Triballeau Nicolas, Van Name Eric, Laslier Guillaume, Cai Diana, Paillard Guillaume, Sorensen Peter W, Hoffmann Rémy, Bertrand Hugues-Olivier, Ngai John, Acher Francine C
Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, CNRS UMR-8601, Université Paris Descartes, 45 rue des Saints Pères, 75270 Paris Cedex 06, France.
Neuron. 2008 Dec 10;60(5):767-74. doi: 10.1016/j.neuron.2008.11.014.
The detection of diverse chemical structures by the vertebrate olfactory system is accomplished by the recognition of odorous ligands by their cognate receptors. In the present study, we used computational screening to discover novel high-affinity agonists of an olfactory G protein-coupled receptor that recognizes amino acid ligands. Functional testing of the top candidates validated several agonists with potencies higher than any of the receptor's known natural ligands. Computational modeling revealed molecular interactions involved in ligand binding and further highlighted interactions that have been conserved in evolutionarily divergent amino acid receptors. Significantly, the top compounds display robust activities as odorants in vivo and include a natural product that may be used to signal the presence of bacteria in the environment. Our virtual screening approach should be applicable to the identification of new bioactive molecules for probing the structure of chemosensory receptors and the function of chemosensory systems in vivo.
脊椎动物嗅觉系统对多种化学结构的检测是通过其同源受体识别气味配体来实现的。在本研究中,我们利用计算机筛选来发现一种识别氨基酸配体的嗅觉G蛋白偶联受体的新型高亲和力激动剂。对顶级候选物的功能测试验证了几种激动剂,其效力高于该受体任何已知的天然配体。计算机建模揭示了配体结合中涉及的分子相互作用,并进一步突出了在进化上不同的氨基酸受体中保守的相互作用。值得注意的是,顶级化合物在体内作为气味剂表现出强大的活性,其中包括一种天然产物,可用于指示环境中细菌的存在。我们的虚拟筛选方法应适用于鉴定新的生物活性分子,以探究化学感应受体的结构和体内化学感应系统的功能。