Virtual screening of GPCRs: An in silico chemogenomics approach
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* Corresponding author: Laurent Jacob laurent.jacob@mines-paristech.fr
- Equal contributors
1 Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honoré, F-77305, Fontainebleau, France
2 Institut Curie, Paris, F-75248, France
3 INSERM, U900, Paris, F-75248, France
BMC Bioinformatics 2008, 9:363 doi:10.1186/1471-2105-9-363
Published: 6 September 2008Additional files
Additional file 1:
Aligned receptor pocket residues. Residues of 5-hydroxytryptamine 5A receptor, Adenosine A2b receptor, Gamma-aminobutyric acid type B receptor and Relaxin 3 receptor 2 (shown as examples) aligned with β2-adrenergic receptor binding site amino acids. The binding pocket motif of β2-adrenergic receptor has been used as reference to determine residues involved in the formation of the binding site of the 79 other GPCRs. Bold columns correspond to the residues shown on Figure 2.
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Additional file 2:
Source and data. Source code (under GPL license) and benchmark used in the experiments in a compressed archive checker.tgz.
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Additional file 3:
Prediction accuracy by GPCR for the first experiment. Mean prediction accuracy for each GPCR for the first experiment with the 2D Tanimoto ligand kernel and various target kernels. The GPCR identifiers are the GLIDA references. The numbers in bracket are the numbers ligands considered in the experiment for each GPCR. BP is the binding pocket kernel and PBP the poly binding pocket kernel.
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Additional file 4:
Prediction accuracy by GPCR for the second experiment. Mean prediction accuracy for each GPCR for the second experiment with the 2D Tanimoto ligand kernel and various target kernels. The GPCR identifiers are the GLIDA references. The numbers in bracket are the numbers ligands considered in the experiment for each GPCR. BP is the binding pocket kernel and PBP the poly binding pocket kernel.
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