Search research articles

关于 JoVE

概览领导团队博客 JoVE 帮助中心

作者

出版流程编辑委员会范围与政策同行评审常见问题投稿

图书馆员

用户评价订阅访问资源图书馆顾问委员会常见问题

研究

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

Drug Discovery: Overview

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

Antibiotic Selection

Antibiotic Selection

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序

Same author

'Megacluster' of genes enables bacteria to make potent antibiotic mixture.

Nature·2026

Same author

Scoring gene importance by interpreting single-cell foundation models.

Nature biotechnology·2026

Same author

Outer membrane vesicles hijack TIM-1 for cellular uptake.

PLoS pathogens·2026

Same author

Decoding sequence determinants of gene expression in diverse cellular and disease states.

Nature methods·2026

Same author

Disordered protein LAT encodes relative levels of signaling pathways in T cell activation.

Science (New York, N.Y.)·2026

Same author

Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data.

Genome biology·2026

Search research articles

相关实验视频

Updated: Jan 14, 2026

A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules

A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules

Published on: March 10, 2017

基于深度学习的抗菌化合物的虚拟查.

Gabriele Scalia¹, Steven T Rutherford², Ziqing Lu³

¹gRED Computational Sciences, Genentech Research and Early Development, San Francisco, CA, USA. scalia.gabriele@gene.com.

Nature biotechnology

|October 24, 2025

概括

此摘要是机器生成的。

新的深度学习模型通过选数十亿个分子来加速抗生素的发现,识别具有改进的命中率和独特结构的抗菌化合物.

更多相关视频

High-throughput Screening for Broad-spectrum Chemical Inhibitors of RNA Viruses

High-throughput Screening for Broad-spectrum Chemical Inhibitors of RNA Viruses

Published on: May 5, 2014

System for Efficacy and Cytotoxicity Screening of Inhibitors Targeting Intracellular Mycobacterium tuberculosis

System for Efficacy and Cytotoxicity Screening of Inhibitors Targeting Intracellular Mycobacterium tuberculosis

Published on: April 5, 2017

相关实验视频

Last Updated: Jan 14, 2026

A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules

A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules

Published on: March 10, 2017

High-throughput Screening for Broad-spectrum Chemical Inhibitors of RNA Viruses

High-throughput Screening for Broad-spectrum Chemical Inhibitors of RNA Viruses

Published on: May 5, 2014

System for Efficacy and Cytotoxicity Screening of Inhibitors Targeting Intracellular Mycobacterium tuberculosis

System for Efficacy and Cytotoxicity Screening of Inhibitors Targeting Intracellular Mycobacterium tuberculosis

Published on: April 5, 2017

科学领域:

药用化学医学化学
计算生物学计算生物学
微生物学微生物学

背景情况:

越来越多的抗药性细菌需要新型抗生素的开发.
现有的抗生素发现方法面临速度和范围的局限性.

研究的目的:

将高通量查 (HTS) 与深度学习 (DL) 整合起来,以实现高效的抗菌发现.
开发和验证用于预测抗菌活性的DL模型 (GNEprop).
识别具有高强度和选择性的新型抗菌化合物.

主要方法:

使用HTS对敏感的大肠杆菌菌株选了大约200万个小分子.
在HTS数据上训练了一种DL模型 (GNEprop),以预测抗菌活性.
通过训练DL模型对超过14亿种化合物进行虚拟选.

主要成果:

识别了成千上万的HTS最初的成功.
与HTS相比,在虚拟选中实现了90倍更好的成功率.
发现了82种具有抗菌活性的化合物,其中许多与已知的抗生素不同.
对于新发现的化合物,已验证的特定生物标.

结论:

综合的HTS和DL方法显著提高了抗菌发现效率.
GNEprop模型表现出强大的预测能力和概括能力.
鉴定出新的抗菌候选药物为对抗耐药性细菌感染提供了有希望的途径.