Archives

  • 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • Natural product based drug discovery can be enhanced

    2021-11-24

    Natural-product-based drug discovery can be enhanced with computational methods [205]. Because most of the reported small-molecule natural inhibitors of fMLF-induced functional responses were not evaluated in AG-1024 binding assays, we used molecular modeling to predict how well these compounds fit the FPR1 antagonist pharmacophore and their potential for binding to FPR1. The FPR1 antagonists described so far represent a wide range of chemotypes, and it is consequently difficult to derive meaningful SAR on structural grounds [206]. Recently, we built a pharmacophore model of FPR1 antagonists [79] based on field point methodology developed by Cheeseright et al. [207], [208]. This approach allowed us to compare diverse molecules in terms of their electrostatic field similarity and create an alignment of their bioactive conformations [206]. We found that three potent small-molecule synthetic non-peptide FPR1 antagonists that were identified previously using high-throughput screening and/or lead optimization [6-ethyl-2-methyl-3-(1-methyl-1H-benzimidazol-2-yl)-4-oxo-4H-chromen-7-yl acetate, N-(1S)(1-(benzoimidazol-2-yl)-3-(methylthio)propyl)-5-ethoxy-3-methylbenzofuran-2-carboxamide, and AG-1024 6-benzyl-3-(2-chlorophenyl)-5-methyl-2-(trifluoromethyl)pyrazolo[1,5-a]pyrimidin-7(1H)-one (designated previously by us as compounds 1, 5, and 7)] [78], [209] could be overlaid simultaneously with good correspondence of their molecular fields to form an FPR1 antagonist pharmacophore template [79]. Thus, we evaluated the ability of a given molecule to fit the FPR1 antagonist pharmacophore by construction of an extended 4-molecule template containing the molecule under investigation along with compounds 1, 5, and 7. The possibility of forming an extended template can be regulated by the magnitude of μ (maximum score variation between molecule pairs), which is an inner parameter of the FieldTemplater program, with lower values of μ indicating templates of higher similarity. We found that the previously reported FPR1 antagonists (isoflavones 36, 68, 73, and lignan PP-6) (see Table 1) gave extended templates with relatively low μ values (0.03–0.04), indicating high similarity with the FPR1 antagonist pharmacophore, while inactive isoflavones (compounds 54, 58, and 70; compound numbers as designated previously [79]) generally had μ values >0.04 for obtaining an extended template. Based on the outcome of this small training set of 7 molecules, we utilized a simple rule of μ≤0.04 for assessing potential as an FPR1 antagonist based on similarity with the antagonist pharmacophore and used this rule to evaluate a set of 24 naturally occurring compounds that were initially selected from our review of the literature and additional screening because they inhibited of all fMLF-induced functional responses tested but did not exhibit any direct agonist activity or other undesirable effects (Table 2, Table 3). As result of this modeling study, most natural compounds under investigation did not fit into a satisfactory common 4-molecule FPR1 antagonist template (i.e., μ>0.04). Although oleanolic acid and hederagenin showed promising results in our additional testing in human neutrophils and FPR1 HL-60 cells, these compounds were rejected as FPR1 antagonists by the modeling assessment of their ability to fit with the FPR1 antagonist pharmacophore. However, three compounds, in addition to PP-6 (i.e., garcimultiflorone B, cnidimol A, and PL3S), also had μ values ≤0.04 and can be regarded as potential FPR1 antagonists based on all of the available biochemical and molecular modeling criteria. It should be noted that this modeling study is focused on orthosteric interaction of a ligand with FPR1, so allosteric antagonism cannot be excluded with some of the other compounds in the set. To further investigate possible ligand binding, the natural compounds with ability to form a high-quality common 4-molecular template of FPR1 antagonists were subjected to molecular docking into the FPR1 ligand binding site. The best docking poses obtained for garcimultiflorone B, cnidimol A, PL3S, and PP-6 showed that these molecules were oriented similarly to fMLF within the orthosteric FPR1 binding site of the Leu101 FPR1 variant (Fig. 3A), again supporting their potential as FPR1 antagonists. All four natural compounds in their best docking poses were located in area D and cavity B, while garcimultiflorone B and fMLF also occupied the entrance of channel A (notation of the FPR1 binging site regions according to [210]). Analysis of H-bond energies formed by the docked molecules (Table 4) indicated that PP-6 and cnidimol A formed much stronger H-bonds with FPR1 than PL3S and garcimultiflorone B. We found that H-bonds with Thr265 are formed for three of the four natural antagonists investigated by our docking methodology (Table 4). In addition, strong H-bonding interactions of cnidimol A and PP-6 were found with Asp106 and Arg205, respectively. As an example, all three H-bonds for PP-6 in the FPR1 ligand binding site are shown in Fig. 3B.