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In Silico Veritas: The Pitfalls and Challenges of Predicting GPCR-Ligand Interactions
- Source :
- Pharmaceuticals, Vol 4, Iss 9, Pp 1196-1215 (2011), Pharmaceuticals, Pharmaceuticals, 4, 9, pp. 1196-1215, Pharmaceuticals, 4, 1196-1215
- Publication Year :
- 2011
-
Abstract
- Recently the first community-wide assessments of the prediction of the structures of complexes between proteins and small molecule ligands have been reported in the so-called GPCR Dock 2008 and 2010 assessments. In the current review we discuss the different steps along the protein-ligand modeling workflow by critically analyzing the modeling strategies we used to predict the structures of protein-ligand complexes we submitted to the recent GPCR Dock 2010 challenge. These representative test cases, focusing on the pharmaceutically relevant G Protein-Coupled Receptors, are used to demonstrate the strengths and challenges of the different modeling methods. Our analysis indicates that the proper performance of the sequence alignment, introduction of structural adjustments guided by experimental data, and the usage of experimental data to identify protein-ligand interactions are critical steps in the protein-ligand modeling protocol.
- Subjects :
- Chemical and physical biology [NCMLS 7]
Genetics and epigenetic pathways of disease [NCMLS 6]
Computer science
In silico
G protein-coupled receptor (GPCR)
Pharmaceutical Science
lcsh:Medicine
lcsh:RS1-441
Review
computer.software_genre
lcsh:Pharmacy and materia medica
03 medical and health sciences
comparative modeling
0302 clinical medicine
Modelling methods
DOCK
Drug Discovery
GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries)
030304 developmental biology
G protein-coupled receptor
ligand binding mode prediction
0303 health sciences
lcsh:R
Experimental data
Test case
Workflow
030220 oncology & carcinogenesis
GPCR Dock 2010
Research Programm of Institute for Molecules and Materials
Molecular Medicine
Data mining
computer
Subjects
Details
- ISSN :
- 14248247
- Volume :
- 4
- Database :
- OpenAIRE
- Journal :
- Pharmaceuticals
- Accession number :
- edsair.doi.dedup.....e0979dc939a6701c6476a5a0087da2f6