Overview of experimental models of the blood-brain barrier in CNS drug discovery

Exposure to metam sodium-based pesticide impaired cognitive performances in adult mice: Involvement of oxidative damage and glial activation

Cognitive integrity is a critical aspect of neurological function, and a decline in cognitive function is a hallmark of neurotoxicity. Oxidative stress is a significant pathological feature contributing to cognitive deficits that can arise from exposure to environmental pollutants such as pesticides. Among these, Metam sodium-based pesticides (MS-BP) are an emergent type of pesticide widely used in the agriculture and public health sectors for controlling pests and diseases. Our prior research has shown that animals exposed to MS-BP during the early stages of brain development caused cognitive impairments. In the present study, we tested whether exposure to this compound in a fully matured brain would affect cognitive performance and induce oxidative damage to the central nervous system. In this context, adult mice received chronic treatment with increasing doses of MS-BP and subjected to a set of behavioral paradigms. Following behavioral assessment, oxidative stress and glial activation were evaluated. Our main findings showed that MS-BP chronic exposure impaired recognition and short- and long-term memory. These alterations were accompanied by increased superoxide dismutase activity and malondialdehyde level and a marked decrease in catalase activity in specific brain areas. Moreover, exposure to MS-BP is associated with a significant rise in the density of astrocytic and microglial markers, indicating a possible glial cell response within the prefrontal cortex and hippocampus. The present work demonstrated that MS-BP altered cognitive performance likely through oxidative damage to the brain.

The influence of verapamil on the pharmacokinetics of the pan-HER tyrosine kinase inhibitor neratinib in rats: the role of P-glycoprotein-mediated efflux

Neratinib, an irreversible pan-HER tyrosine kinase inhibitor, has been approved for the treatment of HER2-positive (HER2⁺) early-stage and brain metastatic breast cancer. Thus far, the pharmacology effects and pharmacodynamics of neratinib have been well studied. However, the disposition of neratinib and its influencing factors in vivo remain unclear. P-glycoprotein (P-gp), one of the most extensively studied transporters, substantially restricts penetration of drugs into the body or deeper compartments (i.e., blood-brain barrier, BBB), regarding drug resistance and drug-drug interactions. Thereby, the aim of this study was to investigate the influence of verapamil (a P-gp inhibitor) on the pharmacokinetics of neratinib in rats. Here, we have established a high specific, selective and sensitive ultra-performance liquid chromatography-tandem mass spectrometric (UPLC-MS/MS) method to quantify plasma concentrations of neratinib in rats. Pharmacokinetic results showed that verapamil significantly increased the system exposure of neratinib, as C_max increased by 2.09-fold and AUC_0-t increased by 1.64-fold, respectively. Additionally, the in vitro transport of neratinib was evaluated using Madin-Darby canine kidney II (MDCK II) and human MDR1 gene overexpressed MDCK (MDCK-MDR1) cell line models. As a result, the net flux ratio was over than 2 and decreased over 50% by verapamil, suggesting that neratinib was a substrate of P-gp. Hence, our findings have highlighted the important role of P-gp in the system exposure of neratinib in vivo, and drug-drug interaction should be considered when coadministration of P-gp inhibitors with neratinib. These findings may support the further clinical development and application of neratinib.

Relational graph convolutional networks for predicting blood-brain barrier penetration of drug molecules

MOTIVATION

Evaluating the blood-brain barrier (BBB) permeability of drug molecules is a critical step in brain drug development. Traditional methods for the evaluation require complicated in vitro or in vivo testing. Alternatively, in silico predictions based on machine learning have proved to be a cost-efficient way to complement the in vitro and in vivo methods. However, the performance of the established models has been limited by their incapability of dealing with the interactions between drugs and proteins, which play an important role in the mechanism behind the BBB penetrating behaviors. To address this limitation, we employed the relational graph convolutional network (RGCN) to handle the drug-protein interactions as well as the properties of each individual drug.

RESULTS

The RGCN model achieved an overall accuracy of 0.872, an area under the receiver operating characteristic (AUROC) of 0.919 and an area under the precision-recall curve (AUPRC) of 0.838 for the testing dataset with the drug-protein interactions and the Mordred descriptors as the input. Introducing drug-drug similarity to connect structurally similar drugs in the data graph further improved the testing results, giving an overall accuracy of 0.876, an AUROC of 0.926 and an AUPRC of 0.865. In particular, the RGCN model was found to greatly outperform the LightGBM base model when evaluated with the drugs whose BBB penetration was dependent on drug-protein interactions. Our model is expected to provide high-confidence predictions of BBB permeability for drug prioritization in the experimental screening of BBB-penetrating drugs.

AVAILABILITY AND IMPLEMENTATION

The data and the codes are freely available at https://github.com/dingyan20/BBB-Penetration-Prediction.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cholinergic blockade of neuroinflammation – from tissue to RNA regulators

Inflammatory stimuli and consequent pro-inflammatory immune responses may facilitate neurodegeneration and threaten survival following pathogen infection or trauma, but potential controllers preventing these risks are incompletely understood. Here, we argue that small RNA regulators of acetylcholine (ACh) signaling, including microRNAs (miRs) and transfer RNA fragments (tRFs) may tilt the balance between innate and adaptive immunity, avoid chronic inflammation and prevent the neuroinflammation-mediated exacerbation of many neurological diseases. While the restrictive permeability of the blood–brain barrier (BBB) protects the brain from peripheral immune events, this barrier can be disrupted by inflammation and is weakened with age. The consequently dysregulated balance between pro- and anti-inflammatory processes may modify the immune activities of brain microglia, astrocytes, perivascular macrophages, oligodendrocytes and dendritic cells, leading to neuronal damage. Notably, the vagus nerve mediates the peripheral cholinergic anti-inflammatory reflex and underlines the consistent control of body–brain inflammation by pro-inflammatory cytokines, which affect cholinergic functions; therefore, the disruption of this reflex can exacerbate cognitive impairments such as attention deficits and delirium. RNA regulators can contribute to re-balancing the cholinergic network and avoiding its chronic deterioration, and their activities may differ between men and women and/or wear off with age. This can lead to hypersensitivity of aged patients to inflammation and higher risks of neuroinflammation-driven cholinergic impairments such as delirium and dementia following COVID-19 infection. The age- and sex-driven differences in post-transcriptional RNA regulators of cholinergic elements may hence indicate new personalized therapeutic options for neuroinflammatory diseases.

Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds

Permeation through the blood–brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence number of various substructures, as well as the artificial neural network approach and the double cross-validation procedure, we have developed a predictive in silico LogBB model based on an extensive and verified dataset (529 compounds), which is applicable to diverse drugs and drug-like compounds. The model has good predictivity parameters (Q2=0.815, RMSEcv=0.318) that are similar to or better than those of the most reliable models available in the literature. Larger datasets, and perhaps more sophisticated network architectures, are required to realize the full potential of deep neural networks. The analysis of fragment contributions reveals patterns of influence consistent with the known concepts of structural characteristics that affect the BBB permeability of organic compounds. The external validation of the model confirms good agreement between the predicted and experimental LogBB values for most of the compounds. The model enables the evaluation and optimization of the BBB permeability of potential neuroactive agents and other drug compounds.

ABC Transporters at the Blood-Brain Interfaces, Their Study Models, and Drug Delivery Implications in Gliomas

Drug delivery into the brain is regulated by the blood-brain interfaces. The blood-brain barrier (BBB), the blood-cerebrospinal fluid barrier (BCSFB), and the blood-arachnoid barrier (BAB) regulate the exchange of substances between the blood and brain parenchyma. These selective barriers present a high impermeability to most substances, with the selective transport of nutrients and transporters preventing the entry and accumulation of possibly toxic molecules, comprising many therapeutic drugs. Transporters of the ATP-binding cassette (ABC) superfamily have an important role in drug delivery, because they extrude a broad molecular diversity of xenobiotics, including several anticancer drugs, preventing their entry into the brain. Gliomas are the most common primary tumors diagnosed in adults, which are often characterized by a poor prognosis, notably in the case of high-grade gliomas. Therapeutic treatments frequently fail due to the difficulty of delivering drugs through the brain barriers, adding to diverse mechanisms developed by the cancer, including the overexpression or expression de novo of ABC transporters in tumoral cells and/or in the endothelial cells forming the blood-brain tumor barrier (BBTB). Many models have been developed to study the phenotype, molecular characteristics, and function of the blood-brain interfaces as well as to evaluate drug permeability into the brain. These include in vitro, in vivo, and in silico models, which together can help us to better understand their implication in drug resistance and to develop new therapeutics or delivery strategies to improve the treatment of pathologies of the central nervous system (CNS). In this review, we present the principal characteristics of the blood-brain interfaces; then, we focus on the ABC transporters present on them and their implication in drug delivery; next, we present some of the most important models used for the study of drug transport; finally, we summarize the implication of ABC transporters in glioma and the BBTB in drug resistance and the strategies to improve the delivery of CNS anticancer drugs.

Blood-Brain Barrier and Breast Cancer Resistance Protein: A Limit to the Therapy of CNS Tumors and Neurodegenerative Diseases

The treatment of brain tumors and neurodegenerative diseases, represents an ongoing challenge. In Central Nervous System (CNS) the achievement of therapeutic concentration of chemical agents is complicated by the presence of distinct set of efflux proteins, such as ATP-Binding Cassette (ABC) transporters localized on the Blood-Brain Barrier (BBB). The activity of ABC transporters seems to be a common mechanism that underlies the poor response of CNS diseases to therapies.

The molecular characterization of Breast Cancer Resistance Protein (BCRP/ABCG2), as an ABC transporter conferring multidrug resistance (MDR), has stimulated many studies to investigate its activity on the BBB, its involvement in physiology and CNS diseases and its role in limiting the delivery of drugs in CNS.

In this review, we highlight the activity and localization of BCRP on the BBB and the action that this efflux pump has on many conventional drugs or latest generation molecules used for the treatment of CNS tumors and other neurodegenerative diseases.

Mechanistic diversity in ATP-binding cassette (ABC) transporters

ABC transporters catalyze transport reactions, such as the high-affinity uptake of micronutrients into bacteria and the export of cytotoxic compounds from mammalian cells. Crystal structures of ABC domains and full transporters have provided a framework for formulating reaction mechanisms of ATP-driven substrate transport, but recent studies have suggested remarkable mechanistic diversity within this protein family. This review evaluates the differing mechanistic proposals and outlines future directions for the exploration of ABC-transporter-catalyzed reactions.

The mechanisms of neurotoxicity and the selective vulnerability of nervous system sites

The spatial heterogeneity of the structure, function, and cellular composition of the nervous system confers extraordinary complexity and a multiplicity of mechanisms of chemical neurotoxicity. Because of its relatively high metabolic demands and functional dependence on postmitotic neurons, the nervous system is vulnerable to a variety of xenobiotics that affect essential homeostatic mechanisms that support function. Despite protection from the neuroglia and blood-brain barrier, the central nervous system is prone to attack from lipophilic toxicants and those that hijack endogenous transport, receptor, metabolic, and other biochemical systems. The inherent predilection of chemicals for highly conserved biochemical systems confers selective vulnerability of the nervous system to neurotoxicants. This chapter discusses selective vulnerability of the nervous system in the context of neuron-specific decrements (axonopathy, myelinopathy, disruption of neurotransmission), and the degree to which neuronal damage is facilitated or ameliorated by surrounding nonneural cells in both the central and peripheral nervous systems.