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Library Screening by Means of Mass Spectrometry (MS) Binding Assays—Exemplarily Demonstrated for a Pseudostatic Library Addressing y-Aminobutyric Acid (GABA) Transporter 1 (GAT1)

机译:通过质谱(MS)结合测定法进行的文库筛选-示例性展示了针对y-氨基丁酸(GABA)转运蛋白1(GAT1)的假静态文库

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In the present study, the application of mass spectrometry (MS) binding assays as a tool for library screening is reported. For library generation, dynamic combinatorial chemistry (DCC) was used. These libraries can be screened by means of MS binding assays when appropriate measures are taken to render the libraries pseudostatic. That way, the efficiency of MS binding assays to determine ligand binding in compound screening with the ease of library generation by DCC is combined. The feasibility of this approach is shown for γ-aminobutyric acid (GABA) transporter 1 (GAT1) as a target, representing the most important subtype of the GABA transporters. For the screening, hydrazone libraries were employed that were generated in the presence of the target by reacting various sets of aldehydes with a hydrazine derivative that is delineated from pi-peridine-3-carboxylic acid (nipecotic acid), a common fragment of known GAT1 inhibitors. To ensure that the library generated is pseudostatic, a large excess of the nipecotic acid derivative is employed. As the library is generated in a buffer system suit- able for binding and the target is already present, the mixtures can be directly analyzed by MS binding assays—the process of library generation and screening thus becoming simple to perform. The binding affinities of the hits identified by deconvolu-tion were confirmed in conventional competitive MS binding assays performed with single compounds obtained by separate synthesis, in this way, two nipecotic acid derivatives exhibiting a biaryl moiety, 1-{2-[2'-(1,1'-biphenyl-2-ylmethylidene)hydrazi-ne]ethyl}piperidine-3-carboxylic acid and 1-(2-{2'-[1-(2-thiophe-nylphenyl)methylidene]hydrazine}ethyl)piperidine-3-carboxylic acid, were found to be potent GAT1 ligands exhibiting pK, values of 6.186 ± 0.028 and 6.229 ±0.039, respectively. This method enables screening of libraries, whether generated by conventional chemistry or DCC, and is applicable to all kinds of targets including membrane-bound targets such as G protein coupled receptors (GPCRs), ion channels and transporters. As such, this strategy displays high potential in the drug discovery process.
机译:在本研究中,报道了质谱(MS)结合测定作为文库筛选工具的应用。对于文库生成,使用了动态组合化学(DCC)。当采取适当的措施使文库具有伪静态性时,可以通过MS结合测定法筛选这些文库。通过这种方式,结合了MS结合测定在化合物筛选中确定配体结合的效率以及DCC产生文库的简便性。以γ-氨基丁酸(GABA)转运蛋白1(GAT1)为靶标,表明了该方法的可行性,代表了GABA转运蛋白的最重要亚型。为了进行筛选,使用了libraries文库,该libraries文库是在靶标存在下通过使各种醛类与肼衍生物反应而生成的,肼衍生物是由已知的GAT1的常见片段-哌啶-3-羧酸(庚酸)描绘的抑制剂。为了确保生成的文库是假静态的,请使用大量过量的菜酸衍生物。由于文库是在适合结合的缓冲液系统中生成的,并且已经存在靶标,因此可以通过MS结合测定法直接分析混合物-库生成和筛选的过程因此变得易于执行。通过反卷积鉴定的命中的结合亲和力在通过单独合成获得的单一化合物进行的常规竞争性MS结合测定中得到了证实,这样,两种具有联芳基部分的1-N-2- [2- [2'- (1,1'-联苯基-2-基亚甲基)肼基]乙基}哌啶-3-羧酸和1-(2- {2'-[1-(2-硫代-苯基苯基)亚甲基]肼}乙基)发现哌啶-3-羧酸是显示pK的有效GAT1配体,pK值分别为6.186±0.028和6.229±0.039。该方法能够筛选通过常规化学方法或DCC生成的文库,并且适用于各种靶标,包括膜结合靶标,例如G蛋白偶联受体(GPCR),离子通道和转运蛋白。这样,该策略在药物发现过程中显示出很高的潜力。

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