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Updated: Jun 25, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

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DDMut-PPI:使用基于图形的深度学习预测突变对蛋白质-蛋白质相互作用的影响.

Yunzhuo Zhou1,2, YooChan Myung1,2, Carlos H M Rodrigues1

  • 1The Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, University of Queensland, St Lucia, Queensland 4072, Australia.

Nucleic acids research
|May 23, 2024
PubMed
概括

DDMut-PPI是一种新的深度学习模型,准确地预测突变如何影响蛋白质与蛋白质相互作用 (PPI). 该工具增强了对疾病机制的理解,并通过分析绑定自由能量变化来帮助开发新疗法.

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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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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
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