虚拟筛选
G蛋白偶联受体
同源建模
化学
计算生物学
对接(动物)
化学型
配体(生物化学)
受体
药物发现
分子模型
敌手
生物物理学
立体化学
生物化学
生物
医学
色谱法
酶
护理部
精油
作者
Claudio N. Cavasotto,Andrew Orry,Nicholas Murgolo,Michael Czarniecki,Sue Ann Kocsi,Brian E. Hawes,Kim A. O’Neill,Heather Hine,Marybeth S. Burton,Johannes Voigt,Ruben Abagyan,Marvin Bayne,Frederick J. Monsma
摘要
Melanin-concentrating hormone receptor 1 (MCH-R1) is a G-protein-coupled receptor (GPCR) and a target for the development of therapeutics for obesity. The structure-based development of MCH-R1 and other GPCR antagonists is hampered by the lack of an available experimentally determined atomic structure. A ligand-steered homology modeling approach has been developed (where information about existing ligands is used explicitly to shape and optimize the binding site) followed by docking-based virtual screening. Top scoring compounds identified virtually were tested experimentally in an MCH-R1 competitive binding assay, and six novel chemotypes as low micromolar affinity antagonist "hits" were identified. This success rate is more than a 10-fold improvement over random high-throughput screening, which supports our ligand-steered method. Clearly, the ligand-steered homology modeling method reduces the uncertainty of structure modeling for difficult targets like GPCRs.
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