Molecular modeling on pyrimidine-urea inhibitors of TNF-α production: an integrated approach using a combination of molecular docking, classification techniques, and 3D-QSAR CoMSIA

Journal of Chemical Information and Modeling
Varnavas D MouchlisAntreas Afantitis

Abstract

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-α production. Using the crystal structure of p38α, 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. "Active" and "inactive" 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 IC(50) values. This novel multistep framework gives insight into the structural characteristics that affect the binding and the inhibitory activity of these analogues on p38α 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.

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Citations

Sep 27, 2014·International Journal of Molecular Sciences·Mingwei WuLing Yang
Oct 23, 2015·Environmental Science and Pollution Research International·Pingru SuZhemin Shen
Nov 26, 2015·BMC Complementary and Alternative Medicine·Sarbani Dey RaySaikat Dewanjee
Dec 3, 2020·Scientific Reports·Komal ZiaZaheer Ul-Haq
Dec 24, 2021·Chemical Biology & Drug Design·Shiyang Zhou, Gangliang Huang

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