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利用机器人合成的可溶性文库进行肽和非肽先导化合物的发现。

Peptide and nonpeptide lead discovery using robotically synthesized soluble libraries.

作者信息

Fauchère J L, Henlin J M, Boutin J A

机构信息

Institut de recherches Servier, Suresnes, France.

出版信息

Can J Physiol Pharmacol. 1997 Jun;75(6):683-9.

PMID:9276149
Abstract

The method of combinatorial synthesis of peptide and nonpeptide libraries on solid phase is analyzed and the automation of the mix and divide key step described. A set of amino acids leading to a high molecular diversity is proposed as well as a number of scaffolds for the preparation of variable polyamide libraries. Adequacy of the resin bead quantities to library size and to the ratio of the synthesized peptide types is discussed. Examples of the use of capillary electrophoresis and of spectroscopic methods (MS, MS/MS, and NMR) for the analysis of the library content are given. The iterative deconvolution SURF (synthetic unrandomization of randomized fragments) is compared with positional scanning and the success of coupling of mixtures evaluated. It is concluded that extension of the original mix and divide method and the SURF deconvolution (as proposed by Houghten et al. Nature (London), 354: 84-86 1991) to nonpeptide libraries affords new leads that can be optimized towards useful therapeutics.

摘要

分析了在固相上进行肽和非肽文库组合合成的方法,并描述了混合与分割关键步骤的自动化过程。提出了一组能产生高分子多样性的氨基酸,以及一些用于制备可变聚酰胺文库的支架。讨论了树脂珠数量与文库大小以及合成肽类型比例的适配性。给出了使用毛细管电泳和光谱方法(质谱、串联质谱和核磁共振)分析文库内容的实例。将迭代反卷积SURF(随机片段的合成非随机化)与位置扫描进行了比较,并评估了混合物偶联的成功率。得出的结论是,将原始的混合与分割方法以及SURF反卷积(如霍顿等人在《自然》(伦敦),354:84 - 86,1991年所提出)扩展到非肽文库可提供新的线索,这些线索可针对有用的治疗方法进行优化。

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