Impact of template choice on homology model efficiency in virtual screening

Homology modeling is a reliable method of predicting the three-dimensional structures of proteins that lack NMR or X-ray crystallographic data. It employs the assumption that a structural resemblance exists between closely related proteins. Despite the availability of many crystal structures of possible templates, only the closest ones are chosen for homology modeling purposes. To validate the aforementioned approach, we performed homology modeling of four serotonin receptors (5-HT1AR, 5-HT2AR, 5-HT6R, 5-HT7R) for virtual screening purposes, using 10 available G-Protein Coupled Receptors (GPCR) templates with diverse evolutionary distances to the targets, with various approaches to alignment construction and model building. The resulting models were further validated in two steps by means of ligand docking and enrichment calculation, using Glide software. The final quality of the models was determined in virtual screening-like experiments by the AUROC score of the resulting ROC curves. The outcome of this research showed that no correlation between sequence identity and model quality was found, leading to the conclusion that the closest phylogenetic relative is not always the best template for homology modeling.