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Protein Networks02:26

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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 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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Structure-Activity Relationships and Drug Design01:28

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Drug Design based on Protein Structure Network.

Zhongjie Liang, Guang Hu1

  • 1Center for Systems Biology, Soochow University, Suzhou 215006, China. huguang@suda.edu.cn.

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Summary
This summary is machine-generated.

Protein structure networks (PSNs) offer a computational approach to understand protein structure and function. These networks are emerging as valuable tools for advancing structure-based drug design and exploring polypharmacology for complex diseases.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Drug Discovery

Background:

  • Structure-based drug design (SBDD) is crucial but faces challenges.
  • Systems biology and 'omics' advances enable polypharmacology for complex diseases.
  • Protein structure networks (PSNs) model proteins as residue interaction networks.

Purpose of the Study:

  • To provide an overview of recent advances in PSNs.
  • To discuss the pharmacological applications of PSN concepts and tools.
  • To highlight PSN applications in GPCRs and Hsp90 drug target families.

Main Methods:

  • Utilizing PSNs to analyze protein structures and intramolecular interactions.
  • Reviewing computational methods for PSN construction and analysis.
  • Examining PSN applications in predicting functional residues and allosteric pathways.

Main Results:

  • PSNs facilitate the study of protein structure-function relationships.
  • PSNs can characterize protein-protein interactions and allosteric communication.
  • Recent advances show potential for PSNs in drug discovery and polypharmacology.

Conclusions:

  • PSNs offer a computationally efficient framework for drug discovery.
  • PSNs have potential applications in polypharmacology research.
  • PSNs are poised to become a significant tool in future drug development.