Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
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 JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Microorganisms in Medicine and Therapeutics01:29

Microorganisms in Medicine and Therapeutics

911
Microorganisms play a fundamental role in vaccine development, gene therapy, and therapeutic production. Their biological properties are harnessed to advance medicine and public health. Beyond immunization, microorganisms contribute to gut health, antibiotic synthesis, and genetic disease treatment.Live Attenuated and Inactivated VaccinesLive attenuated vaccines, such as the measles, mumps, and rubella (MMR) vaccine, utilize weakened forms of pathogens to closely resemble natural infections.
911

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

TROP-2 in Solid Tumors: From Oncogenic Driver to Therapeutic Target with Antibody-Drug Conjugates.

Critical reviews in oncology/hematology·2026
Same author

Boundary-Aware Clustering of Spatial Transcriptomics Data Via Fourier Feature Mapping and Dynamic Self-Supervision.

IEEE transactions on computational biology and bioinformatics·2026
Same author

Align Then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Game Theory Inspired Cross-View Interaction Alignment for Partially View-Aligned Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Brassinolide Improves the Tolerance of <i>Hydrilla verticillata</i> to Low-Temperature Stress.

Biology·2026
Same author

Conditional Diffusion Model-Based Method for Annotation of Antibiotic Resistance Gene Properties.

Journal of chemical information and modeling·2026

相关实验视频

Updated: Jan 7, 2026

Development of a Backbone Cyclic Peptide Library as Potential Antiparasitic Therapeutics Using Microwave Irradiation
08:48

Development of a Backbone Cyclic Peptide Library as Potential Antiparasitic Therapeutics Using Microwave Irradiation

Published on: January 26, 2016

12.3K

一个新的生成框架,用于设计具有可编程物理化学性质的病原体向抗微生物.

Weizhong Zhao1,2,3, Kaijieyi Hou1,2,3, Chang Tang1,2,3

  • 1Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, Hubei, China.

PLoS computational biology
|December 29, 2025
PubMed
概括

这项研究引入了一个新的AI框架来设计针对特定细菌的抗微生物 (AMP). 开发的模型在制造有效和安全的AMP来对抗细菌耐药性方面表现出卓越的性能.

更多相关视频

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

888
Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids
11:56

Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids

Published on: May 4, 2018

13.0K

相关实验视频

Last Updated: Jan 7, 2026

Development of a Backbone Cyclic Peptide Library as Potential Antiparasitic Therapeutics Using Microwave Irradiation
08:48

Development of a Backbone Cyclic Peptide Library as Potential Antiparasitic Therapeutics Using Microwave Irradiation

Published on: January 26, 2016

12.3K
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

888
Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids
11:56

Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids

Published on: May 4, 2018

13.0K

科学领域:

  • 生物技术是生物技术.
  • 计算生物学 计算生物学
  • 药物发现 药物发现 药物发现

背景情况:

  • 抗微生物药物耐药性构成了全球卫生危机.
  • 现有的新型抗微生物 (AMP) 设计方法在为特定病原体量身定制特性方面存在局限性.

研究的目的:

  • 提出一种新的生成AI框架,用于设计具有可编程物理化学性质的病原体向AMP.
  • 为解决针对特定细菌感染的当前AMP设计策略的局限性.

主要方法:

  • 使用条件变异自编码器 (VAE) 来生成具有可编辑物理化学性质的AMP.
  • 开发了一种条件扩散模型,以学习AMP表征用于病原体向.
  • 针对特定细菌菌株的构建最小抑制度 (MIC) 预测器.

主要成果:

  • 与现有模型相比,拟议的框架证明了针对特定细菌点的优越抗微生物疗效.
  • 对大肠杆菌和金黄色杆菌确定了两种新型明星AMP,具有出色的抗菌活性.
  • 对有利的血液溶解和毒性概况进行评估并确定了AMP.

结论:

  • 该研究为下一代智能平台为抗菌剂设计提供了坚实的技术基础.
  • 该框架允许开发具有针对目标细菌病原体量身定制特性的AMP.
  • 这种方法提供了一个有前途的策略,以打击抗微生物药物耐药性日益增长的威胁.