Investigating mechanistic insights of curcumin in blocking the Interleukin-8 signaling pathway associated with Breast Cancer: An in-silico approach.

Interleukin-8 (IL-8) is a chemokine, a type of signaling molecule that has a role in immunological responses and inflammation. In recent years, IL-8 is additionally related to cancer growth and recurrence. Breast cancer growth, progression, and metastatic development are all linked to IL-8. Breast cancer cells are known to develop faster when IL-8 stimulates their proliferation and survival. It can also cause angiogenesis, or the creation of new blood vessels, which is necessary for tumor nutrition and growth. IL-8 and curcumin have been subjects of interest in drug design, particularly in the context of inflammation-related disorders and cancer. This study aims to give an overview of the role of IL-8. Inhibitor-based treatment approaches were being used to target IL-8 with curcumin. Molecular docking method was employed to find a potential interaction to supress competitive inhibition of IL-8 with curcumin. PASS analysis and ADMET characteristics were also being carried out. In the end, IL-8 complexed with curcumin is chosen for MD simulations. Overall, our results showed that during the simulation, the complex stayed comparatively stable. It is also possible to investigate curcumin further as a possible treatment option. The combined results imply that IL-8 and their genetic alterations can be studied in precision cancer therapeutic treatments, utilizing target-driven therapy and early diagnosis.

Varicella-zoster virus-related neurological complications: From infection to immunomodulatory therapies.

The Varicella-zoster virus (VZV), classified as a neurotropic member of the Herpesviridae family, exhibits a characteristic pathogenicity, predominantly inducing varicella, commonly known as chickenpox, during the initial infectious phase, and triggering the reactivation of herpes zoster, more commonly recognized as shingles, following its emergence from a latent state. The pathogenesis of VZV-associated neuroinflammation involves a complex interplay between viral replication within sensory ganglia and immune-mediated responses that contribute to tissue damage and dysfunction. Upon primary infection, VZV gains access to sensory ganglia, establishing latent infection within neurons. During reactivation, the virus can spread along sensory nerves, triggering a cascade of inflammatory mediators, chemokines, and immune cell infiltration in the affected neural tissues. The role of both adaptive and innate immune reactions, including the contributions of T and B cells, macrophages, and dendritic cells, in orchestrating the immune-mediated damage in the central nervous system is elucidated. Furthermore, the aberrant activation of the natural defence mechanism, characterised by the dysregulated production of immunomodulatory proteins and chemokines, has been implicated in the pathogenesis of VZV-induced neurological disorders, such as encephalitis, myelitis, and vasculopathy. The intricate balance between protective and detrimental immune responses in the context of VZV infection emphasises the necessity for an exhaustive comprehension of the immunopathogenic mechanisms propelling neuroinflammatory processes. Despite the availability of vaccines and antiviral therapies, VZV-related neurological complications remain a significant concern, particularly in immunocompromised individuals and the elderly. Elucidating these mechanisms might facilitate the emergence of innovative immunomodulatory strategies and targeted therapies aimed at mitigating VZV-induced neuroinflammatory damage and improving clinical outcomes. This comprehensive understanding enhances our grasp of viral pathogenesis and holds promise for pioneering therapeutic strategies designed to mitigate the neurological ramifications of VZV infections.

Harnessing machine learning potential for personalised drug design and overcoming drug resistance.

Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing complex datasets, identifying patterns, and predicting treatment outcomes. Leveraging diverse data sources such as genomic profiles, clinical records, and drug response assays, ML uncovers molecular mechanisms of drug resistance, enabling personalised treatment, maximising efficacy and minimising adverse effects. Various ML algorithms contribute to the drug discovery process - Random Forest and Decision Trees predict drug-target interactions and aid in virtual screening, and SVM classify leads on bioactivity data. Neural Networks model QSAR to optimise lead compounds and K-means clustering group compounds with similar chemical properties aiding compound selection. Gaussian Processes predict drug responses, Bayesian Networks infer causal relationships, Autoencoders generate novel compounds, and Genetic Algorithms optimise molecular structures. These algorithms collectively enhance efficiency and success rates in drug design endeavours, from lead identification to optimisation and are cost-effective, empowering clinicians with real-time treatment monitoring and improving patient outcomes. This review highlights the immense potential of ML in revolutionising cancer care through effective drug design to reduce drug resistance, and we have also discussed various limitations and research gaps to understand better.

Molecular expression, purification and structural characterization of recombinant L-Glutaminase from Streptomyces roseolus.

The present research reports the anti-cancer potential of recombinant L-Glutaminase from Streptomyces roseolus. L-Glutaminase gene was synthesized by codon-optimization, cloned and successfully expressed in E. coli BL21 (DE3). Affinity purified recombinant L-Glutaminase revealed a molecular mass of 32 kDa. Purified recombinant L-Glutaminase revealed stability at pH 7.0-8.0 with optimum activity at 70 °C further indicating its thermostable nature based on thermodynamic characterization. Recombinant L-Glutaminase exhibited profound stability in the presence of several biochemical parameters and demonstrated its metalloenzyme nature and was also found to be highly specific towards favorable substrate (l-Glutamine) based on kinetics. It demonstrated antioxidant property and pronounced cytotoxic effect against breast cancer (MCF-7 cell lines) in a dose dependent behavior with IC50 of 40.68 µg/mL. Matrix-assisted laser desorption ionization-time of flight-mass spectroscopy (MALDI-TOF-MS) analysis of desired mass peaks ascertained the recombinant L-Glutaminase identity. N-terminal amino acid sequence characterization through Edman degradation revealed highest resemblance for L-glutaminase within the Streptomyces sp. family. The purified protein was characterized structurally and functionally by employing spectroscopic methods like Raman, circular dichroism and nuclear magnetic resonance. The thermostability was assessed by thermogravimetric analysis. The outcomes of the study, suggests the promising application of recombinant L-Glutaminase as targeted therapeutic candidate for breast cancer.

Green synthesized silver nanoparticles of Terminalia bellirica leaves extract: synthesis, characterization, in-silico studies, and antimalarial activity.

Malaria is a mosquito-borne infectious disease that is caused by the Plasmodium parasite. Most of the available medication are losing their efficacy. Therefore, it is crucial to create fresh leads to combat malaria. Green silver nanoparticles (AgNPs) have recently attracted a lot of attention in biomedical research. As a result, green mediated AgNPs from leaves of Terminalia bellirica, a medicinal plant with purported antimalarial effects, were used in this investigation. Initially, cysteine-rich proteins from Plasmodium species were studied in silico as potential therapeutic targets. With docking scores between -9.93 and -11.25 kcal/mol, four leaf constituents of Terminalia bellirica were identified. The green mediated silver nanoparticles were afterward produced using leaf extract and were further examined using UV-vis spectrophotometer, DLS, Zeta potential, FTIR, XRD, and FESEM. The size of synthesized TBL-AgNPs was validated by the FESEM results; the average size of TBL-AgNPs was around 44.05 nm. The zeta potential study also supported green mediated AgNPs stability. Additionally, Plasmodium falciparum (3D7) cultures were used to assess the antimalarial efficacy, and green mediated AgNPs could effectively inhibit the parasitized red blood cells (pRBCs). In conclusion, this novel class of AgNPs may be used as a potential therapeutic replacement for the treatment of malaria.

Chlordiazepoxide against signalling, receptor and regulatory proteins of breast cancer: a structure-based in-silico approach.

Among the most prevalent forms of cancer are breast, lung, colon-rectum, and prostate cancers, and breast cancer is a major global health challenge, contributing to 2.26 million cases with approximately 685,000 deaths worldwide in 2020 alone, typically beginning in the milk ducts or lobules that produce and transport milk during lactation and it is becoming challenging to treat as the tissues are developing resistance, which makes urgent calls for new multitargeted drugs. The multitargeted drug design provides a better solution, simultaneously targeting multiple pathways, even when the drug resists one, it remains effective for others. In this study, we included four crucial proteins that perform signalling, receptor, and regulatory action, namely- NUDIX Hydrolases, Dihydrofolate Reductase, HER2/neu Kinase and EGFR and performed multitargeted molecular docking studies against human-approved drugs using HTVS, SP and extra precise algorithms and filtered the poses with MM\GBSA, suggested a benzodiazepine derivative chlordiazepoxide, used as an anxiolytic agent, can be a multitargeted inhibitor with docking and MM\GBSA score ranging from - 4.628 to - 7.877 and - 18.59 to - 135.86 kcal/mol, respectively, and the most interacted residues were 6ARG, 6GLU, 3TRP, and 3VAL. The QikProp-based ADMET and DFT computations showed the suitability and stability of the drug candidate followed by 100 ns MD simulation in water and MMGBSA on trajectories, resulting in stable performance and many intermolecular interactions to make the complexes stable, which favours that chlordiazepoxide can be a multitargeted breast cancer inhibitor. However, experimental validation is needed before its use.

Detection of human platelets antigen polymorphism (HPA-1 and HPA-3) and human factor XIII mutation in Sudanese women with recurrent pregnancy loss.

BACKGROUND: Recurrent pregnancy Loss (RPL) is common problem affecting many couples. A certain genetic variants link to increase the danger of this condition particularly HPA-1, HPA-3 and Human Factor XIII Val34Leu Mutation. The present study aims to find an association between RPL and the Factor XIII Val34Leu polymorphism, as well as HPA-1 and HPA-3 in Sudanese women with RPL. METHODS: This case-control study conducted between June 2022 and December 2022 included 216 women, with 103 cases having minimum three abortions in the past, and 113 healthy controls with at least two full-term births and no abortion history. DNA was isolated from whole blood and the status of three genetic polymorphisms (HPA-1, HPA-3, and factor XIII) was done using a polymerase chain reaction (PCR). Data was analysed using the SPSS version 24 software. RESULTS: The A/A genotype was found to be more prevalent in cases (79.6%) and controls (96.5%) regarding HPA-1. A significant difference was observed in overall allele frequency for B allele (97.0%) and expected frequency of A allele was (81.1%) using the Hardy-Weinberg distribution (p < 0.001). The genotype A/A was most common in these patients (90.3%) and controls (100%), while B/B genotype was only (9.7%) in patients regarding HPA-3. Furthermore, the frequency of Val/Val genotype was higher in cases (88.3%) as compared with controls (90.3%). The risk of RPL in patients was nearly the same in Val/Leu individuals and controls group but all these differences were not statistically significant (p > 0.05). CONCLUSION: Our results indicate a link between Human Platelet Antigen-1 (HPA-1), Human Platelet Antigen-3 (HPA-3) and Factor XIII gene polymorphism with RPL.

Mitoxantrone 2HCl's adroit activity against cervical cancer replication and maintenance proteins: a multitargeted approach.

Cervical cancer poses a significant global health challenge, ranking as the fourth most common cancer among women worldwide and resulting in approximately 300,000 deaths yearly, predominantly caused by high-risk human papillomavirus strains (HPV), mainly types 16 and 18. The scenario poses the urgent need of the hour to develop effective treatment strategies that can address the complexity of cervical cancer and multitargeted inhibitor designing that holds promise as it can simultaneously target multiple proteins and pathways involved in its progression and have the potential to enhance treatment efficacy, reduce the likelihood of drug resistance. In this study, we have performed multitargeted molecular docking of FDA-approved drugs against cervical cancer replication and maintenance proteins- Xenopus kinesin-like protein-2 (3KND), cell division cycle protein-20 (4N14), MCM2-histone complex (4UUZ) and MCM6 Minichromosome maintenance (2KLQ) with HTVS, SP and XP algorithms and have obtained the docking and MM\GBSA score ranging from -8.492 to -5.189 Kcal/mol and -58.16 to -39.07 Kcal/mol. Further, the molecular interaction fingerprints identified ALA, THR, SER, ASN, LEU, and ILE were among the most interacted residues, leaning towards hydrophobic and polar amino acids. The pharmacokinetics and DFT of the compound have shown promising results. The complexes were simulated for 100 ns to study the stability by computing the deviation, fluctuations, and intermolecular interactions formed during the simulation. This study produced promising results, satisfying the criteria that Mitoxantrone 2HCl can be a multitargeted inhibitor against cervical cancer proteins-however, experimental validation is a must before human use.Communicated by Ramaswamy H. Sarma.

Sakuranetin ameliorates streptozotocin-induced diabetes in rodents by inhibiting caspase-3 activity, modulating hematological parameters, and suppressing inflammatory cytokines: a molecular docking and dynamics study.

Diabetes affects people of all ages, regardless of gender and background. To date, there is no evidence for the effect of sakuranetin against the streptozotocin (STZ)-induced diabetes paradigm. The research was directed to evaluate the antidiabetic activity of sakuranetin in the STZ model invoking the diabetes-induced disease paradigm. STZ (I.P. 60 mg/kg) is directed to induce type 2 diabetes in experimental rats. Recent research pursued to regulate the anti-diabetic ability of sakuranetin at both 10 and 20 mg/kg in STZ-induced rats. Furthermore, molecular docking research was implemented to evaluate sakuranetin requisite attraction to inflammatory indicators. Various anti-diabetic [(glucose, hemoglobin A1c (HbA1c), and insulin)], lipid profile [triglycerides (TG), total cholesterol (TC), and high-density lipoproteins (HDL)], hematological parameters [Hemoglobin (HGB), packed cell volume (PCV), red blood cells (RBC), mean corpuscular volume (MCV), platelet (PLT), and white blood cells (WBC), pro-inflammatory cytokines [tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), and interleukin-6 (IL-6)], antioxidant level [catalase (CAT), superoxide dismutase (SOD), glutathione (GSH)], lipid oxidation, and caspase-3 were evaluated. Furthermore, molecular docking and dynamics were performed for TNF-α (2AZ5), IL-6 (1ALU), IL-1ß (6Y8M), Caspase-3 (1NME) and serum insulin (4IBM) target ligands. Sakuranetin treatment at both doses restored the biochemical parameters i.e. blood glucose, insulin, HbA1c, lipid profile, hematological parameters, pro-inflammatory markers, antioxidant levels, lipid oxidation, and caspase-3 in the context of diabetic rats. It also showed favorable binding affinity on inflammatory markers. Sakuranetin binds to proteins 2AZ5, 1ALU, 6Y8M, 1NME, and 4IBM at -7.489, -6.381, -6.742, -7.202, and -8.166 Kcal/mol, respectively. All of the findings from the molecular dynamics simulations points toward a considerable change in the conformational dynamics of protein upon binding with sakuranetin. The potential use of sakuranetin as an alternative diabetes medication will aid future research as a potent anti-diabetic agent.Communicated by Ramaswamy H. Sarma.

Structure-based investigation of pyruvate dehydrogenase kinase-3 inhibitory potential of thymoquinone, targeting lung cancer therapy.

Protein kinases are an attractive therapeutic target for cardiovascular, cancer and neurodegenerative diseases. Cancer cells demand energy generation through aerobic glycolysis, surpassing "oxidative phosphorylation" (OXPHOS) in mitochondria. The pyruvate dehydrogenase kinases (PDKs) have many regulatory roles in energy generation balance by controlling the pyruvate dehydrogenase complex. Overexpression of PDKs is associated with the overall survival of cancer. PDK3, an isoform of PDK is highly expressed in various cancer types, is targeted for inhibition in this study. PDK3 has been shown to binds strongly with a natural compound, thymoquinone (TQ), which is known to exhibit anti-cancer potential. Detailed interaction between the PDK3 and TQ was carried out using spectroscopic and docking methods. The overall changes in the protein's structures after TQ binding were estimated by UV-Vis spectroscopy, circular dichroism and fluorescence binding studies. The kinase activity assay was also carried out to see the kinase inhibitory potential of TQ. The enzyme inhibition assay suggested an excellent inhibitory potential of TQ towards PDK3 (IC50 = 5.49 µM). We observed that TQ forms a stable complex with PDK3 without altering its structure and can be a potent PDK3 inhibitor which may be implicated in cancer therapy after desired clinical validation.

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins.

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host-virus protein-protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection. Objective: This study aims to identify therapeutic target proteins in humans that could act as virus-host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors. Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 ("hCoV-2"), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient's mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein. Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein. Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention.

An immunoinformatics and structural vaccinology approach to design a novel and potent multi-epitope base vaccine targeting Zika virus.

Zika virus is an infectious virus, that belongs to Flaviviridae family, which is transferred to humans through mosquito vectors and severely threatens human health; but, apart from available resources, no effective and secure vaccine is present against Zika virus, to prevent such infections. In current study, we employed structural vaccinology approach to design an epitope-based vaccine against Zika virus, which is biocompatible, and secure and might trigger an adaptive and innate immune response by using computational approaches. We first retrieved the protein sequence from National Center for Biotechnology Information (NCBI) database and carried out for BLAST P. After BLAST P, predicted protein sequences were shortlisted and checked for allergic features and antigenic properties. Final sequence of Zika virus, with accession number (APO40588.1) was selected based on high antigenic score and non-allergenicity. Final protein sequence used various computational approaches including antigenicity testing, toxicity evaluation, allergenicity, and conservancy assessment to identify superior B-cell and T-cell epitopes. Two B-cell epitopes, five MHC-six MHC-II epitopes and I were used to construct an immunogenic multi-epitope-based vaccine by using suitable linkers. A 50S ribosomal protein was added at N terminal to improve the immunogenicity of vaccine. In molecular docking, strong interactions were presented between constructed vaccine and Toll-like receptor 9 (- 1100.6 kcal/mol), suggesting their possible relevance in the immunological response to vaccine. The molecular dynamics simulations ensure the dynamic and structural stability of constructed vaccine. The results of C-immune simulation revealed that constructed vaccine activate B and T lymphocytes which induce high level of antibodies and cytokines to combat Zika infection. The constructed vaccine is an effective biomarker with non-sensitization, nontoxicity; nonallergic, good immunogenicity, and antigenicity, however, experimental assays are required to verify the results of present study.

Fenpropathrin provoked kidney damage via controlling the NLRP3/Caspase-1/GSDMD-mediated pyroptosis: The palliative role of curcumin-loaded chitosan nanoparticles.

This study assessed the ability of formulated curcumin-loaded chitosan nanoparticles (CU-CS-NPs) to reduce the kidney damage resulting from fenpropathrin (FPN) in rats compared to curcumin (CU) in rats. Sixty male Sprague Dawley rats were separated into six groups and orally administered 1 mL/kg b.wt corn oil, 50 mg CU/kg b.wt, 50 mg CU-CS-NPs /kg b.wt., 15 mg FPN /kg b.wt, CU+ FPN or CU-CS-NPs + FPN for 60 days. Then, serum renal damage products were assessed. Total antioxidant capacity, reactive oxygen species, interleukin 1ß (IL-1ß), malondialdehyde, NF-κB P65, cleaved-Caspase-1, and Caspase-8 were estimated in kidney homogenates. The cleaved Caspase-3 and TNF-α immunoexpression and pyroptosis-related genes were determined in renal tissues. The results showed that CU-CS-NPS significantly repressed the FPN-induced increment in kidney damage products (urea, uric acid, and creatinine). Moreover, the FPN-associated hypo-proteinemia, renal oxidative stress and apoptotic reactions, and impaired renal histology were considerably repaired by CU and CU-CS-NPs. Additionally, compared to FPN-exposed rats, CU, and CU-CS-NPs-treated rats had considerably lower immunoexpression of cleaved Caspase-3 and TNF-α in renal tissue. The pyroptosis-related genes NLRP3, GSDMD, IL-18, Caspase-3, Caspase-1, IL-1ß, Caspase-8, TNF-α, and NF-κB dramatically upregulated by FPN exposure in the renal tissues. Yet, in CU and CU-CS-NPs-treated rats, the gene above expression deviations were corrected. Notably, CU-CS-NPs were superior to CU in preventing oxidative damage and inflammation and regulating pyroptosis in the renal tissues of the FPN-exposed group. The results of the present study conclusively showed the superior favorable effect of CU-CS-NPs in counteracting renal impairment linked to environmental pollutants.

Exploring the promising potential of noscapine for cancer and neurodegenerative disease therapy through inhibition of integrin-linked kinase-1.

Integrin-linked kinase (ILK), a ß1-integrin cytoplasmic domain interacting protein, supports multi-protein complex formation. ILK-1 is involved in neurodegenerative diseases by promoting neuro-inflammation. On the other hand, its overexpression induces epithelial-mesenchymal transition (EMT), which is a major hallmark of cancer and activates various factors associated with a tumorigenic phenotype. Thus, ILK-1 is considered as an attractive therapeutic target. We investigated the binding affinity and ILK-1 inhibitory potential of noscapine (NP) using spectroscopic and docking approaches followed by enzyme inhibition activity. A strong binding affinity of NP was measured for the ILK-1 with estimated Ksv (M-1) values of 1.9 × 105, 3.6 × 105, and 4.0 × 105 and ∆G0 values (kcal/mol) -6.19554, -7.8557 and -8.51976 at 298 K, 303 K, and 305 K, respectively. NP binds to ILK-1 with a docking score of -6.6 kcal/mol and forms strong interactions with active-site pocket residues (Lys220, Arg323, and Asp339). The binding constant for the interaction of NP to ILK-1 was 1.04 × 105 M-1, suggesting strong affinity and excellent ILK-1 inhibitory potential (IC50 of ∼5.23µM). Conformational dynamics of ILK-1 were also studied in the presence of NP. We propose that NP presumably inhibits ILK-1-mediated phosphorylation of various downstream signalling pathways that are involved in cancer cell survival and neuroinflammation.

Delineated 3-1-BenCarMethInYlPro-Phosphonic Acid's Adroit Activity against Lung Cancer through Multitargeted Docking, MM\GBSA, QM-DFT and Multiscale Simulations.

Lung cancer is a pervasive and challenging disease with limited treatment options, with global health challenges often present with complex molecular profiles necessitating the exploration of innovative therapeutic strategies. Single-target drugs have shown limited success due to the heterogeneity of this disease. Multitargeted drug designing is imperative to combat this complexity by simultaneously targeting multiple target proteins and pathways, which can enhance treatment efficacy and overcome resistance by addressing the dynamic nature of the disease and stopping tumour growth and spread. In this study, we performed the molecular docking studies of Drug Bank compounds with a multitargeted approach against crucial proteins of lung cancer such as heat shock protein 5 (BIP/GRP78) ATPase, myosin 9B RhoGAP, EYA2 phosphatase inhibitor, RSK4 N-terminal kinase, and collapsin response mediator protein-1 (CRMP-1) using HTVS, SP with XP algorithms, and poses were filtered using MM\GBSA which identified [3-(1-Benzyl-3-Carbamoylmethyl-2-Methyl-1h-Indol-5-Yloxy)-Propyl-]-Phosphonic Acid (3-1-BenCarMethIn YlPro-Phosphonic Acid) (DB02504) as multitargeted drug candidate with docking and MM\GBSA score ranges from -5.83 to -10.66 and -7.56 to -50.14 Kcal/mol, respectively. Further, the pharmacokinetic and QM-based DFT studies have shown complete acceptance results, and interaction fingerprinting reveals that ILE, GLY, VAL, TYR, LEU, and GLN were among the most interacting residues. The 100 ns MD simulation in the SPC water model with NPT ensemble showed stable performance with deviation and fluctuations <2 Å with huge interactions, making it a promising multitargeted drug candidate; however, experimental studies are needed before use.

From diagnosis to therapy: The transformative role of lncRNAs in eye cancer management.

The genomic era has brought about a transformative shift in our comprehension of cancer, unveiling the intricate molecular landscape underlying disease development. Eye cancers (ECs), encompassing diverse malignancies affecting ocular tissues, pose distinctive challenges in diagnosis and management. Long non-coding RNAs (lncRNAs), an emerging category of non-coding RNAs, are pivotal actors in the genomic intricacies of eye cancers. LncRNAs have garnered recognition for their multifaceted roles in gene expression regulation and influence on many cellular processes. Many studies support that the lncRNAs have a role in developing various cancers. Recent investigations have pinpointed specific lncRNAs associated with ECs, including retinoblastoma and uveal melanoma. These lncRNAs exert control over critical pathways governing tumor initiation, progression, and metastasis, endowing them with the ability to function as evaluation, predictive, and therapeutic indicators. The article aims to synthesize the existing information concerning the functions of lncRNAs in ECs, elucidating their regulatory mechanisms and clinical significance. By delving into the lncRNAs' expanding relevance in the modulation of oncogenic and tumor-suppressive networks, we gain a deeper understanding of the molecular complexities intrinsic to these diseases. In our exploration of the genomic intricacies of ECs, lncRNAs introduce a fresh perspective, providing an opportunity to function as clinical and therapeutic indicators, and they also have therapeutic benefits that show promise for advancing the treatment of ECs. This comprehensive review bridges the intricate relationship between lncRNAs and ECs within the context of the genomic era.

Bridging autoimmunity and epigenetics: The influence of lncRNA MALAT1.

Autoimmune disorders represent a heterogeneous spectrum of conditions defined by an immune system's atypical reactivity against endogenous constituents. In the complex anatomy of autoimmune pathogenesis, lncRNAs have appeared as pivotal arbiters orchestrating the mechanisms of ailment initiation, immune cascades, and transcriptional modulation. One such lncRNA, MALAT1, has garnered attention for its potential association with the aetiology of several autoimmune diseases. MALAT1 has been shown to influence a wide spectrum of cellular processes, which include cell multiplication and specialization, as well as apoptosis and inflammation. In autoimmune diseases, MALAT1 exhibits both disease-specific and shared patterns of dysregulation, often correlating with disease severity. The molecular mechanisms underlying MALAT1's impact on autoimmune disorders include epigenetic modifications, alternative splicing, and modulation of gene expression networks. Additionally, MALAT1's intricate interactions with microRNAs, other lncRNAs, and protein-coding genes further underscore its role in immune regulation and autoimmune disease progression. Understanding the contribution of MALAT1 in autoimmune pathogenesis across different diseases could offer valuable insights into shared pathways, thereby clearing a path for the creation of innovative and enhanced therapeutic approaches to address these complex disorders. This review aims to elucidate the complex role of MALAT1 in autoimmune disorders, encompassing rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease (Crohn's disease and ulcerative colitis), type 1 diabetes, systemic lupus erythematosus, and psoriasis. Furthermore, it discusses the potential of MALAT1 as a diagnostic biomarker, therapeutic target, and prognostic indicator.

Identification of potential inhibitors of tropomyosin receptor kinase B targeting CNS-related disorders and cancers.

Tropomyosin receptor kinase B (TrkB), also known as neurotrophic tyrosine kinase receptor type 2 (NTRK2), is a protein that belongs to the family of receptor tyrosine kinases (RTKs). NTRK2 plays a crucial role in regulating the development and maturation of the central nervous system (CNS) and peripheral nervous system (PNS). Elevated TrkB expression levels observed in different pathological conditions make it a potential target for therapeutic interventions against neurological disorders, including depression, anxiety, Alzheimer's disease, Parkinson's disease, and certain types of cancer. Targeting TrkB using small molecule inhibitors is a promising strategy for the treatment of a variety of neurological disorders. In this research, a systematic virtual screening was carried out on phytoconstituents found in the IMPPAT library to identify compounds potentially inhibiting TrkB. The retrieved compounds from the IMPPAT library were first filtered using Lipinski's rule of five. The compounds were then sorted based on their docking score and ligand efficiency. In addition, PAINS, ADMET, and PASS evaluations were carried out for selecting drug-like compounds. Finally, in interaction analysis, we found two phytoconstituents, Wedelolactone and 3,8-dihydroxy-1-methylanthraquinone-2-carboxylic acid (DMCA), which possessed considerable docking scores and specificity on the TrkB ATP-binding pocket. The selected compounds were further assessed employing molecular dynamics (MD) simulations and essential dynamics. The results revealed that the elucidated compounds bind well with the TrkB binding pocket and lead to fewer conformations fluctuations. This study highlighted using phytoconstituents, Wedelolactone and DMCA as starting leads in developing novel TrkB inhibitors.Communicated by Ramaswamy H. Sarma.

PVT1 lncRNA in lung cancer: A key player in tumorigenesis and therapeutic opportunities.

The lncRNA PVT1 has emerged as a pivotal component in the intricate landscape of cancer pathogenesis, particularly in lung cancer. PVT1, situated in the 8q24 chromosomal region, has garnered attention for its aberrant expression patterns in lung cancer, correlating with tumor progression, metastasis, and poor prognosis. Numerous studies have unveiled the diverse mechanisms PVT1 contributes to lung cancer pathogenesis. It modulates critical pathways, such as cell proliferation, apoptosis evasion, angiogenesis, and epithelial-mesenchymal transition. PVT1's interactions with other molecules, including microRNAs and proteins, amplify its oncogenic influence. Recent advancements in genomic and epigenetic analyses have also illuminated the intricate regulatory networks that govern PVT1 expression. Understanding PVT1's complex involvement in lung cancer holds substantial clinical implications. Targeting PVT1 presents a promising avenue for developing novel diagnostic biomarkers and therapeutic interventions. This abstract encapsulates the expanding knowledge regarding the oncogenic role of PVT1 in lung cancer, underscoring the significance of further research to unravel its complete mechanistic landscape and exploit its potential for improved patient outcomes.

The emerging role of noncoding RNAs in the EGFR signaling pathway in lung cancer.

Noncoding ribonucleic acids (ncRNAs) have surfaced as essential orchestrators within the intricate system of neoplastic biology. Specifically, the epidermal growth factor receptor (EGFR) signalling cascade shows a central role in the etiological underpinnings of pulmonary carcinoma. Pulmonary malignancy persists as a preeminent contributor to worldwide mortality attributable to malignant neoplasms, with non-small cell lung carcinoma (NSCLC) emerging as the most predominant histopathological subcategory. EGFR is a key driver of NSCLC, and its dysregulation is frequently associated with tumorigenesis, metastasis, and resistance to therapy. Over the past decade, researchers have unveiled a complex network of ncRNAs, encompassing microRNAs, long noncoding RNAs, and circular RNAs, which intricately regulate EGFR signalling. MicroRNAs, as versatile post-transcriptional regulators, have been shown to target various components of the EGFR pathway, influencing cancer cell proliferation, migration, and apoptosis. Additionally, ncRNAs have emerged as critical modulators of EGFR signalling, with their potential to act as scaffolds, decoys, or guides for EGFR-related proteins. Circular RNAs, a relatively recent addition to the ncRNA family, have also been implicated in EGFR signalling regulation. The clinical implications of ncRNAs in EGFR-driven lung cancer are substantial. These molecules exhibit diagnostic potential as robust biomarkers for early cancer detection and personalized treatment. Furthermore, their predictive value extends to predicting disease progression and therapeutic outcomes. Targeting ncRNAs in the EGFR pathway represents a novel therapeutic approach with promising results in preclinical and early clinical studies. This review explores the increasing evidence supporting the significant role of ncRNAs in modulating EGFR signalling in lung cancer, shedding light on their potential diagnostic, prognostic, and therapeutic implications.