Elucidating mechanisms of drug-induced toxicity

Proteome profiling, biochemical and histological analysis of diclofenac-induced liver toxicity in Yersinia enterocolitica and Lactobacillus fermentum fed rat model: a comparative analysis

Diclofenac is a hepatotoxic non-steroidal anti-inflammatory drug (NSAID) that affects liver histology and its protein expression levels. Here, we studied the effect of diclofenac on rat liver when co-administrated with either Yersinia enterocolitica strain 8081 serotype O:8 biovar 1B (D*Y) or Lactobacillus fermentum strain 9338 (D*L). Spectroscopic analysis of stool samples showed biotransformation of diclofenac. When compared with each other, D*Y rats lack peaks at 1709 and 1198 cm-1, while D*L rats lack peaks at 1411 cm-1. However, when compared to control, both groups lack peaks at 1379 and 1170 cm-1. Assessment of serum biomarkers of hepatotoxicity indicated significantly altered activities of AST (D*Y: 185.65 ± 8.575 vs Control: 61.9 ± 2.607, D*L: 247.5 ± 5.717 vs Control: 61.9 ± 2.607), ALT (D*Y: 229.8 ± 6.920 vs Control: 70.7 ± 3.109, D*L: 123.75 ± 6.068 vs Control: 70.7 ± 3.109), and ALP (D*Y: 276.4 ± 18.154 vs Control: 320.6 ± 9.829, D*L: 298.5 ± 12.336 vs Control: 320.6 ± 9.829) in IU/L. The analysis of histological alterations showed hepatic sinusoidal dilation with vein congestion and cell infiltration exclusively in D*Y rats along with other histological changes that are common to both test groups, thereby suggesting more pronounced alterations in D*Y rats. Further, LC-MS/MS based label-free quantitation of proteins from liver tissues revealed 74.75% up-regulated, 25.25% down-regulated in D*Y rats and 51.16% up-regulated, 48.84% down-regulated in D*L experiments. The proteomics-identified proteins majorly belonged to metabolism, apoptosis, stress response and redox homeostasis, and detoxification and antioxidant defence that demonstrated the potential damage of rat liver, more pronounced in D*Y rats. Altogether the results are in favor that the administration of lactobacilli somewhat protected the rat hepatic cells against the diclofenac-induced toxicity.

MolLoG: A Molecular Level Interpretability Model Bridging Local to Global for Predicting Drug Target Interactions

Developing new pharmaceuticals is a costly and time-consuming endeavor fraught with significant safety risks. A critical aspect of drug research and disease therapy is discerning the existence of interactions between drugs and proteins. The evolution of deep learning (DL) in computer science has been remarkably aided in this regard in recent years. Yet, two challenges remain: (i) balancing the extraction of profound, local cohesive characteristics while warding off gradient disappearance and (ii) globally representing and understanding the interactions between the drug and target local attributes, which is vital for delivering molecular level insights indispensable to drug development. In response to these challenges, we propose a DL network structure, MolLoG, primarily comprising two modules: local feature encoders (LFE) and global interactive learning (GIL). Within the LFE module, graph convolution networks and leap blocks capture the local features of drug and protein molecules, respectively. The GIL module enables the efficient amalgamation of feature information, facilitating the global learning of feature structural semantics and procuring multihead attention weights for abstract features stemming from two modalities, providing biologically pertinent explanations for black-box results. Finally, predictive outcomes are achieved by decoding the unified representation via a multilayer perceptron. Our experimental analysis reveals that MolLoG outperforms several cutting-edge baselines across four data sets, delivering superior overall performance and providing satisfactory results when elucidating various facets of drug-target interaction predictions.

Advancing Adverse Drug Reaction Prediction with Deep Chemical Language Model for Drug Safety Evaluation

The accurate prediction of adverse drug reactions (ADRs) is essential for comprehensive drug safety evaluation. Pre-trained deep chemical language models have emerged as powerful tools capable of automatically learning molecular structural features from large-scale datasets, showing promising capabilities for the downstream prediction of molecular properties. However, the performance of pre-trained chemical language models in predicting ADRs, especially idiosyncratic ADRs induced by marketed drugs, remains largely unexplored. In this study, we propose MoLFormer-XL, a pre-trained model for encoding molecular features from canonical SMILES, in conjunction with a CNN-based model to predict drug-induced QT interval prolongation (DIQT), drug-induced teratogenicity (DIT), and drug-induced rhabdomyolysis (DIR). Our results demonstrate that the proposed model outperforms conventional models applied in previous studies for predicting DIQT, DIT, and DIR. Notably, an analysis of the learned linear attention maps highlights amines, alcohol, ethers, and aromatic halogen compounds as strongly associated with the three types of ADRs. These findings hold promise for enhancing drug discovery pipelines and reducing the drug attrition rate due to safety concerns.

Manganese-doped albumin-gelatin composite nanogel loaded with berberine applied to the treatment of gouty arthritis in rats via a SPARC-dependent mechanism

In this study, manganese-doped albumin-gelatin composite nanogels (MAGN) were prepared and used to load berberine (Ber) for the treatment of gouty arthritis (GA). The nanodrug delivery system (Ber-MAGN) can target inflammatory joints due to the intrinsic high affinity of albumin for SPARC, which is overexpressed at the inflammatory site of GA. Characterization of the pharmaceutical properties in vitro showed that Ber-MAGN had good dispersion, and the particle size was 121 ± 10.7 nm. The sustained release effect significantly improved the bioavailability of berberine. In vitro and in vivo experimental results showed that Ber-MAGN has better therapeutic effects in relieving oxidative stress and suppressing inflammation. Therefore, Ber-MAGN, as a potential pharmaceutical preparation for GA, provides a new reference for the clinical treatment plan of GA.

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

PEG2000-PLA-based nanoscale polymeric micelles reduce paclitaxel-related toxicity in beagle dogs

Nanoplatform-based drug delivery plays an important role in clinical practice. Polymeric micellar (Pm) nanocarriers have been demonstrated to reduce the toxicity of paclitaxel in rats and non-small cell lung cancer (NSCLC) patients. However, the underlying toxicological profile needs to be further illustrated. Here, we used beagles as study subjects and sought to further observe the toxicological profile of polymeric micellar paclitaxel (Pm-Pac) via acute toxicity tests and short-term and long-term toxicity tests. The results from the acute toxicity test indicated that the lethal dose of Pm-Pac in beagles was 20-30 mg/kg, and the acute toxicity-targeted organs were the digestive system and immuno-haematopoietic system. The short-term toxicity test suggested that paclitaxel-induced toxicity (peripheral neuropathy toxicity, haemopoietic toxicity, heart system toxicity, and so on) in beagles can be reduced when paclitaxel is delivered via the Pm delivery system. The long-term toxicity test suggested that Pm-Pac can reduce haemopoietic toxicity in beagles. Collectively, this study provides novel insight into the toxicological profile of Pm-Pac in healthy beagles and provides a potential basis for promising clinical combination strategies in the future.

Cardiothoracic complications of immune checkpoint inhibitors

A paradigm shift in cancer treatment occurred with the advent of immune checkpoint inhibitors (ICI). ICI therapy has improved tumor response and increased overall survival in patients with solid tumors and hematologic malignancies. While ICI therapy has improved overall patient outcomes in oncology, it has also introduced novel adverse effects called immune-related adverse effects (irAEs). Studies have shown that the development of irAEs is associated with improved overall survival, but certain irAEs like pneumonitis and myocarditis are life threatening, and could result in death if not identified and treated early. Therefore, it is important for radiologists to be aware of complications arising from ICI administration, especially those related to the heart and lungs as they are associated with greater mortality. This paper will review the imaging features of cardiothoracic toxicities, recurrent and chronic irAEs, and atypical tumor responses associated with irAEs.

The role of cytochrome P450 3A4-mediated metabolism in sorafenib and lapatinib hepatotoxicity

Tyrosine kinase inhibitors (TKIs) are increasingly popular drugs used to treat more than a dozen different diseases, including some forms of cancer. Despite having fewer adverse effects than traditional chemotherapies, they are not without risks. Liver injury is a particular concern. Of the FDA-approved TKIs, approximately 40% cause hepatotoxicity. However, little is known about the underlying pathophysiology. The leading hypothesis is that TKIs are converted by cytochrome P450 3A4 (CYP3A4) to reactive metabolites that damage proteins. Indeed, there is strong evidence for this bioactivation of TKIs in in vitro reactions. However, the actual toxic effects are underexplored. Here, we measured the cytotoxicity of several TKIs in primary mouse hepatocytes, HepaRG cells, and HepG2 cells with and without CYP3A4 modulation. To our surprise, the data indicate that CYP3A4 increases resistance to sorafenib and lapatinib hepatotoxicity. The results have implications for the mechanism of toxicity of these drugs in patients and underline the importance of selecting an appropriate experimental model.

Laboratory safety evaluation of lokivetmab, a canine anti-interleukin-31 monoclonal antibody, in dogs

Lokivetmab (Cytopoint®, Zoetis) is a canine monoclonal antibody that specifically binds and neutralizes interleukin (IL)-31. Lokivetmab is approved for use in dogs for the treatment of atopic dermatitis (AD) and allergic dermatitis. The laboratory safety of lokivetmab was evaluated in 2 studies by adapting the science-based, case-by-case approach used for preclinical and early clinical safety evaluation of human biopharmaceuticals. The main objectives were to demonstrate the safety of lokivetmab in healthy laboratory Beagle dogs by using integrated clinical, morphologic, and functional evaluations. In Study 1, dogs were treated s.c. with saline or lokivetmab at 3.3 mg/kg (1X, label dose) or 10 mg/kg (3X intended dose) for 7 consecutive monthly doses, with terminal pathology and histology assessments. In Study 2, the functional immune response was demonstrated in naïve dogs using the T-cell dependent antibody response (TDAR) test with 2 different dose levels of unadjuvanted keyhole limpet hemocyanin (KLH) as the model immunogen. The primary endpoint was anti-KLH IgG antibody titer, and secondary endpoints were ex vivo IL-2 enzyme-linked immunospot (ELISpot) and peripheral blood mononuclear cell lymphoproliferation assays. Both studies included monitoring general health, periodic veterinary clinical evaluations, serial clinical pathology and toxicokinetics, and monitoring for anti-drug antibodies. In both studies, the health of dogs receiving lokivetmab was similar to controls, with no treatment-related changes uncovered. Extensive pathology evaluations of immune tissues (Study 1) revealed no lokivetmab-related morphologic changes, and in dogs treated at 10 mg/kg lokivetmab, immunization with the model antigen KLH did not impair the functional antibody or T-cell recall responses. There were no immunogenicity-related or hypersensitivity-related responses observed in either study. These studies in healthy laboratory dogs showed that lokivetmab was well-tolerated, did not produce any treatment-related effects, and had no effect on immune system morphology or its functional response. These studies also demonstrated the utility of a science-based case-by-case approach to the safety evaluation of a veterinary biopharmaceutical product.

Gex2SGen: Designing Drug-like Molecules from Desired Gene Expression Signatures

Drug-induced gene expression profiling provides a lot of useful information covering various aspects of drug discovery and development. Most importantly, this knowledge can be used to discover drugs' mechanisms of action. Recently, deep learning-based drug design methods are in the spotlight due to their ability to explore huge chemical space and design property-optimized target-specific drug molecules. Recent advances in accessibility of open-source drug-induced transcriptomic data along with the ability of deep learning algorithms to understand hidden patterns have opened opportunities for designing drug molecules based on desired gene expression signatures. In this study, we propose a deep learning model, Gex2SGen (Gene Expression 2 SMILES Generation), to generate novel drug-like molecules based on desired gene expression profiles. The model accepts desired gene expression profiles in a cell-specific manner as input and designs drug-like molecules which can elicit the required transcriptomic profile. The model was first tested against individual gene-knocked-out transcriptomic profiles, where the newly designed molecules showed high similarity with known inhibitors of the knocked-out target genes. The model was next applied on a triple negative breast cancer signature profile, where it could generate novel molecules, highly similar to known anti-breast cancer drugs. Overall, this work provides a generalized method, where the method first learned the molecular signature of a given cell due to a specific condition, and designs new small molecules with drug-like properties.

Cytogenotoxicity assessment of 3-(3,4-dihydroxyphenyl)-7,8-dihydroxycoumarin on HepG2/C3A cells and leukocytes

3-(3,4-Dihydroxyphenyl)-7,8-dihydroxycoumarin is a newly synthesized coumarin derivative with a potent antioxidant effect. The aim of the present study is to investigate the safety of this compound, determining the in vitro cytotoxic and genotoxic in human peripheral blood mononuclear cells (PBMC) and in HepG2/C3A cells. Cell viability has been investigated by the trypan blue staining test and MTT assay and the genotoxicity by the comet assay and micronucleus test, using concentrations between 0.01 and 10 μg/ml. The compound proved to be noncytotoxic in both cell lines, at all tested concentrations, protecting the cells from the DNA damage. In addition, this molecule does not show clastogenic/aneugenic effects when performing the micronucleus test with cytokinesis blockade. Based on the obtained data, and the conditions of the experiments, we can conclude that the 3-(3,4-dihydroxyphenyl)-7,8-dihydroxycoumarin is a safe molecule up to a concentration of 10 μg/ml, which encourages further studies aiming to explore its potential as a drug candidate.

Emerging Trends in Radionuclide Imaging of Infection and Inflammation in Pediatrics: Focus on FDG PET/CT and Immune Reactivity

The most common indication for ¹⁸F-FDG PET/CT is tumor imaging, which may be performed for initial diagnosis, staging, therapeutic response monitoring, surveillance, or suspected recurrence. In the routine practice of pediatric nuclear medicine, most infectious, inflammatory, and autoimmune processes that are detected on ¹⁸F-FDG PET/CT imaging - except for imaging in fever or inflammation of unknown origin - are coincidental and not the main indication for image acquisition. However, interpreting these "coincidental" findings is of utmost importance to avoid erroneously attributing these findings to a neoplastic process. We review the recent literature on fever of unknown origin as well as inflammation of unknown origin in pediatrics and then focus on the ¹⁸F FDG PET/CT imaging findings seen in two specific entities with increased immune reactivity: hemophagocytic lymphohistiocytosis syndrome and the immune-related adverse events associated with checkpoint inhibitors. We will subsequently close with two sections highlighting related topics and relevant references for further reading.

Krebs cycle enzymes for targeted therapeutics and immunotherapy for anti-leishmanial drug development using: Pathways, potential targets, and future perspectives

Leishmaniasis is a parasitic and neglected tropical disease which majorly impacts poor and developing nations. One of the significant factors that impacts the severity of the pathological condition includes the socioeconomic background of the affected region. The rise of drug-resistant Leishmania is a serious concern for the effectiveness of the present treatment. As a result, the drug options need to be relooked immediately. Leishmania employs Krebs cycle intermediates for its needs after infection for establishing various defense mechanisms to escape the host immune responses. Nevertheless, a variety of immunological reactions are also seen during infection, which clear the parasites. One of the more promising strategies in this regard would involve combining targeted therapy and immunotherapy. The targeted treatments work by obstructing vital pathways that are required for Leishmania to grow and survive. The mechanism of action of immunotherapy is the control of the host immune response, which entails the blockage of molecular pathways essential for the growth and maintenance of the parasite. The Krebs cycle intermediates have important biochemical roles. Additionally, in macrophages and dendritic cells, they play roles as signalling molecules for controlling inflammatory responses. The review brings together the available literature about the importance of Krebs cycle metabolites as potential treatment targets for leishmaniasis.

The endoplasmic reticulum participated in drug metabolic toxicity

Covalent binding of reactive metabolites formed by drug metabolic activation with biological macromolecules is considered to be an important mechanism of drug metabolic toxicity. Recent studies indicate that the endoplasmic reticulum (ER) could play an important role in drug toxicity by participating in the metabolic activation of drugs and could be a primarily attacked target by reactive metabolites. In this article, we summarize the generation and mechanism of reactive metabolites in ER stress and their associated cell death and inflammatory cascade, as well as the systematic modulation of unfolded protein response (UPR)-mediated adaptive pathways.

CoaDTI: multi-modal co-attention based framework for drug-target interaction annotation

MOTIVATION

The identification of drug-target interactions (DTIs) plays a vital role for in silico drug discovery, in which the drug is the chemical molecule, and the target is the protein residues in the binding pocket. Manual DTI annotation approaches remain reliable; however, it is notoriously laborious and time-consuming to test each drug-target pair exhaustively. Recently, the rapid growth of labelled DTI data has catalysed interests in high-throughput DTI prediction. Unfortunately, those methods highly rely on the manual features denoted by human, leading to errors.

RESULTS

Here, we developed an end-to-end deep learning framework called CoaDTI to significantly improve the efficiency and interpretability of drug target annotation. CoaDTI incorporates the Co-attention mechanism to model the interaction information from the drug modality and protein modality. In particular, CoaDTI incorporates transformer to learn the protein representations from raw amino acid sequences, and GraphSage to extract the molecule graph features from SMILES. Furthermore, we proposed to employ the transfer learning strategy to encode protein features by pre-trained transformer to address the issue of scarce labelled data. The experimental results demonstrate that CoaDTI achieves competitive performance on three public datasets compared with state-of-the-art models. In addition, the transfer learning strategy further boosts the performance to an unprecedented level. The extended study reveals that CoaDTI can identify novel DTIs such as reactions between candidate drugs and severe acute respiratory syndrome coronavirus 2-associated proteins. The visualization of co-attention scores can illustrate the interpretability of our model for mechanistic insights.

AVAILABILITY

Source code are publicly available at https://github.com/Layne-Huang/CoaDTI.

In silico Prediction and Pharmacokinetic Studies on Glucosinolates as a Potential Drug and Key Inhibitor Molecule for Lanosterol-14α- demethylase: A Fungal Membrane Biosynthesis Enzyme

BACKGROUND

Glucosinolates (β-thioglucoside-N-hydroxysulfates) are a water-soluble organic anion with sulfur- and nitrogen-containing glycosides which are found in abundance in Cruciferous plants. Ergosterol (ERG13) lanosterol-14α-demethylase protein has been targeted for inhibition studies as a key regulator enzyme of fungal membrane biosynthesis.

OBJECTIVES

To understand the molecular mechanism of inhibition of Ergosterol (ERG13) lanosterol- 14α-demethylase by various phytochemicals from brassicales, i.e., glucosinolates and their potential role as putative drug molecules.

METHODS

In this study, in silico analyses were performed to predict the molecular basis of various glucosinolates as a potential inhibitor of lanosterol-14α-demethylase protein, which is a key regulator of fungal membrane biosynthesis and its pharmacodynamics and toxicity profile. 3d structures of various glucosinolates were retrieved from PubChem, and the target protein, lanosterol-14α-demethylase (Pdb ID- 4lxj), was retrieved from the RCSB protein data bank. Molecular docking and interactions were carried out using the PyRx software using the AutoDOCK toolbar with default parameters. Dru- LiTo, ORISIS web servers were used to predict various drug likeliness predictions and Lipinski's Rule of 5, whereas admetSAR was used for prediction of toxicity, and PASS Program was used to study the antifungal and antimicrobial properties of these compounds.

RESULTS

This study shows that among the different compounds screened, gluconasturtiin, Glucotropaeolin, and Indolylmethyl-Glucosinolate showed the highest binding energies of -8.7 kcal/mol, -8.5 kcal/mol, and -8.3 kcal/mol with the lanosterol-14α-demethylase, respectively. Further all the compounds follow the Lipinski's rule as well as they are found to be non-carcinogenic and non-cytotoxic in nature. These compounds also show antifungal properties.

CONCLUSION

This study thus reveals that various glucosinolates interact with the ERG13 enzyme at various amino acid positions, which behaves as a catalytic site, thus indicates the probable mechanism of inactivation, and subsequently, these can be used as potential drug molecules. In vitro studies can be taken to further examine the utility of these compounds as antifungal agents.

Computational systems biology in disease modeling and control, review and perspectives

Omics-based approaches have become increasingly influential in identifying disease mechanisms and drug responses. Considering that diseases and drug responses are co-expressed and regulated in the relevant omics data interactions, the traditional way of grabbing omics data from single isolated layers cannot always obtain valuable inference. Also, drugs have adverse effects that may impair patients, and launching new medicines for diseases is costly. To resolve the above difficulties, systems biology is applied to predict potential molecular interactions by integrating omics data from genomic, proteomic, transcriptional, and metabolic layers. Combined with known drug reactions, the resulting models improve medicines' therapeutical performance by re-purposing the existing drugs and combining drug molecules without off-target effects. Based on the identified computational models, drug administration control laws are designed to balance toxicity and efficacy. This review introduces biomedical applications and analyses of interactions among gene, protein and drug molecules for modeling disease mechanisms and drug responses. The therapeutical performance can be improved by combining the predictive and computational models with drug administration designed by control laws. The challenges are also discussed for its clinical uses in this work.

Distribution- and Metabolism-Based Drug Discovery: A Potassium-Competitive Acid Blocker as a Proof of Concept

Conventional methods of drug design require compromise in the form of side effects to achieve sufficient efficacy because targeting drugs to specific organs remains challenging. Thus, new strategies to design organ-specific drugs that induce little toxicity are needed. Based on characteristic tissue niche-mediated drug distribution (TNMDD) and patterns of drug metabolism into specific intermediates, we propose a strategy of distribution- and metabolism-based drug design (DMBDD); through a physicochemical property-driven distribution optimization cooperated with a well-designed metabolism pathway, SH-337, a candidate potassium-competitive acid blocker (P-CAB), was designed. SH-337 showed specific distribution in the stomach in the long term and was rapidly cleared from the systemic compartment. Therefore, SH-337 exerted a comparable pharmacological effect but a 3.3-fold higher no observed adverse effect level (NOAEL) compared with FDA-approved vonoprazan. This study contributes a proof-of-concept demonstration of DMBDD and provides a new perspective for the development of highly efficient, organ-specific drugs with low toxicity.

The interactions between DNA nanostructures and cells: A critical overview from a cell biology perspective

DNA nanotechnology has yielded remarkable advances in  composite materials with diverse applications in biomedicine. The specificity and predictability of building 3D structures at the nanometer scale make DNA nanotechnology a promising tool for uses in biosensing, drug delivery, cell modulation, and bioimaging. However, for successful translation of DNA nanostructures to real-world applications, it is crucial to understand how they interact with living cells, and the consequences of such interactions. In this review, we summarize the current state of knowledge on the interactions of DNA nanostructures with cells. We identify key challenges, from a cell biology perspective, that influence progress towards the clinical translation of DNA nanostructures. We close by providing an outlook on what questions must be addressed to accelerate the clinical translation of DNA nanostructures. STATEMENT OF SIGNIFICANCE: Self-assembled DNA nanostructures (DNs) offers unique opportunities to overcome persistent challenges in the nanobiotechnology field. However, the interactions between engineered DNs and living cells are still not well defined. Critical systematization of current cellular models and biological responses triggered by DNs is a crucial foundation for the successful clinical translation of DNA nanostructures. Moreover, such an analysis will identify the pitfalls and challenges that are present in the field, and provide a basis for overcoming those challenges.

Fluorescent probes for biomolecule detection under environmental stress

The use of fluorescent probes in visible detection has been developed over the last several decades. Biomolecules are essential in the biological processes of organisms, and their distribution and concentration are largely influenced by environmental factors. Significant advances have occurred in the applications of fluorescent probes for the detection of the dynamic localization and quantity of biomolecules during various environmental stress-induced physiological and pathological processes. Herein, we summarize representative examples of small molecule-based fluorescent probes that provide bimolecular information when the organism is under environmental stress. The discussion includes strategies for the design of smart small-molecule fluorescent probes, in addition to their applications in biomolecule imaging under environmental stresses, such as hypoxia, ischemia-reperfusion, hyperthermia/hypothermia, organic/inorganic chemical exposure, oxidative/reductive stress, high glucose stimulation, and drug treatment-induced toxicity. We believe that comprehensive insight into the beneficial applications of fluorescent probes in biomolecule detection under environmental stress should enable the further development and effective application of fluorescent probes in the biochemical and biomedical fields.

Lockdown, a selective small-molecule inhibitor of the integrin phosphatase PPM1F, blocks cancer cell invasion

Phosphatase PPM1F is a regulator of cell adhesion by fine-tuning integrin activity and actin cytoskeleton structures. Elevated expression of this enzyme in human tumors is associated with high invasiveness, enhanced metastasis, and poor prognosis. Thus, PPM1F is a target for pharmacological intervention, yet inhibitors of this enzyme are lacking. Here, we use high-throughput screening to identify Lockdown, a reversible and non-competitive PPM1F inhibitor. Lockdown is selective for PPM1F, because this compound does not inhibit other protein phosphatases in vitro and does not induce additional phenotypes in PPM1F knockout cells. Importantly, Lockdown-treated glioblastoma cells fully re-capitulate the phenotype of PPM1F-deficient cells as assessed by increased phosphorylation of PPM1F substrates and corruption of integrin-dependent cellular processes. Ester modification yields Lockdown^Pro with increased membrane permeability and prodrug-like properties. Lockdown^Pro suppresses tissue invasion by PPM1F-overexpressing human cancer cells, validating PPM1F as a therapeutic target and providing an access point to control tumor cell dissemination.

Hepatic Models in Precision Medicine: An African Perspective on Pharmacovigilance

Pharmaceuticals are indispensable to healthcare as the burgeoning global population is challenged by diseases. The African continent harbors unparalleled genetic diversity, yet remains largely underrepresented in pharmaceutical research and development, which has serious implications for pharmaceuticals approved for use within the African population. Adverse drug reactions (ADRs) are often underpinned by unique variations in genes encoding the enzymes responsible for their uptake, metabolism, and clearance. As an example, individuals of African descent (14–34%) harbor an exclusive genetic variant in the gene encoding a liver metabolizing enzyme (CYP2D6) which reduces the efficacy of the breast cancer chemotherapeutic Tamoxifen. However, CYP2D6 genotyping is not required prior to dispensing Tamoxifen in sub-Saharan Africa. Pharmacogenomics is fundamental to precision medicine and the absence of its implementation suggests that Africa has, to date, been largely excluded from the global narrative around stratified healthcare. Models which could address this need, include primary human hepatocytes, immortalized hepatic cell lines, and induced pluripotent stem cell (iPSC) derived hepatocyte-like cells. Of these, iPSCs, are promising as a functional in vitro model for the empirical evaluation of drug metabolism. The scale with which pharmaceutically relevant African genetic variants can be stratified, the expediency with which these platforms can be established, and their subsequent sustainability suggest that they will have an important role to play in the democratization of stratified healthcare in Africa. Here we discuss the requirement for African hepatic models, and their implications for the future of pharmacovigilance on the African continent.

Application of Micro-Engineered Kidney, Liver, and Respiratory System Models to Accelerate Preclinical Drug Testing and Development

Developing novel drug formulations and progressing them to the clinical environment relies on preclinical in vitro studies and animal tests to evaluate efficacy and toxicity. However, these current techniques have failed to accurately predict the clinical success of new therapies with a high degree of certainty. The main reason for this failure is that conventional in vitro tissue models lack numerous physiological characteristics of human organs, such as biomechanical forces and biofluid flow. Moreover, animal models often fail to recapitulate the physiology, anatomy, and mechanisms of disease development in human. These shortfalls often lead to failure in drug development, with substantial time and money spent. To tackle this issue, organ-on-chip technology offers realistic in vitro human organ models that mimic the physiology of tissues, including biomechanical forces, stress, strain, cellular heterogeneity, and the interaction between multiple tissues and their simultaneous responses to a therapy. For the latter, complex networks of multiple-organ models are constructed together, known as multiple-organs-on-chip. Numerous studies have demonstrated successful application of organ-on-chips for drug testing, with results comparable to clinical outcomes. This review will summarize and critically evaluate these studies, with a focus on kidney, liver, and respiratory system-on-chip models, and will discuss their progress in their application as a preclinical drug-testing platform to determine in vitro drug toxicology, metabolism, and transport. Further, the advances in the design of these models for improving preclinical drug testing as well as the opportunities for future work will be discussed.

Genetically encoding latent bioreactive amino acids and the development of covalent protein drugs

As natural proteins generally do not bind targets in a covalent mode, the therapeutic potential of covalent protein drugs remains largely unexplored. Recently, latent bioreactive amino acids have been incorporated into proteins through genetic code expansion, which selectively react with nearby natural residues via proximity-enabled reactivity, generating diverse covalent linkages for proteins in vitro and in cells. These new covalent linkages provide novel avenues for protein research and engineering. In addition, a general platform technology, proximity-enabled reactive therapeutics (PERx), has been established for the development of covalent protein drugs. The first covalent protein drug demonstrates advantageous features in cancer immunotherapy in mice. Selective introduction of covalent bonds into proteins will advance biological studies, synthetic biology, and biotherapeutics with the power of biocompatible covalent chemistries.

Electrochemical Simulation of the Oxidative Capsaicin Metabolism

Capsaicin, primarily known as the pungent ingredient in hot peppers, is rapidly metabolized in the human body by enzymatic processes altering the pharmacological as well as toxicological properties. Herein, the oxidative transformation of capsaicin was investigated in vitro with electrochemistry as well as human liver microsomal incubations. The reaction mixtures were analyzed with liquid chromatography-mass spectrometry. Structure elucidation involved accurate mass measurements and multistage tandem mass spectrometry experiments. In total, 126 transformation products were detected. Electrochemistry provided evidence for 101 transformation products and the microsomal incubations for 46 species. 21 compounds were observed with both approaches. Identified oxidative pathways likely occurring during the phase I metabolism included dehydrogenation, O-demethylation, and hydroxylation reactions as well as combinations thereof. Furthermore, trapping of reactive intermediates either with glutathione or with electrochemically activated ribonucleosides provided evidence for the possible production of phase II metabolites and covalent adducts with a genetic material. Evidence for the occurrence of some capsaicin metabolites in humans was obtained by urine screening.

Therapeutic Targeting of Nrf2 Signaling by Maggot Extracts Ameliorates Inflammation-Associated Intestinal Fibrosis in Chronic DSS-Induced Colitis

Intestinal fibrosis is induced by excessive myofibroblast proliferation and collagen deposition, which has been regarded as a general pathological feature in inflammatory bowel disease (IBD). Therefore, identifying clinical markers and targets to treat and prevent intestinal fibrosis is urgently needed. The traditional Chinese medicine maggot, commonly known as “wu gu chong”, has been shown to reduce oxidative stress and alleviate inflammation in chronic colitis. This study investigated the mechanisms underlying the effects of maggot extract (ME) on inflammation-associated intestinal fibrosis in TGF-β1-stimulated human intestinal fibroblasts (CCD-18Co cells) and dextran sodium sulphate (DSS)-induced chronic colitis murine model. To assess the severity of inflammation and fibrosis, histological and macroscopic evaluation were carried out. The results showed that ME was a significant inhibitor of body weight loss and colon length shortening in mice with chronic colitis. In addition, ME suppressed the intestinal fibrosis by downregulating TGF-β1/SMADs pathway via upregulation of Nrf2 expression at both protein and mRNA levels. ME markedly increased the expression of Nrf2, thus resulting in a higher level of HO-1. After treatment with Nrf2 inhibitor (ML385) or siRNA-Nrf2 for deactivating Nrf2 pathway, the protective effects of ME were abolished both in vitro and in vivo. Moreover, the histopathological results for the major organs of DSS mice treated with ME showed no signs of clinically important abnormalities. Treatment with ME had no effect on the viability of CCD-18Co cells, suggesting its low in vitro cytotoxicity. Furthermore, ME could mediate intestine health by keeping the balance of the gut microbes through the enhancement of beneficial microbes and suppression of pathogenic microbes. In conclusion, this is the first ever report demonstrating that ME ameliorates inflammation-associated intestinal fibrosis by suppressing TGF-β1/SMAD pathway via upregulation of Nrf2 expression. Our findings highlight the potential of Nrf2 as an effective therapeutic target for alleviating intestinal fibrosis.

Bioactivation of Isoxazole-Containing Bromodomain and Extra-Terminal Domain (BET) Inhibitors

The 3,5-dimethylisoxazole motif has become a useful and popular acetyl-lysine mimic employed in isoxazole-containing bromodomain and extra-terminal (BET) inhibitors but may introduce the potential for bioactivations into toxic reactive metabolites. As a test, we coupled deep neural models for quinone formation, metabolite structures, and biomolecule reactivity to predict bioactivation pathways for 32 BET inhibitors and validate the bioactivation of select inhibitors experimentally. Based on model predictions, inhibitors were more likely to undergo bioactivation than reported non-bioactivated molecules containing isoxazoles. The model outputs varied with substituents indicating the ability to scale their impact on bioactivation. We selected OXFBD02, OXFBD04, and I-BET151 for more in-depth analysis. OXFBD’s bioactivations were evenly split between traditional quinones and novel extended quinone-methides involving the isoxazole yet strongly favored the latter quinones. Subsequent experimental studies confirmed the formation of both types of quinones for OXFBD molecules, yet traditional quinones were the dominant reactive metabolites. Modeled I-BET151 bioactivations led to extended quinone-methides, which were not verified experimentally. The differences in observed and predicted bioactivations reflected the need to improve overall bioactivation scaling. Nevertheless, our coupled modeling approach predicted BET inhibitor bioactivations including novel extended quinone methides, and we experimentally verified those pathways highlighting potential concerns for toxicity in the development of these new drug leads.

Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interaction

Motivation

Characterizing drug–protein interactions (DPIs) is crucial to the high-throughput screening for drug discovery. The deep learning-based approaches have attracted attention because they can predict DPIs without human trial and error. However, because data labeling requires significant resources, the available protein data size is relatively small, which consequently decreases model performance. Here, we propose two methods to construct a deep learning framework that exhibits superior performance with a small labeled dataset.

Results

At first, we use transfer learning in encoding protein sequences with a pretrained model, which trains general sequence representations in an unsupervised manner. Second, we use a Bayesian neural network to make a robust model by estimating the data uncertainty. Our resulting model performs better than the previous baselines at predicting interactions between molecules and proteins. We also show that the quantified uncertainty from the Bayesian inference is related to confidence and can be used for screening DPI data points.

Availability and implementation

The code is available at https://github.com/QHwan/PretrainDPI.

Supplementary information

Supplementary data are available at Bioinformatics online.

Cold-Start Problems in Data-Driven Prediction of Drug-Drug Interaction Effects

Combining drugs, a phenomenon often referred to as polypharmacy, can induce additional adverse effects. The identification of adverse combinations is a key task in pharmacovigilance. In this context, in silico approaches based on machine learning are promising as they can learn from a limited number of combinations to predict for all. In this work, we identify various subtasks in predicting effects caused by drug–drug interaction. Predicting drug–drug interaction effects for drugs that already exist is very different from predicting outcomes for newly developed drugs, commonly called a cold-start problem. We propose suitable validation schemes for the different subtasks that emerge. These validation schemes are critical to correctly assess the performance. We develop a new model that obtains AUC-ROC =0.843 for the hardest cold-start task up to AUC-ROC =0.957 for the easiest one on the benchmark dataset of Zitnik et al. Finally, we illustrate how our predictions can be used to improve post-market surveillance systems or detect drug–drug interaction effects earlier during drug development.

An intramolecular photoswitch can significantly promote photoactivation of Pt(iv) prodrugs

Selective activation of prodrugs at diseased tissue through bioorthogonal catalysis represents an attractive strategy for precision cancer treatment. Achieving efficient prodrug photoactivation in cancer cells, however, remains challenging. Herein, we report two Pt(iv) complexes, designated as rhodaplatins {rhodaplatin 1, [Pt(CBDCA-O,O)(NH3)2(RhB)OH]; rhodaplatin 2, [Pt(DACH)ox(RhB)(OH)], where CBDCA is cyclobutane-1,1-dicarboxylate, RhB is rhodamine B, DACH is (1R,2R)-1,2-diaminocyclohexane, and ox is oxalate}, that bear an internal photoswitch to realize efficient accumulation, significant co-localization, and subsequent effective photoactivation in cancer cells. Compared with the conventional platform of external photocatalyst plus substrate, rhodaplatins presented up to 4.8 104-fold increased photoconversion efficiency in converting inert Pt(iv) prodrugs to active Pt(ii) species under physiological conditions, due to the increased proximity and covalent bond between the photoswitch and Pt(iv) substrate. As a result, rhodaplatins displayed increased photocytotoxicity compared with a mixture of RhB and conventional Pt(iv) compound in cancer cells including Pt-resistant ones. Intriguingly, rhodaplatin 2 efficiently accumulated in the mitochondria and induced apoptosis without causing genomic DNA damage to overcome drug resistance. This work presents a new approach to develop highly effective prodrugs containing intramolecular photoswitches for potential medical applications.

Identifying Novel Drug Targets by iDTPnd: A Case Study of Kinase Inhibitors

Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. Here, we develop iDTPnd (integrated Drug Target Predictor with negative dataset), a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding sites. To facilitate assessment of unintended targets, iDTPnd also provides a docking-based interaction score and its statistical significance. We confirm the interactions of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity of 52% and a specificity of 55%. We also validate 10 predicted novel targets by using in vitro experiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450, and MHC class I molecules, can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein–small molecule interactions, when sufficient drug–target 3D data are available. The code for constructing the structural signatures is available at https://sfb.kaust.edu.sa/Documents/iDTP.zip.

Computational study of zebrafish immune-targeted microarray data for prediction of preventive drug candidates

Viral hemorrhagic septicemia virus (VHSV) is a rhabdovirus reported to cause economic loss in fish farms. Because of the lack of adequate preventative treatments, the identification of multipath genes involved in VHS infection might be an alternative to explore the possibility of using drugs for the seasonal prevention of this fish disease. We propose labeling a category of drug molecules by further classification and interpretation of the Drug Gene Interaction Database using gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment scores. The study investigated disease networks of up-and down-regulated genes to find those with high interaction as substantial genes in pathways among the different disease networks. We prioritized these genes based on their relationship to those associated with VHS infection in the context of human protein-protein interaction networks and disease pathways. Among the 29 genes as potential drug targets, nine were selected as promising druggable genes (ERBB2, FGFR3, ITGA2B, MAP2K1, NGF, NTRK1, PDGFRA, SCN2B, and SERPINC1). PDGFRA is the most important druggable up-and down-regulated gene and is considered an important gene in the IMATINIB pathway. This study findings indicate a promising approach for drug target prediction for VHS treatment, which might be useful for disease therapeutics.

Allicin, the Odor of Freshly Crushed Garlic: A Review of Recent Progress in Understanding Allicin's Effects on Cells

The volatile organic sulfur compound allicin (diallyl thiosulfinate) is produced as a defense substance when garlic (Allium sativum) tissues are damaged, for example by the activities of pathogens or pests. Allicin gives crushed garlic its characteristic odor, is membrane permeable and readily taken up by exposed cells. It is a reactive thiol-trapping sulfur compound that S-thioallylates accessible cysteine residues in proteins and low molecular weight thiols including the cellular redox buffer glutathione (GSH) in eukaryotes and Gram-negative bacteria, as well as bacillithiol (BSH) in Gram-positive firmicutes. Allicin shows dose-dependent antimicrobial activity. At higher doses in eukaryotes allicin can induce apoptosis or necrosis, whereas lower, biocompatible amounts can modulate the activity of redox-sensitive proteins and affect cellular signaling. This review summarizes our current knowledge of how bacterial and eukaryotic cells are specifically affected by, and respond to, allicin.

Covalent inhibitors of GAPDH: From unspecific warheads to selective compounds

Targeting glycolysis is an attractive approach for the treatment of a wide range of pathologies, such as various tumors and parasitic infections. Due to its pivotal role in the glycolysis, Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) represents a rate-limiting enzyme in those cells that mostly, or exclusively rely on this pathway for energy production. In this context, GAPDH inhibition can be a valuable approach for the development of anticancer and antiparasitic drugs. In addition to its glycolytic role, GAPDH possesses several moonlight functions, whose deregulation is involved in some pathological conditions. Covalent modification on different amino acids of GAPDH, in particular on cysteine residues, can lead to a modulation of the enzyme activity. The selectivity towards specific cysteine residues is essential to achieve a specific phenotypic effect. In this work we report an extensive overview of the latest advances on the numerous compounds able to inhibit GAPDH through the covalent binding to cysteine residues, ranging from endogenous metabolites and xenobiotics, which may serve as pharmacological tools to actual drug-like compounds with promising therapeutic perspectives. Furthermore, we focused on the potentialities of the different warheads, shedding light on the possibility to exploit a combination of a finely tuned electrophilic group with a well-designed recognition moiety. These findings can provide useful information for the rational design of novel covalent inhibitors of GAPDH, with the final goal to expand the current treatment options.

Neonatal and Juvenile Ocular Development in Göttingen Minipigs and Domestic Pigs: A Histomorphological and Immunohistochemical Study

Pigs are considered one of the relevant animal models for ocular research as they share several histological and anatomical similarities with the human eye. With the increasing interest in juvenile animal models, this study aimed to describe the postnatal development of ocular structures in 16 Göttingen minipigs and 25 F2 domestic pigs, between birth and 6 months of age, using histopathology and immunohistochemistry against Ki-67, caspase-3, calbindin, glial fibrillary acidic protein, rhodopsin, and synaptophysin. All ocular structures in both pig breeds were incompletely developed at birth and for variable periods postnatally. Noteworthy histological features of immaturity included vascularization in the corneal stroma in neonatal Göttingen minipigs, increased cellularity in different substructures, remnants of the hyaloid vasculature, short and poorly ramified ciliary body processes, and a poorly developed cone inner segment. Increased cellular proliferation, highlighted by abundant Ki-67 immunolabeling, was observed in almost all developing structures of the pig eye for variable periods postnatally. Apoptosis, highlighted with caspase-3 immunolabeling, was observed in the retinal inner nuclear layer at birth and in the regressing hyaloid vasculature remnants. Immunohistochemistry against rhodopsin, synaptophysin, and calbindin demonstrated the short size of the developing photoreceptors and the immature cone inner segment morphology. Calbindin labeling revealed significant differences in the amount of positively labeled cone nuclei between the retinal area centralis and the non-area centralis regions. The elongation of Müller cell processes in the developing retina was shown with glial fibrillary acidic protein. In both pig breeds, the eyes reached histomorphological and immunohistochemical maturity at 6 months of age.

A two-photon excited near-infrared fluorescent probe for imaging peroxynitrite during drug-induced hepatotoxicity and its remediation

Drug-induced liver injury (DILI) has been a hot issue of public health, owing to its unpredictability and serious harm to public health. Peroxynitrite (ONOO^-) is an important biomarker for the assessment and diagnosis of DILI. In this article, based on a kind of rhodamine analogue with a near-infrared (NIR) emission (610 nm-800 nm) and a two-photon absorption cross section (54 GM), a two-photon excited NIR fluorescence probe (NIR-ONOO) for ONOO^- was developed. With a high selectivity and a high sensitivity to ONOO^-, NIR-ONOO has a linear range for detection of ONOO^- from 5.0 × 10^-8 to 1.0 × 10^-5 M, a good detection limit (15 nM) and a large fluorescence enhancement (340-fold). In addition, NIR-ONOO has been used to monitor ONOO^- in cells with satisfactory results. Because of its two-photon excied NIR emission, NIR-ONOO also showed excellent performances for imaging ONOO^- including low autofluorescence, stable and persistent fluorescence, and a deep penetration (204 μm). Finally, NIR-ONOO was successfully employed to image ONOO^- in inflammatory mouse, drug-induced hepatotoxicity in cells and its remediation. All the results indicated that NIR-ONOO is a powerful chemical tool to image ONOO^- and assay drug-induced hepatotoxicity.

A Review of the Mechanisms and Clinical Implications of Precision Cancer Therapy-Related Toxicity: A Primer for the Radiologist

OBJECTIVE. The purpose of this review is to elucidate the mechanisms, types, and clinical significance of molecular targeted therapy (MTT) and immune checkpoint inhibitors (ICIs) and their related toxicity, emphasizing the radiologic manifestations. CONCLUSION. The related toxicities of MTT and ICIs can have acute, recurrent, chronic, and delayed presentations. These toxicities may serve as markers of response and survival. By understanding the clinical significance of drug toxicities, radiologists can play an important role in personalized cancer therapy.

In silico identification of potential inhibitors from Cinnamon against main protease and spike glycoprotein of SARS CoV-2

Cinnamon has been utilized to remedy a lot of afflictions of humans. Literary works illustrate that it possesses numerous biological activities. Our research study is intended to recognize the phyto-derived antiviral substances from Cinnamon against COVID-19 main protease enzyme and to understand the in silico molecular basis of its activity. In the present study, 48 isolates compounds from Cinnamon retrieved from the PubMed database, are subjected to docking analysis. Docking study was performed using Autodock vina and PyRx software. Afterwards, admetSAR, as well as DruLiTo servers, were used to investigate drug-likeness prophecy. Our study shows that the nine phytochemicals of Cinnamon are very likely against the main protease enzyme of COVID-19. Further MD simulations could identify Tenufolin (TEN) and Pavetannin C1 (PAV) as hit compounds. Utilizing contemporary strategies, these phyto-compounds from a natural origin might establish a reliable medication or support lead identification. Identified hit compounds can be further taken for in vitro and in vivo studies to examine their effectiveness versus COVID-19.

Cytochrome P450s regulates aloperine-induced pathological changes in mouse liver and kidney

Aloperine is a major active component in Sophora alopecuroides L that plays diverse pharmacological properties. Recent studies have indicated the potential effect of aloperine against hypertension and cancers. However, possible toxicity of aloperine has not been carefully studied in vivo. The aim of this study was to assess the effect of intraperitoneal aloperine injection on mouse liver and kidney tissues and to investigate the role of CYP450 genes in aloperine-induced toxicity. 72 BALB/c mice were randomly divided into four groups: vehicle control group (normal saline), low-dose group (4 mg/kg), medium-dose group (8 mg/kg), and high-dose group (16 mg/kg). 18 mice in each group were intraperitoneally injected with aloperine daily for 4 weeks, and were then kept for another 1 or 4 weeks without aloperine treatment. Serum was colleted for analysis of serum biochemical indexes including ALT, AST, BUN and CRE. The liver and kidney were collected for analysis of histopathologic changes and CYP450 expression and activity. Vacuolization of cytoplasm in liver cells, swelling in kidney tubular cells, increased levels of ALT, AST, BUN, and CRE, and alteration in the expression and activity of CYP450 were observed in the high-dose group after 4 weeks of treatment. However, all aloperine-induced damages were recovered to a certain degree after maintained without aloperine for 1 week, and fully recovered after maintained without aloperine for 4 weeks. These findings suggested that aloperine regulated the expression of CYP450, which was possibly involved in aloperine-induced reversible toxicity in mouse liver and kidney tissues.

A review of the imaging manifestations of immune check point inhibitor toxicities

The past decade has witnessed a paradigm shift in cancer therapy owing to the introduction of immune checkpoint inhibitors (ICIs) and it is now commonplace for radiologists to image patients on therapy with these agents. The purpose of this review is to detail the mechanism, radiological manifestations and clinical significance of ICI related toxicities, according to the organ system involved. ICI related toxicities that have known imaging manifestations include colitis, enterocolitis, pancreatitis, hepatitis, endocrine toxicities, pneumonitis, cardiovascular toxicity and musculoskeletal toxicity. These toxicities may be acute, recurrent or chronic in nature. Radiologists must be aware of the imaging features and clinical significance of these toxicities in order to effectively participate in personalized cancer therapy.

A Photocaged, Water-Oxidizing, and Nucleolus-Targeted Pt(IV) Complex with a Distinct Anticancer Mechanism

Targeted anticancer prodrugs that can be controllably activated are highly desired for personalized precision medicine in cancer therapy. Such prodrugs with unique action modes are also promising to overcome drug resistance. Herein, we report coumaplatin, an oxaliplatin-based and photocaged Pt(IV) prodrug, to realize nuclear accumulation along with "on-demand" activation. This prodrug is based on a Pt(IV) complex that can be efficiently photoactivated via water oxidation without the requirement of a reducing agent. Coumaplatin accumulates very efficiently in the nucleoli, and upon photoactivation, this prodrug exhibits a level of photocytotoxicity up to 2 orders of magnitude higher than that of oxaliplatin. Unexpectedly, this prodrug presents strikingly enhanced tumor penetration ability and utilizes a distinct action mode to overcome drug resistance; i.e., coumaplatin but not oxaliplatin induces cell senescence, p53-independent cell death, and immunogenic cell death along with T cell activation. Our findings not only provide a novel strategy for the rational design of controllably activated and nucleolus-targeted Pt(IV) anticancer prodrugs but also demonstrate that accumulating conventional platinum drugs to the nucleus is a practical way to change its canonical mechanism of action and to achieve reduced resistance.

Organ-Specific Screening for Protein Damage Using Magnetic Bead Bioreactors and LC-MS/MS

A new 96-well plate methodology for fast, enzyme-multiplexed screening for metabolite-protein adducts was developed. Magnetic beads coated with metabolic enzymes were used to make potentially reactive metabolites that can react with test protein in the wells, followed by sample workup in multiple 96-well filter plates for LC-MS/MS analysis. Incorporation of human microsomes from multiple organs and selected supersomes of single cytochrome P450 (cyt P450) enzymes on the magnetic beads provided a broad spectrum of metabolic enzymes. The reacted protein was then isolated, denatured, reduced, alkylated, and digested, and peptides were collected in a sequence of 96-well filter plates for analysis. Method performance was evaluated by trapping acetaminophen reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI) with human glutathione S-transferase pi (hGSTP), human serum albumin (HSA), and bovine serum albumin (BSA) as model target proteins. Relative amounts of acetaminophen metabolite and hGSTP adducts were compared with 10 different cyt P450 enzymes. Human liver microsomes and CYP1A2 supersomes showed the highest bioactivation rate for adduct formation, in which all four cysteines of hGSTP reacted with NAPQI. Eight cysteines of HSA and four cysteines of BSA have been detected to react with NAPQI. This method has the potential for fast multienzyme protein adduct screening with high efficiency and accuracy.

A Dual-Emissive Phosphorescent Polymeric Probe for Exploring Drug-Induced Liver Injury via Imaging of Peroxynitrite Elevation In Vivo

Drug-induced liver injury (DILI) is a widespread clinical problem. The pathophysiological mechanisms of DILI are complicated, and the traditional diagnostic methods for DILI have their limitations. Owing to its convenient operation, high sensitivity, and high specificity, luminescent sensing and imaging as an indispensable tool in biological research and clinical trials may provide an important means for DILI study. Herein, we report the rational design and preparation of a near-infrared dual-phosphorescent polymeric probe (P-ONOO) for exploring the DILI via specific imaging of peroxynitrite (ONOO^-) elevation in vivo, which was one of early markers of DILI and very difficult to be detected due to its short half-life and high reactive activity. With the utilization of P-ONOO, the raised ONOO^- was visualized successfully in the drug-treated hepatocytes with a high signal-to-noise ratio via ratiometric and time-resolved photoluminescence imaging. Importantly, the ONOO^- boost in the acetaminophen-induced liver injury in real time was verified, and the direct observation of the elevated ONOO^- production in ketoconazole-induced liver injury was achieved for the first time. Our findings may contribute to understanding the exact mechanism of ketoconazole-induced hepatotoxicity that is still ambiguous. Notably, this luminescent approach for revealing the liver injury works fast and conveniently.

Polymeric Core-Shell Nanoparticles Prepared by Spontaneous Emulsification Solvent Evaporation and Functionalized by the Layer-by-Layer Method

The aim of our study was to develop a novel method for the preparation of polymeric core-shell nanoparticles loaded with various actives for biomedical applications. Poly(caprolactone) (PCL), poly(lactic acid) (PLA) and poly(lactide-co-glycolide) (PLGA) nanoparticles were prepared using the spontaneous emulsification solvent evaporation (SESE) method. The model active substance, Coumarin-6, was encapsulated into formed polymeric nanoparticles, then they were modified/functionalized by multilayer shells' formation. Three types of multilayered shells were formed: two types of polyelectrolyte shell composed of biocompatible and biodegradable polyelectrolytes poly-L-lysine hydrobromide (PLL), fluorescently-labeled poly-L-lysine (PLL-ROD), poly-L-glutamic acid sodium salt (PGA) and pegylated-PGA (PGA-g-PEG), and hybrid shell composed of PLL, PGA, and SPIONs (superparamagnetic iron oxide nanoparticles) were used. Multilayer shells were constructed by the saturation technique of the layer-by-layer (LbL) method. Properties of our polymeric core-shell nanoparticle were optimized for bioimaging, passive and magnetic targeting.

New role for crinamine as a potent, safe and selective inhibitor of human monoamine oxidase B: In vitro and in silico pharmacology and modeling

ETHNOPHARMACOLOGICAL RELEVANCE

The development of selective inhibitors of monoamine oxidase B (MAO-B) has been essential in treating Parkinson's disease. However, the apparent hepatotoxicity and drug-drug interactions of current inhibitors accentuate the need for the development of novel pharmacotherapies. Crossyne guttata (L.) D. & U. Müll-Doblies is used frequently by Rastafarian bush doctors to treat alcoholism, a disorder which is also accentuated by MAO.

OBJECTIVE

The study sought to isolate, identify and characterise the biologically active constituents of C. guttata based on their ability to inhibit the MAO enzymes.

MATERIALS AND METHODS

Column chromatography was used to isolate the biologically active alkaloids of C. guttata. The ability of the alkaloids to inhibit the biotransformation of 4-aminoantipyrine by the MAO enzymes was evaluated in vitro. In silico docking was conducted using AutoDock Vina server while the pharmacokinetic properties of the compounds were evaluated using SwissADME.

RESULTS

Chromatographic separation of an ethanolic fraction of C. guttata yielded the alkaloids crinamine 1 and epibuphanisine 2. 1 and 2 along with structurally related alkaloids haemanthamine 3 and haemanthidine 4 were evaluated for their ability to inhibit the action of isozymes of MAO in vitro. Alkaloids effected submicromolar IC₅₀ values against MAO-B, the most potent of which being crinamine 1 (0.014 μM) > haemanthidine 4 (0.017 μM) > epibuphanisine 2 (0.039 μM) > haemanthamine 3 (0.112 μM). Binding energies of the alkaloids correlated well with their inhibitory potential with crinamine displaying the best binding efficacy and binding energy score with MAO-B.

DISCUSSION AND CONCLUSION

Crinamine and epibuphanisine exhibited potent and selective inhibitory activity towards MAO-B. After comprehensive in silico investigations encompassing robust molecular docking analysis, the drug-like attributes and safety of the alkaloids suggest the crinamine is a potentially safe drug for human application.