title: How to Choose the Suitable Template for Homology Modelling of GPCRs: 5-HT7 Receptor as a Test Case.
abstract: G protein-coupled receptors (GPCRs) are a super-family of membrane proteins that attract great pharmaceutical interest due to their involvement in almost every physiological activity, including extracellular stimuli, neurotransmission, and hormone regulation. Currently, structural information on many GPCRs is mainly obtained by the techniques of computer modelling in general and by homology modelling in particular. Based on a quantitative analysis of eighteen antagonist-bound, resolved structures of rhodopsin family "A" receptors - also used as templates to build 153 homology models - it was concluded that a higher sequence identity between two receptors does not guarantee a lower RMSD between their structures, especially when their pair-wise sequence identity (within trans-membrane domain and/or in binding pocket) lies between 25 % and 40 %. This study suggests that we should consider all template receptors having a sequence identity ≤50 % with the query receptor. In fact, most of the GPCRs, compared to the currently available resolved structures of GPCRs, fall within this range and lack a correlation between structure and sequence. When testing suitability for structure-based drug design, it was found that choosing as a template the most similar resolved protein, based on sequence resemblance only, led to unsound results in many cases. Molecular docking analyses were carried out, and enrichment factors as well as attrition rates were utilized as criteria for assessing suitability for structure-based drug design.
authors.affiliation: Drug Discovery Informatics Lab, Qasemi-Research Center, Al-Qasemi Academic College, Baka El-Garbiah, 30100, Israel.
authors.forename: Nir
authors.initials: N
authors.lastname: Shahaf
authors.affiliation: Department of Drug Sciences . mpappala@unict.it.|Department of Chemical Sciences -, University of Catania -, V.leA.Doria 6, I-95125, Catania, Italy. mpappala@unict.it.
authors.forename: Matteo
authors.initials: M
authors.lastname: Pappalardo
authors.affiliation: Department of Drug Sciences.
authors.forename: Livia
authors.initials: L
authors.lastname: Basile
authors.affiliation: Department of Drug Sciences.
authors.forename: Salvatore
authors.initials: S
authors.lastname: Guccione
authors.affiliation: Drug Discovery Informatics Lab, Qasemi-Research Center, Al-Qasemi Academic College, Baka El-Garbiah, 30100, Israel, . a_rayan@qsm.ac.il.|Institute of Applied Research, Galilee Society, Shefa-Amr, 20200, Israel. a_rayan@qsm.ac.il.
authors.forename: Anwar
authors.initials: A
authors.lastname: Rayan
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D015195:Drug Design; D006801:Humans; D008958:Models, Molecular; D062105:Molecular Docking Simulation / Q000379:methods; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry* / Q000378:metabolism*; D011985:Receptors, Serotonin / Q000737:chemistry* / Q000378:metabolism*; D012243:Rhodopsin / Q000737:chemistry; D017386:Sequence Homology, Amino Acid
chemical_list: D043562:Receptors, G-Protein-Coupled; D011985:Receptors, Serotonin; C104425:serotonin 7 receptor; D012243:Rhodopsin
keywords: 5HT7 receptor; G-Protein Coupled Receptors; Homology Modelling; structure-based drug design