Nagamani Selvaraman, Kesavan Chandrasekhar, Muthusamy Karthikeyan
Deparment of Bioinformatics, Alagappa University, Karaikudi 630 004, Tamil Nadu, India.
Musculoskeletal Disease Center, JLP VA Medical Center, Loma Linda, CA 92357, United States.
Comb Chem High Throughput Screen. 2018;21(5):329-343. doi: 10.2174/1386207321666180607101720.
Vitamin D3 (1,25(OH)2D3) is a biologically active metabolite and plays a wide variety of regulatory functions in human systems. Currently, several Vitamin D analogues have been synthesized and tested against VDR (Vitamin D Receptor). Electrostatic potential methods are greatly influence the structure-based drug discovery. In this study, ab inito (DFT, HF, LMP2) and semi-empirical (RM1, AM1, PM3, MNDO, MNDO/d) charges were examined on the basis of their concert in predicting the docking pose using Induced Fit Docking (IFD) and binding free energy calculations against the VDR.
Initially, we applied ab initio and semi-empirical charges to the 38 vitamin D analogues. Further, the charged analogues have been docked in the VDR active site. We generated the structure-based 3D-QSAR from the docked conformation of vitamin D analogues. On the other hand, we performed pharmacophore-based 3D-QSAR.
The result shows that, AM1 is the good charge model for our study and AM1 charge based QSAR produced more accurate ligand poses. Furthermore, the hydroxyl group in the side chain of vitamin D analogues played an important role in the VDR antagonistic activity.
Overall, we found that charge-based optimizations of ligands were out performed than the pharmacophore based QSAR model.
维生素D3（1,25-二羟基维生素D3）是一种生物活性代谢产物，在人体系统中发挥多种调节功能。目前，已经合成了几种维生素D类似物并针对维生素D受体（VDR）进行了测试。静电势方法对基于结构的药物发现有很大影响。在本研究中，基于从头算（DFT、HF、LMP2）和半经验（RM1、AM1、PM3、MNDO、MNDO/d）电荷在使用诱导契合对接（IFD）预测对接姿势以及针对VDR进行结合自由能计算方面的协同作用进行了研究。
首先，我们将从头算和半经验电荷应用于38种维生素D类似物。此外，将带电荷的类似物对接至VDR活性位点。我们从维生素D类似物的对接构象生成基于结构的3D-QSAR。另一方面，我们进行了基于药效团的3D-QSAR。
结果表明，AM1是我们研究中的良好电荷模型，基于AM1电荷的QSAR产生了更准确的配体姿势。此外，维生素D类似物侧链中的羟基在VDR拮抗活性中起重要作用。
总体而言，我们发现基于电荷的配体优化比基于药效团的QSAR模型表现更好。
