Literature DB >> 25459769

Multi-generational pharmacophore modeling for ligands to the cholane steroid-recognition site in the β₁ modulatory subunit of the BKCa channel.

Jacob E McMillan1, Anna N Bukiya2, Camisha L Terrell3, Shivaputra A Patil4, Duane D Miller5, Alex M Dopico6, Abby L Parrill7.   

Abstract

Large conductance, voltage- and Ca(2+)-gated K(+) (BKCa) channels play a critical role in smooth muscle contractility and thus represent an emerging therapeutic target for drug development to treat vascular disease, gastrointestinal, bladder and uterine disorders. Several compounds are known to target the ubiquitously expressed BKCa channel-forming α subunit. In contrast, just a few are known to target the BKCa modulatory β1 subunit, which is highly expressed in smooth muscle and scarce in most other tissues. Lack of available high-resolution structural data makes structure-based pharmacophore modeling of β1 subunit-dependent BKCa channel activators a major challenge. Following recent discoveries of novel BKCa channel activators that act via β1 subunit recognition, we performed ligand-based pharmacophore modeling that led to the successful creation and fine-tuning of a pharmacophore over several generations. Initial models were developed using physiologically active cholane steroids (bile acids) as template. However, as more compounds that act on BKCa β1 have been discovered, our model has been refined to improve accuracy. Database searching with our best-performing model has uncovered several novel compounds as candidate BKCa β1 subunit ligands. Eight of the identified compounds were experimentally screened and two proved to be activators of recombinant BKCa β1 complexes. One of these activators, sobetirome, differs substantially in structure from any previously reported activator.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BKCa channel; Beta subunit; Pharmacophore model

Mesh:

Substances:

Year:  2014        PMID: 25459769      PMCID: PMC4268273          DOI: 10.1016/j.jmgm.2014.10.008

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


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