Floresta Giuseppe, Cilibrizzi Agostino, Abbate Vincenzo, Spampinato Ambra, Zagni Chiara, Rescifina Antonio
Department of Drug Sciences, University of Catania, V.le A. Doria 6, 95125 Catania, Italy.
Department of Chemical Sciences, University of Catania, V.le A. Doria, 95125 Catania, Italy.
Data Brief. 2018 Dec 19;22:471-483. doi: 10.1016/j.dib.2018.12.047. eCollection 2019 Feb.
The data have been obtained from FABP4 inhibitor molecules previously published. The 120 compounds were used to build a 3D-QSAR model. The development of the QSAR model has been undertaken with the use of Forge software using the PM3 optimized structure and the experimental IC of each compound. The QSAR model was also employed to predict the activity of 3000 new isosteric derivatives of BMS309403. The isosteric replacement was also validated by the synthesis and the biological screening of three new compounds reported in the related research article "3D-QSAR assisted identification of FABP4 inhibitors: An effective scaffold hopping analysis/QSAR evaluation" (Floresta et al., 2019).
这些数据取自先前发表的脂肪酸结合蛋白4（FABP4）抑制剂分子。这120种化合物被用于构建一个三维定量构效关系（3D-QSAR）模型。使用Forge软件，利用PM3优化结构和每种化合物的实验抑制常数（IC）来开展QSAR模型的开发。该QSAR模型还被用于预测BMS309403的3000种新的等排衍生物的活性。相关研究文章《3D-QSAR辅助鉴定FABP4抑制剂：有效的骨架跃迁分析/QSAR评估》（弗洛雷斯塔等人，2019年）中报道的三种新化合物的合成及生物学筛选也验证了等排取代。
