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.
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