Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction

We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exha...

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Bibliographic Details
Published in:Journal of computer-aided molecular design 2012-05, Vol.26 (5), p.617-633
Main Authors: Sulea, Traian, Hogues, Hervé, Purisima, Enrico O.
Format: Article
Language:English
Subjects:
Affinity
Animal Anatomy
Animals
Cattle
Chemistry
Chemistry and Materials Science
Computer Applications in Chemistry
Computer based modeling
Computer Simulation
Entropy
Histology
Ligands
Molecular chemistry
Molecular Structure
Morphology
Perspectives
Physical Chemistry
Protein Binding
Proteins - chemistry
Quantitative Structure-Activity Relationship
Solvents
Thermodynamics
Trypsin - chemistry
Water - chemistry
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Summary:We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exhaustive docking program, Wilma, to provide high-quality poses that were rescored using SIE to provide binding affinity predictions. We also tested the combination of SIE with our latest solvation model, first shell of hydration (FiSH), which captures some of the discrete properties of water within a continuum model. We achieved good enrichment in virtual screening of fragments against trypsin, with an area under the curve of about 0.7 for the receiver operating characteristic curve. Moreover, the early enrichment performance was quite good with 50% of true actives recovered with a 15% false positive rate in a prospective calculation and with a 3% false positive rate in a retrospective application of SIE with FiSH. Binding affinity predictions for both trypsin and host–guest complexes were generally within 2 kcal/mol of the experimental values. However, the rank ordering of affinities differing by 2 kcal/mol or less was not well predicted. On the other hand, it was encouraging that the incorporation of a more sophisticated solvation model into SIE resulted in better discrimination of true binders from binders. This suggests that the inclusion of proper Physics in our models is a fruitful strategy for improving the reliability of our binding affinity predictions.
ISSN:0920-654X
1573-4951
DOI:10.1007/s10822-011-9529-7