Suppr超能文献

通过基于结构的片段类和先导物类化学文库筛选发现肽结合G蛋白偶联受体的配体

Ligand Discovery for a Peptide-Binding GPCR by Structure-Based Screening of Fragment- and Lead-Like Chemical Libraries.

作者信息

Ranganathan Anirudh, Heine Philipp, Rudling Axel, Plückthun Andreas, Kummer Lutz, Carlsson Jens

机构信息

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University , SE-106 91 Stockholm, Sweden.

Department of Biochemistry, University of Zurich , Winterthurerstrasse 190, 8057 Zurich, Switzerland.

出版信息

ACS Chem Biol. 2017 Mar 17;12(3):735-745. doi: 10.1021/acschembio.6b00646. Epub 2017 Jan 24.

Abstract

Peptide-recognizing G protein-coupled receptors (GPCRs) are promising therapeutic targets but often resist drug discovery efforts. Determination of crystal structures for peptide-binding GPCRs has provided opportunities to explore structure-based methods in lead development. Molecular docking screens of two chemical libraries, containing either fragment- or lead-like compounds, against a neurotensin receptor 1 crystal structure allowed for a comparison between different drug development strategies for peptide-binding GPCRs. A total of 2.3 million molecules were screened computationally, and 25 fragments and 27 leads that were top-ranked in each library were selected for experimental evaluation. Of these, eight fragments and five leads were confirmed as ligands by surface plasmon resonance. The hit rate for the fragment screen (32%) was thus higher than for the lead-like library (19%), but the affinities of the fragments were ∼100-fold lower. Both screens returned unique scaffolds and demonstrated that a crystal structure of a stabilized peptide-binding GPCR can guide the discovery of small-molecule agonists. The complementary advantages of exploring fragment- and lead-like chemical space suggest that these strategies should be applied synergistically in structure-based screens against challenging GPCR targets.

摘要

肽识别G蛋白偶联受体(GPCRs)是很有前景的治疗靶点,但往往难以进行药物研发。肽结合GPCRs晶体结构的测定为在先导化合物开发中探索基于结构的方法提供了机会。针对神经降压素受体1晶体结构对两个分别包含片段样或先导化合物样化合物的化学文库进行分子对接筛选,从而能够比较肽结合GPCRs的不同药物开发策略。总共通过计算筛选了230万个分子,并选择了每个文库中排名靠前的25个片段和27个先导化合物进行实验评估。其中,有8个片段和5个先导化合物通过表面等离子体共振被确认为配体。因此,片段筛选的命中率(32%)高于先导化合物样文库(19%),但片段的亲和力低约100倍。两个筛选都得到了独特的骨架,并证明稳定的肽结合GPCRs的晶体结构可以指导小分子激动剂的发现。探索片段样和先导化合物样化学空间的互补优势表明,这些策略应在针对具有挑战性的GPCR靶点的基于结构的筛选中协同应用。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验