PLIP: fully automated protein-ligand interaction profiler

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.

Figure 1.

Example of interaction diagram generated with PLIP: Varicella zoster virus thymidine kinase (1OSN) binding the antiherpes drug brivudine-monophosphate. The binding is dominated by a double π-stacking and polar interactions at the terminal regions of the ligand.

Figure 2.

PLIP result page. An interaction diagram and a table with interaction data is provided for each binding site. JSMol applets allow to view the 3D interaction diagrams in the browser.

Figure 3.

Example illustrating the four steps of PLIP in interaction detection for palmitic acid in Bacillus subtilis DegV protein (PDB ID 3FYS). (A) Structure preparation and detection of relevant ligands. (B) Functional characterization of molecules, here shown for the assignment of charges to amino acid side chains and the ligand carboxyl group. (C) Matching of interacting atoms using a rule-based system of geometric constraints. In the case of salt bridges, the distance between attracting charges is measured. (D) Filtering steps to minimize the number of depicted interactions, particularly important in the case of hydrophobic contacts (shown as solid gray lines).

Figure 4.

Evaluating docking results with PLIP. Natural (A) and alternative pose from redocking (B) of Cathepsin K with a small molecule inhibitor (PDB ID 1VSN). Shared interacting residues are labeled. The second pose lacks characteristic halogen bonds.

Figure 5.

Human aldose reductase with different inhibitors. (A) Zenarestat (1IEI), (B) a sulfonyl-pyridazone inhibitor (1Z89) and (C) a benzothiazepine inhibitor (3P2V). While the first and the last share a salt bridge to His110 and the H-Bonds to Tyr48 and Trp111, there is a common π-stacking to Trp111 in the first two. Unique interactions are, among others, two halogen bonds in zenarestat to the backbones of Val47 and Cys298, additional stacking with Trp20 for the benzothiazepine inhibitor and a water bridge to Trp20 in the last inhibitor. Large parts of all ligands bind via hydrophobic contacts.