In Silico and in Vitro Study of Trace Amines (TA) and Dopamine (DOP) Interaction with Human Alpha 1-Adrenergic Receptor and the Bacterial Adrenergic Receptor QseC.

BACKGROUND/AIMS: Trace amines (TA) are small organic compounds that have neuromodulator activity due to their interaction with some neuron-related receptors, such as trace amine associated receptors (TAARs), α2-adrenergic receptor (α2-AR) and ß-adrenergic receptor (ß-AR). However, there is little information on whether TA and dopamine (DOP) can interact with other adrenergic receptors (ARs) such as the mammalian α1-AR and the bacterial counterpart QseC, which is involved in quorum sensing of some Gram-negative pathogens. The aim of this study was to investigate the interaction of TA and DOP with α1-AR and QseC. METHODS: We performed an in silico study using 3D structure from SWISS MODEL and analyzed the protein interaction via molecular docking using PyMol, PoseView and PyRX 8.0. For the in vitro study, we investigated the QseC kinase activity by measuring the remaining ATP in a reaction containing QseC-enriched membrane incubated together with purified QseB and EPI, TA, DOP, or PTL respectively. We also measured the intracellular Ca++ levels, which represents the α1-AR activation, in LNCAP (pancreatic cell line) cells treated with EPI, TA, DOP and PTL respectively using a fluorescence-based assay. The LNCAP cell proliferation was measured using an MTT-based assay. RESULTS: Our in silico analysis revealed that TAs and DOP have high binding affinity to the human α1-AR and the bacterial adrenergic receptor (QseC), comparable to epinephrine (EPI). Both are membrane-bound kinases. Experimental studies with pancreatic cell line (LNCAP) showed that the TAs and DOP act as α1-AR antagonist by counteracting the effect of EPI. In the presence of EPI, TA and DOP trigger an increase of the intracellular Ca++ levels in the LNCAP cells leading to an inhibition of cell proliferation. Although in silico data suggest an interaction of TA and DOP with QseC, they do not inhibit the kinase activity of QseC, a histidine kinase receptor involved in quorum sensing which is also sensitive to EPI. CONCLUSION: Our study showed that the TAs and DOP act as α1-AR antagonist but no effect was observed for QseC.

Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications.

Biological network models offer a framework for understanding disease by describing the relationships between the mechanisms involved in the regulation of biological processes. Crowdsourcing can efficiently gather feedback from a wide audience with varying expertise. In the Network Verification Challenge, scientists verified and enhanced a set of 46 biological networks relevant to lung and chronic obstructive pulmonary disease. The networks were built using Biological Expression Language and contain detailed information for each node and edge, including supporting evidence from the literature. Network scoring of public transcriptomics data inferred perturbation of a subset of mechanisms and networks that matched the measured outcomes. These results, based on a computable network approach, can be used to identify novel mechanisms activated in disease, quantitatively compare different treatments and time points, and allow for assessment of data with low signal. These networks are periodically verified by the crowd to maintain an up-to-date suite of networks for toxicology and drug discovery applications.