ACS Chemical Neuroscience最新文献

Aggregation of TDP-43 is linked to the pathogenesis of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Notably, electrostatic point mutations such as D169G and P112H, located within the highly conserved functional tandem RNA recognition motif (RRM) domains of the TDP-43 protein (TDP-43^tRRM), have been identified in diseased patients as well. In this study, we address how the electrostatic mutations alter both the native state stability and aggregation propensity of TDP-43^tRRM. The mutants D169G and P112H show increased chemical stability compared to the TDP-43^tRRM at physiological pH. However, at low pH, both the mutants undergo a conformational change to form amyloid-like fibrils, though with variable rates─the P112H mutant being substantially faster than the other two sequences (TDP-43^tRRM and D169G mutant) showing comparable rates. Moreover, among the three sequences, only the P112H mutant undergoes a strong ionic strength-dependent aggregability trend. These observations signify the substantial contribution of the excess charge of the P112H mutant to its unique aggregation process. Complementary simulated observables with atomistic resolution assign the experimentally observed sequence-, pH-, and ionic strength-dependent aggregability pattern to the degree of thermal lability of the mutation site-containing RRM1 domain and its extent of dynamical anticorrelation with the RRM2 domain whose combination eventually dictate the extent of generation of aggregation-prone partially unfolded conformational ensembles. Our choice of a specific charge-modulated pathogenic mutation-based experiment-simulation-combination approach unravels the otherwise hidden residue-wise contribution to the individual steps of this extremely complicated multistep aggregation process.

Intrinsically disordered proteins (IDPs) are closely associated with a number of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease. Due to the highly dynamic nature of IDPs, their structural determination and conformational exploration pose significant challenges for both experimental and computational research. Recently, the integration of machine learning with molecular dynamics (MD) simulations has emerged as a promising methodology for efficiently exploring the conformation spaces of IDPs. In this viewpoint, we briefly review recently developed autoencoder-based models designed to enhance the conformational exploration of IDPs through embedding and latent sampling. We highlight the capability of autoencoders in expanding the conformations sampled by MD simulations and discuss their limitations due to the non-Gaussian latent space distribution and the limited conformational diversity of training conformations. Potential strategies to overcome these limitations are also discussed.

The aberrant aggregation of TAR DNA-binding protein 43 kDa (TDP-43) in cells leads to the pathogenesis of multiple fatal neurodegenerative diseases. Decoding the proposed initial transition between its functional dimeric and aggregation-prone monomeric states can potentially design a viable therapeutic strategy, which is presently limited by the lack of structural detail of the full-length TDP-43. To achieve a complete understanding of such a delicate phase space, we employed a multiscale simulation approach that unearths numerous crucial features, broadly summarized in two categories: (1) state-independent features that involve inherent chain collapsibility, rugged polymorphic landscape dictated by the terminal domains, high β-sheet propensity, structural integrity preserved by backbone-based intrachain hydrogen bonds and electrostatic forces, the prominence of the C-terminal domain in the intrachain cross-domain interfaces, and equal participation of hydrophobic and hydrophilic (charged and polar) residues in cross-domain interfaces; and (2) dimerization-modulated characteristics that encompass slower collapsing dynamics, restricted polymorphic landscape, the dominance of side chains in interchain hydrogen bonds, the appearance of the N-terminal domain in the dimer interface, and the prominence of hydrophilic (specifically polar) residues in interchain homo- and cross-domain interfaces. In our work, the ill-known C-terminal domain appears as the most crucial structure-dictating domain, which preferably populates a compact conformation with a high β-sheet propensity in its isolated state stabilized by intrabackbone hydrogen bonds, and these signatures are comparatively faded in its integrated form. Validation of our simulated observables by a complementary spectroscopic approach on multiple counts ensures the robustness of the computationally predicted features of the TDP-43 aggregation landscape.

In searching for putative new therapeutic strategies to treat neurodegenerative diseases, the mitochondrial 18 kDa translocator protein (TSPO) and cerebral isoforms of carbonic anhydrase (CA) were exploited as potential targets. Based on the structures of a class of highly affine and selective TSPO ligands and a class of CA activators, both developed by us in recent years, a small library of 2-phenylindole-based dual TSPO/CA modulators was developed, able to bind TSPO and activate CA VII in the low micromolar/submicromolar range. The interaction with the two targets was corroborated by computational studies. Biological investigation on human microglia C20 cells identified derivative 3 as a promising lead compound worthy of future optimization due to its (i) lack of cytotoxicity, (ii) ability to stimulate TSPO steroidogenic function and activate CA VII, and (iii) ability to effectively upregulate gene expression of the brain-derived neurotrophic factor.

Sophora flavescens, the source of oxymatrine, is gaining popularity due to its potential in neuroprotection and treatment of various neurological conditions like epilepsy, depression, Parkinson's, Alzheimer's and multiple sclerosis. Its natural occurrence and promising preliminary research highlight its ability to reduce nerve cell damage and inflammation, attributed to its antiapoptotic, antioxidant and anti-inflammatory properties. However, challenges like solubility, potential adverse effects and limited bioavailability hinder its full therapeutic utilization. Current strategies, including formulation optimization and innovative drug delivery systems, aim to enhance its efficacy and safety. Despite its potential, further research is necessary to overcome these obstacles and maximize its clinical effectiveness. Conclusively, oxymatrine demonstrates distinct neuroprotective properties, offering unique advantages over other agents currently being studied or used in clinical practice for neurological disorders. nevertheless, additional study is necessary to surmount current obstacles and maximize its effectiveness for clinical settings. This study provides a comprehensive overview of oxymatrine's neuroprotective mechanisms and therapeutic potential while emphasizing the need for continued investigation and development for practical clinical application.