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一种用于基于片段的先导化合物发现的自动化微量热泳筛选方法。

An Automated Microscale Thermophoresis Screening Approach for Fragment-Based Lead Discovery.

作者信息

Linke Pawel, Amaning Kwame, Maschberger Melanie, Vallee Francois, Steier Valerie, Baaske Philipp, Duhr Stefan, Breitsprecher Dennis, Rak Alexey

机构信息

NanoTemper Technologies GmbH, Munich, Germany.

Sanofi R&D, Structure-Design-Informatics, Vitry sur Seine, France.

出版信息

J Biomol Screen. 2016 Apr;21(4):414-21. doi: 10.1177/1087057115618347. Epub 2015 Dec 2.

DOI:10.1177/1087057115618347
PMID:26637553
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4800460/
Abstract

Fragment-based lead discovery has proved to be an effective alternative to high-throughput screenings in identifying chemical matter that can be developed into robust lead compounds. The search for optimal combinations of biophysical techniques that can correctly and efficiently identify and quantify binding can be challenging due to the physicochemical properties of fragments. In order to minimize the time and costs of screening, optimal combinations of biophysical techniques with maximal information content, sensitivity, and robustness are needed. Here we describe an approach utilizing automated microscale thermophoresis (MST) affinity screening to identify fragments active against MEK1 kinase. MST identified multiple hits that were confirmed by X-ray crystallography but not detected by orthogonal methods. Furthermore, MST also provided information about ligand-induced aggregation and protein denaturation. The technique delivered a large number of binders while reducing experimentation time and sample consumption, demonstrating the potential of MST to execute and maximize the efficacy of fragment screening campaigns.

摘要

基于片段的先导化合物发现已被证明是高通量筛选的一种有效替代方法,可用于识别能够开发成强大先导化合物的化学物质。由于片段的物理化学性质,寻找能够正确且有效地识别和量化结合的生物物理技术的最佳组合可能具有挑战性。为了将筛选的时间和成本降至最低,需要具有最大信息含量、灵敏度和稳健性的生物物理技术的最佳组合。在此,我们描述了一种利用自动微量热泳动(MST)亲和力筛选来识别对MEK1激酶有活性的片段的方法。MST鉴定出多个命中片段,这些片段通过X射线晶体学得到证实,但未被正交方法检测到。此外,MST还提供了有关配体诱导的聚集和蛋白质变性的信息。该技术在减少实验时间和样品消耗的同时提供了大量结合物,证明了MST在执行片段筛选活动并使其功效最大化方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/3cf98cfdf32b/10.1177_1087057115618347-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/81a282d1cf5b/10.1177_1087057115618347-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/3d0f6510b49c/10.1177_1087057115618347-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/8ab5f1ce3d15/10.1177_1087057115618347-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/3cf98cfdf32b/10.1177_1087057115618347-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/81a282d1cf5b/10.1177_1087057115618347-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/3d0f6510b49c/10.1177_1087057115618347-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/8ab5f1ce3d15/10.1177_1087057115618347-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34fe/4800460/3cf98cfdf32b/10.1177_1087057115618347-fig4.jpg

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