Design, synthesis, and evaluation of potential inhibitors of nitric oxide synthase

• Published in: Bioorganic & medicinal chemistry 2008-06, Vol.16 (11), p.6193-6206
• Main Authors: Castaño, Tania, Encinas, Arantxa, Pérez, Concepción, Castro, Ana, Campillo, Nuria E., Gil, Carmen
• Format: Article
• Language: English
• Subjects: Artificial neural network; Biological and medical sciences; CODES; Drug Design; Enzyme Inhibitors - chemical synthesis; Enzyme Inhibitors - pharmacology; Isoenzymes - antagonists & inhibitors; Medical sciences; Neural Networks (Computer); Neuropharmacology; Neuroprotective agent; Nitric Oxide Synthase Type I - antagonists & inhibitors; NOS; Pharmacology. Drug treatments; Predictive Value of Tests; QSAR; Quantitative Structure-Activity Relationship; Thiadiazole; Thiadiazoles - chemical synthesis; Thiadiazoles - pharmacology; Thiourea - analogs & derivatives; Thiourea - chemical synthesis; Thiourea - pharmacology
• ISSN: 0968-0896; 1464-3391
• DOI: 10.1016/j.bmc.2008.04.036

Selective inhibitors of neuronal nitric oxide synthase (nNOS) were shown to protect brain and may be useful in the treatment of neurodegenerative diseases. In this context, our purpose has been to design and synthesize a new family of derivatives of thiadiazoles as possible inhibitors of nNOS. To achieve it a supervised artificial neural network model has been developed for the prediction of inhibition of Nitric Oxide Synthase using a dataset of 119 nNOS inhibitors. The definition of the molecules was achieved from a not-supervised neural network using a home made program named CODES. Also, thiadiazole-based heterocycles, previously predicted, were prepared as conformationally restricted analogues of a selective nNOS inhibitor, S-ethyl N-phenylisothiourea.