Chemical Function Based Pharmacophore Generation of Endothelin-A Selective Receptor Antagonists

Abstract

Both quantitative and qualitative chemical function based pharmacophore models of endothelin-A (ET(A)) selective receptor antagonists were generated by using the two algorithms HypoGen and HipHop, respectively, which are implemented in the Catalyst molecular modeling software. The input for HypoGen is a training set of 18 ET(A) antagonists exhibiting IC(50) values ranging between 0.19 nM and 67 microM. The best output hypothesis consists of five features: two hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI) function. The highest scoring Hip Hop model consists of six features: three hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI). It is the result of an input of three highly active, selective, and structurally diverse ET(A) antagonists. The predictive power of the quantitative model could be approved by using a test set of 30 compounds, whose activity values spread over 6 orders of magnitude. The two pharmacophores were tested according to their ability to extract known endothelin antagonists from the 3D molecular structure database of Derwent's World Drug Index. Thereby the main part of selective ET(A) antagonistic entries was detected by the two hypotheses. Furthermore, the pharmacophores were used to screen the Maybridge database. Six compounds were chosen from the output hit lists for in vitro testing of their ability to displace endothelin-1 from its receptor. Two of these are new potential lead compounds because they are structurally novel and exhibit satisfactory activity in the binding assay.

Hydrophobic Core around Tyrosine for Human Endothelin-1 Investigated by Photochemically Induced Dynamic Nuclear Polarization Nuclear Magnetic Resonance and Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry

“…The structure can sufficiently be matched to the many antagonist molecules, and can explain broad structural findings (12,13,25,26). The ring formation and charge location agree well with the antagonist structures.…”

“…The Trp 21 signal enhancements agree with the solvent accessibility of the C-terminus (Figure 1a). Figure 2b shows a control experiment of C-terminal fragment ET-1 (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21), indicating clear photo-CIDNP signals for both tyrosine and tryptophan, which correspond to residues 13 and 21 in the ET-1 sequence, respectively. Because the fragment was not soluble at a lower pH, it was measured at pH 7.5, whereas ET-1 was not soluble at pH >4.…”

“…ET-1 and endothelin-3 (ET-3) were purchased from Peptide Institute Inc. (Osaka, Japan). ET-1 C-terminal residues 11-21 [ET-1 (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)] was synthesized by a solid-phase procedure on an Applied Biosystems model 431A automated peptide synthesizer on 0.5 mmol of Boc-Trp(CHO)-phenylacetoamidomethyl resin, and was elongated by Boc-amino acid HOBt esters with N,N′-dicyclohexylcarbodiimide. The peptides were dissolved in H 2 O with D 2 O (9:1, v/v), at 297.7 K, with 0.1 mM lumiflavin (luF), and were subjected to the experiments.…”

Discovery of potential negative allosteric modulators of mGluR5 from natural products using pharmacophore modeling, molecular docking, and molecular dynamics simulation studies

“…During this process, an activity uncertainty of 2 for each compound was recommended due to statistical straggling 36 . And other parameters were set at default values.…”

“…The location where the excluded volumes should be added was defined by the activity difference between active compounds and lower active compounds. Then, the algorithm inspected the volume space of the active and lower active compounds to locate reasonable positions for adding an excluded volume 34,36 . The Maximum Excluded Volumes (Ev) value was set to 5.…”