Optimization of a higher throughput microsomal stability screening assay for profiling drug discovery candidates

Metabolic stability plays an important role in the success of drug candidates. First-pass metabolism is one of the major causes of poor oral bioavailability and short half-life. Traditionally, metabolic stability was evaluated at a later stage of drug discovery and required laborious manual manipulations. With the advance of high-throughput screening, combinatorial chemistry, and early profiling of drug-like properties, automated and rapid stability assays are needed to meet the increasing demand of throughput, speed, and reproducibility at earlier stages of drug discovery. The authors describe optimization of a simple, robust, high-throughput microsomal stability assay developed in a 96-well format. The assay consists of 2 automated components: robotic sample preparation for incubation and cleanup and rapid liquid chromatography/mass spectrometry/mass spectrometry (LC/MS/MS) analysis to determine percent remaining of the parent compound. The reagent solutions and procedural steps were optimized for automation. Variables affecting assay results were investigated. The variability introduced by microsome preparations from different sources (various vendors and batches) was studied and indicates the need for careful control. Quality control and normalization of the stability results are critical when applying the screening data, generated at different times or research sites, to discovery projects.     

Cherry-picking in an orchard: unattended LC/MS analysis from an autosampler with >32,000 samples online

The 1,536-well microplate format has widely supplanted the 384-well microplate format for high-throughput screening and for IC(50) assays. Previously, liquid chromatography/mass spectrometry (LC/MS) analyses of such samples required manual transfers of the wells of interest from a 1,536-well plate into a 384-well plate. Because this manual transfer introduced a source of potential error, it became clear that a more appropriate solution would be to sample directly from the 1,536-well plates. Currently, commercially available 1,536-well plate auto samplers are not compatible with Waters LC/MS systems. The authors have modified their CTC PAL autosampler to support injection from up to twenty-four 1,536-well plates. This allows them to cherry-pick any sample from up to 36,864 wells on the autosampler. Because of its success at this Institute, sampling from 1,536-well plates has not only become the preferred method for LC/MS analysis from IC(50) plates but also become the standard format used for the handling of and the sampling from large combinatorial libraries.     

High-throughput screening of biocatalytic activity: applications in drug discovery

Enzymes catalyze a diverse set of reactions that propel life's processes and hence serve as valuable therapeutic targets. High-throughput screening methods have become essential for sifting through large chemical libraries in search of drug candidates, and several sensitive and reliable analytical techniques have been specifically adapted to high-throughput measurements of biocatalytic activity. High-throughput biocatalytic assay platforms thus enable rapid screening against enzymatic targets, and have vast potential to impact various stages of the drug discovery process, including lead identification and optimization, and ADME/Tox assessment. These advances are paving the way for the adoption of high-throughput biocatalytic assays as an indispensable tool for the pharmaceutical industry.     

Proteomic analyses using an accurate mass and time tag strategy

An accurate mass and time (AMT) tag approach for proteomic analyses has been developed over the past several years to facilitate comprehensive high-throughput proteomic measurements. An AMT tag database for an organism, tissue, or cell line is established by initially performing standard shotgun proteomic analysis and, most importantly, by validating peptide identifications using the mass measurement accuracy of Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) and liquid chromatography (LC) elution time constraint. Creation of an AMT tag database largely obviates the need for subsequent MS/MS analyses, and thus facilitates high-throughput analyses. The strength of this technology resides in the ability to achieve highly efficient and reproducible one-dimensional reversed-phased LC separations in conjunction with highly accurate mass measurements using FTICR MS. Recent improvements allow for the analysis of as little as picrogram amounts of proteome samples by minimizing sample handling and maximizing peptide recovery. The nanoproteomics platform has also demonstrated the ability to detect >10(6) differences in protein abundances and identify more abundant proteins from subpicogram amounts of samples. The AMT tag approach is poised to become a new standard technique for the in-depth and high-throughput analysis of complex organisms and clinical samples, with the potential to extend the analysis to a single mammalian cell.     

QCMAP: An Interactive Web‐Tool for Performance Diagnosis and Prediction of LC‐MS Systems

The increasing role played by liquid chromatography‐mass spectrometry (LC‐MS)‐based proteomics in biological discovery has led to a growing need for quality control (QC) on the LC‐MS systems. While numerous quality control tools have been developed to track the performance of LC‐MS systems based on a pre‐defined set of performance factors (e.g., mass error, retention time), the precise influence and contribution of the performance factors and their generalization property to different biological samples are not as well characterized. Here, a web‐based application (QCMAP) is developed for interactive diagnosis and prediction of the performance of LC‐MS systems across different biological sample types. Leveraging on a standardized HeLa cell sample run as QC within a multi‐user facility, predictive models are trained on a panel of commonly used performance factors to pinpoint the precise conditions to a (un)satisfactory performance in three LC‐MS systems. It is demonstrated that the learned model can be applied to predict LC‐MS system performance for brain samples generated from an independent study. By compiling these predictive models into our web‐application, QCMAP allows users to benchmark the performance of their LC‐MS systems using their own samples and identify key factors for instrument optimization. QCMAP is freely available from: http://shiny.maths.usyd.edu.au/QCMAP/ .     

High-throughput microsomal stability assay for screening new chemical entities in drug discovery

In this work, the authors present a novel, robotic, automated protocol for assessing a metabolic stability protocol assembled on a Hamilton platform and a new strategy for pooling samples (cassette analysis). To increase the high throughput of the liquid chromatography (LC) step, fast chromatography and automated liquid chromatography tandem mass spectrometry (LC/MS/MS) analytical methods were also developed, and a rapid data analysis system was generated that converts peak areas obtained by LC/MS/MS in intrinsic clearance values. All of the steps of the microsomal stability assay were carefully studied and optimized. Standard errors and confidence intervals of the measured clearances were also automatically generated in the process to allow an immediate evaluation of the significance of observed values. Methods based on pooling analysis of 2 and 4 different analytes were compared with a standard method without pooling. A simple statistical treatment was used to show their equivalence. The different protocols developed were analyzed in terms of the best compromise between accuracy and high-throughput capabilities.     

In vitro ADME profiling using high-throughput rapidfire mass spectrometry: cytochrome p450 inhibition and metabolic stability assays

Early assessment of absorption, distribution, metabolism, and excretion (ADME) properties of drug candidates has become an essential component of modern drug discovery. ADME characterization is important in identifying compounds early that are likely to fail in later clinical development because of suboptimal pharmacokinetic properties or undesirable drug-drug interactions. Proper utilization of ADME results, meanwhile, can prioritize candidates that are more likely to have good pharmacokinetic properties and also minimize potential drug-drug interactions. By integrating a RapidFire system with an API4000 mass spectrometer (RF-MS), we have established a high-throughput capability to profile compounds (>100 compounds/wk) in a panel of ADME assays in parallel with biochemical and cellular characterizations. Cytochrome P450 inhibition and time-dependent inhibition assays and microsomal stability assays were developed and fully optimized on the system. Compared with the classic liquid chromatography-mass spectrometry method, the RF-MS system generates consistent data with approximately 20-fold increase in throughput. The lack of chromatographic separation of compounds, substrates, and metabolites can complicate data interpretation, but this occurs in a small number of cases that are readily identifiable. Overall, this system has enabled a real-time and quantitative measurement of a large number of ADME samples, providing a rapid evaluation of clinically important drug-drug interaction potential and drug metabolic stability.     

Definitive screening design enables optimization of LC–ESI–MS/MS parameters in proteomics

In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC–ESI–MS/MS to comprehensively identify these peptides. However, there are many parameters for LC–ESI–MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC–ESI–MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC–ESI–MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC–ESI–MS/MS systems.     

A liquid chromatography/mass spectrometry-based generic detection method for biochemical assay and hit discovery of histone methyltransferases

Epigenetic modifications of the genome, such as DNA methylation and posttranslational modifications of histone proteins, contribute to gene regulation. Growing evidence suggests that histone methyltransferases are associated with the development of various human diseases, including cancer, and are promising drug targets. High-quality generic assays will facilitate drug discovery efforts in this area. In this article, we present a liquid chromatography/mass spectrometry (LC/MS)-based S-adenosyl homocysteine (SAH) detection assay for histone methyltransferases (HMTs) and its applications in HMT drug discovery, including analyzing the activity of newly produced enzymes, developing and optimizing assays, performing focused compound library screens and orthogonal assays for hit confirmations, selectivity profiling against a panel of HMTs, and studying mode of action of select hits. This LC/MS-based generic assay has become a critical platform for our methyltransferase drug discovery efforts.     

UniCarb-DB: a database resource for glycomic discovery

Glycosylation is one of the most important post-translational modifications of proteins, known to be involved in pathogen recognition, innate immune response and protection of epithelial membranes. However, when compared to the tools and databases available for the processing of high-throughput proteomic data, the glycomic domain is severely lacking. While tools to assist the analysis of mass spectrometry (MS) and HPLC are continuously improving, there are few resources available to support liquid chromatography (LC)-MS/MS techniques for glycan structure profiling. Here, we present a platform for presenting oligosaccharide structures and fragment data characterized by LC-MS/MS strategies. The database is annotated with high-quality datasets and is designed to extend and reinforce those standards and ontologies developed by existing glycomics databases. AVAILABILITY: http://www.unicarb-db.org     

Affinity chromatography as a method for sample preparation in gas chromatography/mass spectrometry.

Analytical chemistry aims at developing analytical methods and techniques for unequivocal identification and accurate quantitation of natural and synthetic compounds in a given matrix. Analytical methods based on the mass spectrometry (MS) technology, e.g., GC/MS and LC/MS and their variants, GC/tandem MS and LC/tandem MS, are best suited both for qualitative and quantitative analyses. GC/MS methods not only serve as reference methods, e.g., in clinical chemistry, but they are now widely and routinely used for quantitative determination of numerous analytes. However, despite inherent accuracy, analytical methods based on GC/MS commonly consist of several analytical steps, including extraction and derivatization of the analyte. In general, unequivocal identification and accurate quantification of an analyte in very low concentrations in complex matrices require further chromatographic techniques, such as high-performance liquid chromatography (HPLC) and thin-layer chromatography (TLC) for sample purification. In recent years, affinity chromatography (e.g., boronate and immunoaffinity chromatography) has been developed to a superior technique for sample preparation of numerous classes of compounds in GC/MS. In this article, the application and importance of affinity chromatography as a method for sample preparation in modern quantitative GC/MS method is described and discussed, using as examples various natural and synthetic compounds, such as arachidonic acid derivates, nitrosylated and nitrated proteins, steroids, drugs, and toxins.     

Online immunoaffinity LC/MS/MS. A general method to increase sensitivity and specificity: How do you do it and what do you need?

There is an increased emphasis on hyphenated techniques such as immunoaffinity LC/MS/MS (IA-LC/MS/MS) or IA-LC/MRM. These techniques offer competitive advantages with respect to sensitivity and selectivity over traditional LC/MS and are complementary to ligand binding assays (LBA) or ELISA's. However, these techniques are not entirely straightforward and there are several tips and tricks to routine sample analysis. We describe here our methods and procedures for how to perform online IA-LC/MS/MS including a detailed protocol for the preparation of antibody (Ab) enrichment columns. We have included sample trapping and Ab methods. Furthermore, we highlight tips, tricks, minimal and optimal approaches. This technology has been shown to be viable for several applications, species and fluids from small molecules to proteins and biomarkers to PK assays.     

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.     

Ampicillin/penicillin-binding protein interactions as a model drug-target system to optimize affinity pull-down and mass spectrometric strategies for target and pathway identification

The identification and validation of the targets of active compounds identified in cell-based assays is an important step in preclinical drug development. New analytical approaches that combine drug affinity pull-down assays with mass spectrometry (MS) could lead to the identification of new targets and druggable pathways. In this work, we investigate a drug-target system consisting of ampicillin- and penicillin-binding proteins (PBPs) to evaluate and compare different amino-reactive resins for the immobilization of the affinity compound and mass spectrometric methods to identify proteins from drug affinity pull-down assays. First, ampicillin was immobilized onto various amino-reactive resins, which were compared in the ampicillin-PBP model with respect to their nonspecific binding of proteins from an Escherichia coli membrane extract. Dynal M-270 magnetic beads were chosen to further study the system as a model for capturing and identifying the targets of ampicillin, PBPs that were specifically and covalently bound to the immobilized ampicillin. The PBPs were identified, after in situ digestion of proteins bound to ampicillin directly on the beads, by using either one-dimensional (1-D) or two-dimensional (2-D) liquid chromatography (LC) separation techniques followed by tandem mass spectrometry (MS/MS) analysis. Alternatively, an elution with N-lauroylsarcosine (sarcosyl) from the ampicillin beads followed by in situ digestion and 2-D LC-MS/MS analysis identified proteins potentially interacting noncovalently with the PBPs or the ampicillin. The in situ approach required only little time, resources, and sample for the analysis. The combination of drug affinity pull-down assays with in situ digestion and 2-D LC-MS/MS analysis is a useful tool in obtaining complex information about a primary drug target as well as its protein interactors.     

More sensitive and quantitative proteomic measurements using very low flow rate porous silica monolithic LC columns with electrospray ionization-mass spectrometry

The sensitivity of proteomics measurements using liquid chromatography (LC) separations interfaced with electrospray ionization-mass spectrometry (ESI-MS) improves approximately inversely with liquid flow rate (for the columns having the same separation efficiency, linear velocity, and porosity), making attractive the use of smaller inner diameter LC columns. We report the development and initial application of 10 microm i.d. silica-based monolithic LC columns providing more sensitive proteomics measurements. A 50-microm-i.d. micro solid-phase extraction precolumn was used for ease of sample injection and cleanup prior to the reversed-phase LC separation, enabling the sample volume loading speed to be increased by approximately 50-fold. Greater than 10-fold improvement in sensitivity was obtained compared to analyses using more conventional capillary LC, enabling e.g. the identification of >5000 different peptides by MS/MS from 100-ng of a Shewanella oneidensis tryptic digest using an ion trap MS. The low nL/min LC flow rates provide more uniform responses for different peptides, and provided improved quantitative measurements compared to conventional separation systems without the use of internal standards or isotopic labeling. The improved sensitivity allowed LC-MS measurements of immunopurified protein phosphatase 5 that were in good agreement with quantitative Western blot analyses.     

An automated robotic platform for rapid profiling oligosaccharide analysis of monoclonal antibodies directly from cell culture

Oligosaccharides attached to Asn297 in each of the C_H2 domains of monoclonal antibodies play an important role in antibody effector functions by modulating the affinity of interaction with Fc receptors displayed on cells of the innate immune system. Rapid, detailed, and quantitative N-glycan analysis is required at all stages of bioprocess development to ensure the safety and efficacy of the therapeutic. The high sample numbers generated during quality by design (QbD) and process analytical technology (PAT) create a demand for high-performance, high-throughput analytical technologies for comprehensive oligosaccharide analysis. We have developed an automated 96-well plate-based sample preparation platform for high-throughput N-glycan analysis using a liquid handling robotic system. Complete process automation includes monoclonal antibody (mAb) purification directly from bioreactor media, glycan release, fluorescent labeling, purification, and subsequent ultra-performance liquid chromatography (UPLC) analysis. The entire sample preparation and commencement of analysis is achieved within a 5-h timeframe. The automated sample preparation platform can easily be interfaced with other downstream analytical technologies, including mass spectrometry (MS) and capillary electrophoresis (CE), for rapid characterization of oligosaccharides present on therapeutic antibodies.     

Image analysis tools and emerging algorithms for expression proteomics

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-DE technique of protein separation, and by first covering signal analysis for MS, we also explain the current image analysis workflow for the emerging high-throughput 'shotgun' proteomics platform of LC coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whereas existing commercial and academic packages and their workflows are described from both a user's and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models, and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS.     

Granger causality in integrated GC–MS and LC–MS metabolomics data reveals the interface of primary and secondary metabolism

Metabolomics has emerged as a key technique of modern life sciences in recent years. Two major techniques for metabolomics in the last 10 years are gas chromatography coupled to mass spectrometry (GC–MS) and liquid chromatography coupled to mass spectrometry (LC–MS). Each platform has a specific performance detecting subsets of metabolites. GC–MS in combination with derivatisation has a preference for small polar metabolites covering primary metabolism. In contrast, reversed phase LC–MS covers large hydrophobic metabolites predominant in secondary metabolism. Here, we present an integrative metabolomics platform providing a mean to reveal the interaction of primary and secondary metabolism in plants and other organisms. The strategy combines GC–MS and LC–MS analysis of the same sample, a novel alignment tool MetMAX and a statistical toolbox COVAIN for data integration and linkage of Granger Causality with metabolic modelling. For metabolic modelling we have implemented the combined GC–LC–MS metabolomics data covariance matrix and a stoichiometric matrix of the underlying biochemical reaction network. The changes in biochemical regulation are expressed as differential Jacobian matrices. Applying the Granger causality, a subset of secondary metabolites was detected with significant correlations to primary metabolites such as sugars and amino acids. These metabolic subsets were compiled into a stoichiometric matrix N. Using N the inverse calculation of a differential Jacobian J from metabolomics data was possible. Key points of regulation at the interface of primary and secondary metabolism were identified.