Advances in high-throughput mass spectrometry in drug discovery

Emerging affinity methods for protein-drug interaction analysis

The study of protein-drug interaction plays a crucial role in understanding drug mechanisms, identifying new drug targets and biomarkers, and facilitating drug development and disease treatment. In recent years, significant progress has been made in various protein-drug interaction research methods due to the rapid development and in-depth application of mass spectrometry, nuclear magnetic resonance, Raman spectroscopy, and other technologies. The progress has enhanced the sensitivity, precision, accuracy, and applicability of analytical methods, enabling the establishment of drug-protein interaction networks. This review discusses various emerging research methods, such as native mass spectrometry, infrared spectroscopy, nuclear magnetic resonance and spectrum, biosensor technologies employing surface enhanced Raman, electrochemistry, and magneto resistive signals, as well as affinity magnetic levitation and affinity chromatography. The article also delves into the principles, applications, advantages, and limitations of these technologies.

Streamlining Phenotype Classification and Highlighting Feature Candidates: A Screening Method for Non-Targeted Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS) Data

Nontargeted analysis (NTA) is increasingly utilized for its ability to identify key molecular features beyond known targets in complex samples. NTA is particularly advantageous in exploratory studies aimed at identifying phenotype-associated features or molecules able to classify various sample types. However, implementing NTA involves extensive data analyses and labor-intensive annotations. To address these limitations, we developed a rapid data screening capability compatible with NTA data collected on a liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) platform that allows for sample classification while highlighting potential features of interest. Specifically, this method aggregates the thousands of IMS-MS spectra collected across the LC space for each sample and collapses the LC dimension, resulting in a single summed IMS-MS spectrum for screening. The summed IMS-MS spectra are then analyzed with a bootstrapped Lasso technique to identify key regions or coordinates for phenotype classification via support vector machines. Molecular annotations are then performed by examining the features present in the selected coordinates, highlighting potential molecular candidates. To demonstrate this summed IMS-MS screening approach, we applied it to clinical plasma lipidomic NTA data and exposomic NTA data from water sites with varying contaminant levels. Distinguishing coordinates were observed in both studies, enabling the evaluation of phenotypic molecular annotations and resulting in screening models capable of classifying samples with up to a 25% increase in accuracy compared to models using annotated data.

Exploring the versatility of mass spectrometry: Applications across diverse scientific disciplines

Mass spectrometry (MS) has become a pivotal analytical tool across various scientific disciplines due to its ability to provide detailed molecular information with high sensitivity and specificity. MS plays a crucial role in various fields, including drug discovery and development, proteomics, metabolomics, environmental analysis, and clinical diagnostics and Forensic science. In this article we are discussing the application of MS across the diverse scientific disciplines by focusing on some classical examples from each field of application. As the technology continues to evolve, it promises to unlock new possibilities in scientific research and practical applications, cementing its position as an essential tool in modern analytical science.

Label-free assessment of complement-dependent cytotoxicity of therapeutic antibodies via a whole-cell MALDI mass spectrometry bioassay

Potency assessment of monoclonal antibodies or corresponding biosimilars in cell-based assays is an essential prerequisite in biopharmaceutical research and development. However, cellular bioassays are still subject to limitations in sample throughput, speed, and often need costly reagents or labels as they are based on an indirect readout by luminescence or fluorescence. In contrast, whole-cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass Spectrometry (MS) has emerged as a direct, fast and label-free technology for functional drug screening being able to unravel the molecular complexity of cellular response to pharmaceutical reagents. However, this approach has not yet been used for cellular testing of biologicals. In this study, we have conceived, developed and benchmarked a label-free MALDI-MS based cell bioassay workflow for the functional assessment of complement-dependent cytotoxicity (CDC) of Rituximab antibody. By computational evaluation of response profiles followed by subsequent m/z feature annotation via fragmentation analysis and trapped ion mobility MS, we identified adenosine triphosphate and glutathione as readily MS-assessable metabolite markers for CDC and demonstrate that robust concentration-response characteristics can be obtained by MALDI-TOF MS. Statistical assay performance indicators suggest that whole-cell MALDI-TOF MS could complement the toolbox for functional cellular testing of biopharmaceuticals.

Rapid spectrophotometric detection for optimized production of landomycins and characterization of their therapeutic potential

Microbial-derived natural products remain a major source of structurally diverse bioactive compounds and chemical scaffolds that have the potential as new therapeutics to target drug-resistant pathogens and cancers. In particular, genome mining has revealed the vast number of cryptic or low-yield biosynthetic gene clusters in the genus Streptomyces. However, low natural product yields-improvements to which have been hindered by the lack of high throughput methods-have slowed the discovery and development of many potential therapeutics. Here, we describe our efforts to improve yields of landomycins-angucycline family polyketides under investigation as cancer therapeutics-by a genetically modified Streptomyces cyanogenus 136. After simplifying the extraction process from S. cyanogenus cultures, we identified a wavelength at which the major landomycin products are absorbed in culture extracts, which we used to systematically explore culture medium compositions to improve total landomycin titers. Through correlational analysis, we simplified the culture optimization process by identifying an alternative wavelength at which culture supernatants absorb yet is representative of total landomycin titers. Using the subsequently improved sample throughput, we explored landomycin production during the culturing process to further increase landomycin yield and reduce culture time. Testing the antimicrobial activity of the isolated landomycins, we report broad inhibition of Gram-positive bacteria, inhibition of fungi by landomycinone, and broad landomycin resistance by Gram-negative bacteria that is likely mediated by the exclusion of landomycins by the bacterial membrane. Finally, the anticancer activity of the isolated landomycins against A549 lung carcinoma cells agrees with previous reports on other cell lines that glycan chain length correlates with activity. Given the prevalence of natural products produced by Streptomyces, as well as the light-absorbing moieties common to bioactive natural products and their metabolic precursors, our method is relevant to improving the yields of other natural products of interest.

Integrating Computational Design and Experimental Approaches for Next-Generation Biologics

Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases.

Natural Products in the Treatment of Retinopathy of Prematurity: Exploring Therapeutic Potentials

Retinopathy of prematurity (ROP) is a vascular disorder affecting the retinas of preterm infants. This condition arises when preterm infants in incubators are exposed to high oxygen levels, leading to oxidative stress, inflammatory responses, and a downregulation of vascular endothelial growth factors, which causes the loss of retinal microvascular capillaries. Upon returning to room air, the upregulation of vascular growth factors results in abnormal vascular growth of retinal endothelial cells. Without appropriate intervention, ROP can progress to blindness. The prevalence of ROP has risen, making it a significant cause of childhood blindness. Current treatments, such as laser therapy and various pharmacologic approaches, are limited by their potential for severe adverse effects. Therefore, a deeper understanding of ROP's pathophysiology and the development of innovative treatments are imperative. Natural products from plants, fungi, bacteria, and marine organisms have shown promise in treating various diseases and have gained attention in ROP research due to their minimal side effects and wide-ranging beneficial properties. This review discusses the roles and mechanisms of natural products that hold potential as therapeutic agents in ROP management.

A duplexed high-throughput mass spectrometry assay for bifunctional POLB polymerase and lyase activity

Polymerase β (POLB), with dual functionality as a lyase and polymerase, plays a critical role in the base excision repair (BER) pathway to maintain genomic stability. POLB knockout and rescue studies in BRCA1/2-mutant cancer cell lines revealed that inhibition of lyase and polymerase activity is required for the synthetic lethal interaction observed with PARP inhibitors, highlighting POLB as a valuable therapeutic target. Traditional biochemical assays to screen for enzyme inhibitors focus on a single substrate to product relationship and limit the comprehensive analysis of enzymes such as POLB that utilize multiple substrates or catalyze a multi-step reaction. This report describes the first high-throughput mass spectrometry-based screen to measure the two distinct biochemical activities of POLB in a single assay using a duplexed self-assembled monolayer desorption ionization (SAMDI) mass spectrometry methodology. A multiplexed assay for POLB dual enzymatic activities was developed optimizing for kinetically balanced conditions and a collection of 200,000 diverse small molecules was screened in the duplexed format. Small molecule modulators identified in the screen were confirmed in a traditional fluorescence-based polymerase strand-displacement assay and an orthogonal label-free binding assay using SAMDI affinity selection mass spectrometry (ASMS). This work demonstrates the flexibility of high-throughput mass spectrometry approaches in drug discovery and highlights a novel application of SAMDI technology that opens new avenues for multiplexed high-throughput screening.

[Recent advances in protein precipitation-based methods for drug-target screening]

Drug targets are biological macromolecules that bind drug molecules in vivo. Therefore, the system-wide identification of drug targets plays a vital role in fully understanding the mechanism of drug action, efficacy, and side effects. The unbiased screening of drug targets may accelerate the process of drug discovery and candidate screening. Mass spectrometry is a key tool for large-scale protein identification and accurate quantification owing to its high acquisition speed, resolution, and sensitivity. Mass spectrometry-based proteomics has been widely used for drug-target screening. It can systematically identify the protein-target landscape of a drug and elucidate drug-protein interactions. Commonly used drug-target characterization methods, such as labeling-based affinity enrichment, require the chemical derivatization of drug molecules, which is not only time-consuming but may also affect the affinity of the drug towards its targets. Furthermore, the spatial effects of the derivatization groups may block interactions between the drug and its targets. Considering the disadvantages of affinity-enrichment methods, strategies that do not require chemical derivatization have received widespread attention. Proteins may undergo denaturation, unfolding, and precipitation under different conditions such as high temperatures, extreme pH, denaturants, and mechanical stress. Binding to small-molecule drugs may alter the folding balance of target proteins. The conformational stability of target proteins can be stabilized by binding with drugs, and protein-drug complexes are more resistant than free proteins to the precipitation induced by different conditions. Based on this mechanism, various large-scale drug-target identification methods using protein precipitation have been developed by combining proteomics and mass spectrometry analysis, including thermal proteome profiling and solvent-, mechanical stress-, and pH-induced protein precipitation. These methods have been successfully applied to the characterization of small-molecule drug targets. In this review, we describe the protein precipitation-based methods used for the high-throughput discovery of drug targets and elucidation of the interactions between drugs and proteins in the past decade. We also summarize the characteristics of each method and discuss their application potential in drug-efficacy evaluation and drug discovery.

Reverse-Phase Protein Microarrays for Overexpressed Escherichia coli Lysates Reveal a Novel Tyrosine Kinase

Tyrosine phosphorylation is one of the most important posttranslational modifications in bacteria, linked to regulating growth, migration, virulence, secondary metabolites, biofilm formation, and capsule production. Only two tyrosine kinases (yccC (etk) and wzc) have been identified in Escherichia coli. The investigation by similarity has not revealed any novel BY-kinases in silico so far, most probably due to their sequence and structural variability. Here we developed a reverse-phase protein array from 4126 overexpressed E. coli clones, lysed, and printed on coated glass slides. These high-density E. coli lysate arrays (ECLAs) were quality controlled by the reproducibility and immobilization of total lysate proteins and specific overexpressed proteins. ECLAs were used to interrogate the relationship between protein overexpression and tyrosine phosphorylation in the total lysate. We identified 6 protein candidates, including etk and wzc, with elevated phosphotyrosine signals in the total lysates. Among them, we identified a novel kinase nrdD with autophosphorylation and transphosphorylation activities in the lysates. Moreover, the overexpression of nrdD induced biofilm formation. Since nrdD is a novel kinase, we used E. coli proteome microarrays (purified 4,126 E. coli proteins) to perform an in vitro kinase assay and identified 33 potential substrates. Together, this study established a new ECLA platform for interrogating posttranslational modifications and identified a novel kinase that is important in biofilm formation, which will shed some light on bacteria biochemistry and new ways to impede drug resistance.

Morphological profiling for drug discovery in the era of deep learning

Morphological profiling is a valuable tool in phenotypic drug discovery. The advent of high-throughput automated imaging has enabled the capturing of a wide range of morphological features of cells or organisms in response to perturbations at the single-cell resolution. Concurrently, significant advances in machine learning and deep learning, especially in computer vision, have led to substantial improvements in analyzing large-scale high-content images at high throughput. These efforts have facilitated understanding of compound mechanism of action, drug repurposing, characterization of cell morphodynamics under perturbation, and ultimately contributing to the development of novel therapeutics. In this review, we provide a comprehensive overview of the recent advances in the field of morphological profiling. We summarize the image profiling analysis workflow, survey a broad spectrum of analysis strategies encompassing feature engineering- and deep learning-based approaches, and introduce publicly available benchmark datasets. We place a particular emphasis on the application of deep learning in this pipeline, covering cell segmentation, image representation learning, and multimodal learning. Additionally, we illuminate the application of morphological profiling in phenotypic drug discovery and highlight potential challenges and opportunities in this field.

Data-oriented protein kinase drug discovery

The continued growth of data from biological screening and medicinal chemistry provides opportunities for data-driven experimental design and decision making in early-phase drug discovery. Approaches adopted from data science help to integrate internal and public domain data and extract knowledge from historical in-house data. Protein kinase (PK) drug discovery is an exemplary area where large amounts of data are accumulating, providing a valuable knowledge base for discovery projects. Herein, the evolution of PK drug discovery and development of small molecular PK inhibitors (PKIs) is reviewed, highlighting milestone developments in the field and discussing exemplary studies providing a basis for increasing data orientation of PK discovery efforts.

Fragment-based drug discovery for disorders of the central nervous system: designing better drugs piece by piece

Fragment-based drug discovery (FBDD) has emerged as a powerful strategy to confront the challenges faced by conventional drug development approaches, particularly in the context of central nervous system (CNS) disorders. FBDD involves the screening of libraries that comprise thousands of small molecular fragments, each no greater than 300 Da in size. Unlike the generally larger molecules from high-throughput screening that limit customisation, fragments offer a more strategic starting point. These fragments are inherently compact, providing a strong foundation with good binding affinity for the development of drug candidates. The minimal elaboration required to transition the hit into a drug-like molecule is not only accelerated, but also it allows for precise modifications to enhance both their activity and pharmacokinetic properties. This shift towards a fragment-centric approach has seen commercial success and holds considerable promise in the continued streamlining of the drug discovery and development process. In this review, we highlight how FBDD can be integrated into the CNS drug discovery process to enhance the exploration of a target. Furthermore, we provide recent examples where FBDD has been an integral component in CNS drug discovery programs, enabling the improvement of pharmacokinetic properties that have previously proven challenging. The FBDD optimisation process provides a systematic approach to explore this vast chemical space, facilitating the discovery and design of compounds piece by piece that are capable of modulating crucial CNS targets.

Evolution of techniques and tools for replication fork proteome and protein interaction studies

Understanding the complex network of protein-protein interactions (PPI) that govern cellular functions is essential for unraveling the molecular basis of biological processes and diseases. Mass spectrometry (MS) has emerged as a powerful tool for studying protein dynamics, enabling comprehensive analysis of protein function, structure, post-translational modifications, interactions, and localization. This article provides an overview of MS techniques and their applications in proteomics studies, with a focus on the replication fork proteome. The replication fork is a multi-protein assembly involved in DNA replication, and its proper functioning is crucial for maintaining genomic integrity. By combining quantitative MS labeling techniques with various data acquisition methods, researchers have made significant strides in elucidating the complex processes and molecular mechanisms at the replication fork. Overall, MS has revolutionized our understanding of protein dynamics, offering valuable insights into cellular processes and potential targets for therapeutic interventions.

Covalent hits and where to find them

Covalent hits for drug discovery campaigns are neither fantastic beasts nor mythical creatures, they can be routinely identified through electrophile-first screening campaigns using a suite of different techniques. These include biophysical and biochemical methods, cellular approaches, and DNA-encoded libraries. Employing best practice, however, is critical to success. The purpose of this review is to look at state of the art covalent hit identification, how to identify hits from a covalent library and how to select compounds for medicinal chemistry programmes.

Ultra-high-throughput mass spectrometry in drug discovery: fundamentals and recent advances

INTRODUCTION

Ultra-high-throughput mass spectrometry, uHT-MS, is a technology that utilizes ionization and sample delivery technologies optimized to enable sampling from well plates at > 1 sample per second. These technologies do not need a chromatographic separation step and can be utilized in a wide variety of assays to detect a broad range of analytes including small molecules, lipids, and proteins.

AREAS COVERED

This manuscript provides a brief historical review of high-throughput mass spectrometry and the recently developed technologies that have enabled uHT-MS. The report also provides examples and references on how uHT-MS has been used in biochemical and chemical assays, nuisance compound profiling, protein analysis and high throughput experimentation for chemical synthesis.

EXPERT OPINION

The fast analysis time provided by uHT-MS is transforming how biochemical and chemical assays are performed in drug discovery. The potential to associate phenotypic responses produced by 1000's of compound treatments with changes in endogenous metabolite and lipid signals is becoming feasible. With the augmentation of simple, fast, high-throughput sample preparation, the scope of uHT-MS usage will increase. However, it likely will not supplant LC-MS for analyses that require low detection limits from complex matrices or characterization of complex biotherapeutics such as antibody-drug conjugates.

High-throughput intact Glycopeptide quantification strategy with targeted-MS (HTiGQs-target) reveals site-specific IgG N-glycopeptides as biomarkers for hepatic disorder diagnosis and staging

Liver disease is one of the leading causes of global mortality, and identifying biomarkers for diagnosing the progression of liver diseases is crucial for improving its outcomes. Targeted mass spectrometry technology is a powerful tool with unique advantages for verifying biomarker candidates and clinical applications. It is particularly useful in validating protein biomarkers with post-translational modifications, eliminating the need for site-specific antibodies. Especially, targeted mass spectrometry technique is particularly critical for translation of glycoproteins into clinical applications as there are no site-specific antibodies for N-glycosylation. Nevertheless, its limitation in analyzing only one sample per run has become apparent when dealing with a large number of clinical samples. Herein, we developed a high-throughput intact N-glycopeptides quantification strategy with targeted-MS (HTiGQs-Target), which allows the validation of 20 samples per run with an average analysis time of only 3 min per sample. We applied HTiGQs-Target in a cohort of 461 serum samples (including 120 healthy controls (HC), 127 chronic hepatitis B (CHB) cases, 106 liver cirrhosis (LC) cases, and 108 hepatocellular carcinomas (HCC) cases) and found that a panel of 10 IgG N-glycopeptides have strong clinical utility in evaluating the severity of the liver disease.

Accelerating Pharmaceutical Process Development with an Acoustic Droplet Ejection-Multiple Reaction Monitoring-Mass Spectrometry Workflow

Fast-paced pharmaceutical process developments (e.g., high-throughput experimentation, directed evolution, and machine learning) involve the introduction of fast, sensitive, and accurate analytical assays using limited sample volumes. In recent years, acoustic droplet ejection (ADE) coupled with an open port interface has been invented as a sampling technology for mass spectrometry, providing high-throughput nanoliter analytical measurements directly from the standard microplates. Herein, we introduce an ADE-multiple reaction monitoring-mass spectrometry (ADE-MRM-MS) workflow to accelerate pharmaceutical process research and development (PR&D). This systematic workflow outlines the selection of MRM transitions and optimization of assay parameters in a data-driven manner using rapid measurements (1 sample/s). The synergy between ADE sampling and MRM analysis enables analytical assays with excellent sensitivity, selectivity, and speed for PR&D reaction screenings. This workflow was utilized to develop new ADE-MRM-MS assays guiding a variety of industrial processes, including (1) screening of Ni-based catalysts for C-N cross-coupling reaction at 1 Hz and (2) high-throughput regioisomer analysis-enabled enzyme library screening for peptide ligation reaction. ADE-MRM-MS assays were demonstrated to deliver accurate results that are comparable to conventional liquid chromatography (LC) experiments while providing >100-fold throughput enhancement.

Determining KRAS4B-Targeting Compound Specificity by Top-Down Mass Spectrometry

We present a novel method to determine engagement and specificity of KRAS4B-targeting compounds in vitro. By employing top-down mass spectrometry (MS), which analyzes intact and modified protein molecules (proteoforms), we can directly visualize and confidently characterize each KRAS4B species within compound-treated samples. Moreover, by employing targeted MS2 fragmentation, we can precisely localize each compound molecule to a specific residue on a given KRAS4B proteoform. This method allows us to comprehensively evaluate compound specificity, clearly detect nonspecific binding events, and determine the order and frequency with which they occur. We provide two proof-of-concept examples of our method employing publicly available compounds, along with detailed protocols for sample preparation, top-down MS data acquisition, targeted proteoform MS2 fragmentation, and analysis of the resulting data. Our results demonstrate the concentration dependence of KRAS4B-compound engagement and highlight the ability of top-down MS to directly map compound binding location(s) without disrupting the KRAS4B primary structure. Our hope is that this novel method may help accelerate the identification of new successful targeted inhibitors for KRAS4B and other RAS isoforms.

Mpox (formerly monkeypox): pathogenesis, prevention, and treatment

In 2022, a global outbreak of Mpox (formerly monkeypox) occurred in various countries across Europe and America and rapidly spread to more than 100 countries and regions. The World Health Organization declared the outbreak to be a public health emergency of international concern due to the rapid spread of the Mpox virus. Consequently, nations intensified their efforts to explore treatment strategies aimed at combating the infection and its dissemination. Nevertheless, the available therapeutic options for Mpox virus infection remain limited. So far, only a few numbers of antiviral compounds have been approved by regulatory authorities. Given the high mutability of the Mpox virus, certain mutant strains have shown resistance to existing pharmaceutical interventions. This highlights the urgent need to develop novel antiviral drugs that can combat both drug resistance and the potential threat of bioterrorism. Currently, there is a lack of comprehensive literature on the pathophysiology and treatment of Mpox. To address this issue, we conducted a review covering the physiological and pathological processes of Mpox infection, summarizing the latest progress of anti-Mpox drugs. Our analysis encompasses approved drugs currently employed in clinical settings, as well as newly identified small-molecule compounds and antibody drugs displaying potential antiviral efficacy against Mpox. Furthermore, we have gained valuable insights from the process of Mpox drug development, including strategies for repurposing drugs, the discovery of drug targets driven by artificial intelligence, and preclinical drug development. The purpose of this review is to provide readers with a comprehensive overview of the current knowledge on Mpox.

Proteomics provides insights into the theranostic potential of extracellular vesicles

Extracellular vesicles (EVs) encompass a diverse range of membranous structures derived from cells, including exosomes and microvesicles. These vesicles are present in biological fluids and play vital roles in various physiological and pathological processes. They facilitate intercellular communication by enabling the exchange of proteins, lipids, and genetic material between cells. Understanding the cellular processes that govern EV biology is essential for unraveling their physiological and pathological functions and their potential clinical applications. Despite significant advancements in EV research in recent years, there is still much to learn about these vesicles. The advent of improved mass spectrometry (MS)-based techniques has allowed for a deeper characterization of EV protein composition, providing valuable insights into their roles in different physiological and pathological conditions. In this chapter, we provide an overview of proteomics studies conducted to identify the protein contents of EVs, which contribute to their therapeutic and pathological features. We also provided evidence on the potential of EV proteome contents as biomarkers for early disease diagnosis, progression, and treatment response, as well as factors that influence their composition. Additionally, we discuss the available databases containing information on EV proteome contents, and finally, we highlight the need for further research to pave the way toward their utilization in clinical settings.

Affinity selection mass spectrometry speeding drug discovery

Affinity selection mass spectrometry (AS-MS) has gained momentum in drug discovery. This review summarizes how this technology has slowly risen as a new paradigm in hit identification and its potential synergy with DNA encoded library technology. It presents an overview of the recent results on challenging targets and perspectives on new areas of research, such as RNA targeting with small molecules. The versatility of the approach is illustrated and strategic drivers discussed in terms of the experience of a small-medium CRO and a big pharma organization.

Ultra-High-Throughput and Low-Volume Analysis of Intact Proteins with LAP-MALDI MS

High-throughput (HTP) mass spectrometry (MS) is a rapidly growing field, with many techniques evolving to accommodate ever increasing sample analysis rates. Many of these techniques, such as AEMS and IR-MALDESI MS, require volumes of at least 20-50 μL for analysis. Here, liquid atmospheric pressure-matrix-assisted laser desorption/ionization (LAP-MALDI) MS is presented as an alternative for ultra-high-throughput analysis of proteins requiring only femtomole quantities of protein in 0.5 μL droplets. By moving a 384-well microtiter sample plate with a high-speed XY-stage actuator, sample acquisition rates of up to 10 samples per second have been achieved at a data acquisition rate of 200 spectra per scan. It is shown that protein mixture solutions with concentrations of ≤2 μM can be analyzed at this speed, while individual protein solutions can be analyzed at concentrations of ≤0.2 μM. Thus, LAP-MALDI MS provides a promising platform for multiplexed HTP protein analysis.