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Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

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相关实验视频

Updated: Jan 16, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

通过与PepMimic的结合界面模拟来设计.

Xiangzhe Kong^1,2, Rui Jiao^1,2, Haowei Lin^3,4

¹Department of Computer Science and Technology, Tsinghua University, Beijing, China.

Nature biomedical engineering

|October 1, 2025

概括

此摘要是机器生成的。

一个人工智能算法,PepMimic,通过模仿结合接口来创建针对性治疗的类结合剂. 这种方法产生高亲和度,优于随机查,并显示出诊断和治疗的潜力.

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Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Published on: June 20, 2014

Peptide-based Identification of Functional Motifs and their Binding Partners

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

相关实验视频

Last Updated: Jan 16, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Published on: June 20, 2014

Peptide-based Identification of Functional Motifs and their Binding Partners

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

科学领域:

生物技术是生物技术.
人工智能的人工智能
药物发现药物发现药物发现

背景情况:

可以为向治疗提供优势,包括口服生物可用性,细胞透性和高特异性.
传统的小分子和生物制剂在向治疗方面存在局限性.
开发新的结剂对于推进向疗法的发展至关重要.

研究的目的:

开发一种人工智能 (AI) 算法,PepMimic,用于设计结剂.
模仿已知的目标和结合物的结合接口,以创建短结合剂.
探索人工智能设计的的潜力,用于诊断成像和向治疗.

主要方法:

开发了PepMimic,这是一个人工智能算法,通过模仿结合接口来设计结剂.
将PepMimic应用于药物点,包括PD-L1,CD38,BCMA,HER2和CD4.
使用表面等离子体共振成像和体内小鼠模型验证的结剂.

主要成果:

佩普米米克成功设计了具有10^-9 M低的解离常数 (KD) 值的结体.
与随机图书馆查相比,人工智能设计的具有显著更高的结合亲和力.
在乳腺,骨髓瘤和肺瘤小鼠模型中进行了广泛的验证,证实了有效的膜结合.

结论:

PepMimic是一种强大的AI工具,用于设计高亲和度结合剂.
人工智能生成的对临床诊断成像和有针对性的治疗应用具有重大潜力.
这种方法促进了基于的药物发现和开发.