An aspartate in the second extracellular loop of the α(1B) adrenoceptor regulates agonist binding.

The extracellular loops of the adrenoceptors present a potential therapeutic target in the design of highly selective adrenergic drugs. These regions are less conserved than the orthosteric binding site but have to date not been implicated in activation of adrenoceptors. A previously generated homology model identified an extracellular residue, D191, as a potential regulator of agonist binding. We have generated mutants of the α1B adrenoceptor replacing the charged aspartate, D191, as well as a potential interaction partner, K331, with uncharged alanines to observe effects on ligand binding and receptor activation. Significant 4-6 fold reductions in affinity for the endogenous agonists, epinephrine and norepinephrine were observed for receptors with the D191A mutation in the second extracellular loop. While changes in EC50 were observed, operational analysis yielded no apparent change in receptor activation. Based on these findings, we suggest that D191, in the second extracellular loop of the α1B adrenoceptor, acts as a 'point of first contact' for the receptor's endogenous agonists. Implication of the non-conserved extracellular regions of the receptor in agonist binding makes it a potential target for the design of highly selective drugs.

A novel structural framework for α(1A/D)-adrenoceptor selective antagonists identified using subtype selective pharmacophores.

In this study four and five-feature pharmacophores for selective antagonists at each of the three α(1)-adrenoceptor (AR) subtypes were used to identify novel α(1)-AR subtype selective compounds in the National Cancer Institute and Tripos LeadQuest databases. 12 compounds were selected, based on diversity of structure, predicted high affinity and selectivity at the α(1D)- subtype compared to α(1A)- and α(1B)-ARs. 9 out of 12 of the tested compounds displayed affinity at the α(1A) and α(1D) -AR subtypes and 6 displayed affinity at all three α(1)-AR subtypes, no α(1B)-AR selective compounds were identified. 8 of the 9 compounds with α(1)-AR affinity were antagonists and one compound displayed partial agonist characteristics. This virtual screening has successfully identified an α(1A/D)-AR selective antagonist, with low µM affinity with a novel structural scaffold of a an isoquinoline fused three-ring system and good lead-like qualities ideal for further drug development.

Pharmacophore design and database searching for selective monoamine neurotransmitter transporter ligands.

Neuronal monoamine transporters (MATs) are involved in the pathophysiology and treatment of mental health conditions such as depression, attention deficit hyperactivity disorder, substance abuse and neurodegenerative disorders including Alzheimer's disease and Parkinson's disease. Various structural classes of compounds have been synthesized and tested in vitro for activity against transporters of three monoamine signaling molecules: noradrenaline (NET); serotonin (SERT) and dopamine (DAT). We have developed and validated a number of pharmacophore models describing the interaction of two classes of compounds with each of these three MATs. These pharmacophores explain the selectivity of binding to the MATs for various compound classes and have been used to search in silico databases for novel, potentially selective ligands. These ligands, after confirmation of their activities, will provide tools for investigating the function of MATs as well as the potential for new therapeutic agents in mental health applications. The database searches also retrieved close analogues of known MAT ligands, further validating the approach.

Selective pharmacophore design for alpha1-adrenoceptor subtypes.

Alpha1-adrenoceptors are G-protein coupled receptors found in a variety of vascular tissues and responsible for vasoconstriction. Selectivity for each of the three subtypes is an important consideration in drug design in order to minimise the possibility of side effects. Using Catalyst we developed ligand-based pharmacophores from alpha(1a,b,d)-selective antagonists available in the literature using three separate training sets. Four-feature pharmacophores were developed for the alpha(1a) and alpha(1b) subtype-selective antagonists and a five-feature pharmacophore was developed for the alpha(1d) subtype-selective antagonists. The alpha(1a) pharmacophore represents both class I and II compounds with good predictivity for other compounds outside the training set as well. The alpha(1b) pharmacophore best predicts the activity of prazosin analogues as these make up the majority of alpha(1b)-selective antagonists. Unexpectedly, no positive ionisable feature was incorporated in the alpha(1b) pharmacophore. The alpha(1d) pharmacophore was based primarily on one structural class of compounds, but has good predictivity for a heterogeneous test set. Preliminary docking studies using AutoDock and optimised alpha1-adrenoceptor homology models, conducted with the antagonists prazosin (32) and 66, showed good agreement with the findings from the pharmacophores.

Homology modelling of RNA polymerase and associated transcription factors from Bacillus subtilis.

RNA polymerase (RNAP) is the central enzyme of transcription and requires interaction with transcription factors in vivo for correct processivity. Both the transcription initiation complex and the ternary elongation complex are stabilised by and require protein-protein interactions between the various components involved. These interactions may form the basis for rational design of small peptide mimics of one or more proteins involved in order to inhibit protein-protein interactions and thus transcription. Here, we present homology models of the model Gram positive organism Bacillus subtilis RNA polymerase in the core and holoenzyme forms. Interactions between RNA polymerase and the transcription factor sigmaA were investigated in order to design peptide mimics of the major interactions.