The Isomeric Preference of an Atypical Dopamine Transporter Inhibitor Contributes to Its Selection of the Transporter Conformation

Abramyan, Ara M.; Stolzenberg, Sebastian; Zheng, Lu; Løland, Claus J.; Noé, Frank; Shi, Lei

doi:10.1021/acschemneuro.7b00094

Cited by 32 publications

(72 citation statements)

References 102 publications

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“…For a range of numbers of MIs (50, 75, 100, 150, 200, 300), we estimated an MSM for each situation and concluded that the 100-MI MSM performs best based on two analysis. We first calculated scores in terms of variational principle [ 44 , 45 ], using cross-validation [ 46 ] as previously described [ 47 ]. This analysis showed the variational scores were comparable for small numbers of MI and decreased when the number of MI is larger than 150.…”

Section: Methodsmentioning

confidence: 99%

“…e ., if Eq ( 1 ) can be satisfied: where P (τ) is the transition matrix estimated from the data at lag time τ (the Markov model), and P ( k τ) is the transition matrix estimated from the same data at longer lag times k τ. In practice, we use P ( k τ) and P k (τ), respectively, to propagate probability starting from one of the metastable states, and measure how much probability ends up in each metastable state [ 47 ].…”

Section: Methodsmentioning

confidence: 99%

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The E2.65A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors

et al. 2018

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The dopamine D2 and D3 receptors (D2R and D3R) are important targets for antipsychotics and for the treatment of drug abuse. SB269652, a bitopic ligand that simultaneously binds both the orthosteric binding site (OBS) and a secondary binding pocket (SBP) in both D2R and D3R, was found to be a negative allosteric modulator. Previous studies identified Glu 2.65 in the SBP to be a key determinant of both the affinity of SB269652 and the magnitude of its cooperativity with orthosteric ligands, as the E 2.65A mutation decreased both of these parameters. However, the proposed hydrogen bond (H-bond) between Glu 2.65 and the indole moiety of SB269652 is not a strong interaction, and a structure activity relationship study of SB269652 indicates that this H-bond may not be the only element that determines its allosteric properties. To understand the structural basis of the observed phenotype of E 2.65A, we carried out molecular dynamics simulations with a cumulative length of~77 μs of D2R and D3R wild-type and their E 2.65 A mutants bound to SB269652. In combination with Markov state model analysis and by characterizing the equilibria of ligand binding modes in different conditions, we found that in both D2R and D3R, whereas the tetrahydroisoquinoline moiety of SB269652 is stably bound in the OBS, the indole-2-carboxamide moiety is dynamic and only intermittently forms H-bonds with Glu 2.65. Our results also indicate that the E 2.65 A mutation significantly affects the overall shape and size of the SBP, as well as the conformation of the N terminus. Thus, our findings suggest that the key role of Glu 2.65 in mediating the allosteric properties of SB269652 extends beyond a direct interaction with SB269652, and provide structural insights for rational design of SB269652 derivatives that may retain its allosteric properties. Author summaryG protein-coupled receptors (GPCRs) are targets of more than 25% of prescription drugs on the market. Due to their critical roles in human physiology, competitive modulation of these receptors has been found to be associated with many undesired side effects. Allosteric modulation holds the promise of retaining normal receptor function and improving selectivity. However, the underlying molecular mechanisms of the allosteric modulation of GPCRs have remained largely uncharted. The dopamine D2-like receptors have been implicated in voluntary movement, reward, sleep, learning, and memory. Based on previous experimental findings, we computationally characterized the binding of a negative allosteric modulator of dopamine D2 and D3 receptors, and revealed the dynamic binding mode of this modulator in a secondary binding pocket (SBP) of the receptors. Our results highlight the key role of a Glu in mediating the allosteric properties of the modulator by shaping the dynamically formed SBP, and shed light on rational design and optimization of allosteric modulators of GPCRs.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The E2.65A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors

et al. 2018

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“…S3D). These changes are characteristic features of the transporter transitioning to an inward-facing conformation [39][40][41].…”

Section: Jjc8-091 Reduces and Jjc8-088 Enhances Optical Brain-stimulamentioning

confidence: 99%

“…To further characterize this observation, we quantified differences of structural elements between the hDAT/JJC8-091 and hDAT/JJC8-088 complexes, by applying the previously described pairwise interaction analyzer for DAT (PIA-DAT) [39]. Specifically, our analysis showed that the side chain phenyl group of Phe320 rotates to a "closed" conformation in the presence of JJC8-091, but not JJC8-088, making hydrophobic interactions with the propanol moiety of JJC8-091 ( Fig.…”

Section: Jjc8-091 Reduces and Jjc8-088 Enhances Optical Brain-stimulamentioning

confidence: 99%

Translating the atypical dopamine uptake inhibitor hypothesis toward therapeutics for treatment of psychostimulant use disorders

Newman

Cao

Keighron

et al. 2019

Neuropsychopharmacol.

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109

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Medication-assisted treatments are unavailable to patients with cocaine use disorders. Efforts to develop potential pharmacotherapies have led to the identification of a promising lead molecule, JJC8-091, that demonstrates a novel binding mode at the dopamine transporter (DAT). Here, JJC8-091 and a structural analogue, JJC8-088, were extensively and comparatively assessed to elucidate neurochemical correlates to their divergent behavioral profiles. Despite sharing significant structural similarity, JJC8-088 was more cocaine-like, increasing extracellular DA concentrations in the nucleus accumbens shell (NAS) efficaciously and more potently than JJC8-091. In contrast, JJC8-091 was not self-administered and was effective in blocking cocaine-induced reinstatement to drug seeking. Electrophysiology experiments confirmed that JJC8-091 was more effective than JJC8-088 at inhibiting cocaine-mediated enhancement of DA neurotransmission. Further, when VTA DA neurons in DAT-cre mice were optically stimulated, JJC8-088 produced a significant leftward shift in the stimulation-response curve, similar to cocaine, while JJC8-091 shifted the curve downward, suggesting attenuation of DA-mediated brain reward. Computational models predicted that JJC8-088 binds in an outward facing conformation of DAT, similar to cocaine. Conversely, JJC8-091 steers DAT towards a more occluded conformation. Collectively, these data reveal the underlying molecular mechanism at DAT that may be leveraged to rationally optimize leads for the treatment of cocaine use disorders, with JJC8-091 representing a compelling candidate for development.

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“…In previous studies of specific biomolecular systems with MSMs based on MD simulations, reported longest implicit timescales turned out to be smaller than the aggregate sampling by at least one order of magnitude [5][6][7][8][9][10][11][12][13][14][15][16][17] or comparable to the aggregate sampling. [18][19][20][21][22] In this paper, we analyze several MSMs with different topologies to uncover the reasons for the above empirical rule. These MSMs represent typical cases when slow dynamics is observed in biomolecular systems.…”

Section: Introductionmentioning

confidence: 99%

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

Sinitskiy

Pande

2018

The Journal of Chemical Physics

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Markov state models (MSMs) have been widely used to analyze computer simulations of various biomolecular systems. They can capture conformational transitions much slower than an average or maximal length of a single molecular dynamics (MD) trajectory from the set of trajectories used to build the MSM. A rule of thumb claiming that the slowest implicit timescale captured by an MSM should be comparable by the order of magnitude to the aggregate duration of all MD trajectories used to build this MSM has been known in the field. However, this rule have never been formally proved. In this work, we present analytical results for the slowest timescale in several types of MSMs, supporting the above rule. We conclude that the slowest implicit timescale equals the product of the aggregate sampling and four factors that quantify: (1) how much statistics on the conformational transitions corresponding to the longest implicit timescale is available, (2) how good the sampling of the destination Markov state is, (3) the gain in statistics from using a sliding window for counting transitions between Markov states, and (4) a bias in the estimate of the implicit timescale arising from finite sampling of the conformational transitions. We demonstrate that in many practically important cases all these four factors are on the order of unity, and we analyze possible scenarios that could lead to their significant deviation from unity. Overall, we provide for the first time analytical results on the slowest timescales captured by MSMs. These results can guide further practical applications of MSMs to biomolecular dynamics and allow for higher computational efficiency of simulations.2

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The Isomeric Preference of an Atypical Dopamine Transporter Inhibitor Contributes to Its Selection of the Transporter Conformation

Cited by 32 publications

References 102 publications

The E2.65A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors

The E2.65A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors

Translating the atypical dopamine uptake inhibitor hypothesis toward therapeutics for treatment of psychostimulant use disorders

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

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