Weiwei Zhang

Publications (3)8.27 Total impact

• Article: Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors.

  Wenting Tai, Tao Lu, Haoliang Yuan, Fengxiao Wang, Haichun Liu, Shuai Lu, Ying Leng, Weiwei Zhang, Yulei Jiang, Yadong Chen
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  ABSTRACT: Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC(50) values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer's randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.
  Journal of Molecular Modeling 12/2011; 18(7):3087-100. · 1.80 Impact Factor
• Article: A selectivity study on mTOR/PI3Kα inhibitors by homology modeling and 3D-QSAR.

  Ting Ran, Tao Lu, Haoliang Yuan, Haichun Liu, Jian Wang, Weiwei Zhang, Ying Leng, Guowu Lin, Shulin Zhuang, Yadong Chen
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  ABSTRACT: The phosphatidylinositol-3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway plays a critical role in the regulation of cellular growth, survival and proliferation. mTOR and PI3K have attracted particular attention as cancer targets. These kinases belong to the phosphatidylinositol-3-kinase-related kinase (PIKK) family and therefore have considerable homology in their active sites. To accelerate the discovery of inhibitors with selective activity against mTOR and PI3K as cancer targets, in this work, a homology model of mTOR was developed to identify the structural divergence in the active sites between mTOR and PI3Kα. Furthermore, two highly predictive comparative molecular similarity index analyses (CoMSIA) models were built based on 304 selective inhibitors docked into mTOR and PI3Kα, respectively (mTOR: q(2) = 0.658, r(pre)(2) = 0.839; PI3Kα: q(2) = 0.540, r(pre)(2) = 0.719). The results showed that steric and electrostatic fields have an important influence on selectivity towards mTOR and PI3Kα-a finding consistent with the structural divergence between the active sites. The findings may be helpful in investigating selective mTOR/PI3Kα inhibitors.
  Journal of Molecular Modeling 04/2011; 18(1):171-86. · 1.80 Impact Factor
• Article: Novel strategy for three-dimensional fragment-based lead discovery.

  Haoliang Yuan, Tao Lu, Ting Ran, Haichun Liu, Shuai Lu, Wenting Tai, Ying Leng, Weiwei Zhang, Jian Wang, Yadong Chen
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  ABSTRACT: Fragment-based drug design (FBDD) is considered a promising approach in lead discovery. However, for a practical application of this approach, problems remain to be solved. Hence, a novel practical strategy for three-dimensional lead discovery is presented in this work. Diverse fragments with spatial positions and orientations retained in separately adjacent regions were generated by deconstructing well-aligned known inhibitors in the same target active site. These three-dimensional fragments retained their original binding modes in the process of new molecule construction by fragment linking and merging. Root-mean-square deviation (rmsd) values were used to evaluate the conformational changes of the component fragments in the final compounds and to identify the potential leads as the main criteria. Furthermore, the successful validation of our strategy is presented on the basis of two relevant tumor targets (CDK2 and c-Met), demonstrating the potential of our strategy to facilitate lead discovery against some drug targets.
  Journal of Chemical Information and Modeling 03/2011; 51(4):959-74. · 4.68 Impact Factor