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首页> 外文期刊>RSC Advances >Sequential ligand- and structure-based virtual screening approach for the identification of potential G protein-coupled estrogen receptor-1 (GPER-1) modulators
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Sequential ligand- and structure-based virtual screening approach for the identification of potential G protein-coupled estrogen receptor-1 (GPER-1) modulators

机译:基于序列配体和结构的虚拟筛选方法,用于识别潜在的G蛋白偶联雌激素受体1(GPER-1)调节剂

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G protein-coupled estrogen receptor-1 (GPER-1) is a seven transmembrane receptor, responsible for mediating rapid estrogen signaling in many physiological responses in reproductive, nervous, endocrine, immune and cardiovascular systems. Due to unavailability of the crystal structure of GPER-1, we have performed sequential ligand-based virtual screening (LBVS) and structure-based screening (SBVS) to identify potential GPER-1 modulators. LBVS and SBVS approaches were validated retrospectively using the Receiver Operating Curve (ROC) plot and the early Enrichment Factor (EF). LBVS was performed based on a GPER-1 agonist, G1, as a query model for screening of the eMolecules library using the Rapid Overlay of Chemical Structure (ROCS) and the electrostatic potential screening (EON) approaches. Top-scored hits from LBVS were further screened by SBVS. SBVS was based on generating homology models of GPER-1 and subsequent molecular docking studies. Using Chemguass4 score, we filtered the final hits with the higher score in comparison to G1 (Chemguass4 score = ?11.575). The top-ranked hits were clustered based on similarity in their scaffolds. Prospective validation was performed by evaluating the antiproliferative activity of synthesized compounds ( SK0 and SK0P ) which were representative of top hits obtained from our virtual screening approach.
机译:G蛋白偶联雌激素受体1(GPER-1)是七种跨膜受体,负责在生殖,神经,内分泌,免疫和心血管系统的许多生理反应中介导快速雌激素信号传导。由于无法获得GPER-1的晶体结构,我们已经进行了基于配体的顺序虚拟筛选(LBVS)和基于结构的筛选(SBVS),以识别潜在的GPER-1调节剂。 LBVS和SBVS方法已使用接收器工作曲线(ROC)图和早期富集因子(EF)进行了回顾性验证。 LBVS是基于GPER-1激动剂G1作为查询模型进行的,该查询模型使用化学结构快速叠加(ROCS)和静电势筛选(EON)方法筛选eMolecules文库。 SBVS进一步筛选了LBVS得分最高的匹配项。 SBVS基于生成GPER-1的同源性模型和随后的分子对接研究。使用Chemguass4分数,我们筛选出了比G1高的分数(Chemguass4分数=?11.575)。排名最高的命中根据其支架的相似性进行聚类。通过评估合成化合物(SK0和SK0P)的抗增殖活性进行了前瞻性验证,这些化合物代表了从我们的虚拟筛选方法中获得的最高成功率。

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