Graph neural network (GNN) is a computational drug discovery framework that learns from molecular graphs to model compounds and their interactions, often by extracting both local substructures and global molecular topology. In practice, it can be multiscale-aware and densely connected, which helped improve screening of about 1.3 million compounds for novel antileishmanial hits and accelerated…
Autoimmune disease is a broad class of disorders in which the immune system attacks the body’s own tissues and organs, and its clinical use here is centered on disease prognosis and therapeutic response prediction. Non-coding RNAs are highlighted as prognostic biomarkers in non coding rnas, suggesting a biomarker-driven approach to stratifying patients and anticipating outcomes….
Melatonin is a small-molecule therapeutic agent with preclinical and emerging clinical evidence, and it is discussed here as a compound with mechanistic promise in ovarian aging and as a comparator for the novel nasal-administered analog mt a2. Its primary relevance is as a protective, pleiotropic agent that can modulate oxidative stress, inflammation, and mitochondrial biogenesis,…
Immunotherapy is a cancer treatment modality that works by harnessing or modulating the immune response, and in this entry it is described as a therapy context used to evaluate outcomes, including a model that predicted deep hypergraph for nsclc-based immunotherapy outcomes in NSCLC. It is being applied across multiple malignancies, including oral precancer, prostate cancer,…
B7-H3 Summary B7-H3 (CD276) is a tumor-associated immune-related protein that is markedly upregulated across EGFR-positive malignancies while showing minimal expression in healthy tissues, making it a tumor-selective binding target. It can mediate cis-inhibition in the context of an EGFR/B7-H3 bispecific antibody, supporting a mechanism for enhanced anti-tumor efficacy with reduced toxicity. B7-H3 is also elevated…
