Towards therapeutic applications of arthropod venom k(+)-channel blockers in CNS neurologic diseases involving memory acquisition and storage

Identification of Mild Cognitive Impairment Subtypes using an Interpretable Neural Network based Clustering of Gene Expression Data and Neuroimaging Markers

In this study, an attempt is made to cluster the gene expression data and neuroimaging markers using an interpretable neural network model to identify Mild Cognitive Impairment (MCI) subtypes. For this, structural Magnetic Resonance (MR) brain images and gene expression data of early and late MCI subjects are considered from a public database. A neural network model is employed to cluster the gene expression data and regional MR volumes. To evaluate the performance of model, clustering metrics are employed and model is explained using perturbation-based method. Results indicate that the developed model is able to identify MCI subtypes. The network learns latent embeddings of disease-specific genes and MR images markers. The clustering metrics are found to be highest when both the imaging and genetic markers are employed. Volumes of lateral ventricles, hippocampus, amygdala and thalamus are found to be associated with late MCI. Significant scores suggest that genes such as StAR, CCDC108, APOO, TRMT13, RASAL2 and ZNF43 play a key role in identifying the MCI subtypes.Clinical Relevance-Identifying distinct MCI subtypes offer potential for precision diagnostics and targeted clinical recruitment.

An Information-Theory-Based Approach for Optimal Model Reduction of Biomolecules

In theoretical modeling of a physical system, a crucial step consists of the identification of those degrees of freedom that enable a synthetic yet informative representation of it. While in some cases this selection can be carried out on the basis of intuition and experience, straightforward discrimination of the important features from the negligible ones is difficult for many complex systems, most notably heteropolymers and large biomolecules. We here present a thermodynamics-based theoretical framework to gauge the effectiveness of a given simplified representation by measuring its information content. We employ this method to identify those reduced descriptions of proteins, in terms of a subset of their atoms, that retain the largest amount of information from the original model; we show that these highly informative representations share common features that are intrinsically related to the biological properties of the proteins under examination, thereby establishing a bridge between protein structure, energetics, and function.

Therapeutic Effects of Apamin as a Bee Venom Component for Non-Neoplastic Disease

Bee venom is a natural toxin produced by honeybees and plays an important role in defending bee colonies. Bee venom has several kinds of peptides, including melittin, apamin, adolapamine, and mast cell degranulation peptides. Apamin accounts for about 2%-3% dry weight of bee venom and is a peptide neurotoxin that contains 18 amino acid residues that are tightly crosslinked by two disulfide bonds. It is well known for its pharmacological functions, which irreversibly block Ca2+-activated K+ (SK) channels. Apamin regulates gene expression in various signal transduction pathways involved in cell development. The aim of this study was to review the current understanding of apamin in the treatment of apoptosis, fibrosis, and central nervous system diseases, which are the pathological processes of various diseases. Apamin's potential therapeutic and pharmacological applications are also discussed.

Pharmacological Alternatives for the Treatment of Neurodegenerative Disorders: Wasp and Bee Venoms and Their Components as New Neuroactive Tools

Neurodegenerative diseases are relentlessly progressive, severely impacting affected patients, families and society as a whole. Increased life expectancy has made these diseases more common worldwide. Unfortunately, available drugs have insufficient therapeutic effects on many subtypes of these intractable diseases, and adverse effects hamper continued treatment. Wasp and bee venoms and their components are potential means of managing or reducing these effects and provide new alternatives for the control of neurodegenerative diseases. These venoms and their components are well-known and irrefutable sources of neuroprotectors or neuromodulators. In this respect, the present study reviews our current understanding of the mechanisms of action and future prospects regarding the use of new drugs derived from wasp and bee venom in the treatment of major neurodegenerative disorders, including Alzheimer’s Disease, Parkinson’s Disease, Epilepsy, Multiple Sclerosis and Amyotrophic Lateral Sclerosis.