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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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PLIP: fully automated protein-ligand interaction profiler.

Sebastian Salentin1, Sven Schreiber1, V Joachim Haupt1

  • 1Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany.

Nucleic Acids Research
|April 16, 2015
PubMed
Summary

The protein-ligand interaction profiler (PLIP) is a new, free web service that automatically detects and visualizes non-covalent interactions in protein-ligand complexes. It aids structural bioinformatics and drug discovery by detailing seven interaction types without requiring structure preparation.

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Area of Science:

  • Structural Bioinformatics
  • Computational Drug Discovery
  • Molecular Biology

Background:

  • Characterizing protein-ligand interactions is crucial for drug discovery and structural bioinformatics.
  • Existing tools lack comprehensive, freely available solutions for analyzing these interactions.
  • Automated analysis of non-covalent contacts in 3D protein-ligand structures is needed.

Purpose of the Study:

  • To present the protein-ligand interaction profiler (PLIP), a novel web service for automated detection and visualization of protein-ligand contacts.
  • To provide a freely accessible tool for researchers in structural bioinformatics and drug discovery.
  • To offer detailed analysis of non-covalent interactions at the atomic level.

Main Methods:

  • Developed a rule-based algorithm for detecting protein-ligand interactions.
  • Integrated a web service accepting various input formats (PDB, protein/ligand names, custom complexes).
  • Implemented automated detection of seven interaction types: hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation, salt bridges, water bridges, and halogen bonds.

Main Results:

  • PLIP accurately detects and visualizes seven types of non-covalent interactions in protein-ligand complexes.
  • The service requires no prior structure preparation, accepting direct input.
  • Offers publication-ready images, PyMOL session files, and parsable output files.
  • Provides a command-line mode for high-throughput analysis.

Conclusions:

  • PLIP is a valuable, freely available resource for detailed protein-ligand interaction analysis.
  • Its automated, comprehensive approach facilitates structural bioinformatics and drug discovery research.
  • The tool's flexibility and output options support publication and further data processing.