The emerging role of mass spectrometry-based proteomics in drug discovery

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Proteomics analysis of histone deacetylase inhibitor-resistant solid tumors reveals resistant signatures and potential drug combinations

Histone deacetylase inhibitors (HDACis) are important drugs for cancer therapy, but the indistinct resistant mechanisms of solid tumor therapy greatly limit their clinical application. In this study we conducted HDACi-perturbated proteomics and phosphoproteomics analyses in HDACi-sensitive and -resistant cell lines using a tandem mass tag (TMT)-based quantitative proteomic strategy. We found that the ribosome biogenesis proteins MRTO4, PES1, WDR74 and NOP16 vital to tumorigenesis might regulate the tumor sensitivity to HDACi. By integrating HDACi-perturbated protein signature with previously reported proteomics and drug sensitivity data, we predicted and validated a series of drug combination pairs potentially to enhance the sensitivity of HDACi in diverse solid tumor. Functional phosphoproteomic analysis further identified the kinase PDK1 and ROCK as potential HDACi-resistant signatures. Overall, this study reveals the potential HDACi-resistant signatures and may provide promising drug combination strategies to attenuate the resistance of solid tumor to HDACi.

Integrative multi-omic analysis reveals conserved cell-projection deficits in human Down syndrome brains

Down syndrome (DS) is the most common genetic cause of cognitive disability. However, it is largely unclear how triplication of a small gene subset may impinge on diverse aspects of DS brain physiopathology. Here, we took a multi-omic approach and simultaneously analyzed by RNA-seq and proteomics the expression signatures of two diverse regions of human postmortem DS brains. We found that the overexpression of triplicated genes triggered global expression dysregulation, differentially affecting transcripts, miRNAs, and proteins involved in both known and novel biological candidate pathways. Among the latter, we observed an alteration in RNA splicing, specifically modulating the expression of genes involved in cytoskeleton and axonal dynamics in DS brains. Accordingly, we found an alteration in axonal polarization in neurons from DS human iPSCs and mice. Thus, our study provides an integrated multilayer expression database capable of identifying new potential targets to aid in designing future clinical interventions for DS.

Coupling of surface plasmon resonance and mass spectrometry for molecular interaction studies in drug discovery

Various analytical technologies have been developed for the study of target-ligand interactions. The combination of these technologies gives pivotal information on the binding mechanism, kinetics, affinity, residence time, and changes in molecular structures. Mass spectrometry (MS) offers structural information, enabling the identification and quantification of target-ligand interactions. Surface plasmon resonance (SPR) provides kinetic information on target-ligand interaction in real time. The coupling of MS and SPR complements each other in the studies of target-ligand interactions. Over the last two decades, the capabilities and added values of SPR-MS have been reported. This review summarizes and highlights the benefits, applications, and potential for further research of the SPR-MS approach.

Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference

Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step makes it challenging to identify optimal workflows that maximize the identification of differentially expressed proteins. To identify optimal workflows and their common properties, we conduct an extensive study involving 34,576 combinatoric experiments on 24 gold standard spike-in datasets. Applying frequent pattern mining techniques to top-ranked workflows, we uncover high-performing rules that demonstrate optimality has conserved properties. Via machine learning, we confirm optimal workflows are indeed predictable, with average cross-validation F1 scores and Matthew's correlation coefficients surpassing 0.84. We introduce an ensemble inference to integrate results from individual top-performing workflows for expanding differential proteome coverage and resolve inconsistencies. Ensemble inference provides gains in pAUC (up to 4.61%) and G-mean (up to 11.14%) and facilitates effective aggregation of information across varied quantification approaches such as topN, directLFQ, MaxLFQ intensities, and spectral counts. However, further development and evaluation are needed to establish acceptable frameworks for conducting ensemble inference on multiple proteomics workflows.

Keeping Analytical Chemistry Training Up-to-Date

The undergraduate analytical chemistry curriculum serves to equip students with the knowledge and skills for work outside of classroom training. As such, instructors face a challenging task in deciding the breadth and depth of topics for their courses to ensure their syllabi can remain up-to-date with today's needs. We propose that instructors consider covering capillary electrophoresis (CE) and lab-on-a-chip (LOC) technologies in their analytical chemistry courses. Past surveys of the curriculum show a noticeable lack of emphasis on these topics, which we feel is a missed opportunity and one that holds potential for the collective benefit of instructors and students. CE and LOCs are utilized in a diverse array of fields like biochemistry, pharmaceutical production, materials science, and environmental analysis, and their applications are becoming increasingly important amidst the growing movement toward environmentally sustainable practices and green chemistry. They are also more accessible in the analytical chemistry classroom compared with typical benchtop instruments due to the flexibility of their size and cost. This makes them easier to obtain, maintain, and transport for use and demonstration purposes. Additionally, interwoven in these topics are core concepts that are fundamental to analytical chemistry; thus, covering them will inherently reinforce students' understanding of fundamental knowledge. Therefore, we believe increased coverage of CE and LOCs can better prepare undergraduates for modern analytical chemistry work in various industries and fields of research.

Interleukin-13 Treatment of Living Lung Tissue Model Alters the Metabolome and Proteome-A Nano-DESI MS Metabolomics and Shotgun Proteomics Study

Asthma is a chronic respiratory disease with one of the largest numbers of cases in the world; thus, constant investigation and technical development are needed to unravel the underlying biochemical mechanisms. In this study, we aimed to develop a nano-DESI MS method for the in vivo characterization of the cellular metabolome. Using air-liquid interface (ALI) cell layers, we studied the role of Interleukin-13 (IL-13) on differentiated lung epithelial cells acting as a lung tissue model. We demonstrate the feasibility of nano-DESI MS for the in vivo monitoring of basal-apical molecular transport, and the subsequent endogenous metabolic response, for the first time. Conserving the integrity of the ALI lung-cell layer enabled us to perform temporally resolved metabolomic characterization followed by "bottom-up" proteomics on the same population of cells. Metabolic remodeling was observed upon histamine and corticosteroid treatment of the IL-13-exposed lung cell monolayers, in correlation with alterations in the proteomic profile. This proof of principle study demonstrates the utility of in vivo nano-DESI MS for characterizing ALI tissue layers, and the new markers identified in our study provide a good starting point for future, larger-scale studies.

HDAC inhibitors activate lipid peroxidation and ferroptosis in gastric cancer

Gastric cancer remains among the deadliest neoplasms worldwide, with limited therapeutic options. Since efficacies of targeted therapies are unsatisfactory, drugs with broader mechanisms of action rather than a single oncogene inhibition are needed. Preclinical studies have identified histone deacetylases (HDAC) as potential therapeutic targets in gastric cancer. However, the mechanism(s) of action of HDAC inhibitors (HDACi) are only partially understood. This is particularly true with regard to ferroptosis as an emerging concept of cell death. In a panel of gastric cancer cell lines with different molecular characteristics, tumor cell inhibitory effects of different HDACi were studied. Lipid peroxidation levels were measured and proteome analysis was performed for the in-depth characterization of molecular alterations upon HDAC inhibition. HDACi effects on important ferroptosis genes were validated on the mRNA and protein level. Upon HDACi treatment, lipid peroxidation was found increased in all cell lines. Class I HDACi (VK1, entinostat) showed the same toxicity profile as the pan-HDACi vorinostat. Proteome analysis revealed significant and concordant alterations in the expression of proteins related to ferroptosis induction. Key enzymes like ACSL4, POR or SLC7A11 showed distinct alterations in their expression patterns, providing an explanation for the increased lipid peroxidation. Results were also confirmed in primary human gastric cancer tissue cultures as a relevant ex vivo model. We identify the induction of ferroptosis as new mechanism of action of class I HDACi in gastric cancer. Notably, these findings were independent of the genetic background of the cell lines, thus introducing HDAC inhibition as a more general therapeutic principle.

Poly-pharmacology of existing drugs: How to crack the code?

Drug development in oncology is highly challenging, with less than 5% success rate in clinical trials. This alarming figure points out the need to study in more details the multiple biological effects of drugs in specific contexts. Indeed, the comprehensive assessment of drug poly-pharmacology can provide insights into their therapeutic and adverse effects, to optimize their utilization and maximize the success rate of clinical trials. Recent technological advances have made possible in-depth investigation of drug poly-pharmacology. This review first highlights high-throughput methodologies that have been used to unveil new mechanisms of action of existing drugs. Then, we discuss how emerging chemo-proteomics strategies allow effectively dissecting the poly-pharmacology of drugs in an unsupervised manner.

Podophyllic Aldehyde, a Podophyllotoxin Derivate, Elicits Different Cell Cycle Profiles Depending on the Tumor Cell Line: A Systematic Proteomic Analysis

When new antitumor therapy drugs are discovered, it is essential to address new target molecules from the point of view of chemical structure and to carry out efficient and systematic evaluation. In the case of natural products and derived compounds, it is of special importance to investigate chemomodulation to further explore antitumoral pharmacological activities. In this work, the compound podophyllic aldehyde, a cyclolignan derived from the chemomodulation of the natural product podophyllotoxin, has been evaluated for its viability, influence on the cell cycle, and effects on intracellular signaling. We used functional proteomics characterization for the evaluation. Compared with the FDA-approved drug etoposide (another podophyllotoxin derivative), we found interesting results regarding the cytotoxicity of podophyllic aldehyde. In addition, we were able to observe the effect of mitotic arrest in the treated cells. The use of podophyllic aldehyde resulted in increased cytotoxicity in solid tumor cell lines, compared to etoposide, and blocked the cycle more successfully than etoposide. High-throughput analysis of the deregulated proteins revealed a selective antimitotic mechanism of action of podophyllic aldehyde in the HT-29 cell line, in contrast with other solid and hematological tumor lines. Also, the apoptotic profile of podophyllic aldehyde was deciphered. The cell death mechanism is activated independently of the cell cycle profile. The results of these targeted analyses have also shown a significant response to the signaling of kinases, key proteins involved in signaling cascades for cell proliferation or metastasis. Thanks to this comprehensive analysis of podophyllic aldehyde, remarkable cytotoxic, antimitotic, and other antitumoral features have been discovered that will repurpose this compound for further chemical transformations and antitumoral analysis.

Proteomic Discovery of RNA-Protein Molecular Clamps Using a Thermal Shift Assay with ATP and RNA (TSAR)

Uncompetitive inhibition is an effective strategy for suppressing dysregulated enzymes and their substrates, but discovery of suitable ligands depends on often-unavailable structural knowledge and serendipity. Hence, despite surging interest in mass spectrometry-based target identification, proteomic studies of substrate-dependent target engagement remain sparse. Herein, we describe the Thermal Shift Assay with ATP and RNA (TSAR) as a template for proteome-wide discovery of substrate-dependent ligand binding. Using proteomic thermal shift assays, we show that simple biochemical additives can facilitate detection of target engagement in native cell lysates. We apply our approach to rocaglates, a family of molecules that specifically clamp RNA to eukaryotic translation initiation factor 4A (eIF4A), DEAD-box helicase 3X (DDX3X), and potentially other members of the DEAD-box (DDX) family of RNA helicases. To identify unexpected interactions, we optimized a target class-specific thermal denaturation window and evaluated ATP analog and RNA probe dependencies for key rocaglate-DDX interactions. We report novel DDX targets of the rocaglate clamping spectrum, confirm that DDX3X is a common target of several widely studied analogs, and provide structural insights into divergent DDX3X affinities between synthetic rocaglates. We independently validate novel targets of high-profile rocaglates, including the clinical candidate Zotatifin (eFT226), using limited proteolysis-mass spectrometry and fluorescence polarization experiments. Taken together, our study provides a model for screening uncompetitive inhibitors using a systematic chemical-proteomics approach to uncover actionable DDX targets, clearing a path towards characterization of novel molecular clamps and associated RNA helicase targets.

A chemical proteomics approach for global mapping of functional lysines on cell surface of living cell

Cell surface proteins are responsible for many crucial physiological roles, and they are also the major category of drug targets as the majority of therapeutics target membrane proteins on the surface of cells to alter cellular signaling. Despite its great significance, ligand discovery against membrane proteins has posed a great challenge mainly due to the special property of their natural habitat. Here, we design a new chemical proteomic probe OPA-S-S-alkyne that can efficiently and selectively target the lysines exposed on the cell surface and develop a chemical proteomics strategy for global analysis of surface functionality (GASF) in living cells. In total, we quantified 2639 cell surface lysines in Hela cell and several hundred residues with high reactivity were discovered, which represents the largest dataset of surface functional lysine sites to date. We discovered and validated that hyper-reactive lysine residues K382 on tyrosine kinase-like orphan receptor 2 (ROR2) and K285 on Endoglin (ENG/CD105) are at the protein interaction interface in co-crystal structures of protein complexes, emphasizing the broad potential functional consequences of cell surface lysines and GASF strategy is highly desirable for discovering new active and ligandable sites that can be functionally interrogated for drug discovery.

Bacterial growth-mediated systems remodelling of Nicotiana benthamiana defines unique signatures of target protein production in molecular pharming

The need for therapeutics to treat a plethora of medical conditions and diseases is on the rise and the demand for alternative approaches to mammalian-based production systems is increasing. Plant-based strategies provide a safe and effective alternative to produce biological drugs but have yet to enter mainstream manufacturing at a competitive level. Limitations associated with batch consistency and target protein production levels are present; however, strategies to overcome these challenges are underway. In this study, we apply state-of-the-art mass spectrometry-based proteomics to define proteome remodelling of the plant following agroinfiltration with bacteria grown under shake flask or bioreactor conditions. We observed distinct signatures of bacterial protein production corresponding to the different growth conditions that directly influence the plant defence responses and target protein production on a temporal axis. Our integration of proteomic profiling with small molecule detection and quantification reveals the fluctuation of secondary metabolite production over time to provide new insight into the complexities of dual system modulation in molecular pharming. Our findings suggest that bioreactor bacterial growth may promote evasion of early plant defence responses towards Agrobacterium tumefaciens (updated nomenclature to Rhizobium radiobacter). Furthermore, we uncover and explore specific targets for genetic manipulation to suppress host defences and increase recombinant protein production in molecular pharming.

Transient isotachophoresis-Capillary zone electrophoresis-Mass spectrometry method with off-line microscale solid phase extraction pretreatment for quantitation of intact low molecular mass proteins in various biological fluids

Quantification of proteins is still predominantly done by the traditional bottom-up approach. Targeting of intact proteins in complex biological matrices is connected with multiple challenges during the sample pretreatment, separation, and detection step of the analytical workflow. In this work, we focused on the development of an on-line hyphenated capillary zone electrophoresis-mass spectrometry method employing off-line microscale solid-phase extraction based on hydrophilic lipophilic balance (HLB) sorbent as a sample pretreatment step for the analysis of low molecular mass intact proteins (<20 kDa) spiked in various biological fluids (human serum, plasma, urine, and saliva). A detailed optimization process involved the selection of a suitable capillary surface, background electrolyte (BGE), and comparison of two in-capillary preconcentration methods, namely transient isotachophoresis (tITP) and dynamic pH junction (DPJ), to enhance the sensitivity of the method. Optimum separation of the analytes was achieved using uncoated bare fused silica capillary employing 500 mM formic acid (pH 1.96) + 5 % (v/v) acetonitrile as BGE. tITP was utilized as an optimum preconcentration technique, achieving a 19- to 127-fold increase in the signal intensity when using 200 mM ammonium formate (adjusted to pH 4.00) as the leading electrolyte and BGE as the terminating electrolyte. Off-line microscale solid-phase extraction with various eluate treatment procedures was evaluated to ensure the compatibility of the sample pretreatment method with the selected in-capillary preconcentration, separation, and detection process. Achieved extraction recoveries of spiked proteins were in the range of 76-100 % for urine, 12-54 % for serum, 21-106 % for plasma, and 25-98 % for saliva when the eluate was evaporated and reconstituted in the solution of the leading electrolyte to achieve the tITP process. The optimum method was validated across different biological matrices, offering good linearity, accuracy, and precision, and making it suitable for proteomic studies (e.g., therapeutic drug monitoring, biomarker research) in different biological samples.

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.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Protein translation: biological processes and therapeutic strategies for human diseases

Protein translation is a tightly regulated cellular process that is essential for gene expression and protein synthesis. The deregulation of this process is increasingly recognized as a critical factor in the pathogenesis of various human diseases. In this review, we discuss how deregulated translation can lead to aberrant protein synthesis, altered cellular functions, and disease progression. We explore the key mechanisms contributing to the deregulation of protein translation, including functional alterations in translation factors, tRNA, mRNA, and ribosome function. Deregulated translation leads to abnormal protein expression, disrupted cellular signaling, and perturbed cellular functions- all of which contribute to disease pathogenesis. The development of ribosome profiling techniques along with mass spectrometry-based proteomics, mRNA sequencing and single-cell approaches have opened new avenues for detecting diseases related to translation errors. Importantly, we highlight recent advances in therapies targeting translation-related disorders and their potential applications in neurodegenerative diseases, cancer, infectious diseases, and cardiovascular diseases. Moreover, the growing interest lies in targeted therapies aimed at restoring precise control over translation in diseased cells is discussed. In conclusion, this comprehensive review underscores the critical role of protein translation in disease and its potential as a therapeutic target. Advancements in understanding the molecular mechanisms of protein translation deregulation, coupled with the development of targeted therapies, offer promising avenues for improving disease outcomes in various human diseases. Additionally, it will unlock doors to the possibility of precision medicine by offering personalized therapies and a deeper understanding of the molecular underpinnings of diseases in the future.

High-throughput drug target discovery using a fully automated proteomics sample preparation platform

Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.

Strophanthidin Induces Apoptosis of Human Lung Adenocarcinoma Cells by Promoting TRAIL-DR5 Signaling

Strophanthidin (SPTD), one of the cardiac glycosides, is refined from traditional Chinese medicines such as Semen Lepidii and Antiaris toxicaria, and was initially used for the treatment of heart failure disease in clinic. Recently, SPTD has been shown to be a potential anticancer agent, but the underlying mechanism of action is poorly understood. Herein, we explored the molecular mechanism by which SPTD exerts anticancer effects in A549 human lung adenocarcinoma cells by means of mass spectrometry-based quantitative proteomics in combination with bioinformatics analysis. We revealed that SPTD promoted the expression of tumor necrosis factor (TNF)-related apoptosis-inducing ligand receptor 2 (TRAIL-R2, or DR5) in A549 cells to activate caspase 3/6/8, in particular caspase 3. Consequently, the activated caspases elevated the expression level of apoptotic chromatin condensation inducer in the nucleus (ACIN1) and prelamin-A/C (LMNA), ultimately inducing apoptosis via cooperation with the SPTD-induced overexpressed barrier-to-autointegration factor 1 (Banf1). Moreover, the SPTD-induced DEPs interacted with each other to downregulate the p38 MAPK/ERK signaling, contributing to the SPTD inhibition of the growth of A549 cells. Additionally, the downregulation of collagen COL1A5 by SPTD was another anticancer benefit of SPTD through the modulation of the cell microenvironment.

Large-scale characterization of drug mechanism of action using proteome-wide thermal shift assays

In response to an ever-increasing demand of new small molecules therapeutics, numerous chemical and genetic tools have been developed to interrogate compound mechanism of action. Owing to its ability to characterize compound-dependent changes in thermal stability, the proteome-wide thermal shift assay has emerged as a powerful tool in this arsenal. The most recent iterations have drastically improved the overall efficiency of these assays, providing an opportunity to screen compounds at a previously unprecedented rate. Taking advantage of this advance, we quantified 1.498 million thermal stability measurements in response to multiple classes of therapeutic and tool compounds (96 compounds in living cells and 70 compounds in lysates). When interrogating the dataset as a whole, approximately 80% of compounds (with quantifiable targets) caused a significant change in the thermal stability of an annotated target. There was also a wealth of evidence portending off-target engagement despite the extensive use of the compounds in the laboratory and/or clinic. Finally, the combined application of cell- and lysate-based assays, aided in the classification of primary (direct ligand binding) and secondary (indirect) changes in thermal stability. Overall, this study highlights the value of these assays in the drug development process by affording an unbiased and reliable assessment of compound mechanism of action.

Monitoring host-pathogen interactions using chemical proteomics

With the rapid emergence and the dissemination of microbial resistance to conventional chemotherapy, the shortage of novel antimicrobial drugs has raised a global health threat. As molecular interactions between microbial pathogens and their mammalian hosts are crucial to establish virulence, pathogenicity, and infectivity, a detailed understanding of these interactions has the potential to reveal novel therapeutic targets and treatment strategies. Bidirectional molecular communication between microbes and eukaryotes is essential for both pathogenic and commensal organisms to colonise their host. In particular, several devastating pathogens exploit host signalling to adjust the expression of energetically costly virulent behaviours. Chemical proteomics has emerged as a powerful tool to interrogate the protein interaction partners of small molecules and has been successfully applied to advance host-pathogen communication studies. Here, we present recent significant progress made by this approach and provide a perspective for future studies.

Molecularly generated light and its biomedical applications

Molecularly generated light, referred to here as "molecular light", mainly includes bioluminescence, chemiluminescence, and Cerenkov luminescence. Molecular light possesses unique dual features of being both a molecule and a source of light. Its molecular nature enables it to be delivered as molecules to regions deep within the body, overcoming the limitations of natural sunlight and physically generated light sources like lasers and LEDs. Simultaneously, its light properties make it valuable for applications such as imaging, photodynamic therapy, photo-oxidative therapy, and photobiomodulation. In this review article, we provide an updated overview of the diverse applications of molecular light and discuss the strengths and weaknesses of molecular light across various domains. Lastly, we present forward-looking perspectives on the potential of molecular light in the realms of molecular imaging, photobiological mechanisms, therapeutic applications, and photobiomodulation. While some of these perspectives may be considered bold and contentious, our intent is to inspire further innovations in the field of molecular light applications.

Capture of the Mouse Organ Membrane Proteome Specificity in Peptidisc Libraries

Membrane proteins, particularly those on the cell surface, play pivotal roles in diverse physiological processes, and their dysfunction is linked to a broad spectrum of diseases. Despite being crucial biomarkers and therapeutic drug targets, their low abundance and hydrophobic nature pose challenges in isolation and quantification, especially when extracted from tissues and organs. To overcome these hurdles, we developed the membrane-mimicking peptidisc, enabling the isolation of the membrane proteome in a water-soluble library conducive to swift identification through liquid chromatography with tandem mass spectrometry. This study applies the method across five mice organs, capturing between 200 and 450 plasma membrane proteins in each case. More than just membrane protein identification, the peptidisc is used to estimate the relative abundance across organs, linking cell-surface protein molecular functions to organ biological roles, thereby contributing to the ongoing discourse on organ specificity. This contribution holds substantial potential for unveiling new avenues in the exploration of biomarkers and downstream applications involving knowledge of the organ cell-surface proteome.

Deciphering Drug Targets and Actions with Single-Cell and Spatial Resolution

Recent advances in chemical, molecular, and genetic approaches have provided us with an unprecedented capacity to identify drug-target interactions across the whole proteome and genome. Meanwhile, rapid developments of single-cell and spatial omics technologies are revolutionizing our understanding of the molecular architecture of biological systems. However, a significant gap remains in how we align our understanding of drug actions, traditionally based on molecular affinities, with the in vivo cellular and spatial tissue heterogeneity revealed by these newer techniques. Here, we review state-of-the-art methods for profiling drug-target interactions and emerging multiomics tools to delineate the tissue heterogeneity at single-cell resolution. Highlighting the recent technical advances enabling high-resolution, multiplexable in situ small-molecule drug imaging (clearing-assisted tissue click chemistry, or CATCH), we foresee the integration of single-cell and spatial omics platforms, data, and concepts into the future framework of defining and understanding in vivo drug-target interactions and mechanisms of actions.

Ligand Modification-Free Methods for the Profiling of Protein-Environmental Chemical Interactions

Adverse health outcomes caused by environmental chemicals are often initiated via their interactions with proteins. Essentially, one environmental chemical may interact with a number of proteins and/or a protein may interact with a multitude of environmental chemicals, forming an intricate interaction network. Omics-wide protein-environmental chemical interaction profiling (PECI) is of prominent importance for comprehensive understanding of these interaction networks, including the toxicity mechanisms of action (MoA), and for providing systematic chemical safety assessment. However, such information remains unknown for most environmental chemicals, partly due to their vast chemical diversity. In recent years, with the continuous efforts afforded, especially in mass spectrometry (MS) based omics technologies, several ligand modification-free methods have been developed, and new attention for systematic PECI profiling was gained. In this Review, we provide a comprehensive overview on these methodologies for the identification of ligand-protein interactions, including affinity interaction-based methods of affinity-driven purification, covalent modification profiling, and activity-based protein profiling (ABPP) in a competitive mode, physicochemical property changes assessment methods of ligand-directed nuclear magnetic resonance (ligand-directed NMR), MS integrated with equilibrium dialysis for the discovery of allostery systematically (MIDAS), thermal proteome profiling (TPP), limited proteolysis-coupled mass spectrometry (LiP-MS), stability of proteins from rates of oxidation (SPROX), and several intracellular downstream response characterization methods. We expect that the applications of these ligand modification-free technologies will drive a considerable increase in the number of PECI identified, facilitate unveiling the toxicological mechanisms, and ultimately contribute to systematic health risk assessment of environmental chemicals.

Recent Advances in Metalloproteomics

Interactions between proteins and metal ions and their complexes are important in many areas of the life sciences, including physiology, medicine, and toxicology. Despite the involvement of essential elements in all major processes necessary for sustaining life, metalloproteomes remain ill-defined. This is not only owing to the complexity of metalloproteomes, but also to the non-covalent character of the complexes that most essential metals form, which complicates analysis. Similar issues may also be encountered for some toxic metals. The review discusses recently developed approaches and current challenges for the study of interactions involving entire (sub-)proteomes with such labile metal ions. In the second part, transition metals from the fourth and fifth periods are examined, most of which are xenobiotic and also tend to form more stable and/or inert complexes. A large research area in this respect concerns metallodrug-protein interactions. Particular attention is paid to separation approaches, as these need to be adapted to the reactivity of the metal under consideration.

TTD: Therapeutic Target Database describing target druggability information

Target discovery is one of the essential steps in modern drug development, and the identification of promising targets is fundamental for developing first-in-class drug. A variety of methods have emerged for target assessment based on druggability analysis, which refers to the likelihood of a target being effectively modulated by drug-like agents. In the therapeutic target database (TTD), nine categories of established druggability characteristics were thus collected for 426 successful, 1014 clinical trial, 212 preclinical/patented, and 1479 literature-reported targets via systematic review. These characteristic categories were classified into three distinct perspectives: molecular interaction/regulation, human system profile and cell-based expression variation. With the rapid progression of technology and concerted effort in drug discovery, TTD and other databases were highly expected to facilitate the explorations of druggability characteristics for the discovery and validation of innovative drug target. TTD is now freely accessible at: https://idrblab.org/ttd/.

Cytoplasmic Shotgun Proteomic Points to Key Proteins and Pathways in Temozolomide-Resistant Glioblastoma Multiforme

Temozolomide (TMZ) is the first line of chemotherapy to treat primary brain tumors of the type glioblastoma multiforme (GBM). TMZ resistance (TMZR) is one of the main barriers to successful treatment and is a principal factor in relapse, resulting in a poor median survival of 15 months. The present paper focuses on proteomic analyses of cytosolic fractions from TMZ-resistant (TMZR) LN-18 cells. The experimental workflow includes an easy, cost-effective, and reproducible method to isolate subcellular fraction of cytosolic (CYTO) proteins, mitochondria, and plasma membrane proteins for proteomic studies. For this study, enriched cytoplasmic fractions were analyzed in replicates by nanoflow liquid chromatography tandem high-resolution mass spectrometry (nLC-MS/MS), and proteins identified were quantified using a label-free approach (LFQ). Statistical analysis of control (CTRL) and temozolomide-resistant (TMZR) proteomes revealed proteins that appear to be differentially controlled in the cytoplasm. The functions of these proteins are discussed as well as their roles in other cancers and TMZ resistance in GBM. Key proteins are also described through biological processes related to gene ontology (GO), molecular functions, and cellular components. For protein-protein interactions (PPI), network and pathway involvement analyses have been performed, highlighting the roles of key proteins in the TMZ resistance phenotypes. This study provides a detailed insight into methods of subcellular fractionation for proteomic analysis of TMZ-resistant GBM cells and the potential to apply this approach to future large-scale studies. Several key proteins, protein-protein interactions (PPI), and pathways have been identified, underlying the TMZ resistance phenotype and highlighting the proteins' biological functions.

Proteomic Profiling of Samples Derived from a Murine Model Following Cryptococcus neoformans Infection

Proteomic profiling provides in-depth information about the regulation of diverse biological processes, activation of and communication across signaling networks, and alterations to protein production, modifications, and interactions. For infectious disease research, mass spectrometry-based proteomics enables detection of host defenses against infection and mechanisms used by the pathogen to evade such responses. In this chapter, we outline protein extraction from organs, tissues, and fluids collected following intranasal inoculation of a murine model with the human fungal pathogen Cryptococcus neoformans. We describe sample preparation, followed by purification, processing on the mass spectrometer, and a robust bioinformatics analysis. The information gleaned from proteomic profiling of fungal infections supports the detection of novel biomarkers for diagnostic and prognostic purposes.

iProPhos: A Web-Based Interactive Platform for Integrated Proteome and Phosphoproteome Analysis

Large-scale omics studies have generated a wealth of mass spectrometry-based proteomics data, which provide additional insights into disease biology spanning genomic boundaries. However, there is a notable lack of web-based analysis and visualization tools that facilitate the reutilization of these data. Given this challenge, we present iProPhos, a user-friendly web server to deliver interactive and customizable functionalities. iProPhos incorporates a large number of samples, including 1444 tumor samples and 746 normal samples across 12 cancer types, sourced from the Clinical Proteomic Tumor Analysis Consortium. Additionally, users can also upload their own proteomics/phosphoproteomics data for analysis and visualization. In iProPhos, users can perform profiling plotting and differential expression, patient survival, clinical feature-related, and correlation analyses, including protein-protein, mRNA-protein, and kinase-substrate correlations. Furthermore, functional enrichment, protein-protein interaction network, and kinase-substrate enrichment analyses are accessible. iProPhos displays the analytical results in interactive figures and tables with various selectable parameters. It is freely accessible at http://longlab-zju.cn/iProPhos without login requirement. We present two case studies to demonstrate that iProPhos can identify potential drug targets and upstream kinases contributing to site-specific phosphorylation. Ultimately, iProPhos allows end-users to leverage the value of big data in cancer proteomics more effectively and accelerates the discovery of novel therapeutic targets.

GRP94 in cerebrospinal fluid may contribute to a potential biomarker of depression: Based on proteomics

The present study was designed to investigate potential biomarkers of depression and targets of antidepressants from the perspective of hippocampal endoplasmic reticulum stress (ERS) based on cerebrospinal fluid (CSF) proteomics. Firstly, a six-week depression model was established and treated with fluoxetine (FLX). We found antidepressant-FLX could ameliorate depression-like behaviors and cognition in depressed rats caused by chronic unpredictable mild stress (CUMS). FLX significantly increased neuronal numbers in dentate gyrus (DG) and CA3 regions of hippocampus. CSF proteome data revealed thirty-seven differentially expressed proteins (DEPs) co-regulated by CUMS and FLX, including GRP94 and EIF2α. Results of Gene Oncology (GO) annotation and KEGG pathway enrichment for DEPs mainly included PERK-mediated unfolded protein response, endoplasmic reticulum, and translational initiation. The expression levels of GRP94, p-PERK, p-EIF2α, CHOP and Caspase-12 were increased in hippocampus of CUMS rats, and FLX worked the opposite way. FLX had strong affinity and binding activity with GRP94 protein, and four key proteins on the PERK pathway (PERK, EIF2α, p-EIF2α, CHOP). We proposed that FLX may exert antidepressant effects and neuroprotective action by alleviating excessive activation of the hippocampal PERK pathway and reducing neuronal deficits in depressed rats. PERK, EIF2α, p-EIF2α, and CHOP may be potential targets for antidepressant-FLX. GRP94 in CSF may be a potential biomarker of depression and the therapeutic effects of antidepressants.

MultiPro: DDA-PASEF and diaPASEF acquired cell line proteomic datasets with deliberate batch effects

Mass spectrometry-based proteomics plays a critical role in current biological and clinical research. Technical issues like data integration, missing value imputation, batch effect correction and the exploration of inter-connections amongst these technical issues, can produce errors but are not well studied. Although proteomic technologies have improved significantly in recent years, this alone cannot resolve these issues. What is needed are better algorithms and data processing knowledge. But to obtain these, we need appropriate proteomics datasets for exploration, investigation, and benchmarking. To meet this need, we developed MultiPro (Multi-purpose Proteome Resource), a resource comprising four comprehensive large-scale proteomics datasets with deliberate batch effects using the latest parallel accumulation-serial fragmentation in both Data-Dependent Acquisition (DDA) and Data Independent Acquisition (DIA) modes. Each dataset contains a balanced two-class design based on well-characterized and widely studied cell lines (A549 vs K562 or HCC1806 vs HS578T) with 48 or 36 biological and technical replicates altogether, allowing for investigation of a multitude of technical issues. These datasets allow for investigation of inter-connections between class and batch factors, or to develop approaches to compare and integrate data from DDA and DIA platforms.

MMCL-CDR: enhancing cancer drug response prediction with multi-omics and morphology images contrastive representation learning

MOTIVATION

Cancer is a complex disease that results in a significant number of global fatalities. Treatment strategies can vary among patients, even if they have the same type of cancer. The application of precision medicine in cancer shows promise for treating different types of cancer, reducing healthcare expenses, and improving recovery rates. To achieve personalized cancer treatment, machine learning models have been developed to predict drug responses based on tumor and drug characteristics. However, current studies either focus on constructing homogeneous networks from single data source or heterogeneous networks from multiomics data. While multiomics data have shown potential in predicting drug responses in cancer cell lines, there is still a lack of research that effectively utilizes insights from different modalities. Furthermore, effectively utilizing the multimodal knowledge of cancer cell lines poses a challenge due to the heterogeneity inherent in these modalities.

RESULTS

To address these challenges, we introduce MMCL-CDR (Multimodal Contrastive Learning for Cancer Drug Responses), a multimodal approach for cancer drug response prediction that integrates copy number variation, gene expression, morphology images of cell lines, and chemical structure of drugs. The objective of MMCL-CDR is to align cancer cell lines across different data modalities by learning cell line representations from omic and image data, and combined with structural drug representations to enhance the prediction of cancer drug responses (CDR). We have carried out comprehensive experiments and show that our model significantly outperforms other state-of-the-art methods in CDR prediction. The experimental results also prove that the model can learn more accurate cell line representation by integrating multiomics and morphological data from cell lines, thereby improving the accuracy of CDR prediction. In addition, the ablation study and qualitative analysis also confirm the effectiveness of each part of our proposed model. Last but not least, MMCL-CDR opens up a new dimension for cancer drug response prediction through multimodal contrastive learning, pioneering a novel approach that integrates multiomics and multimodal drug and cell line modeling.

AVAILABILITY AND IMPLEMENTATION

MMCL-CDR is available at https://github.com/catly/MMCL-CDR.

Proteomics contributions to epigenetic drug discovery

The combined activity of epigenetic features, which include histone post-translational modifications, DNA methylation, and nucleosome positioning, regulates gene expression independently from changes in the DNA sequence, defining how the shared genetic information of an organism is used to generate different cell phenotypes. Alterations in epigenetic processes have been linked with a multitude of diseases, including cancer, fueling interest in the discovery of drugs targeting the proteins responsible for writing, erasing, or reading histone and DNA modifications. Mass spectrometry (MS)-based proteomics has emerged as a versatile tool that can assist drug discovery pipelines from target validation, through target deconvolution, to monitoring drug efficacy in vivo. Here, we provide an overview of the contributions of MS-based proteomics to epigenetic drug discovery, describing the main approaches that can be used to support different drug discovery pipelines and highlighting how they contributed to the development and characterization of epigenetic drugs.

Different chemical proteomic approaches to identify the targets of lapatinib

The process of identifying the protein targets and off-targets of a biologically active compound is of great importance in modern drug discovery. Various chemical proteomics approaches have been established for this purpose. To compare the different approaches, and to understand which method would provide the best results, we have chosen the EGFR inhibitor lapatinib as an example molecule. Lapatinib derivatives were designed using linkers with motifs, including amino (amidation), alkyne (click chemistry) and the diazirine group (photo-affinity). These modified lapatinib analogues were validated for their ability to inhibit EGFR activity in vitro and were shown to pull down purified recombinant EGFR protein. In all of the approaches evaluated here, we identified EGFR as the main protein target from the lysate of immortalised cell line expressing EGFR, thus validating its potential use to identify unknown protein targets. Taken together, the results reported here give insight into the cellular activities of lapatinib.

Virus-like Iron-Gold Heterogeneous Nanoparticles for Drug Target Screening

Drug-target recognition has great impacts on revealing mechanisms of pharmacological activities, especially drug resistance and off-target effects. In recent years, chemoproteomics has been widely used for drug target screening and discovery due to its high-throughput, high accuracy, and sensitivity. However, there still remain challenges on how to efficiently and unambiguously track target proteins from complex biological matrices. Herein, we report a drug target screening method based on virus-like iron-gold heterogeneous nanoparticles (Au@Fe3O4 NPs). The unique structure of Au@Fe3O4 NPs not only maintains the magnetism of Fe3O4 NPs to facilitate protein enrichment and purification, but also increases drug modification by introducing more active sites on the surface of Au NPs. After coincubating the drug modified NPs with the cell lysate, the high loading of drug on the surface of Au@Fe3O4 NPs was beneficial for capturing target proteins with low abundance. This well-designed heterogeneous nanomaterial provides a novel strategy for improving the efficiency and accuracy of affinity-based proteomics.

Small-Molecule Probes as Pharmacological Tools for the Bone Morphogenetic Protein Signaling Pathway

The bone morphogenetic protein (BMP) pathway is highly conserved and plays central roles in health and disease. The quality and quantity of its signaling outputs are regulated at multiple levels, offering pharmacological options for targeted modulation. Both target-centric and phenotypic drug discovery (PDD) approaches were applied to identify small-molecule BMP inhibitors and stimulators. In this Review, we accumulated and systematically classified the different reported chemotypes based on their targets as well as modes-of-action, and herein we illustrate the discovery history of selected candidates. A comprehensive summary of available biochemical, cellular, and in vivo activities is provided for the most relevant BMP modulators, along with recommendations on their preferred use as chemical probes to study BMP-related (patho)physiological processes. There are a number of high-quality probes used as BMP inhibitors that potently and selectively interrogate the kinase activities of distinct type I (16 chemotypes available) and type II receptors (3 chemotypes available). In contrast, only a few high-quality BMP stimulator modalities have been introduced to the field due to a lack of profound target knowledge. FK506-derived macrolides such as calcineurin-sparing FKBP12 inhibitors currently represent the best-characterized chemical tools for direct activation of BMP-SMAD signaling at the receptor level. However, several PDD campaigns succeeded in expanding the druggable space of BMP stimulators. Albeit the majority of them do not entirely fulfill the strict chemical probe criteria, many chemotypes exhibit unique and unrecognized mechanisms as pathway potentiators or synergizers, serving as valuable pharmacological tools for BMP perturbation.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Proteomics-Based Discovery of First-in-Class Chemical Probes for Programmed Cell Death Protein 2 (PDCD2)

Chemical probes are essential tools for understanding biological systems and for credentialing potential biomedical targets. Programmed cell death 2 (PDCD2) is a member of the B-cell lymphoma 2 (Bcl-2) family of proteins, which are critical regulators of apoptosis. Here we report the discovery and characterization of 10 e, a first-in-class small molecule degrader of PDCD2. We discovered this PDCD2 degrader by serendipity using a chemical proteomics approach, in contrast to the conventional approach for making bivalent degraders starting from a known binding ligand targeting the protein of interest. Using 10 e as a pharmacological probe, we demonstrate that PDCD2 functions as a critical regulator of cell growth by modulating the progression of the cell cycle in T lymphoblasts. Our work provides a useful pharmacological probe for investigating PDCD2 function and highlights the use of chemical proteomics to discover selective small molecule degraders of unanticipated targets.

Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium

The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have implemented an efficient integrative experimental and computational framework leveraging the systematic generation and analysis of drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Protein activity-based analyses revealed highly reproducible, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide polypharmacology map, characterization of MoA-related drug clusters and off-target effects, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins. The proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, could help support more systematic and quantitative approaches to precision oncology.

Design, synthesis, and evaluation of a mitoxantrone probe (MXP) for biological studies

Mitoxantrone (MX) is a robust chemotherapeutic with well-characterized applications in treating certain leukemias and advanced breast and prostate cancers. The canonical mechanism of action associated with MX is its ability to intercalate DNA and inhibit topoisomerase II, giving it the designation of a topoisomerase II poison. Years after FDA approval, investigations have unveiled novel protein-binding partners, such as methyl-CpG-binding domain protein (MBD2), PIM1 serine/threonine kinase, RAD52, and others that may contribute to the therapeutic profile of MX. Moreover, recent proteomic studies have revealed MX's ability to modulate protein expression, illuminating the complex cellular interactions of MX. Although mechanistically relevant, the differential expression across the proteome does not address the direct interaction with potential binding partners. Identification and characterization of these MX-binding cellular partners will provide the molecular basis for the alternate mechanisms that influence MX's cytotoxicity. Here, we describe the design and synthesis of a MX-biotin probe (MXP) and negative control (MXP-NC) that can be used to define MX's cellular targets and expand our understanding of the proteome-wide profile for MX. In proof of concept studies, we used MXP to successfully isolate a recently identified protein-binding partner of MX, RAD52, in a cell lysate pulldown with streptavidin beads and western blotting.

Recent applications of quantitative mass spectrometry in biopharmaceutical process development and manufacturing

Biopharmaceutical products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Aligning with the quality by design (QbD) framework and realization, recent advances in liquid chromatography-mass spectrometry (LC-MS) instrumentation and related techniques have enhanced biopharmaceutical characterization capabilities and have supported an increased development of biopharmaceutical products. Beyond its routine qualitative characterization, the quantitative feature of LC-MS has unique applications in biopharmaceutical process development and manufacturing. This review describes the recent applications and implications of the advancement of quantitative MS methods in biopharmaceutical process development, and characterization of biopharmaceutical product, product-related variants, and process-related impurities. We also provide insights on the emerging applications of quantitative MS in the lifecycle of biopharmaceutical product development including quality control in the Good Manufacturing Practice (GMP) environment and process analytical technology (PAT) practices during process development and manufacturing. Through collaboration with instrument and software vendors and regulatory agencies, we envision broader adoption of phase-appropriate quantitative MS-based methods for the analysis of biopharmaceutical products, which in turn has the potential to enable manufacture of higher quality products for patients.

Intracellular spatiotemporal metabolism in connection to target engagement

The metabolism in eukaryotic cells is a highly ordered system involving various cellular compartments, which fluctuates based on physiological rhythms. Organelles, as the smallest independent sub-cell unit, are important contributors to cell metabolism and drug metabolism, collectively designated intracellular metabolism. However, disruption of intracellular spatiotemporal metabolism can lead to disease development and progression, as well as drug treatment interference. In this review, we systematically discuss spatiotemporal metabolism in cells and cell subpopulations. In particular, we focused on metabolism compartmentalization and physiological rhythms, including the variation and regulation of metabolic enzymes, metabolic pathways, and metabolites. Additionally, the intricate relationship among intracellular spatiotemporal metabolism, metabolism-related diseases, and drug therapy/toxicity has been discussed. Finally, approaches and strategies for intracellular spatiotemporal metabolism analysis and potential target identification are introduced, along with examples of potential new drug design based on this.

Opportunities and challenges in drug discovery targeting the orphan receptor GPR12

G-protein-coupled receptor 12 (GPR12) is a brain-specific expression orphan G-protein-coupled receptor (oGPCR) that regulates various physiological processes. It is an emerging therapeutic target for central nervous system (CNS) disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), attention deficit hyperactivity disorder (ADHD), and schizophrenia, as well as other human diseases, such as cancer, obesity, and metabolic disorders. GPR12 remains a less extensively investigated oGPCR, particularly in terms of its biological functions, signaling pathways, and ligand discovery. The discovery of drug-like small-molecule modulators to probe the brain functions of GPR12 or to act as a potential drug candidates, as well as the identification of reliable biomarkers, are vital to elucidate the roles of this receptor in various human diseases and develop novel target-based therapeutics.

The rise of degrader drugs

The cancer genomics revolution has served up a plethora of promising and challenging targets for the drug discovery community. The field of targeted protein degradation (TPD) uses small molecules to reprogram the protein homeostasis system to destroy desired target proteins. In the last decade, remarkable progress has enabled the rational development of degraders for a large number of target proteins, with over 20 molecules targeting more than 12 proteins entering clinical development. While TPD has been fully credentialed by the prior development of immunomodulatory drug (IMiD) class for the treatment of multiple myeloma, the field is poised for a "Gleevec moment" in which robust clinical efficacy of a rationally developed novel degrader against a preselected target is firmly established. Here, we endeavor to provide a high-level evaluation of exciting developments in the field and comment on steps that may realize the full potential of this new therapeutic modality.

Small-molecule probes from bench to bedside: advancing molecular analysis of drug-target interactions toward precision medicine

Over the past decade, remarkable advances have been witnessed in the development of small-molecule probes. These molecular tools have been widely applied for interrogating proteins, pathways and drug-target interactions in preclinical research. While novel structures and designs are commonly explored in probe development, the clinical translation of small-molecule probes remains limited, primarily due to safety and regulatory considerations. Recent synergistic developments - interfacing novel chemical probes with complementary analytical technologies - have introduced and expedited diverse biomedical opportunities to molecularly characterize targeted drug interactions directly in the human body or through accessible clinical specimens (e.g., blood and ascites fluid). These integrated developments thus offer unprecedented opportunities for drug development, disease diagnostics and treatment monitoring. In this review, we discuss recent advances in the structure and design of small-molecule probes with novel functionalities and the integrated development with imaging, proteomics and other emerging technologies. We further highlight recent applications of integrated small-molecule technologies for the molecular analysis of drug-target interactions, including translational applications and emerging opportunities for whole-body imaging, tissue-based measurement and blood-based analysis.

Potential of Negative-Ion-Mode Proteomics: An MS1-Only Approach

Current proteomics approaches rely almost exclusively on using the positive ionization mode, resulting in inefficient ionization of many acidic peptides. This study investigates protein identification efficiency in the negative ionization mode using the DirectMS1 method. DirectMS1 is an ultrafast data acquisition method based on accurate peptide mass measurements and predicted retention times. Our method achieves the highest rate of protein identification in the negative ion mode to date, identifying over 1000 proteins in a human cell line at a 1% false discovery rate. This is accomplished using a single-shot 10 min separation gradient, comparable to lengthy MS/MS-based analyses. Optimizing separation and experimental conditions was achieved by utilizing mobile buffers containing 2.5 mM imidazole and 3% isopropanol. The study emphasized the complementary nature of data obtained in positive and negative ion modes. Combining the results from all replicates in both polarities increased the number of identified proteins to 1774. Additionally, we analyzed the method's efficiency using different proteases for protein digestion. Among the four studied proteases (LysC, GluC, AspN, and trypsin), trypsin and LysC demonstrated the highest protein identification yield. This suggests that digestion procedures utilized in positive-mode proteomics can be effectively applied in the negative ion mode. Data are deposited to ProteomeXchange: PXD040583.

Molecular Glue Discovery: Current and Future Approaches

The intracellular interactions of biomolecules can be maneuvered to redirect signaling, reprogram the cell cycle, or decrease infectivity using only a few dozen atoms. Such "molecular glues," which can drive both novel and known interactions between protein partners, represent an enticing therapeutic strategy. Here, we review the methods and approaches that have led to the identification of small-molecule molecular glues. We first classify current FDA-approved molecular glues to facilitate the selection of discovery methods. We then survey two broad discovery method strategies, where we highlight the importance of factors such as experimental conditions, software packages, and genetic tools for success. We hope that this curation of methodologies for directed discovery will inspire diverse research efforts targeting a multitude of human diseases.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

Evaluation of the Orbitrap Ascend Tribrid Mass Spectrometer for Shotgun Proteomics

Mass spectrometry (MS)-based proteomics is a powerful technology to globally profile protein abundances, activities, interactions, and modifications. The extreme complexity of proteomics samples, which often contain hundreds of thousands of analytes, necessitates continuous development of MS techniques and instrumentation to improve speed, sensitivity, precision, and accuracy, among other analytical characteristics. Here, we systematically evaluated the Orbitrap Ascend Tribrid mass spectrometer in the context of shotgun proteomics, and we compared its performance to that of the previous generation of Tribrid instruments─the Orbitrap Eclipse. The updated architecture of the Orbitrap Ascend includes a second ion-routing multipole (IRM) in front of the redesigned C-trap/Orbitrap and a new ion funnel that allows gentler ion introduction, among other changes. These modifications in Ascend hardware configuration enabled an increase in parallelizable ion injection time during higher-energy collisional dissociation (HCD) Orbitrap tandem MS (FTMS2) analysis of ∼5 ms. This enhancement was particularly valuable in the analyses of limited sample amounts, where improvements in sensitivity resulted in up to 140% increase in the number of identified tryptic peptides. Further, analysis of phosphorylated peptides enriched from the K562 human cell line yielded up to ∼50% increase in the number of unique phosphopeptides and localized phosphosites. Strikingly, we also observed a ∼2-fold boost in the number of detected N-glycopeptides, likely owing to the improvements in ion transmission and sensitivity. In addition, we performed the multiplexed quantitative proteomics analyses of TMT11-plex labeled HEK293T tryptic peptides and observed 9-14% increase in the number of quantified peptides. In conclusion, the Orbitrap Ascend consistently outperformed its predecessor the Orbitrap Eclipse in various bottom-up proteomic analyses, and we anticipate that it will generate reproducible and in-depth datasets for numerous proteomic applications.