scholarly journals Development of a High-Throughput Fluorescence Polarization Assay to Detect Inhibitors of the FAK–Paxillin Interaction

2019 ◽  
Vol 25 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Timothy Marlowe ◽  
Carlos Alvarado ◽  
Andrew Rivera ◽  
Felicia Lenzo ◽  
Rohini Nott ◽  
...  

Focal adhesion kinase (FAK) is a promising cancer drug target due to its massive overexpression in multiple solid tumors and its critical role in the integration of signals that control proliferation, invasion, apoptosis, and metastasis. Previous FAK drug discovery and high-throughput screening have exclusively focused on the identification of inhibitors that target the kinase domain of FAK. Because FAK is both a kinase and scaffolding protein, the development of novel screening assays that detect inhibitors of FAK protein–protein interactions remains a critical need. In this report, we describe the development of a high-throughput fluorescence polarization (FP) screening assay that measures the interactions between FAK and paxillin, a focal adhesion–associated protein. We designed a tetramethylrhodamine (TAMRA)-tagged paxillin peptide based on the paxillin LD2 motif that binds to the focal adhesion targeting (FAT) domain with significant dynamic range, specificity, variability, stability, and a Z’-factor suitable for high-throughput screening. In addition, we performed a pilot screen of 1593 compounds using this FP assay, showing its feasibility for high-throughput drug screening. Finally, we identified three compounds that show dose-dependent competition of FAT–paxillin binding. This assay represents the first described high-throughput screening assay for FAK scaffold inhibitors and can accelerate drug discovery efforts for this promising drug target.

Molecules ◽  
2019 ◽  
Vol 24 (18) ◽  
pp. 3352 ◽  
Author(s):  
Carlos Alvarado ◽  
Erik Stahl ◽  
Karissa Koessel ◽  
Andrew Rivera ◽  
Brian R. Cherry ◽  
...  

The Focal Adhesion Targeting (FAT) domain of Focal Adhesion Kinase (FAK) is a promising drug target since FAK is overexpressed in many malignancies and promotes cancer cell metastasis. The FAT domain serves as a scaffolding protein, and its interaction with the protein paxillin localizes FAK to focal adhesions. Various studies have highlighted the importance of FAT-paxillin binding in tumor growth, cell invasion, and metastasis. Targeting this interaction through high-throughput screening (HTS) provides a challenge due to the large and complex binding interface. In this report, we describe a novel approach to targeting FAT through fragment-based drug discovery (FBDD). We developed two fragment-based screening assays—a primary SPR assay and a secondary heteronuclear single quantum coherence nuclear magnetic resonance (HSQC-NMR) assay. For SPR, we designed an AviTag construct, optimized SPR buffer conditions, and created mutant controls. For NMR, resonance backbone assignments of the human FAT domain were obtained for the HSQC assay. A 189-compound fragment library from Enamine was screened through our primary SPR assay to demonstrate the feasibility of a FAT-FBDD pipeline, with 19 initial hit compounds. A final total of 11 validated hits were identified after secondary screening on NMR. This screening pipeline is the first FBDD screen of the FAT domain reported and represents a valid method for further drug discovery efforts on this difficult target.


2009 ◽  
Vol 65 ◽  
pp. S120
Author(s):  
Gaku Murakami ◽  
Haruhisa Inoue ◽  
Kayoko Tsukita ◽  
Yasuyuki Asai ◽  
Kazuhiro Aiba ◽  
...  

2019 ◽  
Vol 25 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Brad A. Haubrich ◽  
Chakk Ramesha ◽  
David C. Swinney

Nicotinamide mononucleotide adenylyltransferase (NMNAT; EC 2.7.7.1) catalyzes the reversible production of NAD+ from NMN+ and ATP and is a potential drug target for cancer and neurodegenerative diseases. A sensitive bioluminescent assay format suitable to high-throughput screening (HTS) and mechanistic follow-up has not been reported and is of value to identify new modulators of NMNATs. To this end, we report the development of a bioluminescent assay using Photinus pyralis ATP-dependent luciferase and luciferin for NMNAT1 in a 384-well plate format. We also report a mechanistic follow-up paradigm using this format to determine time dependence and competition with substrates. The assay and follow-up paradigm were used to screen 912 compounds from the National Cancer Institute (NCI) Mechanistic Diversity Set II and the Approved Oncology Set VI against NMNAT1. Twenty inhibitors with greater than 35% inhibition at 20 µM were identified. The follow-up studies showed that seven actives were time-dependent inhibitors of NMNAT1. 2,3-Dibromo-1,4-naphthoquinone was the most potent, time-dependent inhibitor with IC50 values of 0.76 and 0.26 µM for inhibition of the forward and reverse reactions of the enzyme, respectively, and was shown to be NMN and ATP competitive. The bioluminescent NMNAT assay and mechanistic-follow-up will be of use to identify new modulators of NAD biosynthesis.


2013 ◽  
Vol 18 (5) ◽  
pp. 567-575 ◽  
Author(s):  
Claire McWhirter ◽  
Michael Tonge ◽  
Helen Plant ◽  
Ian Hardern ◽  
Willem Nissink ◽  
...  

Flap endonuclease-1 (FEN1) is a highly conserved metallonuclease and is the main human flap endonuclease involved in the recognition and cleavage of single-stranded 5′ overhangs from DNA flap structures. The involvement of FEN1 in multiple DNA metabolism pathways and the identification of FEN1 overexpression in a variety of cancers has led to interest in FEN1 as an oncology target. In this article, we describe the development of a 1536-well high-throughput screening assay based on the change in fluorescence polarization of a FEN1 DNA substrate labeled with Atto495 dye. The assay was subsequently used to screen 850 000 compounds from the AstraZeneca compound collection, with a Z′ factor of 0.66 ± 0.06. Hits were followed up by IC50 determination in both a concentration-response assay and a technology artifact assay.


2010 ◽  
Vol 68 ◽  
pp. e311
Author(s):  
Gaku Murakami ◽  
Haruhisa Inoue ◽  
Kayoko Tsukita ◽  
Yasuyuki Asai ◽  
Kazuhiro Aiba ◽  
...  

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