Abstract
MERTK plays an important role in cell biology and is correlated with many cancers, such as mantle cell lymphomas, pituitary adenomas, and T-cell acute lympholoblastic leukemia. So identification of new MERTK inhibitors is of extreme importance. In this study, 107 MERTK inhibitors with known activities were gathered to generate a ligand-based pharmacophore model (ADDHH.4), followed by building a 3D-QSAR model, which had high value of coefficient of determination (R2=0.9061) and high value of coefficient of determination (Q2=0.7442). For the pharmacophore model, two hydrogen bond donors (D), one hydrogen bond receptor (A), and two hydrophobic groups (H) were considered as the key elements contributing to ligand activity. The model then served to search a drug-like database with 1.5 million molecules, and 47832 hits were obtained. Subsequently, docking procedure was applied on these hits, and 840 compounds were obtained through high-throughput virtual screening (HTVS). Standard precision (SP), extra precision (XP) and rule of five were also used in virtual screening protocol. Finally, six candidates were identified as potential MERTK inhibitors, with the docking mode in MERTK analyzed.
Keywords: MERTK inhibitors, pharmacophore, 3D-QSAR, virtual screening, molecular docking, ADME.
Combinatorial Chemistry & High Throughput Screening
Title:Pharmacophore-Based 3D-QSAR Modeling, Virtual Screening and Molecular Docking Analysis for the Detection of MERTK Inhibitors with Novel Scaffold
Volume: 19 Issue: 1
Author(s): Suwen Zhou, Lu Zhou, Ruguo Cui, Yahui Tian, Xiaoli Li, Rong You and Liangliang Zhong
Affiliation:
Keywords: MERTK inhibitors, pharmacophore, 3D-QSAR, virtual screening, molecular docking, ADME.
Abstract: MERTK plays an important role in cell biology and is correlated with many cancers, such as mantle cell lymphomas, pituitary adenomas, and T-cell acute lympholoblastic leukemia. So identification of new MERTK inhibitors is of extreme importance. In this study, 107 MERTK inhibitors with known activities were gathered to generate a ligand-based pharmacophore model (ADDHH.4), followed by building a 3D-QSAR model, which had high value of coefficient of determination (R2=0.9061) and high value of coefficient of determination (Q2=0.7442). For the pharmacophore model, two hydrogen bond donors (D), one hydrogen bond receptor (A), and two hydrophobic groups (H) were considered as the key elements contributing to ligand activity. The model then served to search a drug-like database with 1.5 million molecules, and 47832 hits were obtained. Subsequently, docking procedure was applied on these hits, and 840 compounds were obtained through high-throughput virtual screening (HTVS). Standard precision (SP), extra precision (XP) and rule of five were also used in virtual screening protocol. Finally, six candidates were identified as potential MERTK inhibitors, with the docking mode in MERTK analyzed.
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Cite this article as:
Zhou Suwen, Zhou Lu, Cui Ruguo, Tian Yahui, Li Xiaoli, You Rong and Zhong Liangliang, Pharmacophore-Based 3D-QSAR Modeling, Virtual Screening and Molecular Docking Analysis for the Detection of MERTK Inhibitors with Novel Scaffold, Combinatorial Chemistry & High Throughput Screening 2016; 19 (1) . https://dx.doi.org/10.2174/1386207319666151203002228
DOI https://dx.doi.org/10.2174/1386207319666151203002228 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
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