Ligand-based pharmacophore model of N-Aryl and N-Heteroaryl piperazine alpha 1A-adrenoceptors antagonists using GALAHAD
- PMID: 20538497
- DOI: 10.1016/j.jmgm.2010.05.002
Ligand-based pharmacophore model of N-Aryl and N-Heteroaryl piperazine alpha 1A-adrenoceptors antagonists using GALAHAD
Abstract
Computer aided drug discovery for selective antagonism effects on alpha(1A) subtypes of G-protein coupled receptors are important in the treatment of benign prostatic hyperplasia (BPH). Ligand-based pharmacophore models of N-Aryl and N-Heteroaryl piperazine alpha(1A)-antagonists were developed using two separate training sets. Pharmacophore models were generated using the flexible align method within the GALAHAD module, implemented in SYBYL8.1 software. The most significant pharmacophore hypothesis, characterized by the conflicting demands of maximizing pharmacophore consensus, maximizing steric consensus, and minimizing energy, consisted of one positive nitrogen center, one donor atom center, two acceptor atom centers, and two hydrophobic groups. The most active compound in each class training set showed a good fit with all features of the pharmacophore proposed. The resulting models also had something in common with the hypothesis using the Catalyst software reported in other publications. These alpha(1A) pharmacophore models could predict compounds well, both in the training set and the test set. The pharmacophore models were also validated by an external dataset using a portion of the ZINC database. A 3D-QSAR model using the pharmacophore model to align the compounds was established in this study. The CoMFA model with the cross-validated q(2) value of 0.735 revealed that the model was valid. Our research provides a valuable tool for designing new therapeutic compounds with desired biological activity.
(c) 2010 Elsevier Inc. All rights reserved.
Similar articles
-
Selective pharmacophore design for alpha1-adrenoceptor subtypes.J Mol Graph Model. 2006 Sep;25(1):146-57. doi: 10.1016/j.jmgm.2005.12.001. Epub 2006 Jan 6. J Mol Graph Model. 2006. PMID: 16406718
-
Pharmacophore identification of alpha(1A)-adrenoceptor antagonists.Bioorg Med Chem Lett. 2005 Feb 1;15(3):657-64. doi: 10.1016/j.bmcl.2004.11.032. Bioorg Med Chem Lett. 2005. PMID: 15664832
-
Search for influence of spatial properties on affinity at α1-adrenoceptor subtypes for phenylpiperazine derivatives of phenytoin.Bioorg Med Chem Lett. 2010 Oct 15;20(20):6152-6. doi: 10.1016/j.bmcl.2010.07.101. Epub 2010 Jul 30. Bioorg Med Chem Lett. 2010. PMID: 20813529
-
Modeling the interactions between alpha(1)-adrenergic receptors and their antagonists.Curr Comput Aided Drug Des. 2010 Sep;6(3):165-78. doi: 10.2174/157340910791760082. Curr Comput Aided Drug Des. 2010. PMID: 20412040 Review.
-
Arylpiperazines with affinity toward alpha(1)-adrenergic receptors.Curr Med Chem. 2002 Jul;9(13):1303-21. doi: 10.2174/0929867023369961. Curr Med Chem. 2002. PMID: 12052168 Review.
Cited by
-
Synthesis and cytotoxic activity evaluation of novel arylpiperazine derivatives on human prostate cancer cell lines.Molecules. 2014 Aug 12;19(8):12048-64. doi: 10.3390/molecules190812048. Molecules. 2014. PMID: 25120056 Free PMC article.
-
Total Synthesis of Aporphine Alkaloids via Photocatalytic Oxidative Phenol Coupling and Biological Evaluation at the Serotonin 5-HT2 and Adrenergic α1A Receptors.J Med Chem. 2025 Jul 24;68(14):14628-14644. doi: 10.1021/acs.jmedchem.5c00771. Epub 2025 Jul 7. J Med Chem. 2025. PMID: 40623044 Free PMC article.
-
Identification of Novel Protein Kinase Receptor Type 2 Inhibitors Using Pharmacophore and Structure-Based Virtual Screening.Molecules. 2018 Feb 18;23(2):453. doi: 10.3390/molecules23020453. Molecules. 2018. PMID: 29463017 Free PMC article.
-
Identification of new promising Plasmodium falciparum superoxide dismutase allosteric inhibitors through hierarchical pharmacophore-based virtual screening and molecular dynamics.J Mol Model. 2018 Jul 28;24(8):220. doi: 10.1007/s00894-018-3746-0. J Mol Model. 2018. PMID: 30056475
-
The discovery of potentially selective human neuronal nitric oxide synthase (nNOS) Inhibitors: a combination of pharmacophore modelling, CoMFA, virtual screening and molecular docking studies.Int J Mol Sci. 2014 May 14;15(5):8553-69. doi: 10.3390/ijms15058553. Int J Mol Sci. 2014. PMID: 24830557 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources