Structure-based pharmacophore modeling 1. Automated random pharmacophore model generation

被引:4
作者
Szwabowski, Gregory L. [1 ]
Cole, Judith A. [2 ]
Baker, Daniel L. [1 ]
Parrill, Abby L. [1 ]
机构
[1] Univ Memphis, Dept Chem, Memphis, TN 38152 USA
[2] Univ Memphis, Dept Biol Sci, Memphis, TN 38152 USA
关键词
Pharmacophore modeling; Ligand identification; Ligand discovery; Structure-based pharmacophore; GPCR; OPIOID RECEPTOR; CRYSTAL-STRUCTURE; DRUG DISCOVERY; PROTEIN; CHALLENGES; INSIGHTS; COMPLEX; BIOLOGY;
D O I
10.1016/j.jmgm.2023.108429
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Pharmacophores are three-dimensional arrangements of molecular features required for biological activity that are often used in virtual screening efforts to prioritize ligands for experimental testing. G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for ligand discovery and drug development. Ligand-based pharmacophore models can be constructed to identify structural commonalities between known bioactive ligands for targets including GPCR. However, structure-based pharmacophores (which only require an experimentally determined or modeled structure for a protein target) have gained more attention to aid in virtual screening efforts as the number of publicly available experimentally determined GPCR structures have increased (140 unique GPCR represented as of October 24, 2022). Thus, the goal of this study was to develop a method of structure-based pharmacophore model generation applicable to ligand discovery for GPCR that have few known ligands. Pharmacophore models were generated within the active sites of 8 class A GPCR crystal structures via automated annotation of 5 randomly selected functional group fragments to sample diverse combinations of pharmacophore features. Each of the 5000 generated pharmacophores was then used to search a database containing active and decoy/inactive compounds for 30 class A GPCR and scored using enrichment factor and goodness-of-hit metrics to assess performance. Application of this method to the set of 8 class A GPCR produced pharmacophore models possessing the theoretical maximum enrichment factor value in both resolved structures (8 of 8 cases) and homology models (7 of 8 cases), indicating that generated pharmacophore models can prove useful in the context of virtual screening.
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页数:13
相关论文
共 55 条
  • [1] [Anonymous], 2019, MOL OPERATING ENV MO
  • [2] Armstrong J.F., NUCLEIC ACIDS RES
  • [3] GenBank
    Benson, Dennis A.
    Clark, Karen
    Karsch-Mizrachi, Ilene
    Lipman, David J.
    Ostell, James
    Sayers, Eric W.
    [J]. NUCLEIC ACIDS RESEARCH, 2015, 43 (D1) : D30 - D35
  • [4] The Protein Data Bank
    Berman, HM
    Westbrook, J
    Feng, Z
    Gilliland, G
    Bhat, TN
    Weissig, H
    Shindyalov, IN
    Bourne, PE
    [J]. NUCLEIC ACIDS RESEARCH, 2000, 28 (01) : 235 - 242
  • [5] Assessing the Performance of 3D Pharmacophore Models in Virtual Screening: How Good are They?
    Braga, Rodolpho C.
    Andrade, Carolina H.
    [J]. CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2013, 13 (09) : 1127 - 1138
  • [6] Case D.A., 2008, AMBER 10
  • [7] Ligand-based G Protein Coupled Receptor pharmacophore modeling: Assessing the role of ligand function in model development
    Castleman, P.
    Szwabowski, G.
    Bowman, D.
    Cole, J.
    Parrill, A. L.
    Baker, D. L.
    [J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2022, 111
  • [8] GPCR homology model template selection benchmarking: Global versus local similarity measures
    Castleman, Paige N.
    Sears, Chandler K.
    Cole, Judith A.
    Baker, Daniel L.
    Parrill, Abby L.
    [J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2019, 86 : 235 - 246
  • [9] Chen I.-J., Conformational Sampling of Druglike Molecules with MOE and Catalyst: Implications for Pharmacophore Modeling and Virtual Screening, DOI DOI 10.1021/CI800130K
  • [10] High-resolution crystal structure of an engineered human β2-adrenergic G protein-coupled receptor
    Cherezov, Vadim
    Rosenbaum, Daniel M.
    Hanson, Michael A.
    Rasmussen, Soren G. F.
    Thian, Foon Sun
    Kobilka, Tong Sun
    Choi, Hee-Jung
    Kuhn, Peter
    Weis, William I.
    Kobilka, Brian K.
    Stevens, Raymond C.
    [J]. SCIENCE, 2007, 318 (5854) : 1258 - 1265