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PLIP: fully automated protein–ligand interaction profiler
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 nov...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489249/ https://www.ncbi.nlm.nih.gov/pubmed/25873628 http://dx.doi.org/10.1093/nar/gkv315 |
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author | Salentin, Sebastian Schreiber, Sven Haupt, V. Joachim Adasme, Melissa F. Schroeder, Michael |
author_facet | Salentin, Sebastian Schreiber, Sven Haupt, V. Joachim Adasme, Melissa F. Schroeder, Michael |
author_sort | Salentin, Sebastian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4489249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44892492015-07-07 PLIP: fully automated protein–ligand interaction profiler Salentin, Sebastian Schreiber, Sven Haupt, V. Joachim Adasme, Melissa F. Schroeder, Michael Nucleic Acids Res Web Server issue 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. Oxford University Press 2015-07-01 2015-04-14 /pmc/articles/PMC4489249/ /pubmed/25873628 http://dx.doi.org/10.1093/nar/gkv315 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Web Server issue Salentin, Sebastian Schreiber, Sven Haupt, V. Joachim Adasme, Melissa F. Schroeder, Michael PLIP: fully automated protein–ligand interaction profiler |
title | PLIP: fully automated protein–ligand interaction profiler |
title_full | PLIP: fully automated protein–ligand interaction profiler |
title_fullStr | PLIP: fully automated protein–ligand interaction profiler |
title_full_unstemmed | PLIP: fully automated protein–ligand interaction profiler |
title_short | PLIP: fully automated protein–ligand interaction profiler |
title_sort | plip: fully automated protein–ligand interaction profiler |
topic | Web Server issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489249/ https://www.ncbi.nlm.nih.gov/pubmed/25873628 http://dx.doi.org/10.1093/nar/gkv315 |
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