WeChat Mini Program
Old Version Features

高通量筛选靶向革兰阴性菌BamA蛋白的小分子药物初步研究

Chinese Journal of Laboratory Medicine(2023)

Cited 0|Views17
Abstract
目的:通过高通量筛选获得针对革兰阴性杆菌BamA外膜蛋白的小分子抗菌药物。方法:6株鲍曼不动杆菌临床菌株于2022年1—12月分离自中南大学湘雅三医院住院患者。基于分子对接试验,利用sybyl-X2.1软件对Chemdiv化合物数据库中的小分子化合物进行高通量虚拟筛选;对高通量筛选打分排名靠前的150个小分子进行体外生物学试验筛选,选取具有最佳抗菌活性的前4个小分子进行深入的分子对接分析,并选取对接分数最高的小分子8308-0401进行后续试验;通过棋盘稀释试验检测8308-0401与利福平的联用抗菌效果;最后,通过等离子表面共振试验检测8308-0401与靶蛋白BamA的亲合力。结果:通过高通量虚拟筛选,发现了排名靠前的150个小分子的对接打分平均为5.63;通过体外生物学试验,发现了小分子8308-0401、8365-1335、C066-2507和L582-0346具有较强的抗菌活性;其中,8308-0401具有最高的分子对接分数,且与利福平联用对鲍曼不动杆菌标准菌株和临床菌株均具有协同抗菌活性;8308-0401与靶蛋白BamA具有较强的亲合力,其结合常数为182 μmol/L。结论:小分子8308-0401可靶向革兰阴性杆菌BamA外膜蛋白而发挥抗菌活性。
More
Translated text
Key words
Small molecule libraries,Bacterial outer membrane protein,Drug synergism,Acinetobacter baumannii,High-throughput screening assay
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