Prediction and evaluation of the lipase inhibitory activities of tea polyphenols with 3D-QSAR models.

The extraordinary hypolipidemic effects of polyphenolic compounds from tea have been confirmed in our previous study. To gain compounds with more potent activities, using the conformations of the most active compound revealed by molecular docking, a 3D-QSAR pancreatic lipase inhibitor model with good predictive ability was established and validated by CoMFA and CoMISA methods. With good statistical significance in CoMFA (r2cv = 0.622, r2 = 0.956, F = 261.463, SEE = 0.096) and CoMISA (r2cv = 0.631, r2 = 0.932, F = 75.408, SEE = 0.212) model, we summarized the structure-activity relationship between polyphenolic compounds and pancreatic lipase inhibitory activities and find the bulky substituents in R2, R4 and R5, hydrophilic substituents in R1 and electron withdrawing groups in R2 are the key factors to enhance the lipase inhibitory activities. Under the guidance of the 3D-QSAR results, (2R,3R,2'R,3'R)-desgalloyloolongtheanin-3,3'-O-digallate (DOTD), a potent lipase inhibitor with an IC50 of 0.08 µg/ml, was obtained from EGCG oxidative polymerization catalyzed by crude polyphenol oxidase. Furthermore, DOTD was found to inhibit lipid absorption in olive oil-loaded rats, which was related with inhibiting the activities of lipase in the intestinal mucosa and contents.

Design and prediction of new anticoagulants as a selective Factor IXa inhibitor via three-dimensional quantitative structure-property relationships of amidinobenzothiophene derivatives.

Factor IXa (FIXa), a blood coagulation factor, is specifically inhibited at the initiation stage of the coagulation cascade, promising an excellent approach for developing selective and safe anticoagulants. Eighty-four amidinobenzothiophene antithrombotic derivatives targeting FIXa were selected to establish three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models using comparative molecular field analysis and comparative similarity indices analysis methods. Internal and external cross-validation techniques were investigated as well as region focusing and bootstrapping. The satisfactory q (2) values of 0.753 and 0.770, and r (2) values of 0.940 and 0.965 for 3D-QSAR and 3D-QSSR, respectively, indicated that the models are available to predict both the inhibitory activity and selectivity on FIXa against Factor Xa, the activated status of Factor X. This work revealed that the steric, hydrophobic, and H-bond factors should appropriately be taken into account in future rational design, especially the modifications at the 2'-position of the benzene and the 6-position of the benzothiophene in the R group, providing helpful clues to design more active and selective FIXa inhibitors for the treatment of thrombosis. On the basis of the three-dimensional quantitative structure-property relationships, 16 new potent molecules have been designed and are predicted to be more active and selective than Compound 33, which has the best activity as reported in the literature.