Structural basis for the functions of dopamine receptors, neurotransmitter transporters, and sigma 1 receptor

National Institute On Drug Abuse

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Abstract

Aim 1. Structure-function investigations of G-protein coupled receptors The dopamine D2/D3 receptor (D2R/D3R) agonists are used as therapeutics for Parkinsons disease (PD) and other motor disorders. Selective targeting of D3R over D2R is attractive because of D3Rs restricted tissue distribution with potentially fewer side-effects and its putative neuroprotective effect. However, the high sequence homology between the D2R and D3R poses a challenge in the development of D3R selective agonists. To address the ligand selectivity, bitopic ligands were designed and synthesized previously based on a potent D3R-preferential agonist PF592,379 as the primary pharmacophore (PP). This PP was attached to various secondary pharmacophores (SPs) using chemically different linkers. We characterized some of these novel bitopic ligands at both D3R and D2R using BRET-based functional assays. The bitopic ligands showed varying differences in potencies and efficacies. In addition, the chirality of the PP was key to conferring improved D3R potency, selectivity, and G protein signaling bias. In particular, compound AB04-88 exhibited significant D3R over D2R selectivity, and G protein bias at D3R. This bias was consistently observed at various time-points ranging from 8 to 46 min. Together, the structure-activity relationships derived from these functional studies reveal unique pharmacology at D3R and support further evaluation of functionally biased D3R agonists for their therapeutic potential. Aim 2. Structural basis of atypical and allosteric modulators of DAT and SERT Psychostimulant drugs, such as cocaine, inhibit dopamine reuptake via blockade of DAT, which is the primary mechanism underpinning their abuse. Atypical DAT inhibitors are dissimilar to cocaine and can block cocaine or methamphetamine induced behaviors, supporting their development as part of a treatment regimen for psychostimulant use disorders. When developing these atypical DAT inhibitors as medications, it is necessary to avoid off-target binding that can produce unwanted side effects or toxicities. In particular, the blockade of a potassium channel, human ether-a-go-go (hERG), can lead to the potentially lethal ventricular tachycardia. We established a counter screening platform for DAT and against hERG binding by combining machine learning-based quantitative structure-activity relationship (QSAR) modeling, experimental validation, and molecular modeling and simulations. Our results show the available data are adequate to establish robust QSAR models, as validated by chemical synthesis and pharmacological evaluation of a validation set of DAT inhibitors. Further, the QSAR models based on subsets of the data according to experimental approaches used have predictive power as well, which opens the door to target specific functional states of a protein. Complementarily, our molecular modeling and simulations identified the structural elements responsible for a pair of DAT inhibitors having opposite binding affinity trends at DAT and hERG, which can be leveraged for rational optimization of lead atypical DAT inhibitors with desired pharmacological properties.