Emerging therapeutic avenues against Cryptosporidium: A comprehensive review.

Cryptosporidium is among the top causes of life-threatening diarrheal infection in public health and livestock sectors. Despite its high prevalence and economic importance, currently, there is no vaccine. Control of this protozoan is difficult due to the excretion of many resistant oocysts in the feces of the infected host, which contaminate the environment. Paromomycin shows inconsistent results and isn't considered a reliable therapy for cryptosporidiosis. Nitazoxanide (NTZ), the only FDA-approved drug against this parasite, is less productive in impoverished children and PLWHA (people living with HIV/AIDS). The absence of mitochondria and apicoplast, its unique location inside enterocytes separated by parasitophorous vacuole, and, most importantly, challenges in its genetic manipulations are some hurdles to the drug-discovery process. A library of compounds has been tested against Cryptosporidium during in vitro and in vivo trials. However, there has still not been sufficient success in finding the drug of choice against this parasite. Recent genome editing technologies based on CRISPR/Cas-9 have explored the functions of the vital genes by producing transgenic parasites that help to screen a collection of compounds to find target-specific drugs, provided the sufficient availability of in vitro culturing platforms, efficient transfection methods, and analytic techniques. The use of herbal remedies against Cryptosporidium is also an emerging area of interest with sufficient clinical success due to enhanced concern regarding anthelmintic resistance. Here, we highlighted present treatment options with their associated limitations, the use of genetic tools and natural products against it to find safe, effective, and inexpensive drugs to control the ever-increasing global burden of this disease.

Assessing the causal relationship between plasma proteins and osteoporosis: novel insights into pathological mechanisms and therapeutic implications.

Identifying dysregulated plasma proteins in osteoporosis (OP) progression offers insights into prevention and treatment. This study found 8 such proteins associated with OP, suggesting them as therapy targets. This discovery may cut drug development costs and improve personalized treatments. PURPOSE: This study aims to identify potential therapeutic targets for OP using summary data-based Mendelian randomization (SMR) and colocalization analysis methods. Furthermore, we seek to explore the biological significance and pharmacological value of these drug targets. METHODS: To identify potential therapeutic targets for OP, we conducted SMR and colocalization analysis. Plasma protein (pQTL, exposure) data were sourced from the study by Ferkingstad et al. (n = 35,559). Summary statistics for bone mineral density (BMD, outcome) were obtained from the GWAS Catalog (n = 56,284). Additionally, we utilized enrichment analysis, protein-protein interaction (PPI) network analysis, drug prediction, and molecular docking to further analyze the biological significance and pharmacological value of these drug targets. RESULTS: In the SMR analysis, while 20 proteins showed significance, only 8 potential drug targets (GCKR, ERBB3, CFHR1, GPN1, SDF2, VTN, BET1L, and SERPING1) received support from colocalization (PP.H4 > 0.8). These proteins are closely associated with immune function in terms of biological significance. Molecular docking also demonstrated favorable binding of drugs to proteins, consistent with existing structural data, further substantiating the pharmacological value of these targets. CONCLUSIONS: The study identified 8 potential drug targets for OP. These prospective targets are believed to have a higher chance of success in clinical trials, thus aiding in prioritizing OP drug development and reducing development costs.

Identification of potential therapeutic targets for skin cutaneous melanoma on the basic of transcriptomics.

BACKGROUND: Advanced skin cutaneous melanoma (SKCM) is responsible for the majority of skin cancer-related deaths. Apart from the rare BRAF V600F mutation, which can be targeted with specific drugs, there are currently no other novel effective therapeutic targets. METHODS: We used SMR analysis with cis-expressed quantitative trait locus (cis-eQTL) as the exposure variable and SKCM as the outcome variable to identify potential therapeutic targets for SKCM. Colocalization assays and HEIDI tests are used to test whether SKCM risk and gene expression are driven by common SNPs. Replication analysis further validated the findings, and we also constructed protein-protein interaction networks to explore the relationship between the identified genes and known SKCM targets. Drug prediction and molecular docking further validated the medicinal value of drug targets. Transcriptome differential analysis further validated that there were differences between normal tissues and SKCM for the selected targets. RESULTS: We identified 13 genes significantly associated with the risk of SKCM, including five protective genes and eight harmful genes. The HEIDI test and co-localization analysis further indicates a causal association between genes (SOX4, MAFF) and SKCM, categorized as Class 1 evidence targets. The remaining 11 genes, except for HELZ2 show a moderately causal association with SKCM, categorized as Class 2 evidence targets. Target druggability predictions from DGIdb suggest that SOX4, MAFF, ACSF3, CDK10, SPG7, and TCF25 are likely to be future drug targets. CONCLUSION: The study provides genetic evidence for targeting available drug genes for the treatment of SKCM.

Navigating the human-monkeypox virus interactome: HuPoxNET atlas reveals functional insights.

Monkeypox virus, a close relative of variola virus, has significantly increased the incidence of monkeypox disease in humans, with several clinical symptoms. The sporadic spread of the disease outbreaks has resulted in the need for a comprehensive understanding of the molecular mechanisms underlying disease infection and potential therapeutic targets. Protein-protein interactions play a crucial role in various cellular processes and regulate different immune signals during virus infection. Computational algorithms have gained high significance in the prediction of potential protein interaction pairs. Here, we developed a comprehensive database called HuPoxNET (https://kaabil.net/hupoxnet/) using the state-of-the-art MERN stack technology. The database leverages two sequence-based computational models to predict strain-specific protein-protein interactions between human and monkeypox virus proteins. Furthermore, various protein annotations of the human and viral proteins such as gene ontology, KEGG pathways, subcellular localization, protein domains, and novel drug targets identified from our study are also available on the database. HuPoxNET is a user-friendly platform for the scientific community to gain more insights into the monkeypox disease infection and aid in the development of therapeutic drugs against the disease.

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.

Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis.

BACKGROUND: Osteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly. METHODS: We designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised. FINDINGS: Seven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P < 3 × 10-4), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P < 3 × 10-4), finger (OR: 0.50, 95% CI: 0.35-0.73, P < 3 × 10-4), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P < 3 × 10-4) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype. INTERPRETATION: Our findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs. FUNDING: This study was funded by the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (2022), the Shanghai Municipal Health Commission Health Industry Clinical Research Project (Grant No. 20224Y0139), Beijing Natural Science Foundation (Grant No. 7244458), and the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20230130).

Chromenone: An emerging scaffold in anti-Alzheimer drug discovery.

Alzheimer's disease (AD) presents a growing global health concern. In recent decades, natural and synthetic chromenone have emerged as promising drug candidates due to their multi-target potential. Natural chromenone, quercetin, scopoletin, esculetin, coumestrol, umbelliferone, bergapten, and methoxsalen (xanthotoxin), and synthetic chromenone hybrids comprising structures like acridine, 4-aminophenyl, 3-arylcoumarins, quinoline, 1,3,4-oxadiazole, 1,2,3-triazole, and tacrine, have been explored for their potential to combat AD. Key reactions used for synthesis of chromenone hybrids include Perkin and Pechmann condensation. The activity of chromenone hybrids has been reported against several drug targets, including AChE, BuChE, BACE-1, and MAO-A/B. This review comprehensively explores natural, semisynthetic, and synthetic chromenone, elucidating their synthetic routes, possible mode of action/drug targets and structure-activity relationships (SAR). The acquired knowledge provides valuable insights for the development of new chromenone hybrids against AD.

Associations between genetically predicted concentrations of plasma proteins and the risk of prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a leading cause of cancer-related death in men. Understanding the proteomic landscape associated with PCa risk can provide insights into its molecular mechanisms and pave the way for potential therapeutic interventions. METHODS: A proteome-wide Mendelian randomization (MR) analysis was employed to determine associations between genetically predicted protein concentrations in plasma and PCa risk. From an initial list of 4,364 proteins, significant associations were identified and validated. Multiple sensitivity analyses were also conducted to enhance the robustness of our findings. RESULTS: Of the 4,364 genetically predicted proteins, 308 exhibited preliminary associations with PCa risk. After rigorous statistical refinement, genetically predicted concentrations of 14 proteins showed positive associations with PCa risk, with odds ratios spanning from 1.55 (95% CI 1.28-1.87) for ATG4B to 2.67 (95% CI 1.94-3.67) for HCN1. In contrast, genetically predicted concentrations of ATG7, B2M, MSMB, and TMEM108 demonstrated inverse associations with PCa. The replication analysis further substantiated positive associations for MDH1 and LSM1, and a negative one for MSMB with PCa. A meta-analysis harmonizing primary and replication data mirrored these findings. Furthermore, the MVMR analysis pinpointed B2M and MSMB as having significant associations with PCa risk. CONCLUSION: The genetic evidence unveils a refined set of proteins associated with PCa risk. The findings underscore the potential of these proteins as molecular markers or therapeutic targets for PCa, calling for deeper mechanistic studies and exploration into their translational relevance.

PTGES2 and RNASET2 identified as novel potential biomarkers and therapeutic targets for basal cell carcinoma: insights from proteome-wide mendelian randomization, colocalization, and MR-PheWAS analyses.

Introduction: Basal cell carcinoma (BCC) is the most common skin cancer, lacking reliable biomarkers or therapeutic targets for effective treatment. Genome-wide association studies (GWAS) can aid in identifying drug targets, repurposing existing drugs, predicting clinical trial side effects, and reclassifying patients in clinical utility. Hence, the present study investigates the association between plasma proteins and skin cancer to identify effective biomarkers and therapeutic targets for BCC. Methods: Proteome-wide mendelian randomization was performed using inverse-variance-weight and Wald Ratio methods, leveraging 1 Mb cis protein quantitative trait loci (cis-pQTLs) in the UK Biobank Pharma Proteomics Project (UKB-PPP) and the deCODE Health Study, to determine the causal relationship between plasma proteins and skin cancer and its subtypes in the FinnGen R10 study and the SAIGE database of Lee lab. Significant association with skin cancer and its subtypes was defined as a false discovery rate (FDR) < 0.05. pQTL to GWAS colocalization analysis was executed using a Bayesian model to evaluate five exclusive hypotheses. Strong colocalization evidence was defined as a posterior probability for shared causal variants (PP.H4) of ≥0.85. Mendelian randomization-Phenome-wide association studies (MR-PheWAS) were used to evaluate potential biomarkers and therapeutic targets for skin cancer and its subtypes within a phenome-wide human disease category. Results: PTGES2, RNASET2, SF3B4, STX8, ENO2, and HS3ST3B1 (besides RNASET2, five other plasma proteins were previously unknown in expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL)) were significantly associated with BCC after FDR correction in the UKB-PPP and deCODE studies. Reverse MR showed no association between BCC and these proteins. PTGES2 and RNASET2 exhibited strong evidence of colocalization with BCC based on a posterior probability PP.H4 >0.92. Furthermore, MR-PheWAS analysis showed that BCC was the most significant phenotype associated with PTGES2 and RNASET2 among 2,408 phenotypes in the FinnGen R10 study. Therefore, PTGES2 and RNASET2 are highlighted as effective biomarkers and therapeutic targets for BCC within the phenome-wide human disease category. Conclusion: The study identifies PTGES2 and RNASET2 plasma proteins as novel, reliable biomarkers and therapeutic targets for BCC, suggesting more effective clinical application strategies for patients.

Pathological mechanisms and novel drug targets in fibrotic interstitial lung disease.

BACKGROUND: Interstitial lung diseases (ILDs) are a diverse group of conditions characterized by inflammation and fibrosis in the lung. In some patients with ILD, a progressive fibrotic phenotype develops, which is associated with an irreversible decline in lung function and a poor prognosis. MAIN BODY: The pathological mechanisms that underlie this process culminate in fibroblast activation, proliferation, and differentiation into myofibroblasts, which deposit extracellular matrix proteins and result in fibrosis. Upstream of fibroblast activation, epithelial cell injury and immune activation are known initiators of fibrosis progression, with multiple diverse cell types involved. Recent years have seen an increase in our understanding of the complex and interrelated processes that drive fibrosis progression in ILD, in part due to the advent of single-cell RNA sequencing technology and integrative multiomics analyses. Novel pathological mechanisms have been identified, which represent new targets for drugs currently in clinical development. These include phosphodiesterase 4 inhibitors and other molecules that act on intracellular cyclic adenosine monophosphate signaling, as well as inhibitors of the autotaxin-lysophosphatidic acid axis and  α v  integrins. Here, we review current knowledge and recent developments regarding the pathological mechanisms that underlie progressive fibrotic ILD, including potential therapeutic targets. CONCLUSION: Knowledge of the pathological mechanisms that drive progressive fibrosis in patients with ILD has expanded, with the role of alveolar endothelial cells, the immune system, and fibroblasts better elucidated. Drugs that target novel mechanisms hold promise for expanding the future therapeutic armamentarium for progressive fibrotic ILD.

Immunoinformatics and Reverse Vaccinology Approach for the Identification of Potential Vaccine Candidates against Vandammella animalimors.

Vandammella animalimorsus is a Gram-negative and non-motile bacterium typically transmitted to humans through direct contact with the saliva of infected animals, primarily through biting, scratches, or licks on fractured skin. The absence of a confirmed post-exposure treatment of V. animalimorsus bacterium highlights the imperative for developing an effective vaccine. We intended to determine potential vaccine candidates and paradigm a chimeric vaccine against V. animalimorsus by accessible public data analysis of the strain by utilizing reverse vaccinology. By subtractive genomics, five outer membranes were prioritized as potential vaccine candidates out of 2590 proteins. Based on the instability index and transmembrane helices, a multidrug transporter protein with locus ID A0A2A2AHJ4 was designated as a potential candidate for vaccine construct. Sixteen immunodominant epitopes were retrieved by utilizing the Immune Epitope Database. The epitope encodes the strong binding affinity, nonallergenic properties, non-toxicity, high antigenicity scores, and high solubility revealing the more appropriate vaccine construct. By utilizing appropriate linkers and adjuvants alongside a suitable adjuvant molecule, the epitopes were integrated into a chimeric vaccine to enhance immunogenicity, successfully eliciting both adaptive and innate immune responses. Moreover, the promising physicochemical features, the binding confirmation of the vaccine to the major innate immune receptor TLR-4, and molecular dynamics simulations of the designed vaccine have revealed the promising potential of the selected candidate. The integration of computational methods and omics data has demonstrated significant advantages in discovering novel vaccine targets and mitigating vaccine failure rates during clinical trials in recent years.

Plausible mechanism of drug resistance and side-effects of COVID-19 therapeutics: a bottleneck for its eradication.

BACKGROUND: COVID-19 pandemic has turned our world upside down by meddling with our normal lives. While there is no definitive drug against SARS-CoV-2, antiviral drugs that are already in the market, are being repurposed against it, could now complete long-term as well as all age-specific investigations, and they are successful in saving millions of lives. Nevertheless, side-effects are emergingly seen in the patients undergoing treatment, and ineffectiveness is increasingly found due to the emerging notorious variants of the virus. Many of them are also facing serious co-infections including black fungus, Zika, and H1N1 virus to name a few. OBJECTIVES: Therefore, this review highlights both drug resistance, their side-effects, and the significance for proper and long-term clinical trials of all age groups including children. METHODS: We have explored and proposed the mechanisms of drug resistance that may arise due to the misuse or overuse of drugs based on available experimental reports. RESULTS: The review provides solutions to the aforesaid issues of drug-resistance and side-effects by providing combination therapies, ancillary treatments, and other preventive strategies that can be useful in preventing drawbacks thereby curbing COVID-19 or similar future infections to maintain our normal lives. CONCLUSION: COVID-19 and its long-term effects, if any, can be eradicated with strategic and mindful use of related therapeutics in a controlled manner.

Exploiting gender-based biomarkers and drug targets: advancing personalized therapeutic strategies in hepatocellular carcinoma.

This review systematically examines gender differences in hepatocellular carcinoma (HCC), identifying the influence of sex hormones, genetic variance, and environmental factors on the disease's epidemiology and treatment outcomes. Recognizing the liver as a sexually dimorphic organ, we highlight how gender-specific risk factors, such as alcohol consumption and obesity, contribute differently to hepatocarcinogenesis in men and women. We explore molecular mechanisms, including the differential expression of androgen and estrogen receptors, which mediate diverse pathways in tumor biology such as cell proliferation, apoptosis, and DNA repair. Our analysis underscores the critical need for gender-specific research in liver cancer, from molecular studies to clinical trials, to improve diagnostic accuracy and therapeutic effectiveness. By incorporating a gender perspective into all facets of liver cancer research, we advocate for a more precise and personalized approach to cancer treatment that acknowledges gender as a significant factor in both the progression of HCC and its response to treatment. This review aims to foster a deeper understanding of the biological and molecular bases of gender differences in HCC and to promote the development of tailored interventions that enhance outcomes for all patients.

Autophagy modulation in cancer therapy: Challenges coexist with opportunities.

Autophagy, a crucial intracellular degradation process facilitated by lysosomes, plays a pivotal role in maintaining cellular homeostasis. The elucidation of autophagy key genes and signaling pathways has significantly advanced our understanding of this process and has led to the exploration of autophagy as a promising therapeutic approach. This review comprehensively assesses the latest developments in small molecule modulators targeting autophagy. Moreover, the review delves into the most recent strategies for drug discovery, specifically focusing on selective agents that exploit autophagosomes and lysosomes for targeted protein degradation. Additionally, this article highlights the prevailing challenges and outlines potential future advancements in the field. By amalgamating the cutting-edge knowledge in the field, we aim to offer valuable insights and references for the anti-cancer drug development of autophagy-targeted therapies, thus contributing to the advancement of novel therapeutic interventions.

TIN-X version 3: update with expanded dataset and modernized architecture for enhanced illumination of understudied targets.

TIN-X (Target Importance and Novelty eXplorer) is an interactive visualization tool for illuminating associations between diseases and potential drug targets and is publicly available at newdrugtargets.org. TIN-X uses natural language processing to identify disease and protein mentions within PubMed content using previously published tools for named entity recognition (NER) of gene/protein and disease names. Target data is obtained from the Target Central Resource Database (TCRD). Two important metrics, novelty and importance, are computed from this data and when plotted as log(importance) vs. log(novelty), aid the user in visually exploring the novelty of drug targets and their associated importance to diseases. TIN-X Version 3.0 has been significantly improved with an expanded dataset, modernized architecture including a REST API, and an improved user interface (UI). The dataset has been expanded to include not only PubMed publication titles and abstracts, but also full-text articles when available. This results in approximately 9-fold more target/disease associations compared to previous versions of TIN-X. Additionally, the TIN-X database containing this expanded dataset is now hosted in the cloud via Amazon RDS. Recent enhancements to the UI focuses on making it more intuitive for users to find diseases or drug targets of interest while providing a new, sortable table-view mode to accompany the existing plot-view mode. UI improvements also help the user browse the associated PubMed publications to explore and understand the basis of TIN-X's predicted association between a specific disease and a target of interest. While implementing these upgrades, computational resources are balanced between the webserver and the user's web browser to achieve adequate performance while accommodating the expanded dataset. Together, these advances aim to extend the duration that users can benefit from TIN-X while providing both an expanded dataset and new features that researchers can use to better illuminate understudied proteins.

Exploring the mechanism of Si-Miao-Yong-An decoction on heart failure based on molecular docking and network pharmacology.

The SwissTargetPrediction was employed to predict the potential drug targets of the active component of Si-Miao-Yong-An decoction (SMYAD). The therapeutic targets for HF were searched in the Genecard database, and Cytoscape3.9.1 software was used to construct the "drug-component-target-disease network" diagram. In addition, the String platform was used to construct Protein-Protein Interaction (PPI) network, and the DAVID database was used for GO and KEGG analysis. AutoDockTools-1.5.6 software was used for molecular docking verification. Network pharmacology studies have shown that AKT 1, ALB, and CASP 3 are the key targets of action of SMYAD against heart failure. The active compounds are quercetin and kaempferol.

An integrated in silico approach for the identification of novel potential drug target and chimeric vaccine against Neisseria meningitides strain 331401 serogroup X by subtractive genomics and reverse vaccinology.

Neisseria meningitidis, commonly known as the meningococcus, leads to substantial illness and death among children and young adults globally, revealing as either epidemic or sporadic meningitis and/or septicemia. In this study, we have designed a novel peptide-based chimeric vaccine candidate against the N. meningitidis strain 331,401 serogroup X. Through rigorous analysis of subtractive genomics, two essential cytoplasmic proteins, namely UPI000012E8E0(UDP-3-O-acyl-GlcNAc deacetylase) and UPI0000ECF4A9(UDP-N-acetylglucosamine acyltransferase) emerged as potential drug targets. Additionally, using reverse vaccinology, the outer membrane protein UPI0001F4D537 (Membrane fusion protein MtrC) identified by subcellular localization and recognized for its known indispensable role in bacterial survival was identified as a novel chimeric vaccine target. Following a careful comparison of MHC-I, MHC-II, T-cell, and B-cell epitopes, three epitopes derived from UPI0001F4D537 were linked with three types of linkers-GGGS, EAAAK, and the essential PADRE-for vaccine construction. This resulted in eight distinct vaccine models (V1-V8). Among them V1 model was selected as the final vaccine construct. It exhibits exceptional immunogenicity, safety, and enhanced antigenicity, with 97.7 % of its residues in the Ramachandran plot's most favored region. Subsequently, the vaccine structure was docked with the TLR4/MD2 complex and six different HLA allele receptors using the HADDOCK server. The docking resulted in the lowest HADDOCK score of 39.3 ± 9.0 for TLR/MD2. Immune stimulation showed a strong immune response, including antibodies creation and the activation of B-cells, T Cytotoxic cells, T Helper cells, Natural Killer cells, and interleukins. Furthermore, the vaccine construct was successfully expressed in the Escherichia coli system by reverse transcription, optimization, and ligation in the pET-28a (+) vector for the expression study. The current study proposes V1 construct has the potential to elicit both cellular and humoral responses, crucial for the developing an epitope-based vaccine against N. meningitidis strain 331,401 serogroup X.

Action and therapeutic targets of myosin light chain kinase, an important cardiovascular signaling mechanism.

The global incidence of cardiac diseases is increasing, imposing a substantial socioeconomic burden on healthcare systems. The pathogenesis of cardiovascular disease is complex and not fully understood, and the physiological function of the heart is inextricably linked to well-regulated cardiac muscle movement. Myosin light chain kinase (MLCK) is essential for myocardial contraction and diastole, cardiac electrophysiological homeostasis, vasoconstriction of vascular nerves and blood pressure regulation. In this sense, MLCK appears to be an attractive therapeutic target for cardiac diseases. MLCK participates in myocardial cell movement and migration through diverse pathways, including regulation of calcium homeostasis, activation of myosin light chain phosphorylation, and stimulation of vascular smooth muscle cell contraction or relaxation. Recently, phosphorylation of myosin light chains has been shown to be closely associated with the activation of myocardial exercise signaling, and MLCK mediates systolic and diastolic functions of the heart through the interaction of myosin thick filaments and actin thin filaments. It works by upholding the integrity of the cytoskeleton, modifying the conformation of the myosin head, and modulating innervation. MLCK governs vasoconstriction and diastolic function and is associated with the activation of adrenergic and sympathetic nervous systems, extracellular transport, endothelial permeability, and the regulation of nitric oxide and angiotensin II. Additionally, MLCK plays a crucial role in the process of cardiac aging. Multiple natural products/phytochemicals and chemical compounds, such as quercetin, cyclosporin, and ML-7 hydrochloride, have been shown to regulate cardiomyocyte MLCK. The MLCK-modifying capacity of these compounds should be considered in designing novel therapeutic agents. This review summarizes the mechanism of action of MLCK in the cardiovascular system and the therapeutic potential of reported chemical compounds in cardiac diseases by modifying MLCK processes.

Identifying therapeutic targets for breast cancer: insights from systematic Mendelian randomization analysis.

Background: Breast cancer (BC) exhibits a high incidence rate, imposing a substantial burden on healthcare systems. Novel drug targets are urgently needed for BC. Mendelian randomization (MR) has gained widespread application for identifying fresh therapeutic targets. Our endeavor was to pinpoint circulatory proteins causally linked to BC risk and proffer potential treatment targets for BC. Methods: Through amalgamating protein quantitative trait loci from 2,004 circulating proteins and comprehensive genome-wide association study data from the Breast Cancer Association Consortium, we conducted MR analyses. Employing Steiger filtering, bidirectional MR, Bayesian colocalization, phenotype scanning, and replication analyses, we further solidified MR study outcomes. Additionally, protein-protein interaction (PPI) network was harnessed to unveil latent associations between proteins and prevailing breast cancer medications. The phenome-wide MR (Phe-MR) was employed to assess potential side effects and indications for the druggable proteins of BC. Finally, we further affirmed the drugability of potential drug targets through mRNA expression analysis and molecular docking. Results: Through comprehensive analysis, we identified five potential drug targets, comprising four (TLR1, A4GALT, SNUPN, and CTSF) for BC and one (TLR1) for BC_estrogen receptor positive. None of these five potential drug targets displayed reverse causation. Bayesian colocalization suggested that these five latent drug targets shared variability with breast cancer. All drug targets were replicated within the deCODE cohort. TLR1 exhibited PPI with current breast cancer therapeutic targets. Furthermore, Phe-MR unveiled certain adverse effects solely for TLR1 and SNUPN. Conclusion: Our study uncovers five prospective drug targets for BC and its subtypes, warranting further clinical exploration.