Computational modelling of pathogenic protein spread in neurodegenerative diseases

Exploring the toxic effects and mechanism of methoxylated polybrominated diphenyl ethers (MeO-PBDEs) on thyroxine-binding globulin (TBG): Synergy between spectroscopic and computations

The interaction mechanism between thyroxine-binding globulin (TBG) and three methoxylated polybrominated diphenyl ethers (MeO-PBDEs) was analyzed by steady-state fluorescence, ultraviolet-visible (UV-visible) spectroscopy, circular dichroism (CD), molecular docking and molecular dynamics simulation methods. The results of the molecular docking technique revealed that 2'-MeO-BDE-3, 5-MeO-BDE-47, and 3-MeO-BDE-100 combined with TBG at the active site. The steady-state fluorescence spectra displayed that MeO-PBDEs quenched the endogenous fluorescence of TBG through static quenching mechanism, and complex formation between MeO-PBDEs and TBG was further indicated by UV-vis spectroscopy. The thermodynamic quantities showed that the binding process is spontaneous, and the major forces responsible for the binding are hydrogen bonding and hydrophobic interactions, which are consistent with the results of molecular docking to a certain extent. The results of CD confirmed that the secondary structure of TBG was changed after combining with MeO-PBDEs. The dynamic simulation results illustrated that the protein structure is more compact and changes in the secondary structure of TBG after binding to MeO-PBDEs. Additionally, we also utilized the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) method to analyze the binding free energy of TBG and MeO-PBDEs. The results suggest that van der Waals force plays an essential role in the combination.

Prospective role of mitochondrial apoptotic pathway in mediating GMG-ITC to reduce cytotoxicity in H2O2-induced oxidative stress in differentiated SH-SY5Y cells

The antioxidant and neuroprotective activity of Glucomoringin isothiocyanate (GMG-ITC) have been reported in in vivo and in vitro models of neurodegenerative diseases. However, its neuroprotective role via mitochondrial-dependent pathway in a noxious environment remains unknown. The main objective of the present study was to unveil the mitochondrial apoptotic genes' profile and prospectively link with neuroprotective activity of GMG-ITC through its ROS scavenging. The results showed that pre-treatment of differentiated SH-SY5Y cells with 1.25 μg/mL purified isolated GMG-ITC, significantly reduced reactive oxygen species (ROS) production level, compared to H₂O₂ control group, as evidenced by flow cytometry-based evaluation of ROS generation. Presence of GMG-ITC prior to development of oxidative stress condition, downregulated the expression of cyt-c, p53, Apaf-1, Bax, CASP3, CASP8 and CASP9 genes with concurrent upregulation of Bcl-2 gene in mitochondrial apoptotic signalling pathway. Protein Multiplex revealed significant decreased in cyt-c, p53, Apaf-1, Bax, CASP8 and CASP9 due to GMG-ITC pre-treatment in oxidative stress condition. The present findings speculated that pre-treatment with GMG-ITC may alleviate oxidative stress condition in neuronal cells by reducing ROS production level and protect the cells against apoptosis via neurodegenerative disease potential pathways.

Mathematical Biology Models of Parkinson's Disease

Parkinsons disease (PD) is a progressive neurodegenerative disease with substantial and growing socio-economic burden. In this multifactorial disease, aging, environmental, and genetic factors contribute to neurodegeneration and dopamine (DA) deficiency in the brain. Treatments aimed at DA restoration provide symptomatic relief, however, no disease modifying treatments are available, and PD remains incurable to date. Mathematical modeling can help understand such complex multifactorial neurological diseases. We review mathematical modeling efforts in PD with a focus on mechanistic models of pathogenic processes. We consider models of α-synuclein (Asyn) aggregation, feedbacks among Asyn, DA, and mitochondria and proteolytic systems, as well as pathology propagation through the brain. We hope that critical understanding of existing literature will pave the way to the development of quantitative systems pharmacology models to aid PD drug discovery and development.