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Updated: Jan 7, 2026

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

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几何深度学习有助于蛋白质工程. 机遇和挑战 机遇和挑战

Julián García-Vinuesa1, Jorge Rojas2, Nicole Soto-García2

  • 1Departamento de Ingeniería Química, Biotecnología y Materiales, Universidad de Chile, Beauchef 851, Santiago, Chile; Centre for Biotechnology and Bioengineering, CeBiB, Beauchef 851, Universidad de Chile, Santiago, Chile.

Biotechnology advances
|December 28, 2025
PubMed
概括

几何深度学习 (GDL) 通过分析复杂的结构数据,彻底改变了蛋白质工程,克服了用于增强蛋白质设计和功能预测的传统方法的局限性.

关键词:
几何深度学习的几何深度学习机器学习 机器学习蛋白质的设计 蛋白质的设计蛋白质工程是一种蛋白质工程.蛋白质结构预测 蛋白质结构预测

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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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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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