Molecular Modeling on Pyrimidine-Urea Inhibitors of TNF-伪 Production: An Integrated Approach Using a Combination of Molecular Docking, Classification Techniques, and 3D-QSAR CoMSIA
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- 作者：Varnavas D. Mouchlis ; Georgia Melagraki ; Thomas Mavromoustakos ; George Kollias ; Antreas Afantitis
- 刊名：Journal of Chemical Information and Modeling
- 出版年：2012
- 出版时间：March 26, 2012
- 年：2012
- 卷：52
- 期：3
- 页码：711-723
- 全文大小：467K
- 年卷期：v.52,no.3(March 26, 2012)
- ISSN：1549-960X
文摘
Molecular docking, classification techniques, and 3D-QSAR CoMSIA were combined in a multistep framework with the ultimate goal of identifying potent pyrimidine-urea inhibitors of TNF-伪 production. Using the crystal structure of p38伪, all the compounds were docked into the enzyme active site. The docking pose of each compound was subsequently used in a receptor-based alignment for the generation of the CoMSIA fields. 鈥淎ctive鈥?and 鈥渋nactive鈥?compounds were used to build a Random Tree classification model using the docking score and the CoMSIA fields as input parameters. Domain of applicability indicated the compounds for which activity estimations can be accepted with confidence. For the active compounds, a 3D-QSAR CoMSIA model was subsequently built to accurately estimate the IC50 values. This novel multistep framework gives insight into the structural characteristics that affect the binding and the inhibitory activity of these analogues on p38伪 MAP kinase, and it can be extended to other classes of small-molecule inhibitors. In addition, the simplicity of the proposed approach provides expansion to its applicability such as in virtual screening procedures.