Alpha-1 antitrypsin inhibits Clostridium botulinum C2 toxin, Corynebacterium diphtheriae diphtheria toxin and B. anthracis fusion toxin.

The bacterium Clostridium botulinum, well-known for producing botulinum neurotoxins, which cause the severe paralytic illness known as botulism, produces C2 toxin, a binary AB-toxin with ADP-ribosyltranferase activity. C2 toxin possesses two separate protein components, an enzymatically active A-component C2I and the binding and translocation B-component C2II. After proteolytic activation of C2II to C2IIa, the heptameric structure binds C2I and is taken up via receptor-mediated endocytosis into the target cells. Due to acidification of endosomes, the C2IIa/C2I complex undergoes conformational changes and consequently C2IIa forms a pore into the endosomal membrane and C2I can translocate into the cytoplasm, where it ADP-ribosylates G-actin, a key component of the cytoskeleton. This modification disrupts the actin cytoskeleton, resulting in the collapse of cytoskeleton and ultimately cell death. Here, we show that the serine-protease inhibitor α1-antitrypsin (α1AT) which we identified previously from a hemofiltrate library screen for PT from Bordetella pertussis is a multitoxin inhibitor. α1AT inhibits intoxication of cells with C2 toxin via inhibition of binding to cells and inhibition of enzyme activity of C2I. Moreover, diphtheria toxin and an anthrax fusion toxin are inhibited by α1AT. Since α1AT is commercially available as a drug for treatment of the α1AT deficiency, it could be repurposed for treatment of toxin-mediated diseases.

In silico comparative analysis of cestode and human NPC1 provides insights for ezetimibe repurposing to visceral cestodiases treatment.

Visceral cestodiases, like cysticercoses and echinococcoses, are caused by cystic larvae from parasites of the Cestoda class and are endemic or hyperendemic in many areas of the world. Current therapeutic approaches for these diseases are complex and present limitations and risks. Therefore, new safer and more effective treatments are urgently needed. The Niemann-Pick C1 (NPC1) protein is a cholesterol transporter that, based on genomic data, would be the solely responsible for cholesterol uptake in cestodes. Considering that human NPC1L1 is a known target of ezetimibe, used in the treatment of hypercholesterolemia, it has the potential for repurposing for the treatment of visceral cestodiases. Here, phylogenetic, selective pressure and structural in silico analyses were carried out to assess NPC1 evolutive and structural conservation, especially between cestode and human orthologs. Two NPC1 orthologs were identified in cestode species (NPC1A and NPC1B), which likely underwent functional divergence, leading to the loss of cholesterol transport capacity in NPC1A. Comparative interaction analyses performed by molecular docking of ezetimibe with human NPC1L1 and cestode NPC1B pointed out to similarities that consolidate the idea of cestode NPC1B as a target for the repurposing of ezetimibe as a drug for the treatment of visceral cestodiases.

Tanomastat exerts multi-targeted inhibitory effects on viral capsid dissociation and RNA replication in human enteroviruses.

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).

FDA-approved antivirals ledipasvir and daclatasvir downregulate the Src-EPHA2-Akt oncogenic pathway in colorectal and triple-negative breast cancer cells.

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.

Anticancer effect of the antipsychotic agent penfluridol on epithelial ovarian cancer.

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.

Treatment of congenital disorders of glycosylation: An overview.

While the identification and diagnosis of congenital disorders of glycosylation (CDG) have rapidly progressed, the available treatment options are still quite limited. Mostly, we are only able to manage the disease symptoms rather than to address the underlying cause. However, recent years have brought about remarkable advances in treatment approaches for some CDG. Innovative therapies, targeting both the root cause and resulting manifestations, have transitioned from the research stage to practical application. The present paper aims to provide a detailed overview of these exciting developments and the rising concepts that are used to treat these ultra-rare diseases.

Discovery of therapeutic targets in cancer using chromatin accessibility and transcriptomic data.

Most cancer types lack targeted therapeutic options, and when first-line targeted therapies are available, treatment resistance is a huge challenge. Recent technological advances enable the use of assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA sequencing (RNA-seq) on patient tissue in a high-throughput manner. Here, we present a computational approach that leverages these datasets to identify drug targets based on tumor lineage. We constructed gene regulatory networks for 371 patients of 22 cancer types using machine learning approaches trained with three-dimensional genomic data for enhancer-to-promoter contacts. Next, we identified the key transcription factors (TFs) in these networks, which are used to find therapeutic vulnerabilities, by direct targeting of either TFs or the proteins that they interact with. We validated four candidates identified for neuroendocrine, liver, and renal cancers, which have a dismal prognosis with current therapeutic options.

MFF-DTA: Multi-scale feature fusion for drug-target affinity prediction.

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.

A brief review on the lessons learned from COVID-19 on drug discovery and research.

COVID-19 pandemic has taught many lessons regarding drug discovery and development. This review covers these aspects of drug discovery and research for COVID-19 which might be used as a tool for future. It summarizes the positives such as progresses in antiviral drug discovery, drug repurposing, adaptations of clinical trial and its regulations, as well as the negative points such as the need to develop more collaboration among stakeholders and future directions. It also discusses the benefits and limitations of finding new indications for existing drugs, and the lessons learned regarding rigorous and robust clinical trials, pharmacokinetic/pharmacodynamic modelling, as well as combination therapy. The pandemic has also revealed some gaps regarding global collaboration and coordination, data sharing and transparency and equitable distribution. Finally, the review enumerates the future directions and implications of drug discovery and research for COVID-19 and other infectious diseases such as preparedness and resilience, interdisciplinary and integrative approaches, diversity and inclusion, and personalized and precision medicine.

Identifying new molecular signatures and potential therapeutics for idiopathic pulmonary fibrosis: a network medicine approach.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease characterized by excessive collagen deposition and fibrosis of the lung parenchyma, leading to respiratory failure. The molecular mechanisms underlying IPF pathogenesis remain incompletely understood, hindering the development of effective therapeutic strategies. We have used a network medicine approach to comprehensively analyze molecular interactions and identify novel molecular signatures and potential therapeutics associated with IPF progression. Our integrative analysis revealed dysregulated molecular networks that are central to IPF pathophysiology. We have highlighted key molecular players and signaling pathways that are implicated in aberrant fibrotic processes. This systems-level understanding enables the identification of new biomarkers and therapeutic targets for IPF, providing potential avenues for precision medicine. Drug repurposing analysis revealed several drug candidates with anti-fibrotic, anti-inflammatory, and anti-cancer activities that could potentially slow fibrotic progression and improve patient outcomes. This study offers new insights into the molecular underpinnings of IPF and highlights network medicine approaches in uncovering complex disease mechanisms. The molecular signatures and therapeutic targets identified hold promise for developing precision therapies tailored to individual patients, ultimately advancing the management of this debilitating lung disease.

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, including those derived from underrepresented groups, is not trivial when resources are minimal. Using gene expression to predict other measurements has been actively explored; however, systematic investigation of its predictive power in various measurements has not been well studied. Here, we evaluated commonly used machine learning methods and presented TransCell, a two-step deep transfer learning framework that utilized the knowledge derived from pan-cancer tumor samples to predict molecular features and responses. Among these models, TransCell had the best performance in predicting metabolite, gene effect score (or genetic dependency), and drug sensitivity, and had comparable performance in predicting mutation, copy number variation, and protein expression. Notably, TransCell improved the performance by over 50% in drug sensitivity prediction and achieved a correlation of 0.7 in gene effect score prediction. Furthermore, predicted drug sensitivities revealed potential repurposing candidates for new 100 pediatric cancer cell lines, and predicted gene effect scores reflected BRAF resistance in melanoma cell lines. Together, we investigated the predictive power of gene expression in six molecular measurement types and developed a web portal (http://apps.octad.org/transcell/) that enables the prediction of 352,000 genomic and cellular response features solely from gene expression profiles.

Drug repurposing against antibiotic resistant bacterial pathogens.

The growing prevalence of MDR and XDR bacterial pathogens is posing a critical threat to global health. Traditional antibiotic development paths have encountered significant challenges and are drying up thus necessitating innovative approaches. Drug repurposing, which involves identifying new therapeutic applications for existing drugs, offers a promising alternative to combat resistant pathogens. By leveraging pre-existing safety and efficacy data, drug repurposing accelerates the development of new antimicrobial therapy regimes. This review explores the potential of repurposing existing FDA approved drugs against the ESKAPE and other clinically relevant bacterial pathogens and delves into the identification of suitable drug candidates, their mechanisms of action, and the potential for combination therapies. It also describes clinical trials and patent protection of repurposed drugs, offering perspectives on this evolving realm of therapeutic interventions against drug resistance.

Challenges for developing bacterial CA inhibitors as novel antibiotics.

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-, ß- 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 ß-lactams and other clinically used antibiotics.

Shared etiology of Mendelian and complex disease supports drug discovery.

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

Advances in the approaches used to repurpose drugs for neuroblastoma.

INTRODUCTION: Neuroblastoma (NB) remains a challenging pediatric malignancy with limited treatment options, particularly for high-risk cases. Drug repurposing offers a convenient and cost-effective strategy for treating rare diseases like NB. Using existing drugs with known safety profiles accelerates the availability of new treatments, reduces development costs, and mitigates risks, offering hope for improved patient outcomes in challenging conditions. AREAS COVERED: This review provides an overview of the advances in approaches used to repurpose drugs for NB therapy. The authors discuss strategies employed in drug repurposing, including computational and experimental methods, and rational drug design, highlighting key examples of repurposed drugs with promising clinical results. Additionally, the authors examine the challenges and opportunities associated with drug repurposing in NB and discuss future directions and potential areas for further research. EXPERT OPINION: The fact that only one new drug has been approved in the last 30 years for the treatment of neuroblastoma plus a significant proportion of high-risk NB patients that remain uncurable, evidences the need for new fast and cost-effective alternatives. Drug repurposing may accelerate the treatment development process while reducing expenses and risks. This approach can swiftly bring effective NB therapies to market, enhancing survival rates and patient quality of life.

Repurposing anti-osteoporosis drugs for autoimmune diseases: A two-sample Mendelian randomization study.

Background: Despite the increasing availability of therapeutic drugs for autoimmune diseases, many patients still struggle to achieve their treatment goals. Our aim was to identify whether drugs originally used to treat bone density could be applied to the treatment of autoimmune diseases through Mendelian randomization (MR). Methods: Using summary statistics from genome-wide association studies, we used a two-sample MR design to estimate the correlation between autoimmune diseases and BMD-related drug targets. Data from the DrugBank and ChEMBL databases were used to identify the drug targets of anti-osteoporosis medications. The Wald ratio test or inverse-variance weighting method was used to assess the impact of genetic variation in drug target(s) on autoimmune disease therapy. Results: Through our analysis, we discovered a negative correlation between genetic variability in a specific gene (ESR1) in raloxifene/colecalciferol and various autoimmune disorders such as ankylosing spondylitis, endometriosis, IgA nephropathy, rheumatoid arthritis, sarcoidosis, systemic lupus erythematosus, and type 1 diabetes. Conclusion: These results indicate a possible link between genetic differences in the drug targeting ESR1 and susceptibility to autoimmune disorders. Hence, our study offers significant support for the possible use of drugs targeting ESR1 for the management of autoimmune disorders. MR and drug repurposing are utilized to investigate the relationship between autoimmune diseases and bone mineral density, with a focus on ESR1.

Analysis of VEGFR-2 and PDGFR-ß expression in canine splenic hemangiosarcoma to identify drug repositioning candidates.

Splenic tumors are very common in dogs, and canine hemangiosarcoma (HSA) is one of the most important malignant splenic tumors. Surgery followed by chemotherapy (anthracycline-based protocols) is recommended for treating canine HSA; however, patients still do not achieve long-term survival. Therefore, this research aimed to assess vascular endothelial growth factor receptor-2 (VEGFR-2) and platelet-derived growth factor receptor-ß (PDGFR-ß) gene expression in formalin-fixed tissues, evaluate the quality of mRNA for quantitative polymerase chain reaction (qPCR) analysis and identify drug repositioning candidates based on VEGFR-2 and PDGFR-ß. qPCR analysis identified the relative expression of heterogeneous VEGFR-2 and PDGFR-ß, with samples showing no transcripts or very low expression and those with higher relative quantification for both genes. We then used immunohistochemistry to correlate the relative quantification of VEGFR-2 and PDGFR-ß transcripts with respective higher protein expression to validate our results. In the next step, we evaluated drug repositioning candidates and identified small molecule inhibitors (i.e. sorafenib) and natural compounds (curcumin and resveratrol) with the ability to block VEGFR-2 and PDGFR-ß genes. Overall, our results indicated that VEGFR-2 and PDGFR-ß expression is highly variable among canine HSA samples and different drugs can block the expression of both genes. Therefore, a personalized approach could be useful for selecting anti-VEGFR-2 and PDGFR-ß therapies and both genes are potential candidates for future oncological panels.

Os tumores esplênicos são muito comuns em cães, e o hemangiosarcoma (HSA) é um dos tumores esplênicos malignos mais importantes em cães. A cirurgia seguida de quimioterapia (protocolos baseados em antraciclinas) é a abordagem terapêutica mais recomendada para o tratamento da HSA canino; no entanto, os pacientes ainda não alcançam longa sobrevida após tratamento. Portanto, esta pesquisa teve como objetivo avaliar a expressão do receptor do fator de crescimento endotelial vascular-2 (VEGFR-2) e do receptor do fator de crescimento derivado de plaquetas-ß (PDGFR-ß) em tecidos fixados em formalina e identificar candidatos ao reposicionamento de medicamentos baseado na expressão desses genes. A análise qPCR identificou a expressão relativa heterogênea de VEGFR-2 e PDGFR-ß, com amostras sem transcritos ou com expressão muito baixa ou amostras com alta quantificação relativa para ambos os genes. Em seguida, foi realizada o exame imuno-histoquímico para correlacionar a quantificação relativa dos transcritos de VEGFR-2 e PDGFR-ß com a respectiva maior expressão proteica para validar nossos resultados. Na próxima etapa, avaliamos candidatos ao reposicionamento de medicamentos e identificamos inibidores de moléculas pequenas (ou seja, sorafenibe) e compostos naturais (curcumina e resveratrol) com capacidade de bloquear os genes VEGFR-2 e PDGFR-ß. No geral, nossos resultados indicaram que a expressão de VEGFR-2 e PDGFR-ß é altamente variável entre amostras caninas de HSA e diferentes drogas podem bloquear a expressão de ambos os genes. Portanto, uma abordagem personalizada poderia ser útil para selecionar terapias anti-VEGFR-2 e PDGFR-ß e ambos os genes são potenciais candidatos para futuros painéis oncológicos.

Dihydroergotamine and Bromocriptine: Potential Drugs for the Treatment of Major Depressive Disorder and Alzheimer's Disease Comorbidity.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease that is characterized by memory loss and cognitive impairment. Evidence shows that depression is a common co-occurrence in AD patients, and major depressive disorder (MDD) is considered a risk factor for AD. The crosstalk between the biological procedures related to the two disorders makes it very difficult to treat the comorbid conditions caused by them. Considering the common pathophysiological mechanisms underlying AD and MDD, antidepressant drugs may have beneficial therapeutic effects against their concurrence. In this study, we aimed to explore the potential drug candidates for the prevention and treatment of the comorbidity of AD and MDD. First, we screened the potential drugs for treating MDD by evaluating the distances of drug targets to MDD-related genes on the human protein-protein interaction network (PPIN) via a network-based algorithm. Then, the drugs were further screened to identify those that may be effective for AD treatment by analyzing their affinities with tau protein and Aß42 peptide via molecular docking. Furthermore, the most stable binding modes were identified via molecular dynamics simulations, and the regulatory effects of drug candidates on genes involved in the pathogenesis of AD and MDD were analyzed. A total of 506 MDD-related genes were retrieved, and 831 drug candidates for MDD treatment were screened via the network-based approach. The results from molecular docking and molecular dynamics simulations indicated dihydroergotamine had the lowest binding affinity with tau protein and bromocriptine could form the most stable binding mode with Aß42 peptide. Further analyses found that both dihydroergotamine and bromocriptine could regulate the expression of genes involved in the pathogenesis of AD and/or MDD in the brain. The exact mechanisms of the two drugs in treating AD and MDD, as well as their comorbidity, are still unclear, and further exploration is needed to evaluate their roles and mechanisms, both in vitro and in vivo. This study revealed that dihydroergotamine and bromocriptine may be the potential drug candidates for the treatment of the comorbidity of AD and MDD, and the therapeutic effects may be achieved by inhibiting the accumulation and aggregation of Aß42 and tau protein and regulating the expression of disease-related genes in the brain.

Drug repurposing in Rett and Rett-like syndromes: a promising yet underrated opportunity?

Rett syndrome (RTT) and Rett-like syndromes [i.e., CDKL5 deficiency disorder (CDD) and FOXG1-syndrome] represent rare yet profoundly impactful neurodevelopmental disorders (NDDs). The severity and complexity of symptoms associated with these disorders, including cognitive impairment, motor dysfunction, seizures and other neurological features significantly affect the quality of life of patients and families. Despite ongoing research efforts to identify potential therapeutic targets and develop novel treatments, current therapeutic options remain limited. Here the potential of drug repurposing (DR) as a promising avenue for addressing the unmet medical needs of individuals with RTT and related disorders is explored. Leveraging existing drugs for new therapeutic purposes, DR presents an attractive strategy, particularly suited for neurological disorders given the complexities of the central nervous system (CNS) and the challenges in blood-brain barrier penetration. The current landscape of DR efforts in these syndromes is thoroughly examined, with partiuclar focus on shared molecular pathways and potential common drug targets across these conditions.