Dataset Information

Structure-Guided Computational Methods Predict Multiple Distinct Binding Modes for Pyrazoloquinolinones in GABA_A Receptors.

ABSTRACT: Pyrazoloquinolinones (PQs) are a versatile class of GABA_A receptor ligands. It has been demonstrated that high functional selectivity for certain receptor subtypes can be obtained by specific substitution patterns, but so far, no clear SAR rules emerge from the studies. As is the case for many GABA_A receptor targeting chemotypes, PQs can interact with distinct binding sites on a given receptor pentamer. In pentamers of ??? composition, such as the most abundant ?1?2?2 subtype, many PQs are high affinity binders of the benzodiazepine binding site at the extracellular ?+/?2- interfaces. There they display a functionally near silent, flumazenil-like allosteric activity. More recently, interactions with extracellular ?+/?- interfaces have been investigated, where strong positive modulation can be steered toward interesting subtype preferences. The most prominent examples are functionally ?6-selective PQs. Similar to benzodiazepines, PQs also seem to interact with sites in the transmembrane domain, mainly the sites used by etomidate and barbiturates. This promiscuity leads to potential contributions from multiple sites to net modulation. Developing ligands that interact exclusively with the extracellular ?+/?- interfaces would be desired. Correlating functional profiles with binding sites usage is hampered by scarce and heterogeneous experimental data, as shown in our meta-analysis of aggregated published data. In the absence of experimental structures, bound states can be predicted with pharmacophore matching methods and with computational docking. We thus performed pharmacophore matching studies for the unwanted sites, and computational docking for the extracellular ?1,6+/?3- interfaces. The results suggest that PQs interact with their binding sites with diverse binding modes. As such, rational design of improved ligands needs to take a complex structure-activity landscape with branches between sub-series of derivatives into account. We present a workflow, which is suitable to identify and explore potential branching points on the structure-activity landscape of any small molecule chemotype.

SUBMITTER: Fabjan J

PROVIDER: S-EPMC7844064 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Structure-Guided Computational Methods Predict Multiple Distinct Binding Modes for Pyrazoloquinolinones in GABAA Receptors.

Fabjan Jure J Koniuszewski Filip F Schaar Benjamin B Ernst Margot M

Frontiers in neuroscience 20210115

Pyrazoloquinolinones (PQs) are a versatile class of GABAA receptor ligands. It has been demonstrated that high functional selectivity for certain receptor subtypes can be obtained by specific substitution patterns, but so far, no clear SAR rules emerge from the studies. As is the case for many GABAA receptor targeting chemotypes, PQs can interact with distinct binding sites on a given receptor pentamer. In pentamers of αβγ composition, such as the most abundant α1β2γ2 subty ...[more]

PMID: 33519364

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Project description:Key pointsWe confirm that GABAB receptors (GABAB -Rs) are involved in the termination of Up-states; their blockade consistently elongates Up-states. GABAB -Rs also modulate Down-states and the oscillatory cycle, thus having an impact on slow oscillation rhythm and its regularity. The most frequent effect of GABAB -R blockade is elongation of Down-states and subsequent decrease of oscillatory frequency, with an increased regularity. In a quarter of cases, GABAB -R blockade shortened Down-states and increased oscillatory frequency, changes that are independent of firing rates in Up-states. Our computer model provides mechanisms for the experimentally observed dynamics following blockade of GABAB -Rs, for Up/Down durations, oscillatory frequency and regularity. The time course of excitation, inhibition and adaptation can explain the observed dynamics of the network. This study brings novel insights into the role of GABAB -R-mediated slow inhibition on the slow oscillatory activity, which is considered the default activity pattern of the cortical network.AbstractSlow wave oscillations (SWOs) dominate cortical activity during deep sleep, anaesthesia and in some brain lesions. SWOs are composed of periods of activity (Up states) interspersed with periods of silence (Down states). The rhythmicity expressed during SWOs integrates neuronal and connectivity properties of the network and is often altered under pathological conditions. Adaptation mechanisms as well as synaptic inhibition mediated by GABAB receptors (GABAB -Rs) have been proposed as mechanisms governing the termination of Up states. The interplay between these two mechanisms is not well understood, and the role of GABAB -Rs controlling the whole cycle of the SWO has not been described. Here we contribute to its understanding by combining in vitro experiments on spontaneously active cortical slices and computational techniques. GABAB -R blockade modified the whole SWO cycle, not only elongating Up states, but also affecting the subsequent Down state duration. Furthermore, while adaptation tends to yield a rather regular behaviour, we demonstrate that GABAB -R activation desynchronizes the SWOs. Interestingly, variability changes could be accomplished in two different ways: by either shortening or lengthening the duration of Down states. Even when the most common observation following GABAB -Rs blocking is the lengthening of Down states, both changes are expressed experimentally and also in numerical simulations. Our simulations suggest that the sluggishness of GABAB -Rs to follow the excitatory fluctuations of the cortical network can explain these different network dynamics modulated by GABAB -Rs.

Dataset Information

Structure-Guided Computational Methods Predict Multiple Distinct Binding Modes for Pyrazoloquinolinones in GABA_A Receptors.

Publications

Structure-Guided Computational Methods Predict Multiple Distinct Binding Modes for Pyrazoloquinolinones in GABA<sub>A</sub> Receptors.

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