Screening oxime libraries by means of mass spectrometry (MS) binding assays: Identification of new highly potent inhibitors to optimized inhibitors γ-aminobutyric acid transporter 1

Visualizing GABA transporters in vivo: an overview of reported radioligands and future directions

By clearing GABA from the synaptic cleft, GABA transporters (GATs) play an essential role in inhibitory neurotransmission. Consequently, in vivo visualization of GATs can be a valuable diagnostic tool and biomarker for various psychiatric and neurological disorders. Not surprisingly, in recent years several research attempts to develop a radioligand have been conducted, but so far none have led to suitable radioligands that allow imaging of GATs. Here, we provide an overview of the radioligands that were developed with a focus on GAT1, since this is the most abundant transporter and most of the research concerns this GAT subtype. Initially, we focus on the field of GAT1 inhibitors, after which we discuss the development of GAT1 radioligands based on these inhibitors. We hypothesize that the radioligands developed so far have been unsuccessful due to the zwitterionic nature of their nipecotic acid moiety. To overcome this problem, the use of non-classical GAT inhibitors as basis for GAT1 radioligands or the use of carboxylic acid bioisosteres may be considered. As the latter structural modification has already been used in the field of GAT1 inhibitors, this option seems particularly viable and could lead to the development of more successful GAT1 radioligands in the future.

Combination of MS Binding Assays and affinity selection mass spectrometry for screening of structurally homogenous libraries as exemplified for a focused oxime library addressing the neuronal GABA transporter 1

This study presents an efficient screening approach based on combination of mass spectrometry (MS) based binding assays (MS Binding Assays) and affinity selection mass spectrometry (ASMS) customized for screening of structurally homogeneous libraries sharing a common mass spectrometric fragmentation pattern. After reaction of a nipecotic acid derivative possessing a hydroxylamine functionality with aldehydes, the resulting oxime library was screened accordingly toward the GABA transporter subtype 1 (GAT1), a drug target for several neurological disorders. After assessing sublibraries' activities for inhibition of reporter ligand binding, hits in active ones were directly identified. This could be achieved by recording mass transitions for the reporter ligand as well as those predicted for the library components in a single LC-MS/MS run with a triple quadrupole mass spectrometer in the multiple reaction monitoring mode. Identification of hits with a predefined affinity could be reliably accomplished by calculation of IC₅₀-values from specific binding concentrations of library constituents and reporter ligand. Application of this strategy revealed six hits, from which two of them were resynthesized for further biological evaluation. Thereby, the best one displayed a pK_i of 7.38 in MS Binding Assays and a pIC₅₀ of 6.82 in [³H]GABA uptake assays for GAT1.

Protein-Directed Dynamic Combinatorial Chemistry: An Efficient Strategy in Drug Design

Protein-directed dynamic combinatorial chemistry (P-D DCC) is considered a powerful strategy to identify ligands to pharmacologically relevant protein targets. The protein selects its affinity ligands in situ through a thermodynamic templated effect in which the library composition shifts to the formation of specific library members at the expense of other (nonbinding) species. The increase in concentration of the selected species is known as amplification and leads to the discovery of new hit compounds for protein targets. This Mini-Review contains an updated overview of the protein-directed DCC applications and the fundamental aspects to take into account when designing a P-D DCC experiment such as the most biocompatible reversible reactions and the methodology used to analyze the experiments.

Solving the Competitive Binding Equilibria between Many Ligands: Application to High-Throughput Screening and Affinity Optimization

Modern small-molecule drug discovery relies on the selective targeting of biological macromolecules by low-molecular weight compounds. Therefore, the binding affinities of candidate drugs to their targets are key for pharmacological activity and clinical use. For drug discovery methods where multiple drug candidates can simultaneously bind to the same target, a competition is established, and the resulting equilibrium depends on the dissociation constants and concentration of all the species present. Such coupling between all equilibrium-governing parameters complicates analysis and development of improved mixture-based, high-throughput drug discovery techniques. In this work, we present an iterative computational algorithm to solve coupled equilibria between an arbitrary number of ligands and a biomolecular target that is efficient and robust. The algorithm does not require the estimation of initial values to rapidly converge to the solution of interest. We explored binding equilibria under ligand/receptor conditions used in mixture-based library screening by affinity selection-mass spectrometry (AS-MS). Our studies support a facile method for affinity-ranking hits. The ranking method involves varying the receptor-to-ligand concentration ratio in a pool of candidate ligands in two sequential AS-MS analyses. The ranking is based on the relative change in bound ligand concentration. The method proposed does not require a known reference ligand and produces a ranking that is insensitive to variations in the concentration of individual compounds, thereby enabling the use of unpurified compounds generated by mixture-based combinatorial synthesis techniques.

A Library Screening Strategy Combining the Concepts of MS Binding Assays and Affinity Selection Mass Spectrometry

The primary objective of early drug development is to identify hits and leads for a target of interest. To achieve this aim, rapid, and reliable screening techniques for a huge number of compounds are needed. Mass spectrometry based binding assays (MS Binding Assays) represent a well-established technique for library screening based on competitive binding experiments revealing active sublibraries due to reduced binding of a reporter ligand and following hit identification for active libraries by deconvolution in further competitive binding experiments. In the present study, we combined the concepts of MS Binding Assays and affinity selection mass spectrometry (ASMS) to improve the efficiency of the hit identification step. In that case, only a single competitive binding experiment is performed that is in the first step analyzed for reduced binding of the reporter ligand and—only if a sublibrary is active—additionally for specific binding of individual library components. Subsequently, affinities of identified hits as well as activities of reduced sublibraries (i.e., all sublibrary components without hit) are assessed in additional competitive binding experiments. We exemplified this screening concept for the identification of ligands addressing the most widespread GABA transporter subtype in the brain (GAT1) studying in the beginning a library composed of 128 and further on a library of 1,280 well-characterized GAT1 inhibitors, drug substances, and pharmacological tool compounds. Determination of sublibraries' activities was done by quantification of bound NO711 as reporter ligand and hit identification for the active ones achieved in a further LC-ESI-MS/MS run in the multiple reaction monitoring mode enabling detection of all sublibrary components followed by hit verification and investigation of reduced sublibraries in further competitive binding experiments. In this way, we could demonstrate that all GAT1 inhibitors reducing reporter ligand binding below 50% at a concentration of 1 μM are detected reliably without generation of false positive or false negative hits. As the described strategy is apart from its reliability also highly efficient, it can be assumed to become a valuable tool in early drug research, especially for membrane integrated drug targets that are often posing problems in established screening techniques.

Protein-Templated Dynamic Combinatorial Chemistry: Brief Overview and Experimental Protocol

Dynamic combinatorial chemistry (DCC) is a powerful tool to identify bioactive compounds. This efficient technique allows the target to select its own binders and circumvents the need for synthesis and biochemical evaluation of all individual derivatives. An ever-increasing number of publications report the use of DCC on biologically relevant target proteins. This minireview complements previous reviews by focusing on the experimental protocol and giving detailed examples of essential steps and factors that need to be considered, such as protein stability, buffer composition and cosolvents.