Harnessing Brainwave Entrainment: A Non-invasive Strategy To Alleviate Neurological Disorder Symptoms.

From 1990-2019, the burden of neurological disorders varied considerably across countries and regions. Psychiatric disorders, often emerging in early to mid-adulthood, are linked to late-life neurodegenerative diseases like Alzheimer's disease and Parkinson's disease. Individuals with conditions such as Major Depressive Disorder, Anxiety Disorder, Schizophrenia, and Bipolar Disorder face up to four times higher risk of developing neurodegenerative disorders. Contrarily, 65 % of those with neurodegenerative conditions experience severe psychiatric symptoms during their illness. Further, the limitation of medical resources continues to make this burden a significant global and local challenge. Therefore, brainwave entrainment provides therapeutic avenues for improving the symptoms of diseases. Brainwaves are rhythmic oscillations produced either spontaneously or in response to stimuli. Key brainwave patterns include gamma, beta, alpha, theta, and delta waves, yet the underlying physiological mechanisms and the brain's ability to shift between these dynamic states remain areas for further exploration. In neurological disorders, brainwaves are often disrupted, a phenomenon termed "oscillopathy". However, distinguishing these impaired oscillations from the natural variability in brainwave activity across different regions and functional states poses significant challenges. Brainwave-mediated therapeutics represents a promising research field aimed at correcting dysfunctional oscillations. Herein, we discuss a range of non-invasive techniques such as non-invasive brain stimulation (NIBS), neurologic music therapy (NMT), gamma stimulation, and somatosensory interventions using light, sound, and visual stimuli. These approaches, with their minimal side effects and cost-effectiveness, offer potential therapeutic benefits. When integrated, they may not only help in delaying disease progression but also contribute to the development of innovative medical devices for neurological care.

Synergizing drug repurposing and target identification for neurodegenerative diseases.

Despite dedicated research efforts, the absence of disease-curing remedies for neurodegenerative diseases (NDDs) continues to jeopardize human society and stands as a challenge. Drug repurposing is an attempt to find new functionality of existing drugs and take it as an opportunity to discourse the clinically unmet need to treat neurodegeneration. However, despite applying this approach to rediscover a drug, it can also be used to identify the target on which a drug could work. The primary objective of target identification is to unravel all the possibilities of detecting a new drug or repurposing an existing drug. Lately, scientists and researchers have been focusing on specific genes, a particular site in DNA, a protein, or a molecule that might be involved in the pathogenesis of the disease. However, the new era discusses directing the signaling mechanism involved in the disease progression, where receptors, ion channels, enzymes, and other carrier molecules play a huge role. This review aims to highlight how target identification can expedite the whole process of drug repurposing. Here, we first spot various target-identification methods and drug-repositioning studies, including drug-target and structure-based identification studies. Moreover, we emphasize various drug repurposing approaches in NDDs, namely, experimental-based, mechanism-based, and in silico approaches. Later, we draw attention to validation techniques and stress on drugs that are currently undergoing clinical trials in NDDs. Lastly, we underscore the future perspective of synergizing drug repurposing and target identification in NDDs and present an unresolved question to address the issue.

Simulation and Computational Study of RING Domain Mutants of BRCA1 and Ube2k in AD/PD Pathophysiology.

Lysine-based post-translational modification (PTM) such as acylation, acetylation, deamination, methylation, SUMOylation, and ubiquitination has proven to be a major regulator of gene expression, chromatin structure, protein stability, protein-protein interaction, protein degradation, and cellular localization. However, besides all the PTMs, ubiquitination stands as the second most common PTM after phosphorylation that is involved in the etiology of neurodegenerative diseases (NDDs) namely, Alzheimer's disease (AD) and Parkinson's disease (PD). NDDs are characterized by the accumulation of misfolded protein aggregates in the brain that lead to disease-related gene mutation and irregular protein homeostasis. The ubiquitin-proteasome system (UPS) is in charge of degrading these misfolded proteins, which involve an interplay of E1, E2, E3, and deubiquitinase enzymes. Impaired UPS has been commonly observed in NDDs and E3 ligases are the key members of the UPS, thus, dysfunction of the same can accelerate the neurodegeneration process. Therefore, the aim of this study is firstly, to find E3 ligases that are common in both AD and PD through data mining. Secondly, to study the impact of mutation on its structure and function. The study deciphered 74 E3 ligases that were common in both AD and PD. Later, 10 hub genes were calculated of which protein-protein interaction, pathway enrichment, lysine site prediction, domain, and motif analysis were performed. The results predicted BRCA1, PML, and TRIM33 as the top three putative lysine-modified E3 ligases involved in AD and PD pathogenesis. However, based on structural characterization, BRCA1 was taken further to study RING domain mutation that inferred K32Y, K32L, K32C, K45V, K45Y, and K45G as potential mutants that alter the structural and functional ability of BRCA1 to interact with Ube2k, E2-conjugating enzyme. The most probable mutant observed after molecular dynamics simulation of 50 ns is K32L. Therefore, our study concludes BRCA1, a potential E3 ligase common in AD and PD, and RING domain mutation at sites K32 and K45 possibly disturbs its interaction with its E2, Ube2k.

Triaging between post-translational modification of cell cycle regulators and their therapeutics in neurodegenerative diseases.

Neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and Huntington's disease, present challenges in healthcare because of their complicated etiologies and absence of healing remedies. Lately, the emerging role of post-translational modifications (PTMs), in the context of cell cycle regulators, has garnered big interest as a potential avenue for therapeutic intervention. The review explores the problematic panorama of PTMs on cell cycle regulators and their implications in neurodegenerative diseases. We delve into the dynamic phosphorylation, acetylation, ubiquitination, SUMOylation, Glycation, and Neddylation that modulate the key cell cycle regulators, consisting of cyclins, cyclin-dependent kinases (CDKs), and their inhibitors. The dysregulation of these PTMs is related to aberrant cell cycle in neurons, which is one of the factors involved in neurodegenerative pathologies. Moreover, the effect of exogenous activation of CDKs and CDK inhibitors through PTMs on the signaling cascade was studied in postmitotic conditions of NDDs. Furthermore, the therapeutic implications of CDK inhibitors and associated alteration in PTMs were discussed. Lastly, we explored the putative mechanism of PTMs to restore normal neuronal function that might reverse NDDs.

Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis.

The integration of artificial intelligence in precision medicine has revolutionized healthcare delivery. Precision medicine identifies the phenotype of particular patients with less-common responses to treatment. Recent studies have demonstrated that translational research exploring the convergence between artificial intelligence and precision medicine will help solve the most difficult challenges facing precision medicine. Here, we discuss different aspects of artificial intelligence in precision medicine that improve healthcare delivery. First, we discuss how artificial intelligence changes the landscape of precision medicine and the evolution of artificial intelligence in precision medicine. Second, we highlight the synergies between artificial intelligence and precision medicine and promises of artificial intelligence and precision medicine in healthcare delivery. Third, we briefly explain the promise of big data analytics and the integration of nanomaterials in precision medicine. Last, we highlight the challenges and opportunities of artificial intelligence in precision medicine.

Cross talk mechanism of disturbed sleep patterns in neurological and psychological disorders.

The incidence and prevalence of sleep disorders continue to increase in the elderly populace, particularly those suffering from neurodegenerative and neuropsychiatric disorders. This not only affects the quality of life but also accelerates the progression of the disease. There are many reasons behind sleep disturbances in such patients, for instance, medication use, nocturia, obesity, environmental factors, nocturnal motor disturbances and depressive symptoms. This review focuses on the mechanism and effects of sleep dysfunction in neurodegenerative and neuropsychiatric disorders. Wherein we discuss disturbed circadian rhythm, signaling cascade and regulation of genes during sleep deprivation. Moreover, we explain the perturbation in brainwaves during disturbed sleep and the ocular perspective of neurodegenerative and neuropsychiatric manifestations in sleep disorders. Further, as the pharmacological approach is often futile and carries side effects, therefore, the non-pharmacological approach opens newer possibilities to treat these disorders and widens the landscape of treatment options for patients.

Protein S-sulfhydration: Unraveling the prospective of hydrogen sulfide in the brain, vasculature and neurological manifestations.

Hydrogen sulfide (H2S) and hydrogen polysulfides (H2Sn) are essential regulatory signaling molecules generated by the entire body, including the central nervous system. Researchers have focused on the classical H2S signaling from the past several decades, whereas the last decade has shown the emergence of H2S-induced protein S-sulfhydration signaling as a potential therapeutic approach. Cysteine S-persulfidation is a critical paradigm of post-translational modification in the process of H2S signaling. Additionally, studies have shown the cross-relationship between S-sulfhydration and other cysteine-induced post-translational modifications, namely nitrosylation and carbonylation. In the central nervous system, S-sulfhydration is involved in the cytoprotection through various signaling pathways, viz. inflammatory response, oxidative stress, endoplasmic reticulum stress, atherosclerosis, thrombosis, and angiogenesis. Further, studies have demonstrated H2S-induced S-sulfhydration in regulating different biological processes, such as mitochondrial integrity, calcium homeostasis, blood-brain permeability, cerebral blood flow, and long-term potentiation. Thus, protein S-sulfhydration becomes a crucial regulatory molecule in cerebrovascular and neurodegenerative diseases. Herein, we first described the generation of intracellular H2S followed by the application of H2S in the regulation of cerebral blood flow and blood-brain permeability. Further, we described the involvement of S-sulfhydration in different biological and cellular functions, such as inflammatory response, mitochondrial integrity, calcium imbalance, and oxidative stress. Moreover, we highlighted the importance of S-sulfhydration in cerebrovascular and neurodegenerative diseases.

Free radical biology in neurological manifestations: mechanisms to therapeutics interventions.

Recent advancements and growing attention about free radicals (ROS) and redox signaling enable the scientific fraternity to consider their involvement in the pathophysiology of inflammatory diseases, metabolic disorders, and neurological defects. Free radicals increase the concentration of reactive oxygen and nitrogen species in the biological system through different endogenous sources and thus increased the overall oxidative stress. An increase in oxidative stress causes cell death through different signaling mechanisms such as mitochondrial impairment, cell-cycle arrest, DNA damage response, inflammation, negative regulation of protein, and lipid peroxidation. Thus, an appropriate balance between free radicals and antioxidants becomes crucial to maintain physiological function. Since the 1brain requires high oxygen for its functioning, it is highly vulnerable to free radical generation and enhanced ROS in the brain adversely affects axonal regeneration and synaptic plasticity, which results in neuronal cell death. In addition, increased ROS in the brain alters various signaling pathways such as apoptosis, autophagy, inflammation and microglial activation, DNA damage response, and cell-cycle arrest, leading to memory and learning defects. Mounting evidence suggests the potential involvement of micro-RNAs, circular-RNAs, natural and dietary compounds, synthetic inhibitors, and heat-shock proteins as therapeutic agents to combat neurological diseases. Herein, we explain the mechanism of free radical generation and its role in mitochondrial, protein, and lipid peroxidation biology. Further, we discuss the negative role of free radicals in synaptic plasticity and axonal regeneration through the modulation of various signaling molecules and also in the involvement of free radicals in various neurological diseases and their potential therapeutic approaches. The primary cause of free radical generation is drug overdosing, industrial air pollution, toxic heavy metals, ionizing radiation, smoking, alcohol, pesticides, and ultraviolet radiation. Excessive generation of free radicals inside the cell R1Q1 increases reactive oxygen and nitrogen species, which causes oxidative damage. An increase in oxidative damage alters different cellular pathways and processes such as mitochondrial impairment, DNA damage response, cell cycle arrest, and inflammatory response, leading to pathogenesis and progression of neurodegenerative disease other neurological defects.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Post-translational modifications: Regulators of neurodegenerative proteinopathies.

One of the hallmark features in the neurodegenerative disorders (NDDs) is the accumulation of aggregated and/or non-functional protein in the cellular milieu. Post-translational modifications (PTMs) are an essential regulator of non-functional protein aggregation in the pathogenesis of NDDs. Any alteration in the post-translational mechanism and the protein quality control system, for instance, molecular chaperone, ubiquitin-proteasome system, autophagy-lysosomal degradation pathway, enhances the accumulation of misfolded protein, which causes neuronal dysfunction. Post-translational modification plays many roles in protein turnover rate, accumulation of aggregate and can also help in the degradation of disease-causing toxic metabolites. PTMs such as acetylation, glycosylation, phosphorylation, ubiquitination, palmitoylation, SUMOylation, nitration, oxidation, and many others regulate protein homeostasis, which includes protein structure, functions and aggregation propensity. Different studies demonstrated the involvement of PTMs in the regulation of signaling cascades such as PI3K/Akt/GSK3ß, MAPK cascade, AMPK pathway, and Wnt signaling pathway in the pathogenesis of NDDs. Further, mounting evidence suggests that targeting different PTMs with small chemical molecules, which acts as an inhibitor or activator, reverse misfolded protein accumulation and thus enhances the neuroprotection. Herein, we briefly discuss the protein aggregation and various domain structures of different proteins involved in the NDDs, indicating critical amino acid residues where PTMs occur. We also describe the implementation and involvement of various PTMs on signaling cascade and cellular processes in NDDs. Lastly, we implement our current understanding of the therapeutic importance of PTMs in neurodegeneration, along with emerging techniques targeting various PTMs.