In vivo, in vitro and in silico methods for small molecule transfer across the BBB

Realizing brain therapy with "smart medicine": mechanism and case report of molecular hydrogen inhalation for Parkinson's disease

The Michael J. Fox Foundation has been funding research on Parkinson's disease for 35 years, but has yet to find a cure. This is due to a problem with the philosophy behind the development of modern medical treatments. In this paper, we will introduce "smart medicine" with a substance that can solve all the problems of central nervous system drugs. The substance is the smallest diatomic molecule, the hydrogen molecule. Due to their size, hydrogen molecules can easily penetrate the cell membrane and enter the brain. In the midbrain of Parkinson's disease patients, hydroxyl radicals generated by the Fenton reaction cause a chain reaction of oxidation of dopamine, but hydrogen entering the midbrain can convert the hydroxyl radicals into water molecules and inhibit the oxidation of dopamine. In this paper, we focus on the etiology of neurological diseases, especially Parkinson's disease, and present a case in which hydrogen inhalation improves the symptoms of Parkinson's disease, such as body bending and hand tremor. And we confidently state that if Michael J. Fox encountered "smart medicine" that could be realized with molecular hydrogen, he would not be a "lucky man" but a "super-lucky man."

Prediction of blood-brain barrier permeability using machine learning approaches based on various molecular representation

The assessment of compound blood-brain barrier (BBB) permeability poses a significant challenge in the discovery of drugs targeting the central nervous system. Conventional experimental approaches to measure BBB permeability are labor-intensive, cost-ineffective, and time-consuming. In this study, we constructed six machine learning classification models by combining various machine learning algorithms and molecular representations. The model based on ExtraTree algorithm and random partitioning strategy obtains the best prediction result, with AUC value of 0.932±0.004 and balanced accuracy (BA) of 0.837±0.010 for the test set. We employed the SHAP method to identify important features associated with BBB permeability. In addition, matched molecular pair (MMP) analysis and representative substructure derivation method were utilized to uncover the transformation rules and distinctive structural features of BBB permeable compounds. The machine learning models proposed in this work can serve as an effective tool for assessing BBB permeability in the drug discovery for central nervous system disease.

BrainPepPass: A Framework Based on Supervised Dimensionality Reduction for Predicting Blood-Brain Barrier-Penetrating Peptides

Peptides that pass through the blood-brain barrier (BBB) not only are implicated in brain-related pathologies but also are promising therapeutic tools for treating brain diseases, e.g., as shuttles carrying active medicines across the BBB. Computational prediction of BBB-penetrating peptides (B3PPs) has emerged as an interesting approach because of its ability to screen large peptide libraries in a cost-effective manner. In this study, we present BrainPepPass, a machine learning (ML) framework that utilizes supervised manifold dimensionality reduction and extreme gradient boosting (XGB) algorithms to predict natural and chemically modified B3PPs. The results indicate that the proposed tool outperforms other classifiers, with average accuracies exceeding 94% and 98% in 10-fold cross-validation and leave-one-out cross-validation (LOOCV), respectively. In addition, accuracy values ranging from 45% to 97.05% were achieved in the independent tests. The BrainPepPass tool is available in a public repository for academic use (https://github.com/ewerton-cristhian/BrainPepPass).

A machine learning-based quantitative model (LogBB_Pred) to predict the blood-brain barrier permeability (logBB value) of drug compounds

MOTIVATION

Efficient assessment of the blood-brain barrier (BBB) penetration ability of a drug compound is one of the major hurdles in central nervous system drug discovery since experimental methods are costly and time-consuming. To advance and elevate the success rate of neurotherapeutic drug discovery, it is essential to develop an accurate computational quantitative model to determine the absolute logBB value (a logarithmic ratio of the concentration of a drug in the brain to its concentration in the blood) of a drug candidate.

RESULTS

Here, we developed a quantitative model (LogBB_Pred) capable of predicting a logBB value of a query compound. The model achieved an R2 of 0.61 on an independent test dataset and outperformed other publicly available quantitative models. When compared with the available qualitative (classification) models that only classified whether a compound is BBB-permeable or not, our model achieved the same accuracy (0.85) with the best qualitative model and far-outperformed other qualitative models (accuracies between 0.64 and 0.70). For further evaluation, our model, quantitative models, and the qualitative models were evaluated on a real-world central nervous system drug screening library. Our model showed an accuracy of 0.97 while the other models showed an accuracy in the range of 0.29-0.83. Consequently, our model can accurately classify BBB-permeable compounds as well as predict the absolute logBB values of drug candidates.

AVAILABILITY AND IMPLEMENTATION

Web server is freely available on the web at http://ssbio.cau.ac.kr/software/logbb_pred/. The data used in this study are available to download at http://ssbio.cau.ac.kr/software/logbb_pred/dataset.zip.

Design, Synthesis, and Bioactivity Evaluation of Novel Rosin Diterpenoid Derivatives as Potential Anti-glioma Agents

Glioma is the most common brain tumor and its treatment options are limited. Abietic acid and dehydroabietic acid are tricyclic diterpenoid oxygen compounds with strong lip solubility and anti-glioma activity. In this study, novel rosin diterpenoid derivatives were designed and synthesized using abietic acid and dehydrogenated abietic acid as lead compounds and their activities against T98G, U87MG, and U251 cells were evaluated by CCK-8 methods. The in vivo activity of compounds with stronger activity in vitro was preliminarily studied through the Zebrafish model. The results showed that the IC50 values of B6, B8, B10, and B12 were 11.47 to 210.6 μM, which were exhibited higher antiproliferative potency against T98G, U87MG, and U251. The scratch experiment showed that B12 inhibited the migration of T98G in a time-dependent and concentration-dependent manner. The results of in vivo activity further explained that B12 could inhibit the proliferation of the T98G. The pKa values of B6, B8, B10, and B12 were 7.17 to 7.35, which were within the ideal range of glioma drugs. The ADME predictions indicated that these derivatives could pass through the blood-brain barrier. In addition, molecular docking primarily explained interaction between compounds and protein. These results suggested that B12 should be a promising candidate that merits further attention in the development of anti-glioma drugs.

Distribution in Rat Blood and Brain of TDMQ20, a Copper Chelator Designed as a Drug-Candidate for Alzheimer's Disease

(1) Background: TDMQ20 is a specific regulator of copper homeostasis in the brain, able to inhibit cognitive impairment in the early stages of Alzheimer's disease (AD) in mouse models of AD. To promote the further development of this drug-candidate, preliminary data on the pharmacokinetics of TDMQ20 in a mammal model have been collected. Since TDMQ20 should be administered orally, its absorption by the gastrointestinal tract was evaluated by comparison of blood concentrations after administration by oral and IV routes, and its ability to reach its target (the brain) was confirmed by comparison between blood and brain concentrations after oral administration. (2) Methods: plasmatic and brain concentrations of the drug after oral or intravenous treatment of rats at pharmacologically relevant doses were determined as a function of time. (3) Results: oral absorption of TDMQ20 was rapid and bioavailability was high (66% and 86% for males and females, respectively). The drug accumulated in the brain for several hours (brain-plasma ratio 3 h after oral administration = 2.6), and was then efficiently cleared. (4) Conclusions: these data confirm that TDMQ20 efficiently crosses the brain-blood barrier and is a relevant drug-candidate to treat AD.

A merged molecular representation deep learning method for blood-brain barrier permeability prediction

The ability of a compound to permeate across the blood-brain barrier (BBB) is a significant factor for central nervous system drug development. Thus, for speeding up the drug discovery process, it is crucial to perform high-throughput screenings to predict the BBB permeability of the candidate compounds. Although experimental methods are capable of determining BBB permeability, they are still cost-ineffective and time-consuming. To complement the shortcomings of existing methods, we present a deep learning-based multi-model framework model, called Deep-B3, to predict the BBB permeability of candidate compounds. In Deep-B3, the samples are encoded in three kinds of features, namely molecular descriptors and fingerprints, molecular graph and simplified molecular input line entry system (SMILES) text notation. The pre-trained models were built to extract latent features from the molecular graph and SMILES. These features depicted the compounds in terms of tabular data, image and text, respectively. The validation results yielded from the independent dataset demonstrated that the performance of Deep-B3 is superior to that of the state-of-the-art models. Hence, Deep-B3 holds the potential to become a useful tool for drug development. A freely available online web-server for Deep-B3 was established at http://cbcb.cdutcm.edu.cn/deepb3/, and the source code and dataset of Deep-B3 are available at https://github.com/GreatChenLab/Deep-B3.

Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural Networks

Assessing whether compounds penetrate the brain can become critical in drug discovery, either to prevent adverse events or to reach the biological target. Generally, pre-clinical in vivo studies measuring the ratio of brain and blood concentrations (K_p) are required to estimate the brain penetration potential of a new drug entity. In this work, we developed machine learning models to predict in vivo compound brain penetration (as LogK_p) from chemical structure. Our results show the benefit of including in vitro experimental data as auxiliary tasks in multi-task graph neural network (MT-GNN) models. MT-GNNs outperformed single-task (ST) models solely trained on in vivo brain penetration data. The best-performing MT-GNN regression model achieved a coefficient of determination of 0.42 and a mean absolute error of 0.39 (2.5-fold) on a prospective validation set and outperformed all tested ST models. To facilitate decision-making, compounds were classified into brain-penetrant or non-penetrant, achieving a Matthew's correlation coefficient of 0.66. Taken together, our findings indicate that the inclusion of in vitro assay data as MT-GNN auxiliary tasks improves in vivo brain penetration predictions and prospective compound prioritization.

Design and synthesis of benzodiazepines as brain penetrating PARP-1 inhibitors

The poly (ADP-ribose) polymerase (PARP) inhibitors play a crucial role in cancer therapy. However, most approved PARP inhibitors cannot cross the blood-brain barrier, thus limiting their application in the central nervous system. Here, 55 benzodiazepines were designed and synthesised to screen brain penetrating PARP-1 inhibitors. All target compounds were evaluated for their PARP-1 inhibition activity, and compounds with better activity were selected for further assays in vitro. Among them, compounds H34, H42, H48, and H52 displayed acceptable inhibition effects on breast cancer cells. Also, computational prediction together with the permeability assays in vitro and in vivo proved that the benzodiazepine PARP-1 inhibitors we synthesised were brain permeable. Compound H52 exhibited a B/P ratio of 40 times higher than that of Rucaparib and would be selected to develop its potential use in neurodegenerative diseases. Our study provided potential lead compounds and design strategies for the development of brain penetrating PARP-1 inhibitors.

HIGHLIGHTS

Structural fusion was used to screen brain penetrating PARP-1 inhibitors.

55 benzodiazepines were evaluated for their PARP-1 inhibition activity.

Four compounds displayed acceptable inhibition effects on breast cancer cells.

The benzodiazepine PARP-1 inhibitors were proved to be brain permeable.

Chemical Synthesis, Pharmacokinetic Properties and Biological Effects of JM-00266, a Putative Non-Brain Penetrant Cannabinoid Receptor 1 Inverse Agonist

Targeting cannabinoid 1 receptors (CB1R) with peripherally restricted antagonists (or inverse agonists) shows promise to improve metabolic disorders associated with obesity. In this context, we designed and synthetized JM-00266, a new CB1R blocker with limited blood–brain barrier (BBB) permeability. Pharmacokinetics were tested with SwissADME and in vivo in rodents after oral and intraperitoneal administration of JM-00266 in comparison with Rimonabant. In silico predictions indicated JM-00266 is a non-brain penetrant compound and this was confirmed by brain/plasma ratios and brain uptake index values. JM-00266 had no impact on food intake, anxiety-related behavior and body temperature suggesting an absence of central activity. cAMP assays performed in CB1R-transfected HEK293T/17 cells showed that the drug exhibited inverse agonist activity on CB1R. In addition, JM-00266 counteracted anandamide-induced gastroparesis indicating substantial peripheral activity. Acute administration of JM-00266 also improved glucose tolerance and insulin sensitivity in wild-type mice, but not in CB1R^−/− mice. Furthermore, the accumulation of JM-00266 in adipose tissue was associated with an increase in lipolysis. In conclusion, JM-00266 or derivatives can be predicted as a new candidate for modulating peripheral endocannabinoid activity and improving obesity-related metabolic disorders.

How do phosphodiesterase-5 inhibitors affect cancer? A focus on glioblastoma multiforme

Since the discovery of phosphodiesterase-5 (PDE5) enzyme overexpression in the central nervous system (CNS) malignancies, investigations have explored the potential capacity of current PDE5 inhibitor drugs for repositioning in the treatment of brain tumors, notably glioblastoma multiforme (GBM). It has now been recognized that these drugs increase brain tumors permeability and enhance standard chemotherapeutics effectiveness. More importantly, studies have highlighted the promising antitumor functions of PDE5 inhibitors, e.g., triggering apoptosis, suppressing tumor cell growth and invasion, and reversing tumor microenvironment (TME) immunosuppression in the brain. However, contradictory reports have suggested a pro-oncogenic role for neuronal cyclic guanosine monophosphate (cGMP), indicating the beneficial function of PDE5 in the brain of GBM patients. Unfortunately, due to the inconsistent preclinical findings, only a few clinical trials are evaluating the therapeutic value of PDE5 inhibitors in GBM treatment. Accordingly, additional studies should be conducted to shed light on the precise effect of PDE5 inhibitors in GBM biology regarding the existing molecular heterogeneities among individuals. Here, we highlighted and discussed the previously investigated mechanisms underlying the impacts of PDE5 inhibitors in cancers, focusing on GBM to provide an overview of current knowledge necessary for future studies.

In vitro blood brain barrier models: An overview

Understanding the composition and function of the blood brain barrier (BBB) enables the development of novel, innovative techniques for administering central nervous system (CNS) medications and technologies for improving the existing models. Scientific and methodological interest in the pathology of the BBB resulted in the formation of numerous in vitro BBB models. Once successfully studied and modelled, it would be a valuable tool for elucidating the mechanism of action of the CNS disorders prior to their manifestation and the pathogenic factors. Understanding the rationale behind the selection of the models as well as their working may enable the development of state-of-the-art drugs for treating and managing neurological diseases. Hence, to have realistic simulation of the BBB and test its drug permeability the microfluidics-based BBB-on-Chip model has been developed. To summarise, we aim to evaluate the advanced, newly developed and frequently used in vitro BBB models, thereby providing a brief overview of the components essential for in vitro BBB formation, the methods of chip fabrication and cell culturing, its applications and the recent advances in this technological field. This will be critical for developing CNS treatments with improved BBB penetrability and pharmacokinetic properties.

Development of novel 2-aminoalkyl-6-(2-hydroxyphenyl)pyridazin-3(2H)-one derivatives as balanced multifunctional agents against Alzheimer's disease

Based on multitarget-directed ligands approach, through two rounds of screening, a series of 2-aminoalkyl-6-(2-hydroxyphenyl)pyridazin-3(2H)-one derivatives were designed, synthesized and evaluated as innovative multifunctional agents against Alzheimer's disease. In vitro biological assays indicated that most of the hybrids were endowed with great AChE inhibitory activity, excellent antioxidant activity and moderate Aβ_1-42 aggregation inhibition. Taken both efficacy and balance into account, 12a was identified as the optimal multifunctional ligand with significant inhibition of AChE (EeAChE, IC₅₀ = 0.20 μM; HuAChE, IC₅₀ = 37.02 nM) and anti-Aβ activity (IC₅₀ = 1.92 μM for self-induced Aβ_1-42 aggregation; IC₅₀ = 1.80 μM for disaggregation of Aβ_1-42 fibrils; IC₅₀ = 2.18 μM for Cu²⁺-induced Aβ_1-42 aggregation; IC₅₀ = 1.17 μM for disaggregation of Cu²⁺-induced Aβ_1-42 fibrils; 81.7% for HuAChE-induced Aβ_1-40 aggregation). Moreover, it was equipped with the potential to serve as antioxidant (3.03 Trolox equivalents), metals chelator and anti-neuroinflammation agent for synergetic treatment. Finally, in vivo study demonstrated that 12a, with suitable BBB permeability (log BB = -0.61), could efficaciously ameliorate cognitive dysfunction on scopolamine-treated mice by regulating cholinergic system and oxidative stress simultaneously. Altogether, these results highlight the potential of 12a as an innovative balanced multifunctional candidate for Alzheimer's disease treatment.

Multitarget 2'-hydroxychalcones as potential drugs for the treatment of neurodegenerative disorders and their comorbidities

The complex nature of neurodegenerative diseases (NDDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD) calls for multidirectional treatment. Restoring neurotransmitter levels by combined inhibition of cholinesterases (ChEs) and monoamine oxidases (MAOs, MAO-A and MAO-B), in conjunction with strategies to counteract amyloid β (Aβ) aggregation, may constitute a therapeutically strong multi-target approach for the treatment of NDDs. Chalcones are a subgroup of flavonoids with a broad spectrum of biological activity. We report here the synthesis of 2'-hydroxychalcones as MAO-A and MAO-B inhibitors. Compounds 5c (IC50 = 0.031 ± 0.001 μM), 5a (IC50 = 0.084 ± 0.003 μM), 2c (IC50 = 0.095 ± 0.019 μM) and 2a (IC50 = 0.111 ± 0.006 μM) were the most potent, selective and reversible inhibitors of human (h)MAO-B isoform. hMAO-B inhibitors 1a, 2a and 5a also inhibited murine MAO-B in vivo in mouse brain homogenates. Molecular modelling rationalised the binding mode of 2'-hydroxychalcones in the active site of hMAO-B. Additionally, several derivatives inhibited murine acetylcholinesterase (mAChE) (IC50 values from 4.37 ± 0.83 μM to 15.17 ± 6.03 μM) and reduced the aggregation propensity of Aβ. Moreover, some derivatives bound to the benzodiazepine binding site (BDZ-bs) of the γ-aminobutyric acid A (GABAA) receptors (1a and 2a with Ki = 4.9 ± 1.1 μM and 5.0 ± 1.1 μM, respectively), and exerted sedative and/or anxiolytic like effects on mice. The biological results reported here on 2'-hydroxychalcones provide an extension to previous studies on chalcone scaffold and show them as a potential treatment strategy for NDDs and their associated comorbidities.

New In Vitro Methodology for Kinetics Distribution Prediction in the Brain. An Additional Step towards an Animal-Free Approach

Simple Summary

The prevalence of neurological disorders in humans is rising year after year. This fact necessitates the development of new drugs for treating these pathologies. Traditionally, drugs have been tested in animals prior to use in human experiments; however, the use of animals in experimentation must be controlled and as low as possible. Because of that, here we proposed a new in vitro approach with which the access and distribution of drugs into the brain can be evaluated without using/killing any animals.

Abstract

The development of new drugs or formulations for central nervous system (CNS) diseases is a complex pharmacologic and pharmacokinetic process; it is important to evaluate their access to the CNS through the blood–brain barrier (BBB) and their distribution once they have acceded to the brain. The gold standard tool for obtaining this information is the animal microdialysis technique; however, according to 3Rs principles, it would be better to have an “animal-free” alternative technique. Because of that, the purpose of this work was to develop a new formulation to substitute the brain homogenate in the in vitro tests used for the prediction of a drug’s distribution in the brain. Fresh eggs have been used to prepare an emulsion with the same proportion in proteins and lipids as a human brain; this emulsion has proved to be able to predict both the unbound fraction of drug in the brain (f_u,brain) and the apparent volume of distribution in the brain (V_u,brain) when tested in in vitro permeability tests. The new formulation could be used as a screening tool; only the drugs with a proper in vitro distribution would pass to microdialysis studies, contributing to the refinement, reduction and replacement of animals in research.

Physical and chemical properties of carbon nanotubes in view of mechanistic neuroscience investigations. Some outlook from condensed matter, materials science and physical chemistry

The open border between non-living and living matter, suggested by increasingly emerging fields of nanoscience interfaced to biological systems, requires a detailed knowledge of nanomaterials properties. An account of the wide spectrum of phenomena, belonging to physical chemistry of interfaces, materials science, solid state physics at the nanoscale and bioelectrochemistry, thus is acquainted for a comprehensive application of carbon nanotubes interphased with neuron cells. This review points out a number of conceptual tools to further address the ongoing advances in coupling neuronal networks with (carbon) nanotube meshworks, and to deepen the basic issues that govern a biological cell or tissue interacting with a nanomaterial. Emphasis is given here to the properties and roles of carbon nanotube systems at relevant spatiotemporal scales of individual molecules, junctions and molecular layers, as well as to the point of view of a condensed matter or materials scientist. Carbon nanotube interactions with blood-brain barrier, drug delivery, biocompatibility and functionalization issues are also regarded.

Advances in Non-Animal Testing Approaches towards Accelerated Clinical Translation of Novel Nanotheranostic Therapeutics for Central Nervous System Disorders

Nanotheranostics constitute a novel drug delivery system approach to improving systemic, brain-targeted delivery of diagnostic imaging agents and pharmacological moieties in one rational carrier platform. While there have been notable successes in this field, currently, the clinical translation of such delivery systems for the treatment of neurological disorders has been limited by the inadequacy of correlating in vitro and in vivo data on blood-brain barrier (BBB) permeation and biocompatibility of nanomaterials. This review aims to identify the most contemporary non-invasive approaches for BBB crossing using nanotheranostics as a novel drug delivery strategy and current non-animal-based models for assessing the safety and efficiency of such formulations. This review will also address current and future directions of select in vitro models for reducing the cumbersome and laborious mandate for testing exclusively in animals. It is hoped these non-animal-based modelling approaches will facilitate researchers in optimising promising multifunctional nanocarriers with a view to accelerating clinical testing and authorisation applications. By rational design and appropriate selection of characterised and validated models, ranging from monolayer cell cultures to organ-on-chip microfluidics, promising nanotheranostic particles with modular and rational design can be screened in high-throughput models with robust predictive power. Thus, this article serves to highlight abbreviated research and development possibilities with clinical translational relevance for developing novel nanomaterial-based neuropharmaceuticals for therapy in CNS disorders. By generating predictive data for prospective nanomedicines using validated in vitro models for supporting clinical applications in lieu of requiring extensive use of in vivo animal models that have notable limitations, it is hoped that there will be a burgeoning in the nanotherapy of CNS disorders by virtue of accelerated lead identification through screening, optimisation through rational design for brain-targeted delivery across the BBB and clinical testing and approval using fewer animals. Additionally, by using models with tissue of human origin, reproducible therapeutically relevant nanomedicine delivery and individualised therapy can be realised.

B3Pred: A Random-Forest-Based Method for Predicting and Designing Blood-Brain Barrier Penetrating Peptides

The blood–brain barrier is a major obstacle in treating brain-related disorders, as it does not allow the delivery of drugs into the brain. We developed a method for predicting blood–brain barrier penetrating peptides to facilitate drug delivery into the brain. These blood–brain barrier penetrating peptides (B3PPs) can act as therapeutics, as well as drug delivery agents. We trained, tested, and evaluated our models on blood–brain barrier peptides obtained from the B3Pdb database. First, we computed a wide range of peptide features. Then, we selected relevant peptide features. Finally, we developed numerous machine-learning-based models for predicting blood–brain barrier peptides using the selected features. The random-forest-based model performed the best with respect to the top 80 selected features and achieved a maximal 85.08% accuracy with an AUROC of 0.93. We also developed a webserver, B3pred, that implements our best models. It has three major modules that allow users to predict/design B3PPs and scan B3PPs in a protein sequence.

Prediction of the Blood-Brain Barrier (BBB) Permeability of Chemicals Based on Machine-Learning and Ensemble Methods

The ability of chemicals to enter the blood-brain barrier (BBB) is a key factor for central nervous system (CNS) drug development. Although many models for BBB permeability prediction have been developed, they have insufficient accuracy (ACC) and sensitivity (SEN). To improve performance, ensemble models were built to predict the BBB permeability of compounds. In this study, in silico ensemble-learning models were developed using 3 machine-learning algorithms and 9 molecular fingerprints from 1757 chemicals (integrated from 2 published data sets) to predict BBB permeability. The best prediction performance of the base classifier models was achieved by a prediction model based on an random forest (RF) and a MACCS molecular fingerprint with an ACC of 0.910, an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.957, a SEN of 0.927, and a specificity of 0.867 in 5-fold cross-validation. The prediction performance of the ensemble models is better than that of most of the base classifiers. The final ensemble model has also demonstrated good accuracy for an external validation and can be used for the early screening of CNS drugs.

In vitro model for predicting the access and distribution of drugs in the brain using hCMEC/D3 cells

The BBB is a protective entity that prevents external substances from reaching the CNS but it also hinders the delivery of drugs into the brain when they are needed. The main objective of this work was to improve a previously proposed in vitro cell-based model by using a more physiological cell line (hCMEC/D3) to predict the main pharmacokinetic parameters that describe the access and distribution of drugs in the CNS: Kp_uu,brain, f_u,plasma, f_u,brain and V_u,brain. The hCMEC/D3 permeability of seven drugs was studied in transwell systems under different conditions (standard, modified with albumin and modified with brain homogenate). From the permeability coefficients of those experiments, the parameters mentioned above were calculated and four linear IVIVCs were established. The best ones were those that relate the in vitro and in vivo V_u,brain and f_u,brain (r² = 0.961 and r² = 0.940) which represent the binding rate of a substance to the brain tissue, evidencing the importance of using brain homogenate to mimic brain tissue when an in vitro brain permeability assay is done. This methodology could be a high-throughput screening tool in drug development to select the CNS promising drugs in three different in vitro BBB models (hCMEC/D3, MDCK and MDCK-MDR1).

Catalytic photooxygenation degrades brain Aβ in vivo

Protein degradation induced by small molecules by recruiting endogenous protein degradation systems, such as ubiquitin-proteasome systems, to disease-related proteins is an emerging concept to inhibit the function of undruggable proteins. Protein targets without reliable ligands and/or existing outside the cells where ubiquitin-proteasome systems do not exist, however, are beyond the scope of currently available protein degradation strategies. Here, we disclose photooxygenation catalyst 7 that permeates the blood-brain barrier and selectively and directly degrades an extracellular Alzheimer's disease-related undruggable protein, amyloid-β protein (Aβ). Key was the identification of a compact but orange color visible light-activatable chemical catalyst whose activity can be switched on/off according to its molecular mobility, thereby ensuring high selectivity for aggregated Aβ. Chemical catalyst-promoted protein degradation can be applied universally for attenuating extracellular amyloids and various pathogenic proteins and is thus a new entry to induced protein degradation strategies.

Natural Polysaccharide Carriers in Brain Delivery: Challenge and Perspective

Targeted drug delivery systems represent valuable tools to enhance the accumulation of therapeutics in the brain. Here, the presence of the blood brain barrier strongly hinders the passage of foreign substances, often limiting the effectiveness of pharmacological therapies. Among the plethora of materials used for the development of these systems, natural polysaccharides are attracting growing interest because of their biocompatibility, muco-adhesion, and chemical versatility which allow a wide range of carriers with tailored physico-chemical features to be synthetized. This review describes the state of the art in the field of targeted carriers based on natural polysaccharides over the last five years, focusing on the main targeting strategies, namely passive and active transport, stimuli-responsive materials and the administration route. In addition, in the last section, the efficacy of the reviewed carriers in each specific brain diseases is summarized and commented on in terms of enhancement of either blood brain barrier (BBB) permeation ability or drug bioavailability in the brain.

Metals in Imaging of Alzheimer's Disease

One of the hallmarks of Alzheimer's disease (AD) is the deposition of amyloid plaques in the brain parenchyma, which occurs 7-15 years before the onset of cognitive symptoms of the pathology. Timely diagnostics of amyloid formations allows identifying AD at an early stage and initiating inhibitor therapy, delaying the progression of the disease. However, clinically used radiopharmaceuticals based on 11C and 18F are synchrotron-dependent and short-lived. The design of new metal-containing radiopharmaceuticals for AD visualization is of interest. The development of coordination compounds capable of effectively crossing the blood-brain barrier (BBB) requires careful selection of a ligand moiety, a metal chelating scaffold, and a metal cation, defining the method of supposed Aβ visualization. In this review, we have summarized metal-containing drugs for positron emission tomography (PET), magnetic resonance imaging (MRI), and single-photon emission computed tomography (SPECT) imaging of Alzheimer's disease. The obtained data allow assessing the structure-ability to cross the BBB ratio.

Overcoming the Blood-Brain Barrier: Functionalised Chitosan Nanocarriers

The major impediment to the delivery of therapeutics to the brain is the presence of the blood-brain barrier (BBB). The BBB allows for the entrance of essential nutrients while excluding harmful substances, including most therapeutic agents; hence, brain disorders, especially tumours, are very difficult to treat. Chitosan is a well-researched polymer that offers advantageous biological and chemical properties, such as mucoadhesion and the ease of functionalisation. Chitosan-based nanocarriers (CsNCs) establish ionic interactions with the endothelial cells, facilitating the crossing of drugs through the BBB by adsorptive mediated transcytosis. This process is further enhanced by modifications of the structure of chitosan, owing to the presence of reactive amino and hydroxyl groups. Finally, by permanently binding ligands or molecules, such as antibodies or lipids, CsNCs have showed a boosted passage through the BBB, in both in vivo and in vitro studies which will be discussed in this review.

Biomedical and Pharmacological Uses of Fluorescein Isothiocyanate Chitosan-Based Nanocarriers

Chitosan-based nanocarriers (ChNCs) are considered suitable drug carriers due to their ability to encapsulate a variety of drugs and cross biological barriers to deliver the cargo to their target site. Fluorescein isothiocyanate-labeled chitosan-based NCs (FITC@ChNCs) are used extensively in biomedical and pharmacological applications. The main advantage of using FITC@ChNCs consists of the ability to track their fate both intra and extracellularly. This journey is strictly dependent on the physico-chemical properties of the carrier and the cell types under investigation. Other applications make use of fluorescent ChNCs in cell labeling for the detection of disorders in vivo and controlling of living cells in situ. This review describes the use of FITC@ChNCs in the various applications with a focus on understanding their usefulness in labeled drug-delivery systems.

A Reevaluation of Chitosan-Decorated Nanoparticles to Cross the Blood-Brain Barrier

The blood-brain barrier (BBB) is a sophisticated and very selective dynamic interface composed of endothelial cells expressing enzymes, transport systems, and receptors that regulate the passage of nutrients, ions, oxygen, and other essential molecules to the brain, regulating its homeostasis. Moreover, the BBB performs a vital function in protecting the brain from pathogens and other dangerous agents in the blood circulation. Despite its crucial role, this barrier represents a difficult obstacle for the treatment of brain diseases because many therapeutic agents cannot cross it. Thus, different strategies based on nanoparticles have been explored in recent years. Concerning this, chitosan-decorated nanoparticles have demonstrated enormous potential for drug delivery across the BBB and treatment of Alzheimer's disease, Parkinson's disease, gliomas, cerebral ischemia, and schizophrenia. Our main objective was to highlight the high potential of chitosan adsorption to improve the penetrability through the BBB of nanoformulations for diseases of CNS. Therefore, we describe the BBB structure and function, as well as the routes of chitosan for crossing it. Moreover, we define the methods of decoration of nanoparticles with chitosan and provide numerous examples of their potential utilization in a variety of brain diseases. Lastly, we discuss future directions, mentioning the need for extensive characterization of proposed nanoformulations and clinical trials for evaluation of their efficacy.

A Practical Perspective on the Evaluation of Small Molecule CNS Penetration in Drug Discovery

The separation of the brain from blood by the blood-brain barrier and the bloodcerebrospinal fluid (CSF) barrier poses unique challenges for the discovery and development of drugs targeting the central nervous system (CNS). This review will describe the role of transporters in CNS penetration and examine the relationship between unbound brain (Cu-brain) and unbound plasma (Cu-plasma) or CSF (CCSF) concentration. Published data demonstrate that the relationship between Cu-brain and Cu-plasma or CCSF can be affected by transporter status and passive permeability of a drug and CCSF may not be a reliable surrogate for CNS penetration. Indeed, CCSF usually over-estimates Cu-brain for efflux substrates and it provides no additional value over Cu-plasma as the surrogate of Cu-brain for highly permeable non-efflux substrates. A strategy described here for the evaluation of CNS penetration is to use in vitro permeability, P-glycoprotein (Pgp) and breast cancer resistance protein efflux assays and Cu-brain/Cu-plasma in preclinical species. Cu-plasma should be used as the surrogate of Cu-brain for highly permeable non-efflux substrates with no evidence of impaired distribution into the brain. When drug penetration into the brain is impaired, we recommend using (total brain concentration * unbound fraction in the brain) as Cu-brain in preclinical species or Cu-plasma/in vitro Pgp efflux ratio if Pgp is the major limiting mechanism for brain penetration.

N-Substituted Nipecotic Acids as (S)-SNAP-5114 Analogues with Modified Lipophilic Domains

Potential mGAT4 inhibitors derived from the lead substance (S)-SNAP-5114 have been synthesized and characterized for their inhibitory potency. Variations from the parent compound included the substitution of one of its aromatic 4-methoxy and 4-methoxyphenyl groups, respectively, with a more polar moiety, including a carboxylic acid, alcohol, nitrile, carboxamide, sulfonamide, aldehyde or ketone function, or amino acid partial structures. Furthermore, it was investigated how the substitution of more than one of the aromatic 4-methoxy groups affects the potency and selectivity of the resulting compounds. Among the synthesized test substances (S)-1-{2-[(4-formylphenyl)bis(4-methoxyphenyl)-methoxy]ethyl}piperidine-3-carboxylic acid, that features a carbaldehyde function in place of one of the aromatic 4-methoxy moieties of (S)-SNAP-5114, was found to have a pIC50 value of 5.89±0.07, hence constituting a slightly more potent mGAT4 inhibitor than the parent substance while showing comparable subtype selectivity.

Predicting the Blood-Brain Barrier Permeability of New Drug-Like Compounds via HPLC with Various Stationary Phases

The permeation of the blood-brain barrier is a very important consideration for new drug candidate molecules. In this research, the reversed-phase liquid chromatography with different columns (Purosphere RP-18e, IAM.PC.DD2 and Cosmosil Cholester) was used to predict the penetration of the blood-brain barrier by 65 newly-synthesized drug-like compounds. The linear free energy relationships (LFERs) model (log BB = c + eE + sS + aA + bB + vV) was established for a training set of 23 congeneric biologically active azole compounds with known experimental log BB (BB = C_blood/C_brain) values (R² = 0.9039). The reliability and predictive potency of the model were confirmed by leave-one-out cross validation as well as leave-50%-out cross validation. Multiple linear regression (MLR) was used to develop the quantitative structure-activity relationships (QSARs) to predict the log BB values of compounds that were tested, taking into account the chromatographic lipophilicity (log k_w), polarizability and topological polar surface area. The excellent statistics of the developed MLR equations (R² > 0.8 for all columns) showed that it is possible to use the HPLC technique and retention data to produce reliable blood-brain barrier permeability models and to predict the log BB values of our pharmaceutically important molecules.

Multifunctional hybrid sulfonamides as novel therapeutic agents for Alzheimer’s disease

Aim: A breakthrough in modern medicine, in terms of treatment of Alzheimer’s disease, is yet to be seen, as the scene is currently plagued with numerous clinical trial failures. Here, we are exploring multifunctional hybrid sulfonamides for their anti-Alzheimer activity due to the complex nature of the disease. Results & methodology: Compound 41 showed significant inhibition of MMP-2 (IC50: 18.24 ± 1.62 nM), AChE (IC50: 4.28 ± 0.15 μM) and BuChE (IC50: 1.32 ± 0.02 μM). It also exhibited a metal-chelating property, as validated by an in vitro metal-induced Aβ aggregation assay using confocal fluorescence imaging. Whereas, MTT and DPPH assays revealed it to be nontoxic and neuroprotective with substantial antioxidant property. Conclusion: The present study puts forth potent yet nontoxic lead molecules, which foray into the field of multitargeted agents for the treatment of Alzheimer’s disease.

In-vitro blood-brain barrier models for drug screening and permeation studies: an overview

The blood-brain barrier (BBB) is comprised of brain microvascular endothelial central nervous system (CNS) cells, which communicate with other CNS cells (astrocytes, pericytes) and behave according to the state of the CNS, by responding against pathological environments and modulating disease progression. The BBB plays a crucial role in maintaining homeostasis in the CNS by maintaining restricted transport of toxic or harmful molecules, transport of nutrients, and removal of metabolites from the brain. Neurological disorders, such as NeuroHIV, cerebral stroke, brain tumors, and other neurodegenerative diseases increase the permeability of the BBB. While on the other hand, semipermeable nature of BBB restricts the movement of bigger molecules i.e. drugs or proteins (>500 kDa) across it, leading to minimal bioavailability of drugs in the CNS. This poses the most significant shortcoming in the development of therapeutics for CNS neurodegenerative disorders. Although the complexity of the BBB (dynamic and adaptable barrier) affects approaches of CNS drug delivery and promotes disease progression, understanding the composition and functions of BBB provides a platform for novel innovative approaches towards drug delivery to CNS. The methodical and scientific interests in the physiology and pathology of the BBB led to the development and the advancement of numerous in vitro models of the BBB. This review discusses the fundamentals of BBB structure, permeation mechanisms, an overview of all the different in-vitro BBB models with their advantages and disadvantages, and rationale of selecting penetration prediction methods towards the critical role in the development of the CNS therapeutics.

Application of separation methods for in vitro prediction of blood-brain barrier permeability-The state of the art

Despite many efforts, drug discovery pipeline is still a highly inefficient process. Nowadays, when combinatorial chemistry enables to synthesize hundreds of new drugs candidates, methods for rapid assessment of biopharmaceutical parameters of new compounds are highly desired. Over one-third of drugs candidates is rejected because of unsatisfactory pharmacokinetic properties. In the drug discovery process, the blood-brain barrier (BBB) permeability plays a critical role for central nervous system active drugs candidates as well as non-central nervous system active drugs. For this reason, knowledge on the BBB permeability of compounds is essential in the development of new medicines. The review was focused on the application of different separation methods for BBB permeability assessment. Both chromatographic and electrophoretic methods were described. In the article, the advantages and limitations of well-established chromatographic methods like immobilized artificial membrane chromatography or micellar liquid chromatography, and less common techniques were discussed. Special attention was devoted to methods were microemulsion is used as mobile or pseudostationary phases.

RP-18 HPLC Analysis of Drugs’ Ability to Cross the Blood-Brain Barrier

One hundred ten compounds of diverse structures (actives and excipients used in pharmaceutical preparations) were studied by RP-18 HPLC with acetonitrile-pH 7.4 phosphate buffer 1 : 1 (v/v) as the mobile phase. The relationships between the BBB permeation coefficients and the chromatographic parameters log k and (log k)/PSA were compared to those between the blood-brain barrier (BBB) permeation parameters and the RP-18 TLC descriptors Rf and Rf/PSA known from our earlier studies. It was found that the correlations between the BBB permeability and the HPLC data are slightly worse than those achieved for the thin-layer chromatographic data. MLR analysis based upon the physicochemical data confirmed the value of the molecular descriptors, related to the CNS bioavailability. These variables, combined with the HPLC data, made it possible to generate computational models, explaining 70–96% of the total variance of the CNS bioavailability. Contrary to TLC Rf, the advantage of the modification of HPLC log k with PSA (polar surface area) has not been confirmed and the results obtained with log k are superior to those obtained after a novel (log k)/PSA parameter has been introduced. Establishing a firm threshold limit of (log k)/PSA, log k, or even k and k/PSA to distinguish between the CNS+ and CNS− compounds was impossible. On the other hand, discriminant function analyses involving log k and (log k)/PSA as discriminating variables separated the CNS+ and CNS− compounds with the success rate ca. 90%. On the basis of these results, it was concluded that the RP-18 HPLC analytical models are entirely successful in studies and predictions of the BBB permeability.

Predicting Blood⁻Brain Barrier Permeability of Marine-Derived Kinase Inhibitors Using Ensemble Classifiers Reveals Potential Hits for Neurodegenerative Disorders

The recent success of small-molecule kinase inhibitors as anticancer drugs has generated significant interest in their application to other clinical areas, such as disorders of the central nervous system (CNS). However, most kinase inhibitor drug candidates investigated to date have been ineffective at treating CNS disorders, mainly due to poor blood⁻brain barrier (BBB) permeability. It is, therefore, imperative to evaluate new chemical entities for both kinase inhibition and BBB permeability. Over the last 35 years, marine biodiscovery has yielded 471 natural products reported as kinase inhibitors, yet very few have been evaluated for BBB permeability. In this study, we revisited these marine natural products and predicted their ability to cross the BBB by applying freely available open-source chemoinformatics and machine learning algorithms to a training set of 332 previously reported CNS-penetrant small molecules. We evaluated several regression and classification models, and found that our optimised classifiers (random forest, gradient boosting, and logistic regression) outperformed other models, with overall cross-validated model accuracies of 80%⁻82% and 78%⁻80% on external testing. All 3 binary classifiers predicted 13 marine-derived kinase inhibitors with appropriate physicochemical characteristics for BBB permeability.

Impact of Neurodegenerative Diseases on Drug Binding to Brain Tissues: From Animal Models to Human Samples

Drug efficacy in the central nervous system (CNS) requires an additional step after crossing the blood-brain barrier. Therapeutic agents must reach their targets in the brain to modulate them; thus, the free drug concentration hypothesis is a key parameter for in vivo pharmacology. Here, we report the impact of neurodegeneration (Alzheimer's disease (AD) and Parkinson's disease (PD) compared with healthy controls) on the binding of 10 known drugs to postmortem brain tissues from animal models and humans. Unbound drug fractions, for some drugs, are significantly different between healthy and injured brain tissues (AD or PD). In addition, drugs binding to brain tissues from AD and PD animal models do not always recapitulate their binding to the corresponding human injured brain tissues. These results reveal potentially relevant implications for CNS drug discovery.

In Vivo and In Vitro Characteristics of Radiolabeled Vesamicol Analogs as the Vesicular Acetylcholine Transporter Imaging Agents

The vesicular acetylcholine transporter (VAChT), a presynaptic cholinergic neuron marker, is a potential internal molecular target for the development of an imaging agent for early diagnosis of neurodegenerative disorders with cognitive decline such as Alzheimer's disease (AD). Since vesamicol has been reported to bind to VAChT with high affinity, many vesamicol analogs have been studied as VAChT imaging agents for the diagnosis of cholinergic neurodeficit disorder. However, because many vesamicol analogs, as well as vesamicol, bound to sigma receptors (σ₁ and σ₂) besides VAChT, almost all the vesamicol analogs have been shown to be unsuitable for clinical trials. In this report, the relationships between the chemical structure and the biological characteristics of these developed vesamicol analogs were investigated, especially the in vitro binding profile and the in vivo regional brain accumulation.

Blood-brain barrier shuttle peptides: an emerging paradigm for brain delivery

Brain delivery is one of the major challenges in drug development because of the high number of patients suffering from neural diseases and the low efficiency of the treatments available. Although the blood-brain barrier (BBB) prevents most drugs from reaching their targets, molecular vectors - known as BBB shuttles - offer great promise to safely overcome this formidable obstacle. In recent years, peptide shuttles have received growing attention because of their lower cost, reduced immunogenicity, and higher chemical versatility than traditional Trojan horse antibodies and other proteins.

Novel Vilazodone-Tacrine Hybrids as Potential Multitarget-Directed Ligands for the Treatment of Alzheimer's Disease Accompanied with Depression: Design, Synthesis, and Biological Evaluation

Depression is one of the most frequent psychiatric complications of Alzheimer's disease (AD), affecting up to 50% of the patients. A novel series of hybrid molecules were designed and synthesized by combining the pharmacophoric features of vilazodone and tacrine as potential multitarget-directed ligands for the treatment of AD with depression. In vitro biological assays were conducted to evaluate the compounds; among the 30 hybrids, compound 1e showed relatively balanced profiles between acetylcholinesterase inhibition (IC₅₀ = 3.319 ± 0.708 μM), 5-HT_1A agonist (EC₅₀ = 107 ± 37 nM), and 5-HT reuptake inhibition (IC₅₀ = 76.3 ± 33 nM). Compound 1e displayed tolerable hepatotoxicity and moderate hERG inhibition activity, and could penetrate the blood-brain barrier in vivo. Furthermore, an oral intake of 30 mg/kg 1e·HCl could significantly improve the cognitive function of scopolamine-induced amnesia mice and alleviate the depressive symptom in tail suspension test. The effectivity of 1e validates the rationality of our design strategy.

Identification of a Novel 1,2,3,4-Tetrahydrobenzo[b][1,6]naphthyridine Analogue as a Potent Phosphodiesterase 5 Inhibitor with Improved Aqueous Solubility for the Treatment of Alzheimer's Disease

Phosphodiesterase 5 (PDE5) hydrolyzes cyclic guanosine monophosphate (cGMP) leading to increased levels of the cAMP response element binding protein (CREB), a transcriptional factor involved with learning and memory processes. We previously reported potent quinoline-based PDE5 inhibitors (PDE5Is) for the treatment of Alzheimer's disease (AD). However, the low aqueous solubility rendered them undesirable drug candidates. Here we report a series of novel PDE5Is with two new scaffolds, 1,2,3,4-tetrahydrobenzo[b][1,6]naphthyridine and 2,3-dihydro-1H-pyrrolo[3,4-b]quinolin-1-one. Among them, compound 6c, 2-acetyl-10-((3-chloro-4-methoxybenzyl)amino)-1,2,3,4-tetrahydrobenzo[b][1,6]naphthyridine-8-carbonitrile, the most potent compound, has an excellent in vitro IC₅₀ (0.056 nM) and improved aqueous solubility as well as good efficacy in a mouse model of AD. Furthermore, we are proposing two plausible binding modes obtained through in silico docking, which provide insights into the structural basis of the activity of the two series of compounds reported herein.