Serotonin N-acetyltransferase (arylalkylamine N-acetyl-transferase, AANAT) is an enzyme that catalyses the first rate limiting step in the biosynthesis of melatonin (5-methoxy-N-acetyltryptamine). Different physiopathological disorders in human may be due to abnormal secretion of melatonin leading to an inappropriate exposure of melatonin receptors to melatonin. For that reason, we have designed, synthesized and evaluated as inhibitors of human serotonin N-acetyltransferase, a series of compounds that were able to react with coenzyme A to give a bisubstrate analog inhibitor. Compound 12d was found to be a potent AANAT inhibitor (IC50 = 0.18 microM).
The three-dimensional quantitative structure-activity relationship (3D-QSAR) approach using comparative molecular field analysis (CoMFA) was applied to a series of 40 compounds synthesized in our laboratory and evaluated as AANAT inhibitors. The N-bromoacetyltryptamine conformation derived from the X-ray crystal structure of the enzyme bound with a bisubstrate analog, was used to obtain the putative bioactive conformation of these inhibitors. Five statistically significant models were obtained from the randomly constituted training sets (30 compounds) and subsequently validated with the corresponding test sets (10 compounds). The best predictive model (n ¼ 30, q 2 ¼ 0.644, N ¼ 6, r 2 ¼ 0.966, s ¼ 0.145, F ¼ 109.478) can predict inhibitory activity for a wide range of compounds and offers important structural insight into designing novel AANAT inhibitors prior to their synthesis.
The three‐dimensional quantitative structure‐activity relationship (3D‐QSAR) approach using comparative molecular field analysis (CoMFA) was applied to a series of 40 compounds synthesized in our laboratory and evaluated as AANAT inhibitors. The N‐bromoacetyltryptamine conformation derived from the X‐ray crystal structure of the enzyme bound with a bisubstrate analog, was used to obtain the putative bioactive conformation of these inhibitors. Five statistically significant models were obtained from the randomly constituted training sets (30 compounds) and subsequently validated with the corresponding test sets (10 compounds). The best predictive model (n=30, q2=0.644, N=6, r2=0.966, s=0.145, F=109.478) can predict inhibitory activity for a wide range of compounds and offers important structural insight into designing novel AANAT inhibitors prior to their synthesis.
A novel series of melatonin analogues based on the benzothiophene nucleus is described. In these compounds the methoxy group was replaced by electron‐attracting groups such halogens (Br and Cl) with the aim of supplementing structure‐affinity relationships on melatoninergic ligands. Target derivatives were prepared from the corresponding 4‐halo‐thiophenol. Some of these derivatives had high affinity for mt1 and MT2 receptors, almost as high as that of melatonin.
These results prove that the methoxy group is not an essential requirement for binding to melatoninergic receptors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.