Res Sq [Preprint]. 2024 Apr 19:rs.3.rs-4250176. doi: 10.21203/rs.3.rs-4250176/v1.

ABSTRACT

Background Drugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease. Methods In previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations. Results Our analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated. Conclusions Our findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.

PMID:38699347 | PMC:PMC11065072 | DOI:10.21203/rs.3.rs-4250176/v1

Curr Pharm Des. 2024 May 2. doi: 10.2174/0113816128287431240408045732. Online ahead of print.

ABSTRACT

OBJECTIVE: The peculiar aim of this study is to discover and identify the most effective and potential inhibitors against the most influential target ERα receptor by in silico studies of 45 phytochemicals from six diverse ayurvedic medicinal plants.

METHODS: The molecular docking investigation was carried out by the genetic algorithm program of AutoDock Vina. The molecular dynamic (MD) simulation investigations were conducted using the Desmond tool of Schrödinger molecular modelling. This study identified the top ten highest binding energy phytochemicals that were taken for drug-likeness test and ADMET profile prediction with the help of the web-based server QikpropADME.

RESULTS: Molecular docking study revealed that ellagic acid (-9.3 kcal/mol), emodin (-9.1 kcal/mol), rhein (-9.1 kcal/mol), andquercetin (-9.0 kcal/mol) phytochemicals showed similar binding affinity as standard tamoxifen towards the target protein ERα. MD studies showed that all four compounds possess comparatively stable ligand-protein complexes with ERα target compared to the tamoxifen-ERα complex. Among the four compounds, phytochemical rhein formed a more stable complex than standard tamoxifen. ADMET studies for the top ten highest binding energy phytochemicals showed a better safety profile.

CONCLUSION: Additionally, these compounds are being reported for the first time in this study as possible inhibitors of ERα for treating breast cancer, according to the notion of drug repurposing. Hence, these phytochemicals can be further studied and used as a parent core molecule to develop innovative lead molecules for breast cancer therapy.

PMID:38698754 | DOI:10.2174/0113816128287431240408045732

J Intern Med. 2024 May 2. doi: 10.1111/joim.13785. Online ahead of print.

ABSTRACT

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

PMID:38698538 | DOI:10.1111/joim.13785

Int J Pharm. 2024 Apr 30:124187. doi: 10.1016/j.ijpharm.2024.124187. Online ahead of print.

ABSTRACT

Drug repositioning is a high-priority and feasible strategy in the field of oncology research, where the unmet medical needs are continuously unbalanced. Disulfiram is a potential non-chemotherapeutic, adjuvant anticancer agent. However, the clinical translation is limited by the drug's poor bioavailability. Therefore, the molecular encapsulation of disulfiram with cyclodextrins is evaluated to enhance the solubility and stability of the drug. The present work describes for the first time the complexation of disulfiram with randomly methylated-β-cyclodextrin. A parallel analytical andin vitrobiological comparison of disulfiram inclusion complexes with hydroxypropyl-β-cyclodextrin, randomly methylated-β-cyclodextrin and sulfobutylether-β-cyclodextrin is conducted. A significant drug solubility enhancement by about 1000-folds and fast dissolution in 1 min is demonstrated. Thein vitrodissolution-permeation studies and proliferation assays demonstrate the solubility-dependent efficacy of the drug. Throughout the different cancer cell lines' characteristics and disulfiram unspecific antitumoral activity, the inhibitory efficacy of the cyclodextrin encapsulated drug on melanoma (IC50 about 100 nM) and on glioblastoma (IC50 about 7000 nM) cell lines differ by a magnitude. This pre-formulation screening experiment serves as a proof of concept of using cyclodextrin encapsulation as a platform tool for further drug delivery development in repositioning areas.

PMID:38697585 | DOI:10.1016/j.ijpharm.2024.124187

Sci Rep. 2024 May 2;14(1):10072. doi: 10.1038/s41598-024-60756-6.

ABSTRACT

Drug repositioning aims to identify new therapeutic indications for approved medications. Recently, the importance of computational drug repositioning has been highlighted because it can reduce the costs, development time, and risks compared to traditional drug discovery. Most approaches in this area use networks for systematic analysis. Inferring drug-disease associations is then defined as a link prediction problem in a heterogeneous network composed of drugs and diseases. In this article, we present a novel method of computational drug repositioning, named drug repositioning with attention walking (DRAW). DRAW proceeds as follows: first, a subgraph enclosing the target link for prediction is extracted. Second, a graph convolutional network captures the structural features of the labeled nodes in the subgraph. Third, the transition probabilities are computed using attention mechanisms and converted into random walk profiles. Finally, a multi-layer perceptron takes random walk profiles and predicts whether a target link exists. As an experiment, we constructed two heterogeneous networks with drug-drug similarities based on chemical structures and anatomical therapeutic chemical classification (ATC) codes. Using 10-fold cross-validation, DRAW achieved an area under the receiver operating characteristic (ROC) curve of 0.903 and outperformed state-of-the-art methods. Moreover, we demonstrated the results of case studies for selected drugs and diseases to further confirm the capability of DRAW to predict drug-disease associations.

PMID:38698208 | DOI:10.1038/s41598-024-60756-6

Heliyon. 2024 Apr 19;10(9):e29967. doi: 10.1016/j.heliyon.2024.e29967. eCollection 2024 May 15.

ABSTRACT

The COVID-19 pandemic has become a significant global issue in terms of public health. While it is largely associated with respiratory complications, recent reports indicate that patients also experience neurological symptoms and other health issues. The objective of this study is to examine the network of protein-protein interactions (PPI) between SARS-CoV-2 proteins and human host proteins, pinpoint the central genes within this network implicated in disease pathology, and assess their viability as targets for drug development. The study adopts a network-based approach to construct a network of 29 SARS-CoV-2 proteins interacting with 2896 host proteins, with 176 host genes being identified as interacting genes with all the viral proteins. Gene ontology and pathway analysis of these host proteins revealed their role in biological processes such as translation, mRNA splicing, and ribosomal pathways. We further identified EEF2, RPS3, RPL9, RPS16, and RPL11 as the top 5 most connected hub genes in the disease-causing network, with significant interactions among each other. These hub genes were found to be involved in ribosomal pathways and cytoplasmic translation. Further a disease-gene interaction was also prepared to investigate the role of hub genes in other disorders and to understand the condition of comorbidity in COVID-19 patients. We also identified 13 drug molecules having interactions with all the hub genes, and estradiol emerged as the top potential drug target for the COVID-19 patients. Our study provides valuable insights using the protein-protein interaction network of SARS-CoV-2 proteins with host proteins and highlights the molecular basis of manifestation of COVID-19 and proposes drug for repurposing. As the pandemic continues to evolve, it is anticipated that investigating SARS-CoV-2 proteins will remain a critical area of focus for researchers globally, particularly in addressing potential challenges posed by specific SARS-CoV-2 variants in the future.

PMID:38694063 | PMC:PMC11059120 | DOI:10.1016/j.heliyon.2024.e29967

Drug Discov Today. 2024 Apr 29:104008. doi: 10.1016/j.drudis.2024.104008. Online ahead of print.

ABSTRACT

Drug repurposing faces various challenges that can impede its success. We developed a framework outlining key challenges in drug repurposing to explore when and how health technology assessment (HTA) methods can address them. We identified 20 drug-repurposing challenges across the categories of data access, research and development, collaboration, business case, regulatory and legal challenges. Early incorporation of HTA methods, including literature review, empirical research, stakeholder consultation, health economic evaluation and uncertainty assessment, can help to address these challenges. HTA methods canassess the value proposition of repurposed drugs, inform further research and ultimately help to bring cost-effective repurposed drugs to patients.

PMID:38692506 | DOI:10.1016/j.drudis.2024.104008

J Biomed Semantics. 2024 May 1;15(1):5. doi: 10.1186/s13326-024-00308-z.

ABSTRACT

Leveraging AI for synthesizing the deluge of biomedical knowledge has great potential for pharmacological discovery with applications including developing new therapeutics for untreated diseases and repurposing drugs as emergent pandemic treatments. Creating knowledge graph representations of interacting drugs, diseases, genes, and proteins enables discovery via embedding-based ML approaches and link prediction. Previously, it has been shown that these predictive methods are susceptible to biases from network structure, namely that they are driven not by discovering nuanced biological understanding of mechanisms, but based on high-degree hub nodes. In this work, we study the confounding effect of network topology on biological relation semantics by creating an experimental pipeline of knowledge graph semantic and topological perturbations. We show that the drop in drug repurposing performance from ablating meaningful semantics increases by 21% and 38% when mitigating topological bias in two networks. We demonstrate that new methods for representing knowledge and inferring new knowledge must be developed for making use of biomedical semantics for pharmacological innovation, and we suggest fruitful avenues for their development.

PMID:38693563 | DOI:10.1186/s13326-024-00308-z

Front Oncol. 2024 Apr 16;14:1390105. doi: 10.3389/fonc.2024.1390105. eCollection 2024.

ABSTRACT

Multiple myeloma (MM) is an incurable malignant plasma cell disorder characterized by the infiltration of clonal plasma cells in the bone marrow compartment. Gene Expression Profiling (GEP) has emerged as a powerful investigation tool in modern myeloma research enabling the dissection of the molecular background of MM and allowing the identification of gene products that could potentially serve as targets for therapeutic intervention. In this study we investigated shared transcriptomic abnormalities across newly diagnosed multiple myeloma (NDMM) patient cohorts. In total, publicly available transcriptomic data of 7 studies from CD138+ cells from 281 NDMM patients and 44 healthy individuals were integrated and analyzed. Overall, we identified 28 genes that were consistently differentially expressed (DE) between NDMM patients and healthy donors (HD) across various studies. Of those, 9 genes were over/under-expressed in more than 75% of NDMM patients. In addition, we identified 4 genes (MT1F, PURPL, LINC01239 and LINC01480) that were not previously considered to participate in MM pathogenesis. Meanwhile, by mining three drug databases (ChEMBL, IUPHAR/BPS and DrugBank) we identified 31 FDA-approved and 144 experimental drugs that target 8 of these 28 over/under-expressed MM genes. Taken together, our study offers new insights in MM pathogenesis and importantly, it reveals potential new treatment options that need to be further investigated in future studies.

PMID:38690165 | PMC:PMC11058662 | DOI:10.3389/fonc.2024.1390105

Int ACM SIGIR Conf Res Dev Inf Retr. 2023 Jul;2023:2913-2923. doi: 10.1145/3539618.3591897. Epub 2023 Jul 18.

ABSTRACT

This work presents a new, original document classification dataset, BioSift, to expedite the initial selection and labeling of studies for drug repurposing. The dataset consists of 10,000 human-annotated abstracts from scientific articles in PubMed. Each abstract is labeled with up to eight attributes necessary to perform meta-analysis utilizing the popular patient-intervention-comparator-outcome (PICO) method: has human subjects, is clinical trial/cohort, has population size, has target disease, has study drug, has comparator group, has a quantitative outcome, and an "aggregate" label. Each abstract was annotated by 3 different annotators (i.e., biomedical students) and randomly sampled abstracts were reviewed by senior annotators to ensure quality. Data statistics such as reviewer agreement, label co-occurrence, and confidence are shown. Robust benchmark results illustrate neither PubMed advanced filters nor state-of-the-art document classification schemes (e.g., active learning, weak supervision, full supervision) can efficiently replace human annotation. In short, BioSift is a pivotal but challenging document classification task to expedite drug repurposing. The full annotated dataset is publicly available and enables research development of algorithms for document classification that enhance drug repurposing.

PMID:38690157 | PMC:PMC11060830 | DOI:10.1145/3539618.3591897

Heliyon. 2024 Mar 22;10(7):e27982. doi: 10.1016/j.heliyon.2024.e27982. eCollection 2024 Apr 15.

ABSTRACT

OBJECTIVES: The rise of antibiotic-resistant Streptococcus pneumoniae (Sp) poses a significant global health threat, urging the quest for novel antimicrobial solutions. We have discovered that the human hormone l-thyroxine has antibacterial properties. In order to explore its drugability we perform here the characterization of a series of l-thyroxine analogues and describe the structural determinants influencing their antibacterial efficacy.

METHOD: We performed a high-throughput screening of a library of compounds approved for use in humans, complemented with ITC assays on purified Sp-flavodoxin, to pinpoint molecules binding to this protein. Antimicrobial in vitro susceptibility assays of the hit compound (l-thyroxine) as well as of 13 l-thyroxine analogues were done against a panel of Gram-positive and Gram-negative bacteria. Toxicity of compounds on HepG2 cells was also assessed. A combined structure-activity and computational docking analysis was carried out to uncover functional groups crucial for the antimicrobial potency of these compounds.

RESULTS: Human l-thyroxine binds to Sp-flavodoxin, forming a 1:1 complex of low micromolar Kd. While l-thyroxine specifically inhibited Sp growth, some derivatives displayed activity against other Gram-positive bacteria like Staphylococcus aureus and Enterococcus faecalis, while remaining inactive against Gram-negative pathogens. Neither l-thyroxine nor some selected derivatives exhibited toxicity to HepG2 cells.

CONCLUSIONS: l-thyroxine derivatives targeting bacterial flavodoxins represent a new and promising class of antimicrobials.

PMID:38689973 | PMC:PMC11059415 | DOI:10.1016/j.heliyon.2024.e27982

Int J Pharm X. 2024 Apr 20;7:100249. doi: 10.1016/j.ijpx.2024.100249. eCollection 2024 Jun.

ABSTRACT

Breast cancer, the most common cancer among women, caused over 500,000 deaths in 2020. Conventional treatments are expensive and have severe side effects. Drug repurposing is a novel approach aiming to reposition clinically approved non-cancer drugs into newer cancer treatments. Atorvastatin calcium (ATR Ca) which is used for the treatment of hypercholesterolemia has potential to modulate cell growth and apoptosis. The study aimed at utilizing gelucire-based solid lipid nanoparticles (SLNs) and lactoferrin (Lf) as targeting ligand to enhance tumor targeting of atorvastatin calcium for effective management of breast cancer. Lf-decorated-ATR Ca-SLNs showed acceptable particle size and PDI values <200 nm and 0.35 respectively, entrapment efficiency >90% and sustained drug release profile with 78.97 ± 12.3% released after 24 h. In vitro cytotoxicity study on breast cancer cell lines (MCF-7) showed that Lf-decorated-ATR Ca-SLNs obviously improved anti-tumor activity by 2 to 2.5 folds compared to undecorated ATR Ca-SLNs and free drug. Further, In vivo study was also carried out using Ehrlich breast cancer model in mice. Caspase-3 apoptotic marker revealed superior antineoplastic and apoptosis-inducing activity in the groups treated with ATR Ca-SLNs either decorated/ undecorated with Lf in dosage 10 mg/kg/day p < 0.001 with superior activity for lactoferrin-decorated formulation.

PMID:38689601 | PMC:PMC11059436 | DOI:10.1016/j.ijpx.2024.100249

BMJ Open. 2024 Apr 30;14(4):e080500. doi: 10.1136/bmjopen-2023-080500.

ABSTRACT

BACKGROUND: Therapeutic latency, lack of efficacy and adverse drug reactions are the major concerns in current antidepressant therapies. To overcome these treatment hurdles, add-on therapy to conventional antidepressant medications may lead to better therapeutic outcomes. The present randomised controlled trial has been planned to evaluate the efficacy and safety of add-on dextromethorphan to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder (MDD).

METHODS AND ANALYSIS: A randomised, double-blind, add-on, placebo-controlled, group sequential design clinical trial will be conducted on patients with MDD who will be randomly assigned to the control and the test group in a 1:1 ratio. Patients in the test group will get dextromethorphan 30 mg once daily, whereas patients in the control group will receive a placebo once daily as an add-on to ongoing SSRI treatment for 8 weeks. All patients will be evaluated for the primary outcome (change in the Montgomery-Åsberg Depression Rating Scale score) and secondary outcomes (treatment response rate, remission rate, Clinical Global Impression, serum brain-derived neurotrophic factor, serum dextromethorphan and treatment-emergent adverse events) over the period of 8 weeks. Intention-to-treat analysis will be done for all parameters using suitable statistical tools.

ETHICS AND DISSEMINATION: This study was approved by the Institutional Ethics Committee of All India Institute of Medical Sciences, Bhubaneswar, India, and the study conformed to the provisions of the Declaration of Helsinki and ICMR's ethical guidelines for biomedical research on human subjects (2017). Written informed consent will be obtained from the participants before recruitment. The results of this study will be published in peer-reviewed publications.

TRIAL REGISTRATION NUMBER: NCT05181527.

PMID:38688675 | DOI:10.1136/bmjopen-2023-080500

BMC Med Inform Decis Mak. 2024 Apr 30;24(Suppl 2):114. doi: 10.1186/s12911-024-02496-1.

ABSTRACT

BACKGROUND: Traditional literature based discovery is based on connecting knowledge pairs extracted from separate publications via a common mid point to derive previously unseen knowledge pairs. To avoid the over generation often associated with this approach, we explore an alternative method based on word evolution. Word evolution examines the changing contexts of a word to identify changes in its meaning or associations. We investigate the possibility of using changing word contexts to detect drugs suitable for repurposing.

RESULTS: Word embeddings, which represent a word's context, are constructed from chronologically ordered publications in MEDLINE at bi-monthly intervals, yielding a time series of word embeddings for each word. Focusing on clinical drugs only, any drugs repurposed in the final time segment of the time series are annotated as positive examples. The decision regarding the drug's repurposing is based either on the Unified Medical Language System (UMLS), or semantic triples extracted using SemRep from MEDLINE.

CONCLUSIONS: The annotated data allows deep learning classification, with a 5-fold cross validation, to be performed and multiple architectures to be explored. Performance of 65% using UMLS labels, and 81% using SemRep labels is attained, indicating the technique's suitability for the detection of candidate drugs for repurposing. The investigation also shows that different architectures are linked to the quantities of training data available and therefore that different models should be trained for every annotation approach.

PMID:38689287 | DOI:10.1186/s12911-024-02496-1

Biomacromolecules. 2024 Apr 30. doi: 10.1021/acs.biomac.3c01420. Online ahead of print.

ABSTRACT

Drug repurposing uses approved drugs as candidate anticancer therapeutics, harnesses previous research and development efforts, and benefits from available clinically suitable formulations and evidence of patient tolerability. In this work, the drug used clinically to treat chronic alcoholism, disulfiram (DSF), was studied for its antitumor efficacy in a copper-dependent manner. The combination of DSF and copper could achieve a tumor cell growth inhibition effect comparable to those of 5-fluorouracil and taxol on head and neck cancer cells. Both bulk dendrimer hydrogel and microsized dendrimer hydrogel particles were utilized for the localized sustained release of copper in the tumor site. The localized sustained release of copper facilitated the tumor inhibition effect following intratumoral injection in a mouse's head and neck cancer model.

PMID:38687975 | DOI:10.1021/acs.biomac.3c01420

J Am Soc Nephrol. 2024 Apr 30. doi: 10.1681/ASN.0000000000000379. Online ahead of print.

ABSTRACT

BACKGROUND: The therapeutic options for IgA nephropathy are rapidly evolving, but early diagnosis and targeted treatment remain challenging. We aimed to identify circulating plasma proteins associated with IgA nephropathy by proteome-wide mendelian randomization studies across multiple ancestry populations.

METHODS: In this study, we applied Mendelian randomization and colocalization analyses to estimate the putative causal effects of 2615 proteins on IgA nephropathy in Europeans and 235 proteins in East Asians. Following two-stage network Mendelian randomization, multi-trait colocalization analysis and protein-altering variant annotation were performed to strengthen the reliability of the results. A protein-protein interaction network was constructed to investigate the interactions between the identified proteins and the targets of existing medications.

RESULTS: Putative causal effects of 184 and 13 protein-disease pairs in European and East Asian ancestries were identified, respectively. Two protein-disease pairs showed shared causal effects across them (CFHR1 and FCRL2). Supported by the evidence from colocalization analysis, potential therapeutic targets were prioritized and four drug-repurposing opportunities were suggested. The protein-protein interaction network further provided strong evidence for existing medications and pathways that are known to be therapeutically important.

CONCLUSIONS: Our study identified a number of circulating proteins associated with IgA nephropathy and prioritized several potential drug targets that require further investigation.

PMID:38687828 | DOI:10.1681/ASN.0000000000000379

Proc Natl Acad Sci U S A. 2024 May 7;121(19):e2315597121. doi: 10.1073/pnas.2315597121. Epub 2024 Apr 30.

ABSTRACT

Snakebite envenoming is a neglected tropical disease that causes substantial mortality and morbidity globally. The venom of African spitting cobras often causes permanent injury via tissue-destructive dermonecrosis at the bite site, which is ineffectively treated by current antivenoms. To address this therapeutic gap, we identified the etiological venom toxins in Naja nigricollis venom responsible for causing local dermonecrosis. While cytotoxic three-finger toxins were primarily responsible for causing spitting cobra cytotoxicity in cultured keratinocytes, their potentiation by phospholipases A2 toxins was essential to cause dermonecrosis in vivo. This evidence of probable toxin synergism suggests that a single toxin-family inhibiting drug could prevent local envenoming. We show that local injection with the repurposed phospholipase A2-inhibiting drug varespladib significantly prevents local tissue damage caused by several spitting cobra venoms in murine models of envenoming. Our findings therefore provide a therapeutic strategy that may effectively prevent life-changing morbidity caused by snakebite in rural Africa.

PMID:38687786 | DOI:10.1073/pnas.2315597121

J Biomol Struct Dyn. 2024 Apr 30:1-14. doi: 10.1080/07391102.2024.2335293. Online ahead of print.

ABSTRACT

Despite considerable improvement in therapy and diagnosis, brain tumors remain a global public health concern. Among all brain tumors, 80% are due to Glioblastoma. The average survival rate of a patient once diagnosed with glioblastoma is 15 months. Lately, the role of peptidase enzymes, especially Neprilysin, a neutral endopeptidase, is gaining attention for its role in tumor growth regulation. Neprilysin expressions are positively correlated with several tumors including GBM and reduced expression of NEP protein is associated with the pathogenesis of multiple tumors. One of the main reasons for NEP protein downregulation is the action of Histone deacetylase (HDAC) enzymes, especially HDAC1. Additionally, studies have reported that increased levels of HDAC1 are responsible for downregulating NEP gene expression. Hence, HDAC1 inhibition can be a good target to elevate NEP levels, which can be a good therapeutic approach to GBM. This study utilizes the computational drug repurposing tool, Schrodinger Maestro to identify HDAC1 inhibitors from the ZINC15 database.1379 FDA-approved drugs from the ZINC15 database were screened through molecular docking. Based on docking score and ligand-protein interaction, the top ten molecules were selected which were then subjected to binding energy calculation and molecular dynamics (MD) simulations. The three most active drugs from the MD simulations- ZINC22010649 (Panobinostat), ZINC4392649 (Tasimelteon) and ZINC1673 (Melphalan), were tested on C6 and U87 MG glioblastoma cells for cytotoxicity and HDAC1 protein levels using western blot analysis. Among the three drugs, Panobinostat exhibited potent cytotoxic action and showed a significant reduction in the HDAC1 protein levels.Communicated by Ramaswamy H. Sarma.

PMID:38686917 | DOI:10.1080/07391102.2024.2335293

Pestic Biochem Physiol. 2024 May;201:105889. doi: 10.1016/j.pestbp.2024.105889. Epub 2024 Mar 26.

ABSTRACT

Amprolium (AMP) is an organic compound used as a poultry anticoccidiostat. The aim of this work is to repurpose AMP to control the land snail, Eobania vermiculata in the laboratory and in the field. When snails treated with ½ LC₅₀ of AMP, the levels of alkaline phosphatase (ALP), total lipids (TL), urea, creatinine, malondialdehyde (MDA), catalase (CAT), and nitric oxide (NO) were significantly increased, whereas the levels of acetylcholinesterase (AChE), total protein (TP), and glutathione (GSH) decreased. It also induced histopathological and ultrastructural changes in the digestive gland, hermaphrodite gland, kidney, mucus gland, and cerebral ganglion. Furthermore, scanning electron micrographs revealed various damages in the tegumental structures of the mantle-foot region of E. vermiculata snails. The field application demonstrated that the AMP spray caused reduced percentages in snail population of 75 and 84% after 7 and 14 days of treatment. In conclusion, because AMP disrupts the biology and physiology of the land snail, E. vermiculata, it can be used as an effective molluscicide.

PMID:38685220 | DOI:10.1016/j.pestbp.2024.105889

Medicina (B Aires). 2024;84(2):313-323.

ABSTRACT

In recent years, drug repurposing (DR) has gained significant attention as a promising strategy for identifying new therapeutic uses of existing drugs. One potential candidate for DR in cancer treatment is sodium dichloroacetate (DCA), which has been shown to alter tumor metabolism and decrease apoptosis resistance in cancer cells. In this paper, we present a scoping review of the use of DCA for cancer treatment in adult patients, aiming to identify key research gaps in this area. This scoping review aims to explore the existing scientific literature to provide an overview of the use of DCA (any dose, frequency, or route of administration) in adults with cancer. A comprehensive literature search of the medical databases MEDLINE/PubMed, LILACS, EPISTEMONIKOS, the Cochrane Library, and ClinicalTrials was performed. We included publications reporting on adult patients diagnosed with any type of cancer treated with sodium dichloroacetate in combination or not with other drugs. All types of study design were included. A total of 12 articles were included, most of them were case reports. We found a high degree of heterogeneity between them. The most frequent adverse events in the evaluated studies were asthenia, reversible toxicity, and an increase in liver enzymes. Effectiveness was difficult to evaluate. We conclude that there is insufficient evidence to affirm that treatment with DCA in cancer patients is effective or is safe.

PMID:38683516