Abstract
In this study, we report a ligand-guided homology modeling approach allowing the analysis of relevant binding site residue conformations and the identification of two novel histamine H3 receptor ligands with binding affinity in the nanomolar range. The newly developed method is based on exploiting an essential charge interaction characteristic for aminergic G-protein coupled receptors for ranking 3D receptor models appropriate for the discovery of novel compounds through virtual screening.
Highlights
** : **::** * **. .*: :*. : Fig A: Sequence alignment
The depicted multiple sequence alignment was used for ligand-guided homology modeling of human H3R
The multiple sequence alignment contains information about the naming of helices and loops and the sequence similarity. (H1) - helix 1, (ILC1) – intracellular loop 1, (ECL1) – extracellular loop 2, (*) - identical residues, (:) - residues with high similarity, (.) - residues with low similarity
Summary
The depicted multiple sequence alignment was used for ligand-guided homology modeling of human H3R. The template sequences are illustrated according to structural properties. Red sections represent helices and underlined cysteines are involved in a disulfide bond. The multiple sequence alignment contains information about the naming of helices and loops and the sequence similarity. (H1) - helix 1, (ILC1) – intracellular loop 1, (ECL1) – extracellular loop 2, (*) - identical residues, (:) - residues with high similarity, (.) - residues with low similarity. Changed parameters of environ and allhmodel classes in homology modelling using MODELLER 9.1511. Class environ allhmodel allhmodel allhmodel allhmodel allhmodel parameter schedule_scale library_schedule max_var_iterations md_level repeat_optimization max_molpdf setting physical.values(default=1.0, soft_sphere=0.7) autosched.slow 300 refine.slow 2 1e6
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