Structure-based Discovery of Conformationally Selective Inhibitors of the Serotonin Transporter

Abstract

The serotonin transporter (SERT) removes synaptic serotonin and is the target of anti-depressant drugs. SERT adopts three conformations: outward-open, occluded, and inward-open. All known inhibitors target the outward-open state except ibogaine, which has an unusual anti-depressant profile and stabilizes the inward-open conformation. Unfortunately, ibogaine is promiscuous and cardiotoxic, limiting understanding of inward-open state ligands. We computationally docked over 200 million small molecules against the ibogaine stabilized inward-open state of SERT. Thirty-six top-ranking compounds were synthesized and thirteen inhibited with potencies ranging from 29 to 5000 nM. Structure-based optimization led to two novel inhibitors with Ki values down to 3 nM. The new molecules stabilized an outward-closed state of the transporter and had little activity against off-targets. A cryo-EM structure of one of these bound to SERT confirmed the predicted geometry. In mouse behavioral assays, both had anxiolytic and anti- depressant activity, with potencies up to 200 better than fluoxetine.

Modeling the expansion of virtual screening libraries

“…While bio-like molecules confer no advantage in docking hit rate, nor in physical properties, they may have advantages not directly assessed here, including being transporter substrates 32 . Thus far, where molecules from ultra-large-library docking have been tested in vivo they have had favorable plasma and brain exposure on intraperitoneal and even oral dosing 21,25,36,37 , but this remains a small set of experiments. Mechanically, the divergence of the tangible libraries from bio-like molecules has only been measured by one type of topological similarity, other metrics may show different levels of divergence.…”

“…Naturally, this partly reflects the intentional lead-like 35 character of the tangible molecules, reducing Ro5 violations, but since this is the set being docked it remains meaningful. Finally, where molecules deriving from ultra-large-library docking have been tested in vivo they have had favorable plasma and brain exposure on intraperitoneal and even oral dosing 21,25,36,37 . Thus, while we cannot rule out an advantage for bio-like molecules, the physical properties of the tangible molecules put them at no obvious disadvantage.…”

Large library docking for novel SARS-CoV-2 main protease non-covalent and covalent inhibitors

“…While the strengths of this study were the identification of multiple new MPro inhibitor scaffolds, with subsequent crystal structures supporting the docking predictions, the work also revealed liabilities of docking screens. In contrast to campaigns against G protein-coupled receptors [38][39][40][41] and other integral membrane receptors 42,43 , hit rates against MPro were in the 7 to 15% range, rather than the 25 to 60% range. Meanwhile, the activities of the better MPro docking hits were in the 20 to 100 µM range, not the lowto mid-nM range found against the integral membrane proteins.…”

Large library docking for novel SARS‐CoV‐2 main protease non‐covalent and covalent inhibitors

“…While the strengths of this study were the identification of multiple new M Pro inhibitor scaffolds, with subsequent crystal structures supporting the docking predictions, the work also revealed liabilities of our docking strategy. Docking large libraries of lead‐like molecules against G protein‐coupled receptors (Levit Kaplan et al, 2022; Lyu et al, 2019; Stein et al, 2020; Wang et al, 2017) and other integral membrane proteins (Alon et al, 2021; Singh et al, 2022), with well‐formed orthosteric sites and well‐defined ligand‐recognition hot‐spots, can have hit rates in the 25%–60% range, whereas the hit rates against M Pro were in the 6%–15% range. A similar trend is true for the potency of the docking hits against M Pro , which were in the 20–150 μM range, not the low‐ to mid‐nM range found against the integral membrane proteins.…”

“…While the multiple chemotypes explored here, and their crystallographic structures, may template further optimization of M Pro inhibitors, a feature of these studies was docking hit rates between 7% and 15%, with hits often in the mid‐μM range. These rates and affinities are substantially worse than observed in many GPCRs, integral membrane proteins, transporters, and enzymes like β‐lactamase (Alon et al, 2021; Carlsson et al, 2011; Fink et al, 2022; Kaplan et al, 2022; Levit Kaplan et al, 2022; Lyu et al, 2019; Manglik et al, 2016; Singh et al, 2022; Stein et al, 2020; Wang et al, 2018). Meanwhile, the optimized affinities reached here were meaningfully weaker than those achieved by approaches such as fragment‐based discovery, both against M Pro itself and against other SARS‐2 targets, like macrodomain (Gahbauer et al, 2022; Schuller et al, 2021).…”