Computational insights into missense mutations in HTT gene causing Huntington's disease and its interactome networks

Mitochondrial targeted antioxidants as potential therapy for huntington's disease

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expansion in CAG repeat on huntington (Htt) gene, leading to a degeneration of GABAergic medium spiny neurons (MSNs) in the striatum, resulting in the generation of reactive oxygen species, and decrease antioxidant activity. These pathophysiological alterations impair mitochondrial functions, leading to an increase in involuntary hyperkinetic movement. However, researchers investigated the neuroprotective effect of antioxidants using various animal models. Still, their impact is strictly limited to curtailing oxidative stress and increasing the antioxidant enzyme in the brain, which is less effective in HD. Meanwhile, researchers discovered Mitochondria-targeted antioxidants (MTAXs) that can improve mitochondrial functions and antioxidant activity through the modulation of mitochondrial signaling pathways, including peroxisome proliferator-activated receptor (PPAR)-coactivator 1 (PGC-1α), dynamin-related protein 1 (Drp1), mitochondrial fission protein 1 (Fis1), and Silent mating type information regulation 2 homolog 1 (SIRT-1), showing neuroprotective effects in HD. The present review discusses the clinical and preclinical studies that investigate the neuroprotective effect of MTAXs (SS31, XJB-5-131, MitoQ, bezafibrate, rosiglitazone, meldonium, coenzyme Q10, etc.) in HD. This brief literature review will help to understand the relevance of MTAXs in HD and enlighten the importance of MTAXs in future drug discovery and development.

Insights into AlphaFold's breakthrough in neurodegenerative diseases

Neurodegenerative diseases (ND) are disorders of the central nervous system (CNS) characterized by impairment in neurons' functions, and complete loss, leading to memory loss, and difficulty in learning, language, and movement processes. The most common among these NDs are Alzheimer's disease (AD) and Parkinson's disease (PD), although several other disorders also exist. These are frontotemporal dementia (FTD), amyotrophic lateral syndrome (ALS), Huntington's disease (HD), and others; the major pathological hallmark of NDs is the proteinopathies, either of amyloid-β (Aβ), tauopathies, or synucleinopathies. Aggregation of proteins that do not undergo normal configuration, either due to mutations or through some disturbance in cellular pathway contributes to the diseases. Artificial Intelligence (AI) and deep learning (DL) have proven to be successful in the diagnosis and treatment of various congenital diseases. DL approaches like AlphaFold (AF) are a major leap towards success in CNS disorders. This 3D protein geometry modeling algorithm developed by DeepMind has the potential to revolutionize biology. AF has the potential to predict 3D-protein confirmation at an accuracy level comparable to experimentally predicted one, with the additional advantage of precisely estimating protein interactions. This breakthrough will be beneficial to identify diseases' advancement and the disturbance of signaling pathways stimulating impaired functions of proteins. Though AlphaFold has solved a major problem in structural biology, it cannot predict membrane proteins-a beneficial approach for drug designing.