Nucleic Acids Research· 2015Q1
PLIP: fully automated protein–ligand interaction profiler
- 2,321citations
- Q1SCImago
- 2015year
Short summary
PLIP is a novel, freely available web service that automatically detects and visualizes seven types of non-covalent interactions in protein-ligand complexes without requiring structure preparation.
AI-generated from the title and abstract; the full text is not read.
Key points
- PLIP is a novel, fully automated web service for protein-ligand interaction analysis.
- It detects seven types of non-covalent interactions (hydrogen bonds, hydrophobic, pi-stacking, pi-cation, salt bridges, water bridges, halogen bonds) at the atomic level.
- No structure preparation is required, simplifying the process.
- PLIP offers publication-ready images, PyMOL session files, and parsable output files.
- It includes a command-line mode for high-throughput profiling and its source code is available.
AI-generated from the title and abstract; the full text is not read.
Abstract
The characterization of interactions in protein-ligand complexes is essential for research in structural bioinformatics, drug discovery and biology. However, comprehensive tools are not freely available to the research community. Here, we present the protein-ligand interaction profiler (PLIP), a novel web service for fully automated detection and visualization of relevant non-covalent protein-ligand contacts in 3D structures, freely available at projects.biotec.tu-dresden.de/plip-web. The input is either a Protein Data Bank structure, a protein or ligand name, or a custom protein-ligand complex (e.g. from docking). In contrast to other tools, the rule-based PLIP algorithm does not require any structure preparation. It returns a list of detected interactions on single atom level, covering seven interaction types (hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges and halogen bonds). PLIP stands out by offering publication-ready images, PyMOL session files to generate custom images and parsable result files to facilitate successive data processing. The full python source code is available for download on the website. PLIP's command-line mode allows for high-throughput interaction profiling.
The authors' abstract, as published at the source. Nucleic Acids Research, 2015 · DOI ↗
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Field: Computational Theory and Mathematics
Computational Theory and MathematicsComputer Science