Light-responsive functional nanomaterials as pioneering therapeutics: a paradigm shift to combat age-related disorders.

Aging, marked by dysregulated cellular systems, gives rise to a spectrum of age-related disorders, including neurodegeneration, atherosclerosis, immunosenescence, and musculoskeletal issues. These conditions contribute significantly to the global disease burden, posing challenges to health span and economic resources. Current therapeutic approaches, although diverse in mechanism, often fall short in targeting the underlying cellular pathologies.

Saffron (Crocus sativus L.) extract attenuates chronic scopolamine-induced cognitive impairment, amyloid beta, and neurofibrillary tangles accumulation in rats.

Ethnopharmacological Relevance: Crocus sativus L. known as saffron, is a popular food condiment with a high aroma, deep colour, and long and thick threads (stigmas) cultivated in Iran, Morocco, Spain, Italy, China, Japan, France, Turkey, and India. In 'Ayurveda', saffron is acknowledged for its immunostimulant, aphrodisiac, cardiotonic, liver tonic, nervine tonic, carminative, diaphoretic, diuretic, emmenagogue, galactagogue, febrifuge, sedative, relaxant, and anxiolytic activities.

Exploration of good and bad structural fingerprints for inhibition of indoleamine-2,3-dioxygenase enzyme in cancer immunotherapy using Monte Carlo optimization and Bayesian classification QSAR modeling.

Indoleamine-2,3-dioxygenase 1 (IDO1) is an extrahepatic, heme-containing and tryptophan-catalyzing enzyme responsible for causing blockade of T-cell proliferation and differentiation by depleting tryptophan level in cancerous cells. Therefore, inhibition of IDO1 may be a useful strategy for immunotherapy against cancer. In this study, 448 structurally diverse IDO1 inhibitors with a wide range of activity has been taken into consideration for classification QSAR analysis through Monte Carlo Optimization by using different splits as well as different combinations of SMILES-based, graph-based and hybrid descriptors.

Good and bad molecular fingerprints for human rhinovirus 3C protease inhibition: identification, validation, and application in designing of new inhibitors through Monte Carlo-based QSAR study.

HRV 3 C protease (HRV 3C) is an important target for common cold and upper respiratory tract infection. Keeping in view of the non-availability of drug for the treatment, newer computer-based modelling strategies should be applied to rationalize the process of antiviral drug discovery in order to decrease the valuable time and huge expenditure of the process. The present work demonstrates a structure wise optimization using Monte Carlo-based QSAR method that decomposes ligand compounds (in SMILES format) into several molecular fingerprints/descriptors.