WeChat Mini Program
Old Version Features

Quantitative, Wide-Spectrum Kinase Profiling in Live Cells for Assessing the Effect of Cellular ATP on Target Engagement.

Cell chemical biology(2017)

Promega Corp

Cited 205|Views39
Abstract
For kinase inhibitors, intracellular target selectivity is fundamental to pharmacological mechanism. Although a number of acellular techniques have been developed to measure kinase binding or enzymatic inhibition, such approaches can fail to accurately predict engagement in cells. Here we report the application of an energy transfer technique that enabled the first broad-spectrum, equilibrium-based approach to quantitatively profile target occupancy and compound affinity in live cells. Using this method, we performed a selectivity profiling for clinically relevant kinase inhibitors against 178 full-length kinases, and a mechanistic interrogation of the potency offsets observed between cellular and biochemical analysis. For the multikinase inhibitor crizotinib, our approach accurately predicted cellular potency and revealed improved target selectivity compared with biochemical measurements. Due to cellular ATP, a number of putative crizotinib targets are unexpectedly disengaged in live cells at a clinically relevant drug dose.
More
Translated text
Key words
target engagement,BRET,NanoBRET,NanoLuc,kinase,profiling,selectivity,crizotinib,dasatinib,ATP
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined