Thromboxane modulating agents. 2. Thromboxane receptor antagonists derived from the thromboxane synthase inhibitor dazmegrel

Classification models and SAR analysis on thromboxane A2 synthase inhibitors by machine learning methods

Thromboxane A2 synthase (TXS) is a promising drug target for cardiovascular diseases and cancer. In this work, we conducted a structure-activity relationship (SAR) study on 526 TXS inhibitors for bioactivity prediction. Three types of descriptors (MACCS fingerprints, ECFP4 fingerprints, and MOE descriptors) were utilized to characterize inhibitors, 24 classification models were developed by support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and deep neural networks (DNN). Then we reduced the number of fingerprints according to the contribution of descriptors to the models, and constructed 16 extra models on simplified fingerprints. In general, Model_4D built by DNN algorithm and 67 bits MACCS fingerprints performs best. The prediction accuracy of the model on the test set is 0.969, and Matthews correlation coefficient (MCC) is 0.936. The distance between compound and model (dSTD-PRO) was used to characterize the application domain of the model. In the test set of Model_4D, dSTD-PRO of 91.5% compounds is lower than the corresponding training set threshold (threshold0.90 = 0.1055), and the accuracy of these compounds is 0.983. In addition, the important descriptors were summarized and further analyzed. It showed that aromatic nitrogenous heterocyclic groups were beneficial to improve the bioactivity of TXS inhibitors.

Human thromboxane synthase: comparative modeling and docking evaluation with the competitive inhibitors Dazoxiben and Ozagrel

Thromboxane synthase (TXAS) is a P450 epoxygenase that synthesizes thromboxane A2 (TXA2), a potent mediator of platelet aggregation, vasoconstriction and bronchoconstriction. This enzyme plays an important role in several human diseases, including myocardial infarction, stroke, septic shock, asthma and cancer. Despite of the increasing interest on developing TXAS inhibitors, the structure and activity of TXAS are still not totally elucidated. In this study, we used a comparative molecular modeling approach to construct a reliable model of TXAS and analyze its interactions with Dazoxiben and Ozagrel, two competitive inhibitors. Our results were compatible with experimental published data, showing feasible cation-π interaction between the iron atom of the heme group of TXAS and the basic nitrogen atom of the imidazolyl group of those inhibitors. In the absence of the experimental structure of thromboxane synthase, this freely available model may be useful for designing new antiplatelet drugs for diseases related with TXA2.

Thromboxane modulating agents. 4. Design and synthesis of 3-(2-[[(4-chlorophenyl)sulfonyl]-amino]ethyl)benzenepropanoic acid derivatives as potent thromboxane receptor antagonists

The design of a series of thromboxane receptor antagonists based on 3-(2-[[(4-chlorophenyl)sulfonyl]amino]ethyl)benzenepropanoic acid (1) is described. Addition of an arylmethyl group at the 5-position of 1 gave exceptionally potent agents in vitro and in vivo, with 13a (UK-147,535) giving complete blockade of the TxA2 receptor for greater than 12 hours in dogs, following an oral dose of 0.1 mg/kg.