دورية أكاديمية
Assessing GPCR homology models constructed from templates of various transmembrane sequence identities: Binding mode prediction and docking enrichment.
العنوان: | Assessing GPCR homology models constructed from templates of various transmembrane sequence identities: Binding mode prediction and docking enrichment. |
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المؤلفون: | Loo JSE; School of Pharmacy, Taylor's University, No.1 Jalan Taylor's, 47500 Subang Jaya, Selangor, Malaysia. Electronic address: JasonSiauEe.Loo@taylors.edu.my., Emtage AL; School of Pharmacy, The University of Nottingham Malaysia Campus, Jalan Broga, 43500 Semenyih, Selangor, Malaysia., Ng KW; School of Pharmacy, Taylor's University, No.1 Jalan Taylor's, 47500 Subang Jaya, Selangor, Malaysia., Yong ASJ; School of Pharmacy, Taylor's University, No.1 Jalan Taylor's, 47500 Subang Jaya, Selangor, Malaysia., Doughty SW; Penang Medical College, No. 4 Jalan Sepoy Lines, 10450 George Town, Penang, Malaysia. |
المصدر: | Journal of molecular graphics & modelling [J Mol Graph Model] 2018 Mar; Vol. 80, pp. 38-47. Date of Electronic Publication: 2017 Dec 29. |
نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
اللغة: | English |
بيانات الدورية: | Publisher: Elsevier Science, Inc Country of Publication: United States NLM ID: 9716237 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4243 (Electronic) Linking ISSN: 10933263 NLM ISO Abbreviation: J Mol Graph Model Subsets: MEDLINE |
أسماء مطبوعة: | Original Publication: New York, NY : Elsevier Science, Inc., c1997- |
مواضيع طبية MeSH: | Models, Molecular* , Protein Conformation* , Protein Interaction Domains and Motifs*, Receptors, G-Protein-Coupled/*chemistry, Binding Sites ; Ligands ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Protein Binding ; ROC Curve ; Receptors, G-Protein-Coupled/metabolism ; Reproducibility of Results ; Structure-Activity Relationship |
مستخلص: | GPCR crystal structures have become more readily accessible in recent years. However, homology models of GPCRs continue to play an important role as many GPCR structures remain unsolved. The new crystal structures now available provide not only additional templates for homology modelling but also the opportunity to assess the performance of homology models against their respective crystal structures and gain insight into the performance of such models. In this study we have constructed homology models from templates of various transmembrane sequence identities for eight GPCR targets to better understand the relationship between transmembrane sequence identity and model quality. Model quality was assessed relative to the crystal structure in terms of structural accuracy as well as performance in two typical structure-based drug design applications: ligand binding pose prediction and docking enrichment in virtual screening. Crystal structures significantly outperformed homology models in both assessments. Accurate ligand binding pose prediction was possible but difficult to achieve using homology models, even with the use of induced fit docking. In virtual screening using homology models still conferred significant enrichment compared to random selection, with a clear benefit also observed in using models optimized through induced fit docking. Our results indicate that while homology models that are reasonably accurate structurally can be constructed, without significant refinement homology models will be outperformed by crystal structures in ligand binding pose prediction and docking enrichment regardless of the template used, primarily due to the extremely high level of structural accuracy needed for such applications. (Copyright © 2017 Elsevier Inc. All rights reserved.) |
فهرسة مساهمة: | Keywords: GPCR; Homology model; Induced fit docking; Sequence identity; Virtual screening |
المشرفين على المادة: | 0 (Ligands) 0 (Receptors, G-Protein-Coupled) |
تواريخ الأحداث: | Date Created: 20180108 Date Completed: 20190917 Latest Revision: 20190917 |
رمز التحديث: | 20221213 |
DOI: | 10.1016/j.jmgm.2017.12.017 |
PMID: | 29306746 |
قاعدة البيانات: | MEDLINE |
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