GIANT: pattern analysis of molecular interactions in 3D structures of protein–small ligand complexes

Kota Kasahara,Kengo Kinoshita

doi:10.1186/1471-2105-15-12

Abstract

BackgroundInterpretation of binding modes of protein–small ligand complexes from 3D structure data is essential for understanding selective ligand recognition by proteins. It is often performed by visual inspection and sometimes largely depends on a priori knowledge about typical interactions such as hydrogen bonds and π-π stacking. Because it can introduce some biases due to scientists’ subjective perspectives, more objective viewpoints considering a wide range of interactions are required.DescriptionIn this paper, we present a web server for analyzing protein–small ligand interactions on the basis of patterns of atomic contacts, or “interaction patterns” obtained from the statistical analyses of 3D structures of protein–ligand complexes in our previous study. This server can guide visual inspection by providing information about interaction patterns for each atomic contact in 3D structures. Users can visually investigate what atomic contacts in user-specified 3D structures of protein–small ligand complexes are statistically overrepresented. This server consists of two main components: “Complex Analyzer”, and “Pattern Viewer”. The former provides a 3D structure viewer with annotations of interacting amino acid residues, ligand atoms, and interacting pairs of these. In the annotations of interacting pairs, assignment to an interaction pattern of each contact and statistical preferences of the patterns are presented. The “Pattern Viewer” provides details of each interaction pattern. Users can see visual representations of probability density functions of interactions, and a list of protein–ligand complexes showing similar interactions.ConclusionsUsers can interactively analyze protein–small ligand binding modes with statistically determined interaction patterns rather than relying on a priori knowledge of the users, by using our new web server named GIANT that is freely available at http://giant.hgc.jp/.

Highlights

Interpretation of binding modes of protein–small ligand complexes from 3D structure data is essential for understanding selective ligand recognition by proteins
We found 13,512 interaction patterns in Protein databank (PDB) and interactions in these patterns were more enriched in native complex structures than in docking decoys
On the basis of the classification of interactions, we present a new web server for analyzing molecular interactions in the 3D structure of protein–ligand complexes, named “GIANT”, which stands for “Gaussian mixture model-based Interaction ANalyzer focusing on Three-atom fragments”

Summary

Conclusions

The web-server GIANT shows the statistical preferences of each atomic contact in user specified 3D structures of protein–small ligand complexes. When medicinal chemists perform lead optimization with 3D structure data of protein–compound complexes, GIANT suggests parts of compounds where chemical moieties without statistically overrepresented interaction patterns should be replaced to gain binding affinities. This process has usually been performed by experts using their a priori knowledge and intuition, GIANT supports it with statistical, objective information and assists in realizing the concept of so-called rational drug-design.

Background

Findings

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