Photobiological studies of new cyclopentene–psoralens
摘要:
Psoralen analogues bearing a cyclopentane ring fused to either the 4',5' double bond (compound 4) or the 3,4 double bond (compound 7) of the tricyclic furocoumarin structure were prepared. AM1 theoretical calculations performed for these compounds indicated that the electronic properties of their reactive double bonds were very similar to those of psoralen and its derivative 8-methoxypsoralen (8-MOP), though the overall molecular geometries were clearly different, particularly as regards the change in molecular curvature produced by the introduction of the cyclopentane ring. Compound 4 showed a capacity similar to that of 8-MOP to inhibit the growth of human cervix adenocarcinoma cells (HeLa) and to induce mutagenic effects, but it was definitely less phototoxic to skin than 8-MOP. Its ability to photoadd to DNA and to cross-link DNA strands was also demonstrated. Instead. compound 7 was practically devoid of biological activity and no interaction with the macromolecule could be detected. These differences in behaviour between 4 and 7 are probably due to the molecular curvature resulting fi om the introduction of the cyclopentane ring. (C) 1998 Elsevier Science S.A. All rights reserved.
A QSAR Model for in Silico Screening of MAO-A Inhibitors. Prediction, Synthesis, and Biological Assay of Novel Coumarins
摘要:
This work explores the potential of the MARCH-INSIDE methodology to seek a QSAR for MAO-A inhibitors from a heterogeneous series of compounds. A Markov model was used to quickly calculate the molecular electron delocalization, polarizability, refractivity, and n-octanol/water partition coefficients for a series of 1406 active/nonactive compounds. LDA was subsequently used to fit a classification function. The model showed 92.8% and 91.8% global accuracy and predictability in training and validation studies. This QSAR model was validated through a virtual screening of a series of cournarin derivatives. The 15 selected compounds were prepared and evaluated as in vitro MAO-A inhibitors. The theoretical prediction was' compared with the experimental results and the model correctly predicted 13 compounds with only two mistakes on compounds with activities very close to the cutoff point established for the model. Consequently, this method represents a useful tool for the "in silico" screening of MAO-A inhibitors.