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De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction

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Abstract

Vascular endothelial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR) have been identified as promising targets for novel anticancer agents. To achieve new potent inhibitors of KDR, we conducted molecular fragment replacement (MFR) studies for the understanding of 3D-QSAR modeling and the docking investigation of arylphthalazines and 2-((1H-Azol-1-yl)methyl)-N-arylbenzamides-based KDR inhibitors. Two favorable 3D-QSAR models (CoMFA with q 2, 0.671; r 2, 0.969; CoMSIA with q 2, 0.608; r 2, 0.936) have been developed to predict the biological activity of new compounds. The new molecular database generated by MFR was virtually screened using Glide (docking) and further evaluated with CoMFA prediction, protein–ligand interaction fingerprint (PLIF) and ADMET analysis. 44 N-(pyridin-4-ylmethyl)aniline derivatives as novel potential KDR inhibitors were finally obtained. In this paper, the work flow developed could be applied to de novo drug design and virtual screening potential KDR inhibitors, and use hit compounds to further optimize and design new potential KDR inhibitors.

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Authors and Affiliations

  1. Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing, 210009, China

    Yanmin Zhang, Haichun Liu, Yu Jiao, Haoliang Yuan, Fengxiao Wang, Shuai Lu, Sihui Yao, Zhipeng Ke, Wenting Tai, Yulei Jiang, Yadong Chen & Tao Lu

  2. State Key Laboratory of Natural Medicines, China Pharmaceutical University, 24 Tongjiaxiang, Nanjing, 210009, China

    Tao Lu

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  1. Yanmin Zhang
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  2. Haichun Liu
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Correspondence to Yadong Chen or Tao Lu.

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Zhang, Y., Liu, H., Jiao, Y. et al. De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction. Mol Divers 16, 787–802 (2012). https://doi.org/10.1007/s11030-012-9405-y

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