Expression proteomics study to determine metallodrug targets and optimal drug combinations

From the Discovery of Targets to Delivery Systems: How to Decipher and Improve the Metallodrugs' Actions at a Molecular Level

Metals are indispensable for the life of all organisms, and their dysregulation leads to various disorders due to the disruption of their homeostasis. Nowadays, various transition metals are used in pharmaceutical products as diagnostic and therapeutic agents because their electronic structure allows them to adjust the properties of molecules differently from organic molecules. Therefore, interest in the study of metal-drug complexes from different aspects has been aroused, and numerous approaches have been developed to characterize, activate, deliver, and clarify molecular mechanisms. The integration of these different approaches, ranging from chemoproteomics to nanoparticle systems and various activation strategies, enables the understanding of the cellular responses to metal drugs, which may form the basis for the development of new drugs and/or the modification of currently used drugs. The purpose of this review is to briefly summarize the recent advances in this field by describing the technological platforms and their potential applications for identifying protein targets for discovering the mechanisms of action of metallodrugs and improving their efficiency during delivery.

Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication

Cell mechanics is essential to cell development and function, and its dynamics evolution reflects the physiological state of cells. Here, we investigate the dynamical mechanical properties of single cells under various drug conditions, and present two mathematical approaches to quantitatively characterizing the cell physiological state. It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate, and can be mathematically characterized by a linear time-invariant dynamical model. It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions. Furthermore, it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties, and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model. This study builds a relationship between the cellular mechanical properties and the cellular physiological state, adding information for evaluating drug efficacy.

Proteome Integral Solubility Alteration (PISA) for High-Throughput Ligand Target Deconvolution with Increased Statistical Significance and Reduced Sample Amount

Proteome Integral Solubility Alteration (PISA) is a recently developed mass spectrometry-based, deep proteomics method for unbiased, proteome-wide target deconvolution of ligands, requiring no chemical ligand modification. PISA can be applied to living cells for studying target engagement in vivo or alternatively to protein extracts to identify in vitro ligand-interacting proteins. Here we describe the PISA workflow optimized in our lab. PISA improves the target discovery throughput 10-100 folds compared to the previously used proteomics methods and provides higher statistical significance for target candidates by enabling several biological replicates. Sample multiplexing makes all-in-one analysis of multiple ligands simultaneously possible. PISA dramatically reduces analysis costs, allowing many research questions in need of target deconvolution to be addressed, and unlocks the potential of miniaturizing biological models, including primary cells.

Proteome Integral Solubility Alteration (PISA) Assay in Mammalian Cells for Deep, High-Confidence, and High-Throughput Target Deconvolution

Chemical proteomics focuses on the drug-target-phenotype relationship for target deconvolution and elucidation of the mechanism of action-key and bottleneck in drug development and repurposing. Majorly due to the limits of using chemically modified ligands in affinity-based methods, new, unbiased, proteome-wide, and MS-based chemical proteomics approaches have been developed to perform drug target deconvolution, using full proteome profiling and no chemical modification of the studied ligand. Of note among them, thermal proteome profiling (TPP) aims to identify the target(s) by measuring the difference in melting temperatures between each identified protein in drug-treated versus vehicle-treated samples, with the thermodynamic interpretation of "protein melting" and curve fitting of all quantified proteins, at all temperatures, in each biological replicate. Including TPP, all the other chemical proteomics approaches often fail to provide target deconvolution with sufficient proteome depth, statistical power, throughput, and sustainability, which could hardly fulfill the final purpose of drug development. The proteome integral solubility alteration (PISA) assay provides no thermodynamic interpretation, but a throughput 10-100-fold compared to the other proteomics methods, high sustainability, much lower time of analysis and sample amount requirements, high confidence in results, maximal proteome coverage (~10,000 protein IDs), and up to five drugs / test molecules in one assay, with at least biological triplicates of each treatment. Each drug-treated or vehicle-treated sample is split into many fractions and exposed to a gradient of heat as solubility perturbing agent before being recomposed into one sample; each soluble fraction is isolated, then deep and quantitative proteomics is applied across all samples. The proteins interacting with the tested molecules (targets and off-targets), the activated mechanistic factors, or proteins modified during the treatment show reproducible changes in their soluble amount compared to vehicle-treated controls. As of today, the maximal multiplexing capability is 18 biological samples per PISA assay, which enables statistical robustness and flexible experimental design accommodation for fuller target deconvolution, including integration of orthogonal chemical proteomics methods in one PISA assay. Living cells for studying target engagement in vivo or, alternatively, protein extracts to identify in vitro ligand-interacting proteins can be studied, and the minimal need in sample amount unlocks target deconvolution using primary cells and their derived cultures. This protocol was validated in: J Biol Chem (2021), DOI: 10.1016/j.jbc.2021.10153 Graphical abstract.

Dienone Compounds: Targets and Pharmacological Responses

The biological responses to dienone compounds with a 1,5-diaryl-3-oxo-1,4-pentadienyl pharmacophore have been studied extensively. Despite their expected general thiol reactivity, these compounds display considerable degrees of tumor cell selectivity. Here we review in vitro and preclinical studies of dienone compounds including b-AP15, VLX1570, RA-9, RA-190, EF24, HO-3867, and MCB-613. A common property of these compounds is their targeting of the ubiquitin–proteasome system (UPS), known to be essential for the viability of tumor cells. Gene expression profiling experiments have shown induction of responses characteristic of UPS inhibition, and experiments using cellular reporter proteins have shown that proteasome inhibition is associated with cell death. Other mechanisms of action such as reactivation of mutant p53, stimulation of steroid receptor coactivators, and induction of protein cross-linking have also been described. Although unsuitable as biological probes due to widespread reactivity, dienone compounds are cytotoxic to apoptosis-resistant tumor cells and show activity in animal tumor models.

Changes in the plasma microvesicle proteome during the ovarian hyperstimulation phase of assisted reproductive technology

The incidence of pulmonary and venous thromboembolism is increased during the first trimester of pregnancies after assisted reproductive technology (ART) compared to spontaneous conception. We previously found that haemostatic plasma variables changed but within normal limits during controlled ovarian hyperstimulation (COH) concomitant with a major increase in plasma microvesicles (MVs) and markers indicating cell activation. We now explored the proteome of these MVs. Thirty-one women undergoing ART were blood sampled at down-regulation (DR) of oestrogen and at high level stimulation (HLS) with its 10–100-fold increased oestrogen level. Samples were analysed by liquid chromatography and tandem mass spectrometry to identify and quantify the proteome. We identified 306 proteins in the MVs and 72 had changed significantly at HLS compared to DR and more than 20% of them were associated with haemostasis. Thus, proteins related to both haemostasis and complement activation altered in plasma MVs in parallel with MV activation during COH. This needs to be further explored in the clinical context.

A mass spectrometry-based proteome map of drug action in lung cancer cell lines

Mass spectrometry-based discovery proteomics is an essential tool for the proximal readout of cellular drug action. Here, we apply a robust proteomic workflow to rapidly profile the proteomes of five lung cancer cell lines in response to more than 50 drugs. Integration of millions of quantitative protein-drug associations substantially improved the mechanism of action (MoA) deconvolution of single compounds. For example, MoA specificity increased after removal of proteins that frequently responded to drugs and the aggregation of proteome changes across cell lines resolved compound effects on proteostasis. We leveraged these findings to demonstrate efficient target identification of chemical protein degraders. Aggregating drug response across cell lines also revealed that one-quarter of compounds modulated the abundance of one of their known protein targets. Finally, the proteomic data led us to discover that inhibition of mitochondrial function is an off-target mechanism of the MAP2K1/2 inhibitor PD184352 and that the ALK inhibitor ceritinib modulates autophagy.

Comprehensive chemical proteomics for target deconvolution of the redox active drug auranofin

Chemical proteomics encompasses novel drug target deconvolution methods in which compound modification is not required. Herein we use Thermal Proteome Profiling, Functional Identification of Target by Expression Proteomics and multiplexed redox proteomics for deconvolution of auranofin targets to aid elucidation of its mechanisms of action. Auranofin (Ridaura®) was approved for treatment of rheumatoid arthritis in 1985. Because several clinical trials are currently ongoing to repurpose auranofin for cancer therapy, comprehensive characterization of its targets and effects in cancer cells is important. Together, our chemical proteomics tools confirmed thioredoxin reductase 1 (TXNRD1, EC:1.8.1.9) as a main auranofin target, with perturbation of oxidoreductase pathways as the top mechanism of drug action. Additional indirect targets included NFKB2 and CHORDC1. Our comprehensive data can be used as a proteomic signature resource for further analyses of the effects of auranofin. Here we also assessed the orthogonality and complementarity of different chemical proteomics methods that can furnish invaluable mechanistic information and thus the approach can facilitate drug discovery efforts in general.

Time-dependent shotgun proteomics revealed distinct effects of an organoruthenium prodrug and its activation product on colon carcinoma cells

Activation kinetics of metallo-prodrugs control the types of possible interactions with biomolecules. The intact metallo-prodrug is able to engage with potential targets by purely non-covalent bonding, while the activated metallodrug can form additional coordination bonds. It is hypothesized that the additional coordinative bonding might be favourable with respect to the target selectivity of activated metallodrugs. Thus, a time-dependent shotgun proteomics study was conducted in HCT116 colon carcinoma cells with plecstatins, which are organoruthenium anticancer drug candidates. First, the target selectivity was evaluated in a time-dependent fashion, which accounted for their hydrolysis kinetics. The binding selectivity increased from 50- to 160-fold and the average specificity from 0.72 to 0.86, respectively, from the 2 h to the 4 h target profiling experiment. Target profiling after 19 h did not reveal significant enrichments, possibly due to deactivation of the probe via arene cleavage. Up to 450 interactors were identified in the target profiling experiments. A plecstatin analogue that substituted a hydrogen bond acceptor with a hydrogen bond donor abrogated the target selectivity for plectin in HCT116 whole cell lysates, underlining the necessity of this hydrogen bond acceptor for a strong interaction between plecstatin and plectin. Second, time-dependent response profiling experiments provided evidence that plecstatin-2 induced an integrated stress response (ISR) in HCT116 cell culture. The phosphorylation of eIF2α, a key mediator of the ISR, after 3 h treatment indicated that this perturbation was initiated by the intact plecstatin-2 prodrug, while the effects of plectin-targeting are mediated by activated plecstatin-2.

ProTargetMiner as a proteome signature library of anticancer molecules for functional discovery

Deconvolution of targets and action mechanisms of anticancer compounds is fundamental in drug development. Here, we report on ProTargetMiner as a publicly available expandable proteome signature library of anticancer molecules in cancer cell lines. Based on 287 A549 adenocarcinoma proteomes affected by 56 compounds, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. These proteomic signatures cluster by compound targets and action mechanisms. The targets and mechanistic proteins are deconvoluted by partial least square modeling, provided through the website http://protargetminer.genexplain.com. For 9 molecules representing the most diverse mechanisms and the common cancer cell lines MCF-7, RKO and A549, deep proteome datasets are obtained. Combining data from the three cell lines highlights common drug targets and cell-specific differences. The database can be easily extended and merged with new compound signatures. ProTargetMiner serves as a chemical proteomics resource for the cancer research community, and can become a valuable tool in drug discovery.

Anticancer drugs often have widespread effects on the cellular proteome. Here, the authors generate a proteome signature library of drug-treated cancer cell lines and develop a software tool to deconvolute drug targets and gain insights into their mechanisms of action.

Anticancer Effect of Deuterium Depleted Water - Redox Disbalance Leads to Oxidative Stress

Despite the convincing empirical evidence that deuterium depleted water (DDW, 25-125 ppm deuterium) has anticancer effect, the molecular mechanism remains unclear. Here, redox proteomics investigation of the DDW action in A549 cells revealed an increased level of oxidative stress, whereas expression proteomics in combination with thermal profiling uncovered crucial role of mitochondrial proteins. In the proposed scenario, reversal of the normally positive deuterium gradient across the inner membrane leads to an increased export of protons from the matrix to intermembrane space and an increase in the mitochondrial membrane potential, enhancing the production of reactive oxygen species (ROS). The resulting oxidative stress leads to slower growth and can induce apoptosis. However, further deuterium depletion in ambient water triggers a feedback mechanism, which leads to restoration of the redox equilibrium and resumed growth. The DDW-induced oxidative stress, verified by traditional biochemical assays, may be helpful as an adjuvant to ROS-inducing anticancer therapy.

Toward Multi-Targeted Platinum and Ruthenium Drugs-A New Paradigm in Cancer Drug Treatment Regimens?

While medicinal inorganic chemistry has been practised for over 5000 years, it was not until the late 1800s when Alfred Werner published his ground-breaking research on coordination chemistry that we began to truly understand the nature of the coordination bond and the structures and stereochemistries of metal complexes. We can now readily manipulate and fine-tune their properties. This had led to a multitude of complexes with wide-ranging biomedical applications. This review will focus on the use and potential of metal complexes as important therapeutic agents for the treatment of cancer. With major advances in technologies and a deeper understanding of the human genome, we are now in a strong position to more fully understand carcinogenesis at a molecular level. We can now also rationally design and develop drug molecules that can either selectively enhance or disrupt key biological processes and, in doing so, optimize their therapeutic potential. This has heralded a new era in drug design in which we are moving from a single- toward a multitargeted approach. This approach lies at the very heart of medicinal inorganic chemistry. In this review, we have endeavored to showcase how a "multitargeted" approach to drug design has led to new families of metallodrugs which may not only reduce systemic toxicities associated with modern day chemotherapeutics but also address resistance issues that are plaguing many chemotherapeutic regimens. We have focused our attention on metallodrugs incorporating platinum and ruthenium ions given that complexes containing these metal ions are already in clinical use or have advanced to clinical trials as anticancer agents. The "multitargeted" complexes described herein not only target DNA but also contain either vectors to enable them to target cancer cells selectively and/or moieties that target enzymes, peptides, and intracellular proteins. Multitargeted complexes which have been designed to target the mitochondria or complexes inspired by natural product activity are also described. A summary of advances in this field over the past decade or so will be provided.