Integrating Blood Biomarkers and Marine Brown Algae-Derived Inhibitors in Parkinson's Disease: A Multi-scale Approach from Interactomics to Quantum Mechanics.

Parkinson's disease (PD) involves alpha-synuclein accumulation according to Braak's pattern, with diverse clinical progressions that complicate diagnosis and treatment. We aimed to correlate Braak's pattern with rapid progressive PD to identify blood-based biomarkers and therapeutic targets exploiting brown algae-derived bioactives for potential treatment. We implemented a systematic workflow of transcriptomic profiling, co-expression networks, cluster profiling, transcriptional regulator identification, molecular docking, quantum calculations, and dynamic simulations. The transcriptomic analyses exhibited highly expressed genes at each Braak's stage and in rapidly progressive PD. Co-expression networks for Braak's stages were built, and the top five clusters from each stage displayed significant overlap with differentially expressed genes in rapidly progressive PD, indicating shared biomarkers between the blood and the PD brain. Further investigation showed, NF-kappa-B p105 as the master transcriptional regulator of these biomarkers. Molecular docking screened phlorethopentafuhalol-A from brown algae, exhibiting a superior inhibitory effect with p105 (- 7.51 kcal/mol) by outperforming PD drugs and anti-inflammatory compounds (- 5.73 to - 4.38 kcal/mol). Quantum mechanics and molecular mechanics (QM/MM) calculations and dynamic simulations have confirmed the interactive stability of phlorethopentafuhalol-A with p105. Overall, our combined computational study shows that phlorethopentafuhalol-A derived from brown algae, may have healing properties that could help treat PD.

Molecular Regulator Driving Endometriosis Towards Endometrial Cancer: A Multi-Scale Computational Investigation to Repurpose Anti-Cancer drugs.

Endometriosis is a gynecological disorder among reproductive-aged women. Recent epidemiological investigations suggest endometriosis increases the risk of endometrial cancer. However, the molecular entity leading to endometriosis-to-endometrial cancer is largely unknown. This study aimed to combine a variety of computational approaches to identify the key therapeutic target promoting endometriosis-to-endometrial cancer and screen potential inhibitors against target to prevent cancer development. Our systematic investigations, includes transcriptomic profiling, protein network, pharmacophore modeling, docking, binding free energy calculation, dynamics simulation, and quantum mechanics. The gene expression analysis on endometriosis and endometrial cancer was performed and showed 108 shared upregulated genes in both conditions. Further construction of interaction network with 108 genes showed intercellular adhesion molecule 1 (ICAM1) to be a crucial molecule with a high degree of connectivity that influences vital mechanisms related to cancer pathways. We then generated ligand-based pharmacophore models using established ICAM1 inhibitors. Among the models, the ADRRR_8 pharmacophore exhibited a robust area under curve (AUC = 0.83), was employed to screen 1739 anti-cancer drugs. On screening, 421 anti-cancer drugs displayed ICAM1-inhibiting pharmacophore features. Further, the docking of 421 drugs with ICAM1 showed lanreotide (-7.80 kcal/mol) with better affinity than the reference ICAM1 inhibitor (-3.59 kcal/mol). Further validation though binding free energy and dynamics simulation of the lanreotide-ICAM1 complex showed a high binding affinity of -55.90 kcal/mol and contributed stable confirmation. According to quantum chemical calculations, lanreotide's electronic properties favour ICAM1 binding with highest occupied molecular orbital was -6.91 eV and lowest unoccupied molecular orbital was -3.93 eV. Our study supports using lanreotide to treat endometriosis, which could delay or prevent endometrial cancer. These predictions need to be confirmed and examined to determine the use of lanreotide in endometriosis treatment.

Elucidating the Histone Deacetylase Gene Expression Signatures in Peripheral Blood Mononuclear Cells That Correlate Essential Cardiac Function and Aid in Classifying Coronary Artery Disease through a Logistic Regression Model.

A proinflammatory role of HDACs has been implicated in the pathogenesis of atherosclerosis as an emerging novel epigenetic diagnostic biomarker. However, its association with the clinical and cardiovascular function in coronary artery disease is largely unknown. The study aimed to profile the gene expression of HDAC1-11 in human peripheral blood mononuclear cells and to evaluate their influence on hematological, biochemical, and two-dimensional echocardiographic indices in CAD. The HDAC gene expression profiles were assessed in 62 angioproven CAD patients and compared with 62 healthy controls. Among the HDACs, upregulated HDACs 1,2, 4, 6, 8, 9, and 11 were upregulated, and HDAC3 was downregulated, which was significantly (p ≤ 0.05) linked with the hematological (basophils, lymphocytes, monocytes, and neutrophils), biochemical (LDL, HDL, and TGL), and echocardiographic parameters (cardiac function: biplane LVEF, GLS, MV E/A, IVRT, and PV S/D) in CAD. Furthermore, our constructed diagnostic model with the crucial HDACs establishes the most crucial HDACs in the classification of CAD from control with an excellent accuracy of 88.6%. Conclusively, our study has provided a novel perspective on the HDAC gene expression underlying cardiac function that is useful in developing molecular methods for CAD diagnosis.

Screening of Crucial Cytosolicproteins Interconnecting the Endoplasmic Reticulum and Mitochondria in Parkinson's Disease and the Impact of Anti-Parkinson Drugs in the Preservation of Organelle Connectivity.

Mitochondrial dysfunction is well-established in Parkinson's disease (PD); however, its dysfunctions associating with cell organelle connectivity remain unknown. We aimed to establish the crucial cytosolic protein involved in organelle connectivity between mitochondria and the endopalmic reticulum (ER) through a computational approach by constructing an organelle protein network to extract functional clusters presenting the crucial PD protein connecting organelles. Then, we assessed the influence of anti-parkinsonism drugs (n = 35) on the crucial protein through molecular docking and molecular dynamic simulation and further validated its gene expression in PD participants under, istradefylline (n = 25) and amantadine (n = 25) treatment. Based on our investigation, D-aspartate oxidase (DDO )protein was found to be the critical that connects both mitochondria and the ER. Further, molecular docking showed that istradefylline has a high affinity (-9.073 kcal/mol) against DDO protein, which may disrupt mitochondrial-ER connectivity. While amantadine (-4.53 kcal/mol) shows negligible effects against DDO that contribute to conformational changes in drug binding, Successively, DDO gene expression was downregulated in istradefylline-treated PD participants, which elucidated the likelihood of an istradefylline off-target mechanism. Overall, our findings illuminate the off-target effects of anti-parkinsonism medications on DDO protein, enabling the recommendation of off-target-free PD treatments.