Structure-activity relationship of human carbonic anhydrase-II inhibitors: Detailed insight for future development as anti-glaucoma agents.

Human carbonic anhydrase-II (hCA-II) is the most dominant physiologic isoform amongst the sixteen reported hCA isoforms. Because of its high availability in the different anatomical, and cellular sites of the eye like retina and lens, it plays a more prominent role in the regulation of intraocular pressure than the other twelve catalytically active hCA isoforms. This isoform is also located in the brain, kidney, gastric mucosa, osteoclasts, RBCs, skeletal muscle, testes, pancreas, lungs, etc.

Identification of structural fingerprints for toxicity by using Monte Carlo based QSTR modeling of nitroaromatics.

Monte Carlo based method by using either SMILES based or combination of SMILES and Graph-based descriptors is an important strategy to build the QSAR/QSTR model for prediction of different biological endpoints. In this study, Monte Carlo based QSTR approach was applied to the dataset of 90 nitroaromatic compounds related to their toxicity, represented by 50% lethal dose concentration for rats (LD). Both classification and regression-based QSTR models were developed to get an idea about different fingerprints for promoters and hinderers of nitroaromatics toxicity.

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.