Drug Discov Today. 2023 Oct 5:103796. doi: 10.1016/j.drudis.2023.103796. Online ahead of print.

ABSTRACT

Kinases have a crucial role in regulating almost the full range of cellular processes, making them essential targets for therapeutic interventions against various diseases. Accurate kinase-profiling prediction is vital for addressing the selectivity/specificity challenges in kinase drug discovery, which is closely related to lead optimization, drug repurposing, and the understanding of potential drug side effects. In this review, we provide an overview of the latest advancements in machine learning (ML)-based and deep learning (DL)-based quantitative structure-activity relationship (QSAR) models for kinase profiling. We highlight current trends in this rapidly evolving field and discuss the existing challenges and future directions regarding experimental data set construction and model architecture design. Our aim is to offer practical insights and guidance for the development and utilization of these approaches.

PMID:37805065 | DOI:10.1016/j.drudis.2023.103796

Antiviral Res. 2023 Oct 5:105730. doi: 10.1016/j.antiviral.2023.105730. Online ahead of print.

ABSTRACT

The development of antivirals with an extended spectrum of activity is an attractive possibility to protect against future emerging coronaviruses (CoVs). Cyclosporine A (CsA), a clinically approved immunosuppressive drug, has established antiviral activity against diverse unrelated viruses, including several CoVs. However, its antiviral mechanisms of action against CoV infection have remained elusive, precluding the rational design of non-immunosuppressive derivatives with improved antiviral activities. In this study, we evaluated the mechanisms of CsA against HCoV-229 E infection in a human lung epithelial cell line. We demonstrate that the antiviral activity of CsA against HCoV-229 E is independent of classical CsA target proteins, cyclophilin A or B, which are not required host factors for HCoV-229 E in A549 cells. Instead, CsA treatment induces expression of antiviral genes in a manner dependent on interferon regulatory factor 1, but independent of classical interferon responses, which contributes to its inhibitory effect against HCoV-229 E infection. Our results also point to a role for the HCoV-229 E nucleoprotein in antagonizing activation of type I interferon, but we show that CsA treatment does not affect evasion of innate immune signalling pathways by HCoV-229 E. Overall, our findings further the understanding of the antiviral mechanisms of CsA against CoV infection and highlight a novel immunomodulatory strategy to inhibit CoV infection that may inform future drug development efforts.

PMID:37805057 | DOI:10.1016/j.antiviral.2023.105730

Bioorg Med Chem Lett. 2023 Oct 5:129498. doi: 10.1016/j.bmcl.2023.129498. Online ahead of print.

ABSTRACT

Neurodegenerative disease is a debilitating and incurable condition that affects millions of people around the world. The loss of functions or malfunctions of neural cells are the causes of mortality. A proteosome inhibitor, MG132, is well known to cause neurodegeneration in vitro when model neuronal-derived cell lines are exposed to it. Niclosamide, an anthelmintic drug, which has been used to treat tapeworm infections for more than 50 years, has recently attracted renewed attention in drug repurposing because it has been found to be a good candidate in many drug development screenings. We recently found that all markers of MG132-induced neuronal cell toxicity, including the accumulation of ubiquitinated proteins, were prevented by the presence of niclosamide. In addition, niclosamide was shown to enhance autophagy induced by MG132. There results suggested that niclosamide could act as a neuroprotective agent. In the present study, niclosamide derivatives were synthesized, and the structure-activity relationship (SAR) were determined with respect to protein ubiquitination induced by MG132 and effect on cell survival signaling pathways for neuroprotective function. Our results indicate that phenol OH plays a significant role in neuroprotective activity while the niclosamide derivatives without Cl (5- or 2'-Cl) showed almost the same neuroprotective effect. 4'-NO2 can be replaced by N3 or CF3 whereas NH2 significantly decreased activity. These findings provide guidance for the development of new niclosamide analogues against neurodegenerative diseases including Parkinson's disease.

PMID:37804994 | DOI:10.1016/j.bmcl.2023.129498

Methods. 2023 Oct 5:S1046-2023(23)00165-2. doi: 10.1016/j.ymeth.2023.10.002. Online ahead of print.

ABSTRACT

MOTIVATION: The outbreak of the human coronavirus (SARS-CoV-2) has placed a huge burden on public health and the world economy. Compared with de novo drug discovery, drug repurposing is a promising therapeutic strategy that facilitates rapid clinical treatment decisions, shortens the development process, and reduces costs.

RESULTS: In this study, we propose a weighted hypergraph learning and adaptive inductive matrix completion method, WHAIMC, for predicting potential virus-drug associations. Firstly, we integrate multi-source data to describe viruses and drugs from multiple perspectives, including drug chemical structures, drug targets, virus complete genome sequences, and virus-drug associations. Then, WHAIMC establishes an adaptive inductive matrix completion model to improve performance through adaptive learning of similarity relations. Finally, WHAIMC introduces weighted hypergraph learning into adaptive inductive matrix completion to capture higher-order relationships of viruses (or drugs). The results showed that WHAIMC had a strong predictive performance for new virus-drug associations, new viruses, and new drugs. The case study further demonstrates that WHAIMC is highly effective for repositioning antiviral drugs against SARS-CoV-2 and provides a new perspective for virus-drug association prediction. The code and data in this study is freely available at https://github.com/Mayingjun20179/WHAIMC.

PMID:37804962 | DOI:10.1016/j.ymeth.2023.10.002

Virol J. 2023 Oct 6;20(1):226. doi: 10.1186/s12985-023-02195-9.

ABSTRACT

PURPOSE: Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19.

METHODS: Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020.

RESULTS: Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality.

CONCLUSIONS: In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively.

PMID:37803348 | DOI:10.1186/s12985-023-02195-9

Pharm Pat Anal. 2023 Oct 6. doi: 10.4155/ppa-2023-0015. Online ahead of print.

ABSTRACT

Repurposing of approved drugs in a new strategy to combat cancer that leads to savings in time and investment. Atovaquone is a US FDA approved drug for treatment of Pneumocystis carinii pneumonia and malaria. Patent US2023017373 describe the use of mito-atovaquone for the treatment of several types of cancer. Mito-Atovaquone demonstrated antiproliferative activity in cell lines of pancreatic cancer, lung cancer and brain cancer and inhibited tumor growth in syngeneic mouse models and in animals genetically prone to breast cancer. Mito-Atovaquone has the potential to be used successfully in the treatment of various types of tumors.

PMID:37801038 | DOI:10.4155/ppa-2023-0015

J Biomol Struct Dyn. 2023 Oct 5:1-11. doi: 10.1080/07391102.2023.2263895. Online ahead of print.

ABSTRACT

Inhibition of a disintegrin and metalloproteinase-17 (ADAM17), a metzincin, is proposed as a novel therapeutic strategy to suppress overproduction of the proinflammatory cytokine TNF-α in rheumatoid arthritis and inflammatory bowel disease. Existing ADAM17 inhibitors generate toxic metabolites in-vivo or haven't progressed in clinical trials. Previous studies suggest that ligands which bind to ADAM17 active site by interacting with the Zn ion and L-shaped hydrophobic S1'- and S3'-pockets and forming favorable hydrogen bonds could act as potential ADAM17 inhibitors. Here, we investigated whether the FDA-approved anti-bacterial drug ceftolozane, a cephalosporin containing aromatic groups and carboxyl groups as probable zinc binding groups (ZBGs), forms non-covalent interactions resulting in its binding in the active site of ADAM17. In this study, the density functional theory (DFT), molecular docking and molecular dynamics calculations with the catalytic chain of ADAM17 show that carboxyl group of ceftolozane acts as moderate ZBG, and its extended geometry forms hydrogen bonds and hydrophobic interactions resulting in a binding affinity comparable to the co-crystallized known ADAM17 inhibitor. The favorable binding interactions identified here suggest the potential of ceftolozane to modulate ADAM17 activity in inflammatory diseases. ADAM17 cleaves and releases epidermal growth factor (EGF) ligands from the cell surface. The shed EGF ligands then bind to the EGF receptors to drive embryonic development. Therefore, our findings also suggest that use of ceftolozane during pregnancy may inhibit ADAM17-mediated shedding of EGF and thus increase the risk of birth defects in humans.Communicated by Ramaswamy H. Sarma.

PMID:37798935 | DOI:10.1080/07391102.2023.2263895

J Appl Microbiol. 2023 Oct 5:lxad222. doi: 10.1093/jambio/lxad222. Online ahead of print.

ABSTRACT

AIMS: Multidrug resistance is a worrying problem worldwide. The lack of readily available drugs to counter nosocomial infections requires the need for new interventional strategies. Drug repurposing represents a valid alternative to using commercial molecules as antimicrobial agents in a short time and with low costs. Contextually, the present study focused on the antibacterial potential of the ammonium salt N-nitroso-N-phenylhydroxylamine (Cupferron), evaluating the ability to inhibit microbial growth and influence the main virulence factors.

METHODS AND RESULTS: Cupferron cytotoxicity was checked via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) and hemolysis assays. The antimicrobial activity was assessed through the Kirby-Bauer disk diffusion test, broth microdilution method and time-killing kinetics. Furthermore, the impact on different stages of the biofilm life cycle, catalase, swimming and swarming motility was estimated via MTT and crystal violet (CV) assay, H2O2 sensitivity and motility tests, respectively. Cupferron exhibited less than 15% cytotoxicity at 200 μg/mL concentration. The 90% bacterial growth inhibitory concentrations (MIC90) values recorded after 24 hours of exposure were 200 and 100 μg/mL for multidrug-resistant (MDR) and sensitive strains, respectively, exerting a bacteriostatic action. Cupferron-treated bacteria showed increased susceptibility to biofilm production, oxidative stress and impaired bacterial motility in a dose-dependent manner.

CONCLUSIONS: In the new antimicrobial compounds active research scenario, the results indicated that Cupferron could be an interesting candidate for tackling E. coli infections.

PMID:37796875 | DOI:10.1093/jambio/lxad222

Front Genet. 2023 Sep 18;14:1271311. doi: 10.3389/fgene.2023.1271311. eCollection 2023.

ABSTRACT

Background: Drug repositioning is considered a promising drug development strategy with the goal of discovering new uses for existing drugs. Compared with the experimental screening for drug discovery, computational drug repositioning offers lower cost and higher efficiency and, hence, has become a hot issue in bioinformatics. However, there are sparse samples, multi-source information, and even some noises, which makes it difficult to accurately identify potential drug-associated indications. Methods: In this article, we propose a new scheme with improved tensor robust principal component analysis (ITRPCA) in multi-source data to predict promising drug-disease associations. First, we use a weighted k-nearest neighbor (WKNN) approach to increase the overall density of the drug-disease association matrix that will assist in prediction. Second, a drug tensor with five frontal slices and a disease tensor with two frontal slices are constructed using multi-similarity matrices and an updated association matrix. The two target tensors naturally integrate multiple sources of data from the drug-side aspect and the disease-side aspect, respectively. Third, ITRPCA is employed to isolate the low-rank tensor and noise information in the tensor. In this step, an additional range constraint is incorporated to ensure that all the predicted entry values of a low-rank tensor are within the specific interval. Finally, we focus on identifying promising drug indications by analyzing drug-disease association pairs derived from the low-rank drug and low-rank disease tensors. Results: We evaluate the effectiveness of the ITRPCA method by comparing it with five prominent existing drug repositioning methods. This evaluation is carried out using 10-fold cross-validation and independent testing experiments. Our numerical results show that ITRPCA not only yields higher prediction accuracy but also exhibits remarkable computational efficiency. Furthermore, case studies demonstrate the practical effectiveness of our method.

PMID:37795241 | PMC:PMC10545866 | DOI:10.3389/fgene.2023.1271311

Rep Pract Oncol Radiother. 2023 Aug 28;28(4):551-564. doi: 10.5603/RPOR.a2023.0059. eCollection 2023.

ABSTRACT

BACKGROUND: Ovarian cancer is a huge therapeutic and financial problem for which approved treatments have already achieved their limit of efficiency. A cost-effective strategy to extend therapeutic options in this malignancy is drug repurposing aimed at overcoming chemoresistance. Here, angiotensin-converting enzyme inhibitors (ACE-I) are worth considering.

MATERIALS AND METHODS: We searched literature for publications supporting the idea of adjuvant application of ACE-Is in ovarian malignancy. Then, we searched The Cancer Genome Atlas databases for relevant alternations of gene expression patterns. We also performed in silico structure-activity relationship evaluation for predicting ACE-Is' cytotoxicity against ovarian cancer cell lines. Finally, we reviewed the potential obstacles in ACE-Is repurposing process.

RESULTS: The alternation of angiotensin receptor expression in ovarian cancer translates into poorer patient survival. This confirms the participation of the renin-angiotensin system in ovarian carcinogenesis. In observational studies, ACE-Is were shown synergize with both, platinum-based chemotherapy as well as with antiangiogenic therapy. Consistently, our in silico simulation showed that ACE-Is are probably cytotoxic against ovarian cancer cells. However, the publications on their chemopreventive properties were inconclusive. In addition, some reports correlated ACE-Is use with increased general cancer incidence. We hypothesized that this effect could be associated with mutagenic nitrosamine formation in ACE-Is' pharmaceutical formulations, as was the case with angiotensin receptor blockers (ARBs) and other well-established pharmaceuticals.

CONCLUSIONS: Available data warrant further research into repositioning ACE-Is to ovarian cancer as chemosensitizers. Prior to this, however, a special research program is needed to detect possible genotoxic contaminants of ACE-Is.

PMID:37795232 | PMC:PMC10547424 | DOI:10.5603/RPOR.a2023.0059

Trials. 2023 Oct 4;24(1):635. doi: 10.1186/s13063-023-07577-6.

ABSTRACT

BACKGROUND: Repeated COVID-19 waves and corresponding mitigation measures have impacted health systems globally with exceptional challenges. In response to the pandemic, researchers, regulators, and funders rapidly pivoted to COVID-19 research activities. However, many clinical drug studies were not completed, due to often complex and rapidly evolving research conditions.

METHODS: We outline our experience of planning and managing a randomised, adaptive, open-label, phase 2 clinical trial to evaluate the safety and efficacy of four repurposed drug regimens versus standard-of-care (SOC) in outpatients with 'mild to moderate' COVID-19 in Johannesburg, South Africa, in the context of a partnership with multiple stakeholders. The study was conducted between 3 September 2020 and 23 August 2021 during changing COVID-19 restrictions, significant morbidity and mortality waves, and allied supply line, economic, and political instability.

RESULTS: Our clinical study design was pragmatic, including low-risk patients who were treated open label. There was built-in flexibility, including provision for some sample size adjustment and a range of secondary efficacy outcomes. Barriers to recruitment included the timing of waves, staff shortages due to illness, late presentation of patients, COVID-19 misinformation, and political unrest. Mitigations were the use of community health workers, deployment of mobile clinical units, and simplification of screening. Trial management required a radical reorganisation of logistics and processes to accommodate COVID-19 restrictions. These included the delivery of staff training and monitoring remotely, electronic consent, patient training and support to collect samples and report data at home, and the introduction of tele-medicine. These measures were successful for data collection, safe, and well received by patients.

CONCLUSION: Completing a COVID-19 trial in outpatients during the height of the pandemic required multiple innovations in nearly every aspect of clinical trial management, a high commitment level from study staff and patients, and support from study sponsors. Our experience has generated a more robust clinical research infrastructure, building in efficiencies to clinical trial management beyond the pandemic.

PMID:37794489 | DOI:10.1186/s13063-023-07577-6

Nat Commun. 2023 Oct 4;14(1):6172. doi: 10.1038/s41467-023-41180-2.

ABSTRACT

Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

PMID:37794016 | DOI:10.1038/s41467-023-41180-2

Biochim Biophys Acta Gene Regul Mech. 2023 Oct 2:194991. doi: 10.1016/j.bbagrm.2023.194991. Online ahead of print.

ABSTRACT

DDX5 (p68) upregulation has been linked with various cancers of different origins, especially Colon Adenocarcinomas. Similarly, across cancers, MGMT has been identified as the major contributor of chemoresistance against DNA alkylating agents like Temozolomide (TMZ). TMZ is an emerging potent chemotherapeutic agent across cancers under the arena of drug repurposing. Recent studies have established that patients with open MGMT promoters are prone to be innately resistant or acquire resistance against TMZ compared to its closed conformation. However, not much is known about the transcriptional regulation of MGMT gene in the context of colon cancer. This necessitates studying MGMT gene regulation which directly impacts the cellular potential to develop chemoresistance against alkylating agents. Our study aims to uncover an unidentified mechanism of DDX5-mediated MGMT gene regulation. Experimentally, we found that both mRNA and protein expression levels of MGMT were elevated in response to p68 overexpression in multiple human colon cancer cell lines and vice-versa. Since p68 cannot directly interact with the MGMT promoter, transcription factors viz., β-catenin, RelA (p65) and SP1 were also studied as reported contributors. Through co-immunoprecipitation and GST-pull-down studies, p68 was established as an interacting partner of SP1 in addition to β-catenin and NF-κB (p50-p65). Mechanistically, luciferase reporter and chromatin-immunoprecipitation assays demonstrated that p68 interacts with the MGMT promoter via TCF4-LEF, RelA and SP1 sites to enhance its transcription. To the best of our knowledge, this is the first report of p68 as a transcriptional co-activator of MGMT promoter and our study identifies p68 as a novel and master regulator of MGMT gene expression.

PMID:37793472 | DOI:10.1016/j.bbagrm.2023.194991

Comput Biol Med. 2023 Sep 28;166:107496. doi: 10.1016/j.compbiomed.2023.107496. Online ahead of print.

ABSTRACT

The progressive emergence of antimicrobial resistance has become a global health problem in need of rapid solution. Research into new antimicrobial drugs is imperative. Drug repositioning, together with computational mathematical prediction models, could be a fast and efficient method of searching for new antibiotics. The aim of this study was to identify compounds with potential antimicrobial capacity against Escherichia coli from US Food and Drug Administration-approved drugs, and the similarity between known drug targets and E. coli proteins using a topological structure-activity data analysis model. This model has been shown to identify molecules with known antibiotic capacity, such as carbapenems and cephalosporins, as well as new molecules that could act as antimicrobials. Topological similarities were also found between E. coli proteins and proteins from different bacterial species such as Mycobacterium tuberculosis, Pseudomonas aeruginosa and Salmonella Typhimurium, which could imply that the selected molecules have a broader spectrum than expected. These molecules include antitumor drugs, antihistamines, lipid-lowering agents, hypoglycemic agents, antidepressants, nucleotides, and nucleosides, among others. The results presented in this study prove the ability of computational mathematical prediction models to predict molecules with potential antimicrobial capacity and/or possible new pharmacological targets of interest in the design of new antibiotics and in the better understanding of antimicrobial resistance.

PMID:37793206 | DOI:10.1016/j.compbiomed.2023.107496

Front Genet. 2023 Sep 18;14:1170571. doi: 10.3389/fgene.2023.1170571. eCollection 2023.

ABSTRACT

Pancreatic Ductal Adenocarcinoma (PDAC) is a very lethal disease that typically presents at an advanced stage and is non-compliant with most treatments. Recent technologies have helped delineate associated molecular subtypes and genetic variations yielding important insights into the pathophysiology of this disease and having implications for the identification of new therapeutic targets. Drug repurposing has been evaluated as a new paradigm in oncology to accelerate the application of approved or failed target-specific molecules for the treatment of cancer patients. This review focuses on the impact of molecular subtypes on key genomic alterations in PDAC, and the progress made thus far. Importantly, these alterations are discussed in light of the potential role of drug repurposing in PDAC.

PMID:37790705 | PMC:PMC10544984 | DOI:10.3389/fgene.2023.1170571

PeerJ. 2023 Sep 29;11:e16088. doi: 10.7717/peerj.16088. eCollection 2023.

ABSTRACT

BACKGROUND: Recent efforts to repurpose existing drugs to different indications have been accompanied by a number of computational methods, which incorporate protein-protein interaction networks and signaling pathways, to aid with prioritizing existing targets and/or drugs. However, many of these existing methods are focused on integrating additional data that are only available for a small subset of diseases or conditions.

METHODS: We have designed and implemented a new R-based open-source target prioritization and repurposing method that integrates both canonical intracellular signaling information from five public pathway databases and target information from public sources including OpenTargets.org. The Pathway2Targets algorithm takes a list of significant pathways as input, then retrieves and integrates public data for all targets within those pathways for a given condition. It also incorporates a weighting scheme that is customizable by the user to support a variety of use cases including target prioritization, drug repurposing, and identifying novel targets that are biologically relevant for a different indication.

RESULTS: As a proof of concept, we applied this algorithm to a public colorectal cancer RNA-sequencing dataset with 144 case and control samples. Our analysis identified 430 targets and ~700 unique drugs based on differential gene expression and signaling pathway enrichment. We found that our highest-ranked predicted targets were significantly enriched in targets with FDA-approved therapeutics for colorectal cancer (p-value < 0.025) that included EGFR, VEGFA, and PTGS2. Interestingly, there was no statistically significant enrichment of targets for other cancers in this same list suggesting high specificity of the results. We also adjusted the weighting scheme to prioritize more novel targets for CRC. This second analysis revealed epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase (PI3K), and two mitogen-activated protein kinases (MAPK14 and MAPK3). These observations suggest that our open-source method with a customizable weighting scheme can accurately prioritize targets that are specific and relevant to the disease or condition of interest, as well as targets that are at earlier stages of development. We anticipate that this method will complement other approaches to repurpose drugs for a variety of indications, which can contribute to the improvement of the quality of life and overall health of such patients.

PMID:37790614 | PMC:PMC10544355 | DOI:10.7717/peerj.16088

Res Sq. 2023 Sep 12:rs.3.rs-3335643. doi: 10.21203/rs.3.rs-3335643/v1. Preprint.

ABSTRACT

Background Recently, single-nucleus RNA-seq (snRNA-seq) analyses have revealed important cellular and functional features of Alzheimer's disease (AD), a prevalent neurodegenerative disease. However, our knowledge regarding intercellular communication mediated by dysregulated ligand-receptor (LR) interactions remains very limited in AD brains. Methods We systematically assessed the intercellular communication networks by using a discovery snRNA-seq dataset comprising 69,499 nuclei from 48 human postmortem prefrontal cortex (PFC) samples. We replicated the findings using an independent snRNA-seq dataset of 56,440 nuclei from 18 PFC samples. By integrating genetic signals from AD genome-wide association studies (GWAS) summary statistics and whole genome sequencing (WGS) data, we prioritized AD-associated Gene Ontology (GO) terms containing dysregulated LR interactions. We further explored drug repurposing for the prioritized LR pairs using the Therapeutic Targets Database. Results We identified 316 dysregulated LR interactions across six major cell types in AD PFC, of which 210 pairs were replicated. Among the replicated LR signals, we found globally downregulated communications in astrocytes-to-neurons signaling axis, characterized, for instance, by the downregulation of APOE-related and Calmodulin (CALM)-related LR interactions and their potential regulatory connections to target genes. Pathway analyses revealed 60 GO terms significantly linked to AD, highlighting Biological Processes such as 'amyloid precursor protein processing' and 'ion transmembrane transport', among others. We prioritized several drug repurposing candidates, such as cromoglicate, targeting the identified dysregulated LR pairs. Conclusions Our integrative analysis identified key dysregulated LR interactions in a cell type-specific manner and the associated GO terms in AD, offering novel insights into potential therapeutic targets involved in disrupted cell-cell communication in AD.

PMID:37790454 | PMC:PMC10543294 | DOI:10.21203/rs.3.rs-3335643/v1

bioRxiv. 2023 Sep 24:2023.09.22.559001. doi: 10.1101/2023.09.22.559001. Preprint.

ABSTRACT

Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively. Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data. We observe that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue, as well as in tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also uncovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS . Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database. These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management.

PMID:37790409 | PMC:PMC10543009 | DOI:10.1101/2023.09.22.559001

BMC Bioinformatics. 2023 Oct 3;24(1):374. doi: 10.1186/s12859-023-05479-7.

ABSTRACT

BACKGROUND: Drug repurposing is an approach that holds promise for identifying new therapeutic uses for existing drugs. Recently, knowledge graphs have emerged as significant tools for addressing the challenges of drug repurposing. However, there are still major issues with constructing and embedding knowledge graphs.

RESULTS: This study proposes a two-step method called DrugRep-HeSiaGraph to address these challenges. The method integrates the drug-disease knowledge graph with the application of a heterogeneous siamese neural network. In the first step, a drug-disease knowledge graph named DDKG-V1 is constructed by defining new relationship types, and then numerical vector representations for the nodes are created using the distributional learning method. In the second step, a heterogeneous siamese neural network called HeSiaNet is applied to enrich the embedding of drugs and diseases by bringing them closer in a new unified latent space. Then, it predicts potential drug candidates for diseases. DrugRep-HeSiaGraph achieves impressive performance metrics, including an AUC-ROC of 91.16%, an AUC-PR of 90.32%, an accuracy of 84.63%, a BS of 0.119, and an MCC of 69.31%.

CONCLUSION: We demonstrate the effectiveness of the proposed method in identifying potential drugs for COVID-19 as a case study. In addition, this study shows the role of dipeptidyl peptidase 4 (DPP-4) as a potential receptor for SARS-CoV-2 and the effectiveness of DPP-4 inhibitors in facing COVID-19. This highlights the practical application of the model in addressing real-world challenges in the field of drug repurposing. The code and data for DrugRep-HeSiaGraph are publicly available at https://github.com/CBRC-lab/DrugRep-HeSiaGraph .

PMID:37789314 | DOI:10.1186/s12859-023-05479-7

Curr Health Sci J. 2023 Apr-Jun;49(2):210-219. doi: 10.12865/CHSJ.49.02.210. Epub 2023 Jun 30.

ABSTRACT

Stroke is a major cause of death and disability worldwide. Between 1990 and 2010, its global burden increased notably with reference to the absolute number of incident events, number of deaths, and disability-adjusted life-years lost. Trazodone is a triazolopyridine derivative that was approved for more than 40 years as monotherapy or in combination with other antidepressant drugs for the treatment of major depressive disorder in adult patients. The aim was investigated if trazodone can improve behavioural outcome after stroke in a mice model of middle cerebral artery occlusion (MCAo) due to the potential neuroprotective and neurodegenerative effects by using three behavioural tests: adhesive tape test, beam test and hole board test. Trazodone administration show modest improvements regarding the motor-sensorial function after stroke especially in the acute post-stroke phase in aged and young animals. The antidepressant effect of the drug was observed in the post-stroke period in aged animals and to a lesser extent in young animals. Future research is needed to evaluate the effects of trazodone at the cellular level to be sure that it has no benefit in stroke patients who do not suffer from depression.

PMID:37786617 | PMC:PMC10541511 | DOI:10.12865/CHSJ.49.02.210