Exploring natural compound, Panicutine as leucine-rich repeat kinase 2 inhibitor against Parkinson's disease: a structure-guided approach.

Leucine-rich repeat kinase 2 (LRRK2) is a promising drug target for the therapeutic management of Parkinson's disease (PD) and other neurodegenerative disorders. LRRK2 inhibitors have the potential to modulate neuroinflammation, reduce alpha-synuclein aggregation and improve motor symptoms in PD patients. Although LRRK2 inhibitors are still in the early stages of clinical development, the identification of potent and selective inhibitors through structure-guided approaches provides a promising avenue for the development of effective therapies for PD and other neurodegenerative disorders. In this study, natural compounds from the IMPPAT database were screened using a state-of-the-art computational virtual screening approach to identify potential inhibitors of LRRK2. We carried out a docking screening on a library of natural compounds and identified a few compounds with strong binding affinity, docking score and specificity towards LRRK2 as the top hits. These hits were then subjected to further analysis based on multiple parameters for the Pan-assay interference compounds and their physicochemical and pharmacokinetics evaluation followed by a detailed interaction analysis. After careful evaluation, one natural compound, Panicutine, was identified as a promising candidate for LRRK2 due to its significant affinity and specificity towards the LRRK2 binding pocket. Additionally, it exhibited drug-like properties with blood-brain barrier permeability as determined by ADMET properties. To gain a deeper understanding of the stability and conformational changes of the LRRK2-ligand complex, MD simulations were conducted for 100 nanoseconds under explicit solvent conditions followed by principal component analysis and free energy dynamics. The simulation results demonstrated that the LRRK2-Panicutine complex remained stable throughout the simulation trajectories. Based on these findings, it is concluded that Panicutine has the potential to act as a LRRK2 inhibitor against PD and other neurodegenerative disorders.Communicated by Ramaswamy H. Sarma.

Phytochemicals as potential inhibitors of interleukin-8 for anticancer therapy: in silico evaluation and molecular dynamics analysis.

Within the realm of soluble factors that have emerged as potential targets for therapeutic intervention, the chemokine interleukin-8 (IL-8) has garnered attention as a potential contributor to treatment responses in various cancer types. The utilization of naturally occurring anticancer compounds for treating cancer patients has shown substantial advancements in survival rates across early and advanced stages of the disease. In silico research findings provide support for the application of phytochemicals as potential inhibitors of IL-8, and phytochemicals exhibiting a high binding free energy and crucial interactions display promising anticancer properties, positioning them as candidates for future drug development. Noteworthy phytochemicals such as IMPHY006634 (Isohydnocarpin), IMPHY007957 (Chitranone) and IMPHY013015 (1-Hydroxyrutaecarpine) were predicted to possess inhibitory activity against IL-8, with calculated energies ranging from -9.9 to -9.1 kcal/mol, respectively. Several hydrogen bonds, including common amino acid residues Lys9 and CYS48, were identified. Molecular dynamics calculations conducted on these potent inhibitors demonstrated their stability throughout a 200 ns simulation, as indicated by metrics such as RMSD, RMSF, Rg, SASA, H-bonds, PCA and FEL analysis. Moreover, PASS analysis and adherence of these natural compounds to drug-likeness rules like Lipinski's further strengthen their candidacy. Considering these calculations and various parameters, these three prominent natural compounds emerge as promising candidates for anti-IL-8 therapy in the management of cancer.Communicated by Ramaswamy H. Sarma.

Circulating long non-coding RNAs NKILA, NEAT1, MALAT1, and MIAT expression and their association in type 2 diabetes mellitus.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a multifactorial disorder that leads to alterations in gene regulation. Long non-coding RNAs (lncRNAs) have become a major research topic as they are involved in metabolic disorders. METHODS: This study included a total of 400 study subjects; 200 were subjects with T2DM and 200 were healthy subjects. Extracted RNA was used to synthesize cDNA by quantitative real time. Serum analysis was carried out to determine differences in biochemical parameters. Recorded data were used to evaluate associations with expression of lncRNAs NF-kappaB interacting lncRNA (NKILA), nuclear enriched abundant transcript 1 (NEAT1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), and myocardial infarction-associated transcript (MIAT) in T2DM cases. RESULTS: Compared with healthy controls, patients with T2DM showed an overall increase in expression of lncRNAs NKILA, NEAT, MALAT1, and MIAT by 3.94-fold, 5.28-fold, 4.46-fold, and 6.35-fold, respectively. Among patients with T2DM, higher expression of lncRNA NKILA was associated with hypertension (p=0.001), smoking (p<0.0001), and alcoholism (p<0.0001). Altered NEAT1 expression was significantly associated with weight loss (p=0.04), fatigue (p=0.01), slow wound healing (p=0.002), blurred vision (p=0.008), loss of appetite (p=0.007), smoking (p<0.0001), and alcoholism (p<0.0001). Higher expression of lncRNA MALAT1 was significantly linked with weight loss (p=0.003), blurred vision (p=0.01), smoking (p<0.0001), and alcoholism (p<0.0001). Expression of lncRNA MIAT was associated with only blurred vision (p<0.0001), smoking (p<0.0001), and alcoholism (p<0.0001). Positive correlations of lncRNA NKILA with lncRNAs NEAT1 (r=0.42, p<0.0001), MALAT (r=0.36, p<0.0001) and MIAT (r=0.42, p<0.0001) were observed among patients with T2DM. Significant positive correlations of lncRNA NEAT with lncRNAs MALAT and MIAT were observed among patients with T2DM. A positive correlation between lncRNAs MALAT and MIAT was also observed among patients with T2DM. CONCLUSION: Increased circulating NKILA, NEAT1, MALAT, and MIAT expression in patients with T2DM, which is linked with poor patient outcomes and significantly linked with alcoholism and smoking, may influence the degree and severity of disease among patients with T2DM. These lncRNAs may contribute to the progression of T2DM disease or other related diabetes-related complications.

Pneumocystis Jirovecii detection and comparison of multiple diagnostic methods with quantitative real-time PCR in patients with respiratory symptoms.

Pneumocystis jirovecii (PCP) remains a significant cause of mortality and morbidity in patients with respiratory infections. Accurate diagnosis of PCP is still a diagnostic challenge. Hence, the main objectives were to study the incidence of Pneumocystis Jirovecii pneumonia infection among respiratory problems patients and to compare the real-time quantitative PCR technique with various diagnostic methodologies. Patients who have respiratory symptoms of PCP like breathlessness, cough, and fever were enrolled. Bronchoalveolar lavage (BAL) samples were collected and homogenized, and then smears were prepared for examination by Gomorimethanamine silver staining (GMSS), Immunofluorescent staining (IFAT), Toludine blue O (TBO), and Giemsa staining. Further, RT-PCR was also performed for the detection of PCP. The mean patients' age was 52 (SD ±â€¯16) years. 41% were female, and 59% of the patients were male. Weight loss (80%), fever (92%), cough (100%), and dyspnea (76%) were the most common complaints. Twenty-eight patients have been diagnosed with pulmonary infiltrates using chest X-ray. Out of 100 patients, 35% were positive for PCP. The organism was detected using IFAT in all the 35 specimens, 15 of 35 (42.86%) by GMSS, 8 of 35 (17.6%) by Giemsa stain, and 1 of 35 (2.8%) was detected by TBO stains. RT-PCR showed that 39 patients was found to be positive for PCP. Thirty-five of these 39 patients had a positive IFAT (89.74%); the IFAT was negative or undefined in 4 samples. All 39 patients (100%) had signs and symptoms for PCP. Our results suggest that RT-PCR is still the most highly sensitive method for Pneumocystis Jirovecii detection. In poor resource settings where RT-PCR and IFAT is not available, diagnosis of Pneumocystis jirovecii pneumonia remains a complicated issue. In settings where RT-PCR & IFAT are not available, GMSS staining may be the next best choice to detect PCP.