Mol Divers. 2024 Apr 29. doi: 10.1007/s11030-024-10851-7. Online ahead of print.

ABSTRACT

Efficient drug discovery relies on drug repurposing, an important and open research field. This work presents a novel factorization method and a practical comparison of different approaches for drug repurposing. First, we propose a novel tensor-matrix-tensor (TMT) formulation as a new data array method with a gradient-based factorization procedure. Additionally, this paper examines and contrasts four computational drug repurposing approaches-factorization-based methods, machine learning methods, deep learning methods, and graph neural networks-to fulfill the second purpose. We test the strategies on two datasets and assess each approach's performance, drawbacks, problems, and benefits based on results. The results demonstrate that deep learning techniques work better than other strategies and that their results might be more reliable. Ultimately, graph neural methods need to be in an inductive manner to have a reliable prediction.

PMID:38683487 | DOI:10.1007/s11030-024-10851-7

J Biomol Struct Dyn. 2024 Apr 29:1-16. doi: 10.1080/07391102.2024.2335304. Online ahead of print.

ABSTRACT

In lysozyme amyloidosis, fibrillar aggregates of lysozyme are associated with severe renal, hepatic, and gastrointestinal manifestations, with no definite therapy. Current drugs are now being tested in amyloidosis clinical trials as aggregation inhibitors to mitigate disease progression. The tetracycline group among antimicrobials in use is in phase II of clinical trials, whereas some macrolides and cephalosporins have shown neuroprotection. In the present study, two cephalosporins, ceftazidime (CZD) and cefotaxime (CXM), and a glycopeptide, vancomycin (VNC), are evaluated for inhibition of amyloid aggregation of hen egg white lysozyme (HEWL) under two conditions (i) 4 M guanidine hydrochloride (GuHCl) at pH 6.5 and 37° C, (ii) At pH 1.5 and 65 °C. Fluorescence quench titration and molecular docking methods report that CZD, CXM, and VNC interact more strongly with the partially folded intermediates (PFI) in comparison to the protein's natural state (N). However, only CZD and CXM proficiently inhibit the aggregation. Transmission electron microscopy, tinctorial assessments, and aggregation kinetics all support oligomer-level inhibition. Transition structures in CZD-HEWL and CXM-HEWL aggregation are shown by circular dichroism (CD). On the other hand, kinetic variables and soluble fraction assays point to a localized association of monomers. Intrinsic fluorescence (IF),1-Anilino 8-naphthalene sulphonic acid, and CD demonstrate structural and conformational modifications redesigning the PFI. GuHCl-induced unfolding and differential scanning fluorimetry suggested that the PFI monomers bound to CZD and CXM exhibited partial stability. Our results present two mechanisms that function in both solution conditions, creating a novel avenue for the screening of putative inhibitors for drug repurposing. We extend our proposed mechanisms in the designing of physical inhibitors of amyloid aggregation considering shorter time frames and foolproof methods.Communicated by Ramaswamy H. Sarma.

PMID:38682862 | DOI:10.1080/07391102.2024.2335304

ACS Omega. 2024 Apr 9;9(16):18584-18592. doi: 10.1021/acsomega.4c01195. eCollection 2024 Apr 23.

ABSTRACT

Colorectal cancer (CRC) has witnessed a concerning increase in incidence and poses a significant therapeutic challenge due to its poor prognosis. There is a pressing demand to identify novel drug therapies to combat CRC. In this study, we addressed this need by utilizing the pharmacological profiles of anticancer drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) database and developed QSAR models using the Support Vector Machine (SVM) algorithm for prediction of alternative and promiscuous anticancer compounds for CRC treatment. Our QSAR models demonstrated their robustness by achieving a high correlation of determination (R2) after 10-fold cross-validation. For 12 CRC cell lines, R2 ranged from 0.609 to 0.827. The highest performance was achieved for SW1417 and GP5d cell lines with R2 values of 0.827 and 0.786, respectively. Further, we listed the most common chemical descriptors in the drug profiles of the CRC cell lines and we also further reported the correlation of these descriptors with drug activity. The KRFP314 fingerprint was the predominantly occurring descriptor, with the KRFPC314 fingerprint following closely in prevalence within the drug profiles of the CRC cell lines. Beyond predictive modeling, we also confirmed the applicability of our developed QSAR models via in silico methods by conducting descriptor-drug analyses and recapitulating drug-to-oncogene relationships. We also identified two potential anti-CRC FDA-approved drugs, viomycin and diamorphine, using QSAR models. To ensure the easy accessibility and utility of our research findings, we have incorporated these models into a user-friendly prediction Web server named "ColoRecPred", available at https://project.iith.ac.in/cgntlab/colorecpred. We anticipate that this Web server can be used for screening of chemical libraries to identify potential anti-CRC drugs.

PMID:38680332 | PMC:PMC11044175 | DOI:10.1021/acsomega.4c01195

ACS Omega. 2024 Apr 9;9(16):18438-18448. doi: 10.1021/acsomega.4c00470. eCollection 2024 Apr 23.

ABSTRACT

Sortilin (SORT1) is a multifunctional protein intricately involved in atherogenesis, coronary artery disease (CAD), and various neurological disorders. It has materialized as a potential pharmacological target for therapeutic development due to its diverse biological roles in pathological processes. Despite its central role under these conditions, effective therapeutic strategies targeting SORT1 remain challenging. In this study, we introduce a drug repurposing strategy guided by structural insights to identify potent SORT1 inhibitors with broad therapeutic potential. Our approach combines molecular docking, virtual screening, and molecular dynamics (MD) simulations, enabling the systematic evaluation of 3648 FDA-approved drugs for their potential to modulate SORT1. The investigation reveals a subset of repurposed drugs exhibiting highly favorable binding profiles and stable interactions within the binding site of SORT1. Notably, two hits, ergotamine and digitoxin, were carefully chosen based on their drug profiles and subjected to analyze their interactions with SORT1 and stability assessment via all-atom MD simulations spanning 300 ns (ns). The structural analyses uncover the complex binding interactions between these identified compounds and SORT1, offering essential mechanistic insights. Additionally, we explore the clinical implications of repurposing these compounds as potential therapeutic agents, emphasizing their significance in addressing atherogenesis, CAD, and neurological disorders. Overall, this study highlights the efficacy of structure-guided drug repurposing and provides a solid foundation for future research endeavors aimed at the development of effective therapies targeting SORT1 under diverse pathological conditions.

PMID:38680294 | PMC:PMC11044209 | DOI:10.1021/acsomega.4c00470

Cell Biosci. 2024 Apr 27;14(1):55. doi: 10.1186/s13578-024-01230-8.

ABSTRACT

BACKGROUND: Alzheimer's disease (AD) is the most prevalent neurodegenerative disease with limited disease-modifying treatments. Drug repositioning strategy has now emerged as a promising approach for anti-AD drug discovery. Using 5×FAD mice and Aβ-treated neurons in culture, we tested the efficacy of Y-2, a compounded drug containing the antioxidant Edaravone (Eda), a pyrazolone and (+)-Borneol, an anti-inflammatory diterpenoid from cinnamon, approved for use in amyotrophic lateral sclerosis patients.

RESULTS: We examined effects of Y-2 versus Eda alone by i.p. administered in 8-week-old 5×FAD mice (females) for 4 months by comparing cognitive function, Aβ pathologies, neuronal necroptosis and neuroinflammation. Using primary neurons and astrocytes, as well as neuronal and astrocytic cell lines, we elucidated the molecular mechanisms of Y-2 by examining neuronal injury, astrocyte-mediated inflammation and necroptosis. Here, we find that Y-2 improves cognitive function in AD mice. Histopathological data show that Y-2, better than Eda alone, markedly ameliorates Aβ pathologies including Aβ burden, astrogliosis/microgliosis, and Tau phosphorylation. In addition, Y-2 reduces Aβ-induced neuronal injury including neurite damage, mitochondrial impairment, reactive oxygen species production and NAD+ depletion. Notably, Y-2 inhibits astrocyte-mediated neuroinflammation and attenuates TNF-α-triggered neuronal necroptosis in cell cultures and AD mice. RNA-seq further demonstrates that Y-2, compared to Eda, indeed upregulates anti-inflammation pathways in astrocytes.

CONCLUSIONS: Our findings infer that Y-2, better than Eda alone, mitigates AD pathology and may provide a potential drug candidate for AD treatment.

PMID:38678262 | DOI:10.1186/s13578-024-01230-8

Biomed Pharmacother. 2024 Apr 26:116639. doi: 10.1016/j.biopha.2024.116639. Online ahead of print.

NO ABSTRACT

PMID:38677923 | DOI:10.1016/j.biopha.2024.116639

Brain Behav Immun. 2024 Apr 25:S0889-1591(24)00375-1. doi: 10.1016/j.bbi.2024.04.026. Online ahead of print.

ABSTRACT

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory. Response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

PMID:38677625 | DOI:10.1016/j.bbi.2024.04.026

J Mol Graph Model. 2024 Apr 24;130:108783. doi: 10.1016/j.jmgm.2024.108783. Online ahead of print.

ABSTRACT

Drug repurposing is an effective method to reduce the time and cost of drug development. Computational drug repurposing can quickly screen out the most likely associations from large biological databases to achieve effective drug repurposing. However, building a comprehensive model that integrates drugs, proteins, and diseases for drug repurposing remains challenging. This study proposes a drug repurposing method based on the ternary heterogeneous graph attention network (DRTerHGAT). DRTerHGAT designs a novel protein feature extraction process consisting of a large-scale protein language model and a multi-task autoencoder, so that protein features can be extracted accurately and efficiently from amino acid sequences. The ternary heterogeneous graph of drug-protein-disease comprehensively considering the relationships among the three types of nodes, including three homogeneous and three heterogeneous relationships. Based on the graph and the extracted protein features, the deep features of the drugs and the diseases are extracted by graph convolutional networks (GCN) and heterogeneous graph node attention networks (HGNA). In the experiments, DRTerHGAT is proven superior to existing advanced methods and DRTerHGAT variants. DRTerHGAT's powerful ability for drug repurposing is also demonstrated in Alzheimer's disease.

PMID:38677034 | DOI:10.1016/j.jmgm.2024.108783

Viruses. 2024 Apr 22;16(4):651. doi: 10.3390/v16040651.

ABSTRACT

Most repurposed drugs have proved ineffective for treating COVID-19. We evaluated median effective and toxic concentrations (EC50, CC50) of 49 drugs, mostly from previous clinical trials, in Vero cells. Ratios of reported unbound peak plasma concentrations, (Cmax)/EC50, were used to predict the potential in vivo efficacy. The 20 drugs with the highest ratios were retested in human Calu-3 and Caco-2 cells, and their CC50 was determined in an expanded panel of cell lines. Many of the 20 drugs with the highest ratios were inactive in human Calu-3 and Caco-2 cells. Antivirals effective in controlled clinical trials had unbound Cmax/EC50 ≥ 6.8 in Calu-3 or Caco-2 cells. EC50 of nucleoside analogs were cell dependent. This approach and earlier availability of more relevant cultures could have reduced the number of unwarranted clinical trials.

PMID:38675992 | DOI:10.3390/v16040651

Pharmaceuticals (Basel). 2024 Mar 28;17(4):432. doi: 10.3390/ph17040432.

ABSTRACT

SARS-CoV-2 infections, commonly referred to as COVID-19, remain a critical risk to both human life and global economies. Particularly, COVID-19 patients with weak immunity may suffer from different complications due to the bacterial co-infections/super-infections/secondary infections. Therefore, different variants of alternative antibacterial therapeutic agents are required to inhibit those infection-causing drug-resistant pathogenic bacteria. This study attempted to explore these bacterial pathogens and their inhibitors by using integrated statistical and bioinformatics approaches. By analyzing bacterial 16S rRNA sequence profiles, at first, we detected five bacterial genera and taxa (Bacteroides, Parabacteroides, Prevotella Clostridium, Atopobium, and Peptostreptococcus) based on differentially abundant bacteria between SARS-CoV-2 infection and control samples that are significantly enriched in 23 metabolic pathways. A total of 183 bacterial genes were found in the enriched pathways. Then, the top-ranked 10 bacterial genes (accB, ftsB, glyQ, hldD, lpxC, lptD, mlaA, ppsA, ppc, and tamB) were selected as the pathogenic bacterial key genes (bKGs) by their protein-protein interaction (PPI) network analysis. Then, we detected bKG-guided top-ranked eight drug molecules (Bemcentinib, Ledipasvir, Velpatasvir, Tirilazad, Acetyldigitoxin, Entreatinib, Digitoxin, and Elbasvir) by molecular docking. Finally, the binding stability of the top-ranked three drug molecules (Bemcentinib, Ledipasvir, and Velpatasvir) against three receptors (hldD, mlaA, and lptD) was investigated by computing their binding free energies with molecular dynamic (MD) simulation-based MM-PBSA techniques, respectively, and was found to be stable. Therefore, the findings of this study could be useful resources for developing a proper treatment plan against bacterial co-/super-/secondary-infection in SARS-CoV-2 infections.

PMID:38675393 | DOI:10.3390/ph17040432

Pharmaceuticals (Basel). 2024 Mar 27;17(4):427. doi: 10.3390/ph17040427.

ABSTRACT

Discoidin domain receptor 1 (DDR1) kinase has emerged as a promising target for cancer therapy, and selective DDR1 inhibitors have shown promise as effective therapeutic candidates. Herein, we have identified the first coumarin-based selective DDR1 inhibitors via repurposing of a recent series of carbonic anhydrase inhibitors. Among these, ureidocoumarins 3a, 3i, and 3q showed the best DDR1 inhibitory activities. The m-trifluoromethoxy phenyl member 3q potently inhibited DDR1 with an IC50 of 191 nM, while it showed less inhibitory activity against DDR2 (IC50 = 5080 nM). 3q also exhibited favorable selectivity in a screening platform with 23 common off-target kinases, including BCR-ABL. In the cellular context, 3q showed moderate antiproliferative effects, while 3i, with the third rank in DDR1 inhibition, exerted the best anticancer activity with sub-micromolar GI50 values over certain DDR1-dependent cell lines. Molecular docking and MD simulations disclosed the putative binding mode of this coumarin chemotype and provided insights for further optimization of this scaffold. The present findings collectively supported the potential improvement of ureidocoumarins 3i and 3q for cancer treatment.

PMID:38675389 | DOI:10.3390/ph17040427

Pharmaceutics. 2024 Mar 30;16(4):476. doi: 10.3390/pharmaceutics16040476.

ABSTRACT

Vesicular hand eczema (VHE), a clinical subtype of hand eczema (HE), showed limited responsiveness to alitretinoin, the only approved systemic treatment for severe chronic HE. This emphasizes the need for alternative treatment approaches. Therefore, our study aimed to identify drug repurposing opportunities for VHE using transcriptomics and genomics data. We constructed a gene network by combining 52 differentially expressed genes (DEGs) from a VHE transcriptomics study with 3 quantitative trait locus (QTL) genes associated with HE. Through network analysis, clustering, and functional enrichment analyses, we investigated the underlying biological mechanisms of this network. Next, we leveraged drug-gene interactions and retrieved pharmaco-transcriptomics data from the DrugBank database to identify drug repurposing opportunities for (V)HE. We developed a drug ranking system, primarily based on efficacy, safety, and practical and pricing factors, to select the most promising drug repurposing candidates. Our results revealed that the (V)HE network comprised 78 genes that yielded several biological pathways underlying the disease. The drug-gene interaction search together with pharmaco-transcriptomics lookups revealed 123 unique drug repurposing opportunities. Based on our drug ranking system, our study identified the most promising drug repurposing opportunities (e.g., vitamin D analogues, retinoids, and immunomodulating drugs) that might be effective in treating (V)HE.

PMID:38675137 | DOI:10.3390/pharmaceutics16040476

Genes (Basel). 2024 Mar 22;15(4):393. doi: 10.3390/genes15040393.

ABSTRACT

Autoimmunity is defined as the inability to regulate immunological activities in the body, especially in response to external triggers, leading to the attack of the tissues and organs of the host. Outcomes include the onset of autoimmune diseases whose effects are primarily due to dysregulated immune responses. In past years, there have been cases that show an increased susceptibility to other autoimmune disorders in patients who are already experiencing the same type of disease. Research in this field has started analyzing the potential molecular and cellular causes of this interconnectedness, bearing in mind the possibility of advancing drugs and therapies for the treatment of autoimmunity. With that, this study aimed to determine the correlation of four autoimmune diseases, which are type 1 diabetes (T1D), psoriasis (PSR), systemic sclerosis (SSc), and systemic lupus erythematosus (SLE), by identifying highly preserved co-expressed genes among datasets using WGCNA. Functional annotation was then employed to characterize these sets of genes based on their systemic relationship as a whole to elucidate the biological processes, cellular components, and molecular functions of the pathways they are involved in. Lastly, drug repurposing analysis was performed to screen candidate drugs for repositioning that could regulate the abnormal expression of genes among the diseases. A total of thirteen modules were obtained from the analysis, the majority of which were associated with transcriptional, post-transcriptional, and post-translational modification processes. Also, the evaluation based on KEGG suggested the possible role of TH17 differentiation in the simultaneous onset of the four diseases. Furthermore, clomiphene was the top drug candidate for regulating overexpressed hub genes; meanwhile, prilocaine was the top drug for regulating under-expressed hub genes. This study was geared towards utilizing transcriptomics approaches for the assessment of microarray data, which is different from the use of traditional genomic analyses. Such a research design for investigating correlations among autoimmune diseases may be the first of its kind.

PMID:38674328 | DOI:10.3390/genes15040393

Int J Mol Sci. 2024 Apr 22;25(8):4565. doi: 10.3390/ijms25084565.

ABSTRACT

Saracatinib (AZD0530) is a dual Src/Abl inhibitor initially developed by AstraZeneca for cancer treatment; however, data from 2006 to 2024 reveal that this drug has been tested not only for cancer treatment, but also for the treatment of other diseases. Despite the promising pre-clinical results and the tolerability shown in phase I trials, where a maximum tolerated dose of 175 mg was defined, phase II clinical data demonstrated a low therapeutic action against several cancers and an elevated rate of adverse effects. Recently, pre-clinical research aimed at reducing the toxic effects and enhancing the therapeutic performance of saracatinib using nanoparticles and different pharmacological combinations has shown promising results. Concomitantly, saracatinib was repurposed to treat Alzheimer's disease, targeting Fyn. It showed great clinical results and required a lower daily dose than that defined for cancer treatment, 125 mg and 175 mg, respectively. In addition to Alzheimer's disease, this Src inhibitor has also been studied in relation to other health conditions such as pulmonary and liver fibrosis and even for analgesic and anti-allergic functions. Although saracatinib is still not approved by the Food and Drug Administration (FDA), the large number of alternative uses for saracatinib and the elevated number of pre-clinical and clinical trials performed suggest the huge potential of this drug for the treatment of different kinds of diseases.

PMID:38674150 | DOI:10.3390/ijms25084565

Int J Mol Sci. 2024 Apr 9;25(8):4161. doi: 10.3390/ijms25084161.

ABSTRACT

Neuroinflammation and epilepsy are different pathologies, but, in some cases, they are so closely related that the activation of one of the pathologies leads to the development of the other. In this work, we discuss the three main cell types involved in neuroinflammation, namely (i) reactive astrocytes, (ii) activated microglia, and infiltration of (iii) peripheral immune cells in the central nervous system. Then, we discuss how neuroinflammation and epilepsy are interconnected and describe the use of different repurposing drugs with anti-inflammatory properties that have been shown to have a beneficial effect in different epilepsy models. This review reinforces the idea that compounds designed to alleviate seizures need to target not only the neuroinflammation caused by reactive astrocytes and microglia but also the interaction of these cells with infiltrated peripheral immune cells.

PMID:38673747 | DOI:10.3390/ijms25084161

Cancers (Basel). 2024 Apr 11;16(8):1463. doi: 10.3390/cancers16081463.

ABSTRACT

Cancer persists as a global challenge necessitating continual innovation in treatment strategies. Despite significant advancements in comprehending the disease, cancer remains a leading cause of mortality worldwide, exerting substantial economic burdens on healthcare systems and societies. The emergence of drug resistance further complicates therapeutic efficacy, underscoring the urgent need for alternative approaches. Drug repurposing, characterized by the utilization of existing drugs for novel clinical applications, emerges as a promising avenue for addressing these challenges. Repurposed drugs, comprising FDA-approved (in other disease indications), generic, off-patent, and failed medications, offer distinct advantages including established safety profiles, cost-effectiveness, and expedited development timelines compared to novel drug discovery processes. Various methodologies, such as knowledge-based analyses, drug-centric strategies, and computational approaches, play pivotal roles in identifying potential candidates for repurposing. However, despite the promise of repurposed drugs, drug repositioning confronts formidable obstacles. Patenting issues, financial constraints associated with conducting extensive clinical trials, and the necessity for combination therapies to overcome the limitations of monotherapy pose significant challenges. This review provides an in-depth exploration of drug repurposing, covering a diverse array of approaches including experimental, re-engineering protein, nanotechnology, and computational methods. Each of these avenues presents distinct opportunities and obstacles in the pursuit of identifying novel clinical uses for established drugs. By examining the multifaceted landscape of drug repurposing, this review aims to offer comprehensive insights into its potential to transform cancer therapeutics.

PMID:38672545 | DOI:10.3390/cancers16081463

Virol J. 2024 Apr 26;21(1):98. doi: 10.1186/s12985-024-02370-6.

ABSTRACT

About four years have passed since the detection of the first cases of COVID-19 in China. During this lethal pandemic, millions of people have lost their lives around the world. Since the first waves of COVID-19 infection, various pharmacotherapeutic agents have been examined in the management of COVID-19. Despite all these efforts in pharmacotherapy, drug repurposing, and design and development of new drugs, multiple organ involvement and various complications occurred during COVID-19. Some of these complications became chronic and long-lasting which led to the "long COVID" syndrome appearance. Therefore, the best way to eradicate this pandemic is prophylaxis through mass vaccination. In this regard, various vaccine platforms including inactivated vaccines, nucleic acid-based vaccines (mRNA and DNA vaccines), adenovirus-vectored vaccines, and protein-based subunit vaccines have been designed and developed to prevent or reduce COVID-19 infection, hospitalization, and mortality rates. In this focused review, at first, the most commonly reported clinical presentations of COVID-19 during these four years have been summarized. In addition, different therapeutic regimens and their latest status in COVID-19 management have been listed. Furthermore, the "long COVID" and related signs, symptoms, and complications have been mentioned. At the end, the effectiveness of available COVID-19 vaccines with different platforms against early SARS-CoV-2 variants and currently circulating variants of interest (VOI) and the necessity of booster vaccine shots have been summarized and discussed in more detail.

PMID:38671455 | DOI:10.1186/s12985-024-02370-6

Life Sci Space Res (Amst). 2024 May;41:64-73. doi: 10.1016/j.lssr.2024.01.004. Epub 2024 Jan 29.

ABSTRACT

Microgravity in the space environment can potentially have various negative effects on the human body, one of which is bone loss. Given the increasing frequency of human space activities, there is an urgent need to identify effective anti-osteoporosis drugs for the microgravity environment. Traditional microgravity experiments conducted in space suffer from limitations such as time-consuming procedures, high costs, and small sample sizes. In recent years, the in-silico drug discovery method has emerged as a promising strategy due to the advancements in bioinformatics and computer technology. In this study, we first collected a total of 184,915 literature articles related to microgravity and bone loss. We employed a combination of dependency path extraction and clustering techniques to extract data from the text. Afterwards, we conducted data cleaning and standardization to integrate data from several sources, including The Global Network of Biomedical Relationships (GNBR), Curated Drug-Drug Interactions Database (DDInter), Search Tool for Interacting Chemicals (STITCH), DrugBank, and Traditional Chinese Medicines Integrated Database (TCMID). Through this integration process, we constructed the Microgravity Biology Knowledge Graph (MBKG) consisting of 134,796 biological entities and 3,395,273 triplets. Subsequently, the TransE model was utilized to perform knowledge graph embedding. By calculating the distances between entities in the model space, the model successfully predicted potential drugs for treating osteoporosis and microgravity-induced bone loss. The results indicate that out of the top 10 ranked western medicines, 7 have been approved for the treatment of osteoporosis. Additionally, among the top 10 ranked traditional Chinese medicines, 5 have scientific literature supporting their effectiveness in treating bone loss. Among the top 20 predicted medicines for microgravity-induced bone loss, 15 have been studied in microgravity or simulated microgravity environments, while the remaining 5 are also applicable for treating osteoporosis. This research highlights the potential application of MBKG in the field of space drug discovery.

PMID:38670654 | DOI:10.1016/j.lssr.2024.01.004

PLoS Pathog. 2024 Apr 26;20(4):e1011906. doi: 10.1371/journal.ppat.1011906. Online ahead of print.

ABSTRACT

The apicomplexan parasite Cryptosporidium is a leading cause of childhood diarrhea in developing countries. Current treatment options are inadequate and multiple preclinical compounds are being actively pursued as potential drugs for cryptosporidiosis. Unlike most apicomplexans, Cryptosporidium spp. sequentially replicate asexually and then sexually within a single host to complete their lifecycles. Anti-cryptosporidial compounds are generally identified or tested through in vitro phenotypic assays that only assess the asexual stages. Therefore, compounds that specifically target the sexual stages remain unexplored. In this study, we leveraged the ReFRAME drug repurposing library against a newly devised multi-readout imaging assay to identify small-molecule compounds that modulate macrogamont differentiation and maturation. RNA-seq studies confirmed selective modulation of macrogamont differentiation for 10 identified compounds (9 inhibitors and 1 accelerator). The collective transcriptomic profiles of these compounds indicates that translational repression accompanies Cryptosporidium sexual differentiation, which we validated experimentally. Additionally, cross comparison of the RNA-seq data with promoter sequence analysis for stage-specific genes converged on a key role for an Apetala 2 (AP2) transcription factor (cgd2_3490) in differentiation into macrogamonts. Finally, drug annotation for the ReFRAME hits indicates that an elevated supply of energy equivalence in the host cell is critical for macrogamont formation.

PMID:38669269 | DOI:10.1371/journal.ppat.1011906

Cells. 2024 Apr 20;13(8):717. doi: 10.3390/cells13080717.

ABSTRACT

Gynecological and obstetric infectious diseases are crucial to women's health. There is growing evidence that links the presence of Fusobacterium nucleatum (F. nucleatum), an anaerobic oral commensal and potential periodontal pathogen, to the development and progression of various human diseases, including cancers. While the role of this opportunistic oral pathogen has been extensively studied in colorectal cancer in recent years, research on its epidemiological evidence and mechanistic link to gynecological diseases (GDs) is still ongoing. Thus, the present review, which is the first of its kind, aims to undertake a comprehensive and critical reappraisal of F. nucleatum, including the genetics and mechanistic role in promoting adverse pregnancy outcomes (APOs) and various GDs, including cancers. Additionally, this review discusses new conceptual advances that link the immunomodulatory role of F. nucleatum to the development and progression of breast, ovarian, endometrial, and cervical carcinomas through the activation of various direct and indirect signaling pathways. However, further studies are needed to explore and elucidate the highly dynamic process of host-F. nucleatum interactions and discover new pathways, which will pave the way for the development of better preventive and therapeutic strategies against this pathobiont.

PMID:38667331 | DOI:10.3390/cells13080717