High-throughput mechanistic screening of non-equilibrium inhibitors by a fully automated data analysis pipeline in early drug-discovery.

Recent efforts for increasing the success in drug discovery focus on an early, massive, and routine mechanistic and/or kinetic characterization of drug-target engagement as part of a design-make-test-analyze strategy. From an experimental perspective, many mechanistic assays can be translated into a scalable format on automation platforms and thereby enable routine characterization of hundreds or thousands of compounds. However, now the limiting factor to achieve such in-depth characterization at high-throughput becomes the quality-driven data analysis, the sheer scale of which outweighs the time available to the scientific staff of most labs. Therefore, automated analytical workflows are needed to enable such experimental scale-up. We have implemented such a fully automated workflow in Genedata Screener for time-dependent ligand-target binding analysis to characterize non-equilibrium inhibitors. The workflow automates Quality Control (QC) / data modelling and decision-making process in a staged analysis: (1) quality control of raw input data-fluorescence signal-based progress curves - featuring automated rejection of unsuitable measurements; (2) automated model selection - one-step versus two-step binding model - using statistical methods and biological validity rules; (3) result visualization in specific plots and annotated result tables, enabling the scientist to review large result sets efficiently and, at the same time, to rapidly identify and focus on interesting or unusual results; (4) an interactive user interface for immediate adjustment of automated decisions, where necessary. Applying this workflow to first-pass, high-throughput kinetic studies on kinase projects has allowed us to surmount previously rate-limiting manual analysis steps and boost productivity; and is now routinely embedded in a biopharma discovery research process.

Acoustic Mist Ionization Mass Spectrometry for Ultrahigh-Throughput Metabolomics Screening.

Incorporating safety data early in the drug discovery pipeline is key to reducing costly lead candidate failures. For a single drug development project, we estimate that several thousand samples per day require screening (<10 s per acquisition). While chromatography-based metabolomics has proven value at predicting toxicity from metabolic biomarker profiles, it lacks sufficiently high sample throughput. Acoustic mist ionization mass spectrometry (AMI-MS) is an atmospheric pressure ionization approach that can measure metabolites directly from 384-well plates with unparalleled speed. We sought to implement a signal processing and data analysis workflow to produce high-quality AMI-MS metabolomics data and to demonstrate its application to drug safety screening. An existing direct infusion mass spectrometry workflow was adapted, extended, optimized, and tested, utilizing three AMI-MS data sets acquired from technical and biological replicates of metabolite standards and HepG2 cell lysates and a toxicity study. Driven by criteria to minimize variance and maximize feature counts, an algorithm to extract the pulsed scan data was designed; parameters for signal-to-noise-ratio, replicate filter, sample filter, missing value filter, and RSD filter were all optimized; normalization and batch correction strategies were adapted; and cell phenotype filtering was implemented to exclude high cytotoxicity samples. The workflow was demonstrated using a highly replicated HepG2 toxicity data set, comprising 2772 samples from exposures to 16 drugs across 9 concentrations and generated in under 5 h, revealing metabolic phenotypes and individual metabolite changes that characterize specific modes of action. This AMI-MS workflow opens the door to ultrahigh-throughput metabolomics screening, increasing the rate of sample analysis by approximately 2 orders of magnitude.

A Novel High-Throughput FLIPR Tetra-Based Method for Capturing Highly Confluent Kinetic Data for Structure-Kinetic Relationship Guided Early Drug Discovery.

Target engagement by small molecules is necessary for producing a physiological outcome. In the past, a lot of emphasis was placed on understanding the thermodynamics of such interactions to guide structure-activity relationships. It is becoming clearer, however, that understanding the kinetics of the interaction between a small-molecule inhibitor and the biological target [structure-kinetic relationship (SKR)] is critical for selection of the optimum candidate drug molecule for clinical trial. However, the acquisition of kinetic data in a high-throughput manner using traditional methods can be labor intensive, limiting the number of molecules that can be tested. As a result, in-depth kinetic studies are often carried out on only a small number of compounds, and usually at a later stage in the drug discovery process. Fundamentally, kinetic data should be used to drive key decisions much earlier in the drug discovery process, but the throughput limitations of traditional methods preclude this. A major limitation that hampers acquisition of high-throughput kinetic data is the technical challenge in collecting substantially confluent data points for accurate parameter estimation from time course analysis. Here, we describe the use of the fluorescent imaging plate reader (FLIPR), a charge-coupled device (CCD) camera technology, as a potential high-throughput tool for generating biochemical kinetic data with smaller time intervals. Subsequent to the design and optimization of the assay, we demonstrate the collection of highly confluent time-course data for various kinase protein targets with reasonable throughput to enable SKR-guided medicinal chemistry. We select kinase target 1 as a special case study with covalent inhibition, and demonstrate methods for rapid and detailed analysis of the resultant kinetic data for parameter estimation. In conclusion, this approach has the potential to enable rapid kinetic studies to be carried out on hundreds of compounds per week and drive project decisions with kinetic data at an early stage in drug discovery.

Information-rich high-throughput cellular assays using acoustic mist ionisation mass spectrometry.

Cellular metabolites and phospholipids contain a vast amount of information about the current state of a cell, and are a useful resource for understanding the effects of drug candidates in vitro. Typical human cell-based assays in early drug discovery rely on simple readouts such as cell viability, or focus on single end-points revealed by an antibody or other label-based technologies. We introduce a generic 384-well plate-based workflow for data-rich cellular assays using facile sample preparation and direct analysis by acoustic mist ionization mass spectrometry (AMI-MS). The assays are compatible with adherent and suspension cells, and provide simultaneous information about a number of cellular small-molecule components (e.g., amino acids, nucleotides, phospholipids), cellular processes (e.g., proliferation, glycolysis, oxidative stress), as well as compound uptake and metabolism. Thanks to the high-throughput and low cost of analysis, the workflow can be introduced very early into any drug discovery pipeline to help select optimal lead molecules.

Acoustic Mist Ionization Platform for Direct and Contactless Ultrahigh-Throughput Mass Spectrometry Analysis of Liquid Samples.

Mass spectrometry (MS) has many advantages as a quantitative detection technology for applications within drug discovery. However, current methods of liquid sample introduction to a detector are slow and limit the use of mass spectrometry for kinetic and high-throughput applications. We present the development of an acoustic mist ionization (AMI) interface capable of contactless nanoliter-scale "infusion" of up to three individual samples per second into the mass detector. Installing simple plate handling automation allowed us to reach a throughput of 100 000 samples per day on a single mass spectrometer. We applied AMI-MS to identify inhibitors of a human histone deacetylase from AstraZeneca's collection of 2 million small molecules and measured their half-maximal inhibitory concentration. The speed, sensitivity, simplicity, robustness, and consumption of nanoliter volumes of sample suggest that this technology will have a major impact across many areas of basic and applied research.

Nanoparticles and intracellular applications of surface-enhanced Raman spectroscopy.

Surface-enhanced Raman spectrocopy (SERS) offers ultrasensitive vibrational fingerprinting at the nanoscale. Its non-destructive nature affords an ideal tool for interrogation of the intracellular environment, detecting the localisation of biomolecules, delivery and monitoring of therapeutics and for characterisation of complex cellular processes at the molecular level. Innovations in nanotechnology have produced a wide selection of novel, purpose-built plasmonic nanostructures capable of high SERS enhancement for intracellular probing while microfluidic technologies are being utilised to reproducibly synthesise nanoparticle (NP) probes at large scale and in high throughput. Sophisticated multivariate analysis techniques unlock the wealth of previously unattainable biomolecular information contained within large and multidimensional SERS datasets. Thus, with suitable combination of experimental techniques and analytics, SERS boasts enormous potential for cell based assays and to expand our understanding of the intracellular environment. In this review we trace the pathway to utilisation of nanomaterials for intracellular SERS. Thus we review and assess nanoparticle synthesis methods, their toxicity and cell interactions before presenting significant developments in intracellular SERS methodologies and how identified challenges can be addressed.

High-Throughput Screening Using Mass Spectrometry within Drug Discovery.

In order to detect a biochemical analyte with a mass spectrometer (MS) it is necessary to ionize the analyte of interest. The analyte can be ionized by a number of different mechanisms, however, one common method is electrospray ionization (ESI). Droplets of analyte are sprayed through a highly charged field, the droplets pick up charge, and this is transferred to the analyte. High levels of salt in the assay buffer will potentially steal charge from the analyte and suppress the MS signal. In order to avoid this suppression of signal, salt is often removed from the sample prior to injection into the MS. Traditional ESI MS relies on liquid chromatography (LC) to remove the salt and reduce matrix effects, however, this is a lengthy process. Here we describe the use of RapidFire™ coupled to a triple-quadrupole MS for high-throughput screening. This system uses solid-phase extraction to de-salt samples prior to injection, reducing processing time such that a sample is injected into the MS ~every 10 s.

Novel Acoustic Loading of a Mass Spectrometer: Toward Next-Generation High-Throughput MS Screening.

High-throughput, direct measurement of substrate-to-product conversion by label-free detection, without the need for engineered substrates or secondary assays, could be considered the "holy grail" of drug discovery screening. Mass spectrometry (MS) has the potential to be part of this ultimate screening solution, but is constrained by the limitations of existing MS sample introduction modes that cannot meet the throughput requirements of high-throughput screening (HTS). Here we report data from a prototype system (Echo-MS) that uses acoustic droplet ejection (ADE) to transfer femtoliter-scale droplets in a rapid, precise, and accurate fashion directly into the MS. The acoustic source can load samples into the MS from a microtiter plate at a rate of up to three samples per second. The resulting MS signal displays a very sharp attack profile and ions are detected within 50 ms of activation of the acoustic transducer. Additionally, we show that the system is capable of generating multiply charged ion species from simple peptides and large proteins. The combination of high speed and low sample volume has significant potential within not only drug discovery, but also other areas of the industry.

Structure-Based Design of Potent and Selective Inhibitors of the Metabolic Kinase PFKFB3.

A weak screening hit with suboptimal physicochemical properties was optimized against PFKFB3 kinase using critical structure-guided insights. The resulting compounds demonstrated high selectivity over related PFKFB isoforms and modulation of the target in a cellular context. A selected example demonstrated exposure in animals following oral dosing. Examples from this series may serve as useful probes to understand the emerging biology of this metabolic target.

Design and synthesis of novel lactate dehydrogenase A inhibitors by fragment-based lead generation.

Lactate dehydrogenase A (LDHA) catalyzes the conversion of pyruvate to lactate, utilizing NADH as a cofactor. It has been identified as a potential therapeutic target in the area of cancer metabolism. In this manuscript we report our progress using fragment-based lead generation (FBLG), assisted by X-ray crystallography to develop small molecule LDHA inhibitors. Fragment hits were identified through NMR and SPR screening and optimized into lead compounds with nanomolar binding affinities via fragment linking. Also reported is their modification into cellular active compounds suitable for target validation work.