medRxiv [Preprint]. 2024 Aug 21:2024.08.20.24312181. doi: 10.1101/2024.08.20.24312181.

ABSTRACT

BACKGROUND: Patients with post-traumatic stress disorder (PTSD) experience higher risk of adverse cardiovascular (CV) outcomes. This study explores shared loci, and genes between PTSD and CV conditions from three major domains: CV diagnoses from electronic health records (CV-EHR), cardiac and aortic imaging, and CV health behaviors defined in Life's Essential 8 (LE8).

METHODS: We used genome-wide association study (GWAS) of PTSD (N=1,222,882), 246 CV diagnoses based on EHR data from Million Veteran Program (MVP; N=458,061), UK Biobank (UKBB; N=420,531), 82 cardiac and aortic imaging traits (N=26,893), and GWAS of traits defined in the LE8 (N = 282,271 ∼ 1,320,016). Shared loci between PTSD and CV conditions were identified using local genetic correlations (rg), and colocalization (shared causal variants). Overlapping genes between PTSD and CV conditions were identified from genetically regulated proteome expression in brain and blood tissues, and subsequently tested to identify functional pathways and gene-drug targets. Epidemiological replication of EHR-CV diagnoses was performed in AllofUS cohort (AoU; N=249,906).

RESULTS: Among the 76 PTSD-susceptibility risk loci, 33 loci exhibited local rg with 45 CV-EHR traits (|rg|≥0.4), four loci with eight heart imaging traits(|rg|≥0.5), and 44 loci with LE8 factors (|rg|≥0.36) in MVP. Among significantly correlated loci, we found shared causal variants (colocalization probability > 80%) between PTSD and 17 CV-EHR (in MVP) at 11 loci in MVP, that also replicated in UKBB and/or other cohorts. Of the 17 traits, the observational analysis in the AoU showed PTSD was associated with 13 CV-EHR traits after accounting for socioeconomic factors and depression diagnosis. PTSD colocalized with eight heart imaging traits on 2 loci and with LE8 factors on 31 loci. Leveraging blood and brain proteome expression, we found 33 and 122 genes, respectively, shared between PTSD and CVD. Blood proteome genes were related to neuronal and immune processes, while the brain proteome genes converged on metabolic and calcium-modulating pathways (FDR p <0.05). Drug repurposing analysis highlighted DRD2, NOS1, GFAP, and POR as common targets of psychiatric and CV drugs.

CONCLUSION: PTSD-CV comorbidities exhibit shared risk loci, and genes involved in tissue-specific regulatory mechanisms.

PMID:39228734 | PMC:PMC11370495 | DOI:10.1101/2024.08.20.24312181

Parasit Vectors. 2024 Sep 3;17(1):373. doi: 10.1186/s13071-024-06456-6.

ABSTRACT

BACKGROUND: Cystic echinococcosis (CE) is a zoonotic disease caused by the larval stage of the dog tapeworm Echinococcus granulosus sensu lato (E. granulosus), with a worldwide distribution. The current treatment strategy for CE is insufficient. Limited drug screening models severely hamper the discovery of effective anti-echinococcosis drugs.

METHODS: In the present study, using high-content screening technology, we developed a novel high-throughput screening (HTS) assay by counting the ratio of propidium iodide-stained dead protoscoleces (PSCs) to the total number of PSCs. In vitro and ex vivo cyst viability assays were utilized to determine the effect of drugs on cyst viability.

RESULTS: Using the newly established HTS assay, we screened approximately 12,000 clinical-stage or The Food and Drug Administration (FDA)-approved small molecules from the Repurposing, Focused Rescue, and Accelerated Medchem (ReFRAME) library, as well as the LOPAC1280 and SelleckChem libraries, as a strategic approach to facilitate the drug discovery process. Initial screening yielded 173 compounds with anti-echinococcal properties, 52 of which demonstrated dose-response efficacy against E. granulosus PSCs in vitro. Notably, two agents, omaveloxolone and niclosamide, showed complete inhibition upon further validation in cyst and microcyst viability assays in vitro after incubation for 3 days, and in an ex vivo cyst viability assay using cysts isolated from the livers of mice infected with E. granulosus, as determined by morphological assessment.

CONCLUSIONS: Through the development of a novel HTS assay and by repurposing libraries, we identified omaveloxolone and niclosamide as potent inhibitors against E. granulosus. These compounds show promise as potential anti-echinococcal drugs, and our strategic approach has the potential to promote drug discovery for parasitic infections.

PMID:39227942 | DOI:10.1186/s13071-024-06456-6

J Transl Med. 2024 Sep 3;22(1):818. doi: 10.1186/s12967-024-05561-5.

ABSTRACT

BACKGROUND: Dengue virus (DENV) is the most widespread arbovirus. The World Health Organization (WHO) declared dengue one of the top 10 global health threats in 2019. However, it has been underrepresented in bibliometric analyses. This study employs bibliometric analysis to identify research hotspots and trends, offering a comprehensive overview of the current research dynamics in this field.

RESULTS: We present a report spanning from 1995 to 2023 that provides a unique longitudinal analysis of Dengue virus (DENV) research, revealing significant trends and shifts not extensively covered in previous literature. A total of 10,767 DENV-related documents were considered, with a notable increase in publications, peaking at 747 articles in 2021. Plos Neglected Tropical Diseases has become the leading journal in Dengue virus research, publishing 791 articles in this field-the highest number recorded. Our bibliometric analysis provides a comprehensive mapping of DENV research across multiple dimensions, including vector ecology, virology, and emerging therapies. The study delineates a complex network of immune response genes, including IFNA1, DDX58, IFNB1, STAT1, IRF3, and NFKB1, highlighting significant trends and emerging themes, particularly the impacts of climate change and new outbreaks on disease transmission. Our findings detail the progress and current status of key vaccine candidates, including the licensed Dengvaxia, newer vaccines such as Qdenga and TV003, and updated clinical trials. The study underscores significant advancements in antiviral therapies and vector control strategies for dengue, highlighting innovative drug candidates such as AT-752 and JNJ-1802, and the potential of drug repurposing with agents like Ribavirin, Remdesivir, and Lopinavir. Additionally, it discusses biological control methods, including the introduction of Wolbachia-infected mosquitoes and gene-editing technologies.

CONCLUSION: This bibliometric study underscores the critical role of interdisciplinary collaboration in advancing DENV research, identifying key trends and areas needing further exploration, including host-virus dynamics, the development and application of antiviral drugs and vaccines, and the use of artificial intelligence. It advocates for strengthened partnerships across various disciplines to effectively tackle the challenges posed by DENV.

PMID:39227968 | DOI:10.1186/s12967-024-05561-5

Biomed Pharmacother. 2024 Sep 2;179:117325. doi: 10.1016/j.biopha.2024.117325. Online ahead of print.

ABSTRACT

Direct-acting antivirals ledipasvir (LDV) and daclatasvir (DCV) are widely used as part of combination therapies to treat Hepatitis C infections. Here we show that these compounds inhibit the proliferation, invasion, and colony formation of triple-negative MDA-MB-231 breast cancer cells, SRC-transduced SW620 colon cancer cells and SRC- transduced NIH3T3 fibroblasts. DCV also inhibits the expression of PDL-1, which is responsible for resistance to immunotherapy in breast cancer cells. The demonstrated low toxicity in many Hepatitis C patients suggests LDV and DCV could be used in combination therapies for cancer patients. At the molecular level, these direct-acting antivirals inhibit the phosphorylation of Akt and the ephrin type A receptor 2 (EPHA2) by destabilizing a Src-EPHA2 complex, although they do not affect the general kinase activity of Src. Thus, LDV and DCV could be effective drugs for Src-associated cancers without the inherent toxicity of classical Src inhibitors.

PMID:39226729 | DOI:10.1016/j.biopha.2024.117325

EBioMedicine. 2024 Sep 2;107:105277. doi: 10.1016/j.ebiom.2024.105277. Online ahead of print.

ABSTRACT

BACKGROUND: Global cyclical outbreaks of human enterovirus infections has positioned human enterovirus A71 (EV-A71) as a neurotropic virus of clinical importance. However, there remains a scarcity of internationally approved antivirals and vaccines.

METHODS: In pursuit of repurposing drugs for combating human enteroviruses, we employed a comprehensive pharmacophore- and molecular docking-based virtual screen targeting EV-A71 capsid protein VP1-4, 3C protease, and 3D polymerase proteins. Among 15 shortlisted ligand candidates, we dissected the inhibitory mechanism of Tanomastat in cell-based studies and evaluated its in vivo efficacy in an EV-A71-infected murine model.

FINDINGS: We demonstrated that Tanomastat exerts dose-dependent inhibition on EV-A71 replication, with comparable efficacy profiles in enterovirus species A, B, C, and D in vitro. Time-course studies suggested that Tanomastat predominantly disrupts early process(es) of the EV-A71 replication cycle. Mechanistically, live virus particle tracking and docking predictions revealed that Tanomastat specifically impedes viral capsid dissociation, potentially via VP1 hydrophobic pocket binding. Bypassing its inhibition on entry stages, we utilized EV-A71 replication-competent, 3Dpol replication-defective, and bicistronic IRES reporter replicons to show that Tanomastat also inhibits viral RNA replication, but not viral IRES translation. We further showed that orally administered Tanomastat achieved 85% protective therapeutic effect and alleviated clinical symptoms in EV-A71-infected neonatal mice.

INTERPRETATION: Our study establishes Tanomastat as a broad-spectrum anti-enterovirus candidate with promising pre-clinical efficacy, warranting further testing for potential therapeutic application.

FUNDING: MOE Tier 2 grants (MOE-T2EP30221-0005, R571-000-068-592, R571-000-076-515, R571-000-074-733) and A∗STARBiomedical Research Council (BMRC).

PMID:39226680 | DOI:10.1016/j.ebiom.2024.105277

Reprod Fertil. 2024 Sep 1:RAF-24-0022. doi: 10.1530/RAF-24-0022. Online ahead of print.

ABSTRACT

Infertility is estimated to affect more than 50 million couples around the world, with male factor accounting for half of these cases, yet there is a notable absence of effective treatment options for men, other than in-vitro fertilisation (IVF) or intracytoplasmic sperm injection (ICSI). This review considers unlicensed and empirical treatments used for male subfertility, including hormonal therapy, phosphodiesterase inhibitors, and antioxidants. Compounds generally demonstrate variable improvements in sperm function but benefits for fertility are less clear. There is a pressing need for effective treatment options for subfertile men, however, our knowledge of sperm function is limited, restricting the identification of precise treatment targets. The traditional drug discovery pathway is also notorious for its extensive resource and time requirements, often extending over decades and demanding significant financial investment. Unfortunately, a substantial number of potential therapies fail before reaching the marketplace. Furthermore, reliance on mammalian models is not possible in the drug development process for male subfertility, due to significant variability between animals and man. We review recent breakthroughs and highlight novel methods aimed at improving the effectiveness and efficiency of drug discovery for male subfertility. High-throughput screening, combinatorial chemistry, and the repurposing of established medications have great potential. These strategies offer the promise of accelerating the pace of drug development, curbing the extensive demand for resources, and, in the case of drug repurposing, diminish the demand for comprehensive pharmacokinetic and pharmacodynamic studies. As these innovative approaches are adopted, the feasibility of addressing male subfertility through scientific advancements appears to be increasingly attainable.

PMID:39226216 | DOI:10.1530/RAF-24-0022

J Gynecol Oncol. 2024 Aug 27. doi: 10.3802/jgo.2025.36.e28. Online ahead of print.

ABSTRACT

OBJECTIVE: Chemoresistant-epithelial ovarian cancer (EOC) has a poor prognosis, prompting the search for new therapeutic drugs. The diphenylbutylpiperidine (DPBP) class of antipsychotic drugs used in schizophrenia has shown anticancer effects. This study aimed to investigate the preclinical efficacy of penfluridol, fluspirilene, and pimozide (DPBP) using in vitro and in vivo models of EOC.

METHODS: Human EOC cell lines A2780, HeyA8, SKOV3ip1, A2780-CP20, HeyA8-MDR, and SKOV3-TR were treated with penfluridol, fluspirilene, and pimozide, and cell proliferation, apoptosis, and migration were assessed. The preclinical efficacy of DPBP was also investigated using in vivo mouse models, including cell lines and patient-derived xenografts (PDX) of EOC.

RESULTS: DPBP drugs significantly decreased cell proliferation in chemosensitive (A2780, HeyA8, and SKOV3ip1) and chemoresistant (A2780-CP20, HeyA8-MDR, and SKOV3-TR) cell lines. Among these drugs, penfluridol exerted a relatively stronger cytotoxic effect on all cell lines. Penfluridol significantly increased apoptosis and inhibited migration of EOC cells. In the cell line xenograft mouse model with HeyA8, the penfluridol group showed significantly decreased tumor weight compared with the control group. In the paclitaxel-resistant model with HeyA8-MDR, the penfluridol group had significantly decreased tumor weight compared with the paclitaxel or control groups. Penfluridol exerted anticancer effects on the PDX model.

CONCLUSION: Penfluridol exerted significant anticancer effects on EOC cells and xenograft models, including PDX. Thus, penfluridol therapy, as a drug repurposing strategy, might be a potential therapeutic for EOCs.

PMID:39223944 | DOI:10.3802/jgo.2025.36.e28

Enzymes. 2024;55:383-411. doi: 10.1016/bs.enz.2024.05.006. Epub 2024 Jul 3.

ABSTRACT

Acetazolamide, methazolamide, ethoxzolamide and dorzolamide, classical sulfonamide carbonic anhydrase (CA) inhibitors (CAIs) designed for targeting human enzymes, were also shown to effectively inhibit bacterial CAs and were proposed for repurposing as antibacterial agents against several infective agents. CAs belonging to the α-, β- and/or γ-classes from pathogens such as Helicobacter pylori, Neisseria gonorrhoeae, vacomycin resistant enterococci (VRE), Vibrio cholerae, Mycobacterium tuberculosis, Pseudomonas aeruginosa and other bacteria were considered as drug targets for which several classes of potent inhibitors have been developed. Treatment of some of these pathogens with various classes of such CAIs led to an impairment of the bacterial growth, reduced virulence and for drug resistant bacteria, a resensitization to clinically used antibiotics. Here I will discuss the strategies and challenges for obtaining CAIs with enhanced selectivity for inhibiting bacterial versus human enzymes, which may constitute an important weapon for addressing the drug resistance to β-lactams and other clinically used antibiotics.

PMID:39222998 | DOI:10.1016/bs.enz.2024.05.006

Basic Clin Pharmacol Toxicol. 2024 Sep 1. doi: 10.1111/bcpt.14074. Online ahead of print.

ABSTRACT

Over the past decade, increasing off-label use of quetiapine has been reported worldwide from various sources. We wanted to investigate how this is reflected in therapeutic drug monitoring (TDM) data. Requisitions for serum concentration measurements of quetiapine from a TDM service in Central Norway during 2001-2019 were obtained and analysed for age, gender, trends in quetiapine doses, serum concentrations and indicators of diagnoses. There were 19 759 requisitions from 7459 individuals. Daily doses of quetiapine decreased by 24 mg per year (95% CI: -25.61 to -21.48, p < 0.001, N = 4505). A corresponding decrease in quetiapine serum concentrations was not seen. The proportion of requisitions with diagnoses indicating reimbursable use was 13% for the whole study period. Mean daily doses were slightly higher in the reimbursable group, but declined over time in these samples, as well. To our understanding, these results signal a trend towards lower prescribed doses of quetiapine, possibly reflecting drug repurposing and/or off-label use. The discrepancy in the decrease of doses versus serum concentrations may reflect the intake of higher doses than prescribed and/or inappropriate TDM sampling. Our findings show that TDM data have limitations when it comes to making inferences about the use of quetiapine based on serum concentrations and clinical information on the requisitions.

PMID:39219150 | DOI:10.1111/bcpt.14074

Yakugaku Zasshi. 2024;144(9):857-863. doi: 10.1248/yakushi.24-00120.

ABSTRACT

Less than 10% of the candidate drug compounds are associated with male reproductive toxicity. Genetic and/or epigenetic information on sperm may be crucial for fetal development. Therefore, developmental toxicity, such as paternally transmitted birth defects, is possible if genetic abnormalities in the male germ line persist and accumulate in the sperm during spermatogenesis. First, this study provides an overview of chemical and male reproductive toxicity, which may lead to developmental toxicity from the perspective of male reproduction. Second, we demonstrate methods for evaluating male reproductive toxicity to anticipate male-mediated developmental toxicity. We developed a novel staining technique for evaluating sperm quality, as well as a noninvasive imaging analysis of male reproductive toxicity. The former is a mammalian male germ cell-specific staining method using reactive blue 2 dye (RB2), as previously confirmed in human sperm, and a method for detecting the early-stage DNA fragmentation in a single nucleus from mouse spermatozoa using single-cell pulsed-field gel electrophoresis. The latter is a new, ready-to-use, and compact magnetic resonance imaging (MRI) platform utilizing a high-field permanent magnet to evaluate male reproductive toxicity. The histopathological analysis supported the suitability of the MRI platform. The present study, for the first time, revealed a rapid, noninvasive evaluation of male reproductive toxicity in vivo using compact MRI. These novel toxicity assessments can help predict male-mediated developmental toxicity, contributing to accelerated drug discovery and drug repositioning.

PMID:39218652 | DOI:10.1248/yakushi.24-00120

Methods. 2024 Aug 30:S1046-2023(24)00189-0. doi: 10.1016/j.ymeth.2024.08.008. Online ahead of print.

ABSTRACT

Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further optimization. To address this, we propose a multi-perspective feature fusion model, MFF-DTA, which integrates chemical structure, biological sequence, and other data to comprehensively capture drug-target affinity features. The MFF-DTA model incorporates multiple feature learning components, each of which is capable of extracting drug molecular features and protein target information, respectively. These components are able to obtain key information from both global and local perspectives. Then, these features from different perspectives are efficiently combined using specific splicing strategies to create a comprehensive representation. Finally, the model uses the fused features to predict drug-target affinity. Comparative experiments show that MFF-DTA performs optimally on the Davis and KIBA data sets. Ablation experiments demonstrate that removing specific components results in the loss of unique information, thus confirming the effectiveness of the MFF-DTA design. Improvements in DTA prediction methods will decrease costs and time in drug development, enhancing industry efficiency and ultimately benefiting patients.

PMID:39218169 | DOI:10.1016/j.ymeth.2024.08.008

J Ethnopharmacol. 2024 Aug 30:118764. doi: 10.1016/j.jep.2024.118764. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Herbal formulae have been used in China for thousands of years but have unclear clinical positioning and unknown characteristic indications make it difficult to determine their specific application in various diseases, which seriously hamper their clinical value. Identifying the precise clinical positioning and clinical advantages of similar formulae for related diseases is a critical issue.

AIM OF THIS STUDY: To develop a methodology based on modular pharmacology to determine the clinical advantages and precise clinical position of similar formulae.

MATERIALS AND METHODS: In this study, we proposed a modular-based network proximity approach to explore drug repositioning and clinical advantages of three formulae, Shirebi tablets (SRB), Yuxuebi capsules (YXB), and Wangbifukang granules (WBFK), for rheumatic disease. First, we constructed a rheumatology target network, and modules were obtained using the cluster tool molecular complex detection (MCODE). Based on the modular interaction map established by a quantitative approach for inter-module coordination and its transition (IMCC), using a targeting rate (TR) matrix to identify targeted modules of three formulae. Moreover, the network proximity Z-score and Jaccard similarity coefficient were used to identify potential optimal symptomatic indications and related diseases using three formulae. At the same time, the driver genes for SRB and gouty arthritis were identified by flow centrality and shortest distance, and the epresentative driver genes were validated by in vivo experiments.

RESULTS: 32 modules were obtained using the MCODE method. 4, 4, and 14 characteristic targeted modules of SRB, YXB, and WBFK, respectively, were identified using a targeting rate (TR) matrix. Module 2, 16, and 19 were targeted by both SRB and WBFK. The common effects of SRB and WBFK focused on inflammatory response and innate immune response, YXB was found to be involved in the collagen catabolic process, transmembrane receptor protein serine/threonine kinase signaling pathway. Moreover, potential optimal symptomatic indications and representative related diseases were identified for three formulae: SRB was significantly associated with GA (Z=-20.26) ; YXB was significantly associated with AS (Z=-4.532) , MI (Z=-29.11) , RhFv (Z=-6.945) , OA (Z=-39.97) , and GA (Z=-13.03) ; and WBFK was significantly associated with MI (Z=-205.5), SLE (Z=-37.65), RhFv (Z=-42.45), and GA (Z=-17.24). Finally, 8 driver genes for SRB and gouty arthritis were identified,the representative driver genes TRAF6 and NFE2L1 were validated by in vivo experiments.

CONCLUSIONS: The modular-based network proximity approach proposed in this study may provide a new perspective for the precise drug repositioning and clinical advantages of similar formulae in disease treatment.

PMID:39218127 | DOI:10.1016/j.jep.2024.118764

Sci Rep. 2024 Aug 31;14(1):20298. doi: 10.1038/s41598-024-71240-6.

ABSTRACT

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

PMID:39217242 | DOI:10.1038/s41598-024-71240-6

Nat Cardiovasc Res. 2024 Aug 26. doi: 10.1038/s44161-024-00524-x. Online ahead of print.

ABSTRACT

Myocardial injury may ultimately lead to adverse ventricular remodeling and development of heart failure (HF), which is a major cause of morbidity and mortality worldwide. Given the slow pace and substantial costs of developing new therapeutics, drug repurposing is an attractive alternative. Studies of many organs, including the heart, highlight the importance of the immune system in modulating injury and repair outcomes. Glatiramer acetate (GA) is an immunomodulatory drug prescribed for patients with multiple sclerosis. Here, we report that short-term GA treatment improves cardiac function and reduces scar area in a mouse model of acute myocardial infarction and a rat model of ischemic HF. We provide mechanistic evidence indicating that, in addition to its immunomodulatory functions, GA exerts beneficial pleiotropic effects, including cardiomyocyte protection and enhanced angiogenesis. Overall, these findings highlight the potential repurposing of GA as a future therapy for a myriad of heart diseases.

PMID:39215106 | DOI:10.1038/s44161-024-00524-x

Cancer Genet. 2024 Aug 26;288-289:20-31. doi: 10.1016/j.cancergen.2024.08.082. Online ahead of print.

ABSTRACT

Glioblastoma (GBM) is one of the most aggressive and fatal cancers, for which Temozolomide (TMZ) chemo drug is commonly used for its treatment. However, patients gradually develop resistance to this drug, leading to tumor relapse. In our previous study, we have identified lncRNAs that regulate chemoresistance through the competing endogenous RNA (ceRNA) mechanism. In this study, we tried to find FDA-approved drugs against the target proteins of these ceRNA networks through drug repurposing using differential gene expression profiles, which could be used to nullify the effect of lncRNAs and promote the sensitivity of TMZ in GBM. We performed molecular docking and simulation studies of predicted repurposed drugs and their targets. Among the predicted repurposed drugs, we found BMS345541 has a higher binding affinity towards its target protein - FOXG1, making it a more stable complex with FOXG1-DNA. The ADMET analysis of this drug BMS345541 shows a higher half-life and lower cytotoxicity level than other predicted repurposed drugs. Hence, we conjecture that this could be a better drug for increasing the sensitivity of TMZ for treating GBM patients.

PMID:39213700 | DOI:10.1016/j.cancergen.2024.08.082

Sci Adv. 2024 Aug 30;10(35):eadj3010. doi: 10.1126/sciadv.adj3010. Epub 2024 Aug 30.

ABSTRACT

We present an in silico approach for drug discovery, dubbed connectivity enhanced structure activity relationship (ceSAR). Building on the landmark LINCS library of transcriptional signatures of drug-like molecules and gene knockdowns, ceSAR combines cheminformatic techniques with signature concordance analysis to connect small molecules and their targets and further assess their biophysical compatibility using molecular docking. Candidate compounds are first ranked in a target structure-independent manner, using chemical similarity to LINCS analogs that exhibit transcriptomic concordance with a target gene knockdown. Top candidates are subsequently rescored using docking simulations and machine learning-based consensus of the two approaches. Using extensive benchmarking, we show that ceSAR greatly reduces false-positive rates, while cutting run times by multiple orders of magnitude and further democratizing drug discovery pipelines. We further demonstrate the utility of ceSAR by identifying and experimentally validating inhibitors of BCL2A1, an important antiapoptotic target in melanoma and preterm birth-associated inflammation.

PMID:39213358 | DOI:10.1126/sciadv.adj3010

Bioinformatics. 2024 Aug 30:btae536. doi: 10.1093/bioinformatics/btae536. Online ahead of print.

ABSTRACT

SUMMARY: The burgeoning high-throughput technologies have led to a significant surge in the scale of pharmacotranscriptomic datasets, especially for oncology. Signature search methods (SSMs), utilizing oncogenic signatures formed by differentially expressed genes through sequencing, have been instrumental in anti-cancer drug screening and identifying mechanisms of action without relying on prior knowledge. However, various studies have found that different SSMs exhibit varying performance across pharmacotranscriptomic datasets. In addition, the size of the oncogenic signature can also significantly impact the result of drug repurposing. Therefore, finding the optimal SSMs and customized oncogenic signature for a specific disease remains a challenge. To address this, we introduce Signature Search Polestar (SSP), a webserver integrating the largest pharmacotranscriptomic datasets of anti-cancer drugs from LINCS L1000 with five state-of-the-art SSMs (XSum, CMap, GSEA, ZhangScore, XCos). SSP provides three main modules: Benchmark, Robustness, and Application. Benchmark uses two indices, Area Under the Curve and Enrichment Score, based on drug annotations to evaluate SSMs at different oncogenic signature sizes. Robustness, applicable when drug annotations are insufficient, uses a performance score based on drug self-retrieval for evaluation. Application provides three screening strategies, single method, SS_all, and SS_cross, allowing users to freely utilize optimal SSMs with tailored oncogenic signature for drug repurposing.

AVAILABILITY AND IMPLEMENTATION: SSP is free at https://web.biotcm.net/SSP/. The current version of SSP is archived in https://doi.org/10.6084/m9.figshare.26524741.v1, allowing users to directly use or customize their own SSP webserver.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:39213324 | DOI:10.1093/bioinformatics/btae536

Niger J Clin Pract. 2024 Aug 1;27(8):950-957. doi: 10.4103/njcp.njcp_873_23. Epub 2024 Aug 26.

ABSTRACT

BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 is an unparalleled health risk, needing fast antiviral medication development. One of the most effective strategies for developing therapies against novel and emerging viruses is drug repurposing. Recently, systems biology approaches toward the discovery of repurposing medications are gaining prominence.

AIM: This study aimed to implement a systems biology approach to identify crucial drug targets as well as potential drug candidates against COVID infection.

METHODS: Our approach utilizes differential gene expression in COVID conditions that enable the construction of a protein-protein interaction (PPI) network. Core clusters were extracted from this network, followed by molecular enrichment analysis. This process identified critical drug targets and potential drug candidates targeting various stages of COVID-19 infection.

RESULTS: The network was built using the top 200 differently expressed genes in mild, moderate, and severe COVID-19 infections. Top 3 clusters for each disease condition were identified, representing the core mechanism of the network. Molecular enrichment revealed the majority of the pathways in the mild state were associated with transcription regulation, protein folding, angiogenesis, and cytokine-signaling pathways. Whereas, the enriched pathways in moderate and severe disease states were predominately linked with the immune system and apoptotic processes, which include NF-kappaB signaling, cytokine signaling, TNF-mediated signaling, and oxidative stress-induced cell death. Further analysis identifies 28 potential drugs that can be repurposed to treat moderate and severe COVID-19, most of which are currently used in cancer treatment.

CONCLUSION: Interestingly, some of the proposed drugs have demonstrated inhibitory effects against SARS-CoV-2, as supported by literature evidence. Overall, the drug repurposing method described here will help develop potential antiviral medications to treat emerging COVID strains.

PMID:39212430 | DOI:10.4103/njcp.njcp_873_23

SAR QSAR Environ Res. 2024 Aug 30:1-22. doi: 10.1080/1062936X.2024.2392677. Online ahead of print.

ABSTRACT

Dengue fever, prevalent in Southeast Asian countries, currently lacks effective pharmaceutical interventions for virus replication control. This study employs a strategy that combines machine learning (ML)-based quantitative-structure-activity relationship (QSAR), molecular docking, and molecular dynamics simulations to discover potential inhibitors of the NS3 protease of the dengue virus. We used nine molecular fingerprints from PaDEL to extract features from the NS3 protease dataset of dengue virus type 2 in the ChEMBL database. Feature selection was achieved through the low variance threshold, F-Score, and recursive feature elimination (RFE) methods. Our investigation employed three ML models - support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) - for classifier development. Our SVM model, combined with SVM-RFE, had the best accuracy (0.866) and ROC_AUC (0.964) in the testing set. We identified potent inhibitors on the basis of the optimal classifier probabilities and docking binding affinities. SHAP and LIME analyses highlighted the significant molecular fingerprints (e.g. ExtFP69, ExtFP362, ExtFP576) involved in NS3 protease inhibitory activity. Molecular dynamics simulations indicated that amphotericin B exhibited the highest binding energy of -212 kJ/mol and formed a hydrogen bond with the critical residue Ser196. This approach enhances NS3 protease inhibitor identification and expedites the discovery of dengue therapeutics.

PMID:39210743 | DOI:10.1080/1062936X.2024.2392677

Viruses. 2024 Jul 24;16(8):1186. doi: 10.3390/v16081186.

ABSTRACT

Advancing climate change increases the risk of future infectious disease outbreaks, particularly of zoonotic diseases, by affecting the abundance and spread of viral vectors. Concerningly, there are currently no approved drugs for some relevant diseases, such as the arboviral diseases chikungunya, dengue or zika. The development of novel inhibitors takes 10-15 years to reach the market and faces critical challenges in preclinical and clinical trials, with approximately 30% of trials failing due to side effects. As an early response to emerging infectious diseases, CavitOmiX allows for a rapid computational screening of databases containing 3D point-clouds representing binding sites of approved drugs to identify candidates for off-label use. This process, known as drug repurposing, reduces the time and cost of regulatory approval. Here, we present potential approved drug candidates for off-label use, targeting the ADP-ribose binding site of Alphavirus chikungunya non-structural protein 3. Additionally, we demonstrate a novel in silico drug design approach, considering potential side effects at the earliest stages of drug development. We use a genetic algorithm to iteratively refine potential inhibitors for (i) reduced off-target activity and (ii) improved binding to different viral variants or across related viral species, to provide broad-spectrum and safe antivirals for the future.

PMID:39205160 | DOI:10.3390/v16081186