Discovery and Characterization of a Water-Soluble Prodrug of a Dual Inhibitor of Bacterial DNA Gyrase and Topoisomerase IV
ACS medicinal chemistry letters(2015)SCI 3区SCI 2区
Vertex Pharmaceut Inc | Hartford Hosp
Abstract
Benzimidazole 1 is the lead compound resulting from an antibacterial program targeting dual inhibitors of bacterial DNA gyrase and topoisomerase IV. With the goal of improving key drug-like properties, namely, the solubility and the formulability of 1, an effort to identify prodrugs was undertaken. This has led to the discovery of a phosphate ester prodrug 2. This prodrug is rapidly cleaved to the parent drug molecule upon both oral and intravenous administration. The prodrug achieved equivalent exposure of 1 compared to dosing the parent in multiple species. The prodrug 2 has improved aqueous solubility, simplifying both intravenous and oral formulation.
MoreTranslated text
Key words
Prodrug,DNA gyrase,topoisomerase IV,water soluble
PDF
View via Publisher
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
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2019
被引用14 | 浏览
2019
被引用20 | 浏览
2020
被引用24 | 浏览
2020
被引用8 | 浏览
2017
被引用17 | 浏览
2021
被引用7 | 浏览
2021
被引用0 | 浏览
2022
被引用0 | 浏览
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
去 AI 文献库 对话