic Acids Res. 2023 Oct 27:gkad888. doi: 10.1093/nar/gkad888. Online ahead of print.

ABSTRACT

Patient-derived gene expression signatures induced by cancer treatment, obtained from paired pre- and post-treatment clinical transcriptomes, can help reveal drug mechanisms of action (MOAs) in cancer patients and understand the molecular response mechanism of tumor sensitivity or resistance. Their integration and reuse may bring new insights. Paired pre- and post-treatment clinical transcriptomic data are rapidly accumulating. However, a lack of systematic collection makes data access, integration, and reuse challenging. We therefore present the Cancer Drug-induced gene expression Signature DataBase (CDS-DB). CDS-DB has collected 78 patient-derived, paired pre- and post-treatment transcriptomic source datasets with uniformly reprocessed expression profiles and manually curated metadata such as drug administration dosage, sampling time and location, and intrinsic drug response status. From these source datasets, 2012 patient-level gene perturbation signatures were obtained, covering 85 therapeutic regimens, 39 cancer subtypes and 3628 patient samples. Besides data browsing, download and search, CDS-DB also supports single signature analysis (including differential gene expression, functional enrichment, tumor microenvironment and correlation analyses), signature comparative analysis and signature connectivity analysis. This provides insights into drug MOA and its heterogeneity in patients, drug resistance mechanisms, drug repositioning and drug (combination) discovery, etc. CDS-DB is available at http://cdsdb.ncpsb.org.cn/.

PMID:37889038 | DOI:10.1093/nar/gkad888

ACS Infect Dis. 2023 Oct 27. doi: 10.1021/acsinfecdis.3c00350. Online ahead of print.

ABSTRACT

The inhibition of efflux pumps is a promising approach to combating multidrug-resistant bacteria. We have developed a combined structure- and ligand-based model, using OpenEye software, for the identification of inhibitors of AcrB, the inner membrane protein component of the AcrAB-TolC efflux pump in Escherichia coli. From a database of 1391 FDA-approved drugs, 23 compounds were selected to test for efflux inhibition in E. coli. Seven compounds, including ivacaftor (25), butenafine (19), naftifine (27), pimozide (30), thioridazine (35), trifluoperazine (37), and meloxicam (26), enhanced the activity of at least one antimicrobial substrate and inhibited the efflux pump-mediated removal of the substrate Nile Red from cells. Ivacaftor (25) inhibited efflux dose dependently, had no effect on an E. coli strain with genomic deletion of the gene encoding AcrB, and did not damage the bacterial outer membrane. In the presence of a sub-minimum inhibitory concentration (MIC) of the outer membrane permeabilizer colistin, ivacaftor at 1 μg/mL reduced the MICs of erythromycin and minocycline by 4- to 8-fold. The identification of seven potential AcrB inhibitors shows the merits of a combined structure- and ligand-based approach to virtual screening.

PMID:37888944 | DOI:10.1021/acsinfecdis.3c00350

Toxics. 2023 Oct 22;11(10):875. doi: 10.3390/toxics11100875.

ABSTRACT

The process of discovering small molecule drugs involves screening numerous compounds and optimizing the most promising ones, both in vitro and in vivo. However, approximately 90% of these optimized candidates fail during trials due to unexpected toxicity or insufficient efficacy. Current concepts with respect to drug-protein interactions suggest that each small molecule interacts with an average of 6-11 targets. This implies that approved drugs and even discontinued compounds could be repurposed by leveraging their interactions with unintended targets. Therefore, we developed a computational repurposing framework for small molecules, which combines artificial intelligence/machine learning (AI/ML)-based and chemical similarity-based target prediction methods with cross-species transcriptomics information. This repurposing methodology incorporates eight distinct target prediction methods, including three machine learning methods. By using multiple orthogonal methods for a "dataset" composed of 2766 FDA-approved drugs targeting multiple therapeutic target classes, we identified 27,371 off-target interactions involving 2013 protein targets (i.e., an average of around 10 interactions per drug). Relative to the drugs in the dataset, we identified 150,620 structurally similar compounds. The highest number of predicted interactions were for drugs targeting G protein-coupled receptors (GPCRs), enzymes, and kinases with 10,648, 4081, and 3678 interactions, respectively. Notably, 17,283 (63%) of the off-target interactions have been confirmed in vitro. Approximately 4000 interactions had an IC50 of <100 nM for 1105 FDA-approved drugs and 1661 interactions had an IC50 of <10 nM for 696 FDA-approved drugs. Together, the confirmation of numerous predicted interactions and the exploration of tissue-specific expression patterns in human and animal tissues offer insights into potential drug repurposing for new therapeutic applications.

PMID:37888725 | DOI:10.3390/toxics11100875

Res Sq. 2023 Oct 19:rs.3.rs-3443080. doi: 10.21203/rs.3.rs-3443080/v1. Preprint.

ABSTRACT

We developed a computational framework that integrates Genome-Wide Association Studies (GWAS) and post-GWAS analyses, designed to facilitate drug repurposing for COVID-19 treatment. The comprehensive approach combines transcriptomic-wide associations, polygenic priority scoring, 3D genomics, viral-host protein-protein interactions, and small-molecule docking. Through GWAS, we identified nine druggable host genes associated with COVID-19 severity and SARS-CoV-2 infection, all of which show differential expression in COVID-19 patients. These genes include IFNAR1, IFNAR2, TYK2, IL10RB, CXCR6, CCR9, and OAS1. We performed an extensive molecular docking analysis of these targets using 553 small molecules derived from five therapeutically enriched categories, namely antibacterials, antivirals, antineoplastics, immunosuppressants, and anti-inflammatories. This analysis, which comprised over 20,000 individual docking analyses, enabled the identification of several promising drug candidates. All results are available via the DockCoV2 database (https://dockcov2.org/drugs/). The computational framework ultimately identified nine potential drug candidates: Peginterferon alfa-2b, Interferon alfa-2b, Interferon beta-1b, Ruxolitinib, Dactinomycin, Rolitetracycline, Irinotecan, Vinblastine, and Oritavancin. While its current focus is on COVID-19, our proposed computational framework can be applied more broadly to assist in drug repurposing efforts for a variety of diseases. Overall, this study underscores the potential of human genetic studies and the utility of a computational framework for drug repurposing in the context of COVID-19 treatment, providing a valuable resource for researchers in this field.

PMID:37886583 | PMC:PMC10602133 | DOI:10.21203/rs.3.rs-3443080/v1

Recent Adv Inflamm Allergy Drug Discov. 2023 Oct 25. doi: 10.2174/0127722708268538231010041307. Online ahead of print.

ABSTRACT

BACKGROUND: Antibacterial and antimalarial drugs play a critical role in combating infectious diseases. It is a continuous work to develop new types of antibacterial and antimalarial drugs.

OBJECTIVES: To better understand current landscape and association of antibacterial and antimalarial agents, the European patent analysis was performed.

METHODS: Antibacterial and antimalarial agents were analyzed by patent analysis. Patent documents from January 2003 to May 2022 were retrieved and analyzed.

RESULTS: The present study indicated there were virtually three therapeutic approaches for antibacterial agents, including chemical drugs, biological products and siRNA technology. Chemical drugs were a mainstream therapeutic approach for development of both antibacterial and antimalarial agents. However, the present study found that in contrast to antimalarials, siRNA technology had been initially explored as therapeutic strategy for antibacterial agents. Also, our study is the first to show that there is a low correlation between antibacterial and antimalarial agents.

CONCLUSION: Globally, our study is the first one to show that it may be not a fast approach to discover antimalarial drugs from antibacterial agents based on drug repurposing. siRNA technology as therapeutic strategy had been explored and used in antibacterial field.

PMID:37885108 | DOI:10.2174/0127722708268538231010041307

STAR Protoc. 2023 Oct 25;4(4):102666. doi: 10.1016/j.xpro.2023.102666. Online ahead of print.

ABSTRACT

Biomedical knowledge graphs (BKGs) provide a new paradigm for managing abundant biomedical knowledge efficiently. Today's artificial intelligence techniques enable mining BKGs to discover new knowledge. Here, we present a protocol for implementing a computational pipeline for biomedical knowledge discovery (BKD) based on a BKG. We describe steps of the pipeline including data processing, implementing BKD based on knowledge graph embeddings, and prediction result interpretation. We detail how our pipeline can be used for drug repurposing hypothesis generation for Parkinson's disease. For complete details on the use and execution of this protocol, please refer to Su et al.1.

PMID:37883224 | DOI:10.1016/j.xpro.2023.102666

Cancer Sci. 2023 Oct 26. doi: 10.1111/cas.15994. Online ahead of print.

ABSTRACT

Genetic mutations in the isocitrate dehydrogenase (IDH) gene that result in a pathological enzymatic activity to produce oncometabolite have been detected in acute myeloid leukemia (AML) patients. While specific inhibitors that target mutant IDH enzymes and normalize intracellular oncometabolite level have been developed, refractoriness and resistance has been reported. Since acquisition of pathological enzymatic activity is accompanied by the abrogation of the crucial WT IDH enzymatic activity in IDH mutant cells, aberrant metabolism in IDH mutant cells can potentially persist even after the normalization of intracellular oncometabolite level. Comparisons of isogenic AML cell lines with and without IDH2 gene mutations revealed two mutually exclusive signalings for growth advantage of IDH2 mutant cells, STAT phosphorylation associated with intracellular oncometabolite level and phospholipid metabolic adaptation. The latter came to light after the oncometabolite normalization and increased the resistance of IDH2 mutant cells to arachidonic acid-mediated apoptosis. The release of this metabolic adaptation by FDA-approved anti-inflammatory drugs targeting the metabolism of arachidonic acid could sensitize IDH2 mutant cells to apoptosis, resulting in their eradication in vitro and in vivo. Our findings will contribute to the development of alternative therapeutic options for IDH2 mutant AML patients who do not tolerate currently available therapies.

PMID:37882467 | DOI:10.1111/cas.15994

J Biomol Struct Dyn. 2023 Oct 26:1-10. doi: 10.1080/07391102.2023.2256864. Online ahead of print.

ABSTRACT

A number of multidisciplinary methods have piqued the interest of researchers as means to accelerate and lower the cost of medication creation. The goal of this research was to find target proteins and then select a lead drug against SARS-CoV-2. The three-dimensional structure is taken from the RCSB PDB using its specific PDB ID 6lu7. Virtual screening based on pharmacophores is performed using Molecular Operating Environment software. We looked for a potent inhibitor in the FDA-approved database. For docking, AutoDock Vina uses Pyrx. The compound-target protein binding interactions were tested using BIOVIA Discovery Studio. The stability of protein and inhibitor complexes in a physiological setting was investigated using Desmond's Molecular Dynamics Simulation (MD simulation). According to our findings, we repurpose the FDA-approved drugs ZINC000169677008 and ZINC000169289767, which inhibit the activity of the virus's main protease (6lu7). The scientific community will gain from this finding, which might create new medicine. The novel repurposed chemicals were promising inhibitors with increased efficacy and fewer side effects.Communicated by Ramaswamy H. Sarma.

PMID:37882340 | DOI:10.1080/07391102.2023.2256864

Arch Pharm (Weinheim). 2023 Oct 25:e2300340. doi: 10.1002/ardp.202300340. Online ahead of print.

ABSTRACT

Drug repurposing is an emerging field in drug development that has provided many successful drugs. In the current study, paracetamol, a known antipyretic and analgesic agent, was chemically modified to generate paracetamol derivatives as anticancer and anticyclooxygenase-2 (COX-2) agents. Compound 11 bearing a fluoro group was the best cytotoxic candidate with half-maximal inhibitory concentration (IC50 ) values ranging from 1.51 to 6.31 μM and anti-COX-2 activity with IC50 = 0.29 μM, compared to the standard drugs, doxorubicin and celecoxib. The cell cycle and apoptosis studies revealed that compound 11 possesses the ability to induce cell cycle arrest in the S phase and apoptosis in colon Huh-7 cells. These results were strongly supported by docking studies, which showed strong interactions with the amino acids of the COX-2 protein, and in silico pharmacokinetic predictions were found to be favorable for these newly synthesized paracetamol derivatives. It can be concluded that compound 11 could block cell growth and proliferation by inhibiting the COX-2 enzyme in cancer therapy.

PMID:37880869 | DOI:10.1002/ardp.202300340