Molecular determinants of blood-brain barrier permeation

Charge-switchable cell-penetrating peptides for rerouting nanoparticles to glioblastoma treatment

Glioblastoma (GB) is one of the most lethal types of neoplasms with unique anatomic, physiologic, and pathologic features that usually persist after exposure to standard therapeutic modalities. It is biologically aggressive, and the existence of the blood-brain barrier (BBB) limits the efficacy of standard therapies. In this work, we hypothesize the potential of surface-functionalized ultra-small nanostructured lipid carriers (usNLCs) with charge-switchable cell-penetrating peptides (CPPs) to overcome this biological barrier and improve targeted delivery to brain tumor tissues. The big question is: what is the potential of CPPs in directing nanoparticles toward brain tumor tissue? To answer this question, the usNLCs were functionalized with distinct biomolecules [five CPPs, c(RGDfK) and transferrin, Tf] through electrostatic interaction and its ability as a targeting approach to BBB (HBMEC) and glioma cells (U87 cells) evaluated in terms of physicochemical properties, cellular uptake, permeability in a 2D-BBB model, and tumor growth inhibition. Monte Carlo simulations elucidated CPP adsorption patterns. The permeability studies revealed that targeted usNLCs, especially usNLCsTf and usNLCsCPP4, exhibited an increased permeability coefficient compared to the non-targeted usNLCs. Functionalized usNLCs evidenced enhanced uptake in BBB cells, with smaller CPPs showing higher internalization (CPP1 and CPP2). Similarly, functionalized usNLCs exhibited more significant cytotoxicity in glioma cells, with specific CPPs promoting favorable internalization. Analysis of the endocytic pathway indicated that usNLCsCPPs were mainly internalized by direct translocation and caveolae-mediated endocytosis. Optimal usNLCs with dual targeting capabilities to both BBB and GB cells provide a promising therapeutic strategy for GB.

Natural compound screening predicts novel GSK-3 isoform-specific inhibitors

Glycogen synthase kinase-3 (GSK-3) plays important roles in the pathogenesis of cardiovascular, metabolic, neurological disorders and cancer. Isoform-specific loss of either GSK-3α or GSK-3β often provides cytoprotective effects under such clinical conditions. However, available synthetic small molecule inhibitors are relatively non-specific, and their chronic use may lead to adverse effects. Therefore, screening for natural compound inhibitors to identify the isoform-specific inhibitors may provide improved clinical utility. Here, we screened 70 natural compounds to identify novel natural GSK-3 inhibitors employing comprehensive in silico and biochemical approaches. Molecular docking and pharmacokinetics analysis identified two natural compounds Psoralidin and Rosmarinic acid as potential GSK-3 inhibitors. Specifically, Psoralidin and Rosmarinic acid exhibited the highest binding affinities for GSK-3α and GSK-3β, respectively. Consistent with in silico findings, the kinase assay-driven IC50 revealed superior inhibitory effects of Psoralidin against GSK-3α (IC50 = 2.26 μM) vs. GSK-3β (IC50 = 4.23 μM) while Rosmarinic acid was found to be more potent against GSK-3β (IC50 = 2.24 μM) than GSK-3α (IC50 = 5.14 μM). Taken together, these studies show that the identified natural compounds may serve as GSK-3 inhibitors with Psoralidin serving as a better inhibitor for GSK-3α and Rosmarinic for GSK-3β isoform, respectively. Further characterization employing in vitro and preclinical models will be required to test the utility of these compounds as GSK-3 inhibitors for cardiometabolic and neurological disorders and cancers.

Machine Learning Exploration of the Relationship Between Drugs and the Blood-Brain Barrier: Guiding Molecular Modification

OBJECTIVE

This study aimed to improve the efficiency of pharmacotherapy for CNS diseases by optimizing the ability of drug molecules to penetrate the Blood-Brain Barrier (BBB).

METHODS

We established qualitative and quantitative databases of the ADME properties of drugs and derived characteristic features of compounds with efficient BBB penetration. Using these insights, we developed four machine learning models to predict a drug's BBB permeability by assessing ADME properties and molecular topology. We then validated the models using the B3DB database. For acyclovir and ceftriaxone, we modified the Hydrogen Bond Donors and Acceptors, and evaluated the BBB permeability using the predictive model.

RESULTS

The machine learning models performed well in predicting BBB permeability on both internal and external validation sets. Reducing the number of Hydrogen Bond Donors and Acceptors generally improves BBB permeability. Modification only enhanced BBB penetration in the case of acyclovir and not ceftriaxone.

CONCLUSIONS

The machine learning models developed can accurately predict BBB permeability, and many drug molecules are likely to have increased BBB penetration if the number of Hydrogen Bond Donors and Acceptors are reduced. These findings suggest that molecular modifications can enhance the efficacy of CNS drugs and provide practical strategies for drug design and development. This is particularly relevant for improving drug penetration of the BBB.

Unveiling the Potential of Ent-Kaurane Diterpenoids: Multifaceted Natural Products for Drug Discovery

Natural products hold immense potential for drug discovery, yet many remain unexplored in vast libraries and databases. In an attempt to fill this gap and meet the growing demand for effective drugs, this study delves into the promising world of ent-kaurane diterpenoids, a class of natural products with huge therapeutic potential. With a dataset of 570 ent-kaurane diterpenoids obtained from the literature, we conducted an in silico analysis, evaluating their physicochemical, pharmacokinetic, and toxicological properties with a focus on their therapeutic implications. Notably, these natural compounds exhibit drug-like properties, aligning closely with those of FDA-approved drugs, indicating a high potential for drug development. The ranges of the physicochemical parameters were as follows: molecular weights-288.47 to 626.82 g/mol; number of heavy atoms-21 to 44; the number of hydrogen bond donors and acceptors-0 to 8 and 1 to 11, respectively; the number of rotatable bonds-0 to 11; fraction Csp3-0.65 to 1; and TPSA-20.23 to 189.53 Ų. Additionally, the majority of these molecules display favorable safety profiles, with only 0.70%, 1.40%, 0.70%, and 46.49% exhibiting mutagenic, tumorigenic, reproduction-enhancing, and irritant properties, respectively. Importantly, ent-kaurane diterpenoids exhibit promising biopharmaceutical properties. Their average lipophilicity is optimal for drug absorption, while over 99% are water-soluble, facilitating delivery. Further, 96.5% and 28.20% of these molecules exhibited intestinal and brain bioavailability, expanding their therapeutic reach. The predicted pharmacological activities of these compounds encompass a diverse range, including anticancer, immunosuppressant, chemoprotective, anti-hepatic, hepatoprotectant, anti-inflammation, antihyperthyroidism, and anti-hepatitis activities. This multi-targeted profile highlights ent-kaurane diterpenoids as highly promising candidates for further drug discovery endeavors.

Treating Alzheimer's disease using nanoparticle-mediated drug delivery strategies/systems

The administration of promising medications for the treatment of neurodegenerative disorders (NDDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) is significantly hampered by the blood-brain barrier (BBB). Nanotechnology has recently come to light as a viable strategy for overcoming this obstacle and improving drug delivery to the brain. With a focus on current developments and prospects, this review article examines the use of nanoparticles to overcome the BBB constraints to improve drug therapy for AD The potential for several nanoparticle-based approaches, such as those utilizing lipid-based, polymeric, and inorganic nanoparticles, to enhance drug transport across the BBB are highlighted. To shed insight on their involvement in aiding effective drug transport to the brain, methods of nanoparticle-mediated drug delivery, such as surface modifications, functionalization, and particular targeting ligands, are also investigated. The article also discusses the most recent findings on innovative medication formulations encapsulated within nanoparticles and the therapeutic effects they have shown in both preclinical and clinical testing. This sector has difficulties and restrictions, such as the need for increased safety, scalability, and translation to clinical applications. However, the major emphasis of this review aims to provide insight and contribute to the knowledge of how nanotechnology can potentially revolutionize the worldwide treatment of NDDs, particularly AD, to enhance clinical outcomes.

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).

Synthesis and Characterization of a New Carbon-11 Labeled Positron Emission Tomography Radiotracer for Orexin 2 Receptors Neuroimaging

Purpose

Orexin receptors (OXRs) play a crucial role in modulating various physiological and neuropsychiatric functions within the central nervous system (CNS). Despite their significance, the precise role of OXRs in the brain remains elusive. Positron emission tomography (PET) imaging is instrumental in unraveling CNS functions, and the development of specific PET tracers for OXRs is a current research focus.

Methods

The study investigated MDK-5220, an OX2R-selective agonist with promising binding properties (EC50 on OX2R: 0.023 μM, Ki on hOX2R: 0.14 μM). Synthesized and characterized as an OX2R PET probe, [11C]MDK-5220 was evaluated for its potential as a tracer. Biodistribution studies in mice were conducted to assess OX2R binding selectivity, with particular attention to its interaction with P-glycoprotein (P-gp) on the blood-brain barrier.

Results

[11C]MDK-5220 exhibited promising attributes as an OX2R PET probe, demonstrating robust OX2R binding selectivity in biodistribution studies. However, an observed interaction with P-gp impacted its brain uptake. Despite this limitation, [11C]MDK-5220 presents itself as a potential candidate for further development.

Discussion

The study provides insights into the functionality of the OX system and the potential of [11C]MDK-5220 as an OX2R PET probe. The observed interaction with P-gp highlights a consideration for future modifications to enhance brain uptake. The findings pave the way for innovative tracer development and propel ongoing research on OX systems, contributing to a deeper understanding of their role in the CNS.

Conclusion

[11C]MDK-5220 emerges as a promising OX2R PET probe, despite challenges related to P-gp interaction. This study lays the foundation for further exploration and development of PET probes targeting OXRs, opening avenues for advancing our understanding of OX system functionality within the brain.

Application of a new MDCKII-MDR1 cell model to measure the extent of drug distribution in vitro at equilibrium for prediction of in vivo unbound brain-to-plasma drug distribution

INTRO

Reliable estimates of drug uptake from blood to brain parenchyma are crucial in CNS drug discovery and development. While in vivo Kp,uu,brain estimates are the gold standard for investigating brain drug disposition, animal usage is a limitation to high throughput application. This study investigates an in vitro model using P-gp expressing MDCKII-MDR1 cells for predicting in vivo brain drug penetration.

METHODS

In vitro equilibrium distribution studies were conducted in apical and basolateral solutions with high protein content to estimate Kp,brain and Kp,uu,brain values. The correlation between in vitro and in vivo Kp,brain values for a set of compounds was examined.

RESULTS

We observed a good correlation between in vitro and in vivo Kp,brain values (R2 = 0.69, Slope: 1.6), indicating that the in vitro model could predict in vivo drug brain penetration. The 'unilateral (Uni-L)' in vitro setup correctly classified 5 out of 5 unrestricted compounds and 3 out of 5 restricted compounds. Possible reasons for the observed disparities for some compounds have been discussed, such as difference in transport areas between in vitro and in vivo settings and effect of pH changes.

CONCLUSION

The in vitro assay setup developed in this study holds promise for predicting in vivo drug brain penetration in CNS drug discovery. The correlation between in vitro and in vivo Kp,brain values, underscores that the model may have potential for early-stage screening. With minor refinements, this in vitro approach could reduce the reliance on in vivo experiments, accelerating the pace of CNS drug discovery and promoting a more ethical research approach.

In Silico Identification of a Potential TNF-Alpha Binder Using a Structural Similarity: A Potential Drug Repurposing Approach to the Management of Alzheimer's Disease

Introduction

Alzheimer's disease (AD) is a neurodegenerative disorder with no conclusive remedy. Yohimbine, found in Rauwolfia vomitoria, may reduce brain inflammation by targeting tumour necrosis factor-alpha (TNFα), implicated in AD pathogenesis. Metoserpate, a synthetic compound, may inhibit TNFα. The study is aimed at assessing the potential utility of repurposing metoserpate for TNFα inhibition to reduce neuronal damage and inflammation in AD. The development of safe and effective treatments for AD is crucial to address the growing burden of the disease, which is projected to double over the next two decades.

Methods

Our study repurposed an FDA-approved drug as TNFα inhibitor for AD management using structural similarity studies, molecular docking, and molecular dynamics simulations. Yohimbine was used as a reference compound. Molecular docking used SeeSAR, and molecular dynamics simulation used GROMACS.

Results

Metoserpate was selected from 10 compounds similar to yohimbine based on pharmacokinetic properties and FDA approval status. Molecular docking and simulation studies showed a stable interaction between metoserpate and TNFα over 100 ns (100000 ps). This suggests a reliable and robust interaction between the protein and ligand, supporting the potential utility of repurposing metoserpate for TNFα inhibition in AD treatment.

Conclusion

Our study has identified metoserpate, a previously FDA-approved antihypertensive agent, as a promising candidate for inhibiting TNFα in the management of AD.

Blood-brain barrier transporters: a translational consideration for CNS delivery of neurotherapeutics

INTRODUCTION

Successful neuropharmacology requires optimization of CNS drug delivery and, by extension, free drug concentrations at brain molecular targets. Detailed assessment of blood-brain barrier (BBB) physiological characteristics is necessary to achieve this goal. The 'next frontier' in CNS drug delivery is targeting BBB uptake transporters, an approach that requires evaluation of brain endothelial cell transport processes so that effective drug accumulation and improved therapeutic efficacy can occur.

AREAS COVERED

BBB permeability of drugs is governed by tight junction protein complexes (i.e., physical barrier) and transporters/enzymes (i.e., biochemical barrier). For most therapeutics, a component of blood-to-brain transport involves passive transcellular diffusion. Small molecule drugs that do not possess acceptable physicochemical characteristics for passive permeability may utilize putative membrane transporters for CNS uptake. While both uptake and efflux transport mechanisms are expressed at the brain microvascular endothelium, uptake transporters can be targeted for optimization of brain drug delivery and improved treatment of neurological disease states.

EXPERT OPINION

Uptake transporters represent a unique opportunity to optimize brain drug delivery by leveraging the endogenous biology of the BBB. A rigorous understanding of these transporters is required to improve translation from the bench to clinical trials and stimulate the development of new treatment paradigms for neurological diseases.

Lead-oriented synthesis of epigenetic relevant scaffolds

A simple and rational method to rank lead-likeness of molecules using continuous evaluation functions was hereby developed. This strategy proved to be competitive against known methods and finally helped in driving synthetic efforts towards candidates of interest for epigenetic applications against HDAC6, BRD4 and EZH2.

Emerging applications of anti-angiogenic nanomaterials in oncotherapy

Angiogenesis is the process of generating new blood vessels from pre-existing vasculature. Under normal conditions, this process is delicately controlled by pro-angiogenic and anti-angiogenic factors. Tumor cells can produce plentiful pro-angiogenic molecules promoting pathological angiogenesis for uncontrollable growth. Therefore, anti-angiogenic therapy, which aims to inhibit tumor angiogenesis, has become an attractive approach for oncotherapy. However, classic anti-angiogenic agents have several limitations in clinical use, such as lack of specific targeting, low bioavailability, and poor therapeutic outcomes. Hence, alternative angiogenic inhibitors are highly desired. With the emergence of nanotechnology, various nanomaterials have been designed for anti-angiogenesis purposes, offering promising features like excellent targeting capabilities, reduced side effects, and enhanced therapeutic efficacy. In this review, we describe tumor vascular features, discuss current dilemma of traditional anti-angiogenic medicines in oncotherapy, and underline the potential of nanomaterials in tumor anti-angiogenic therapy. Moreover, we discuss the current challenges of anti-angiogenic cancer treatment. We expect that this summary of anti-angiogenic nanomaterials in oncotherapy will offer valuable insights, facilitating their extensive applications in the future.

Recent Advancements and Strategies for Overcoming the Blood-Brain Barrier Using Albumin-Based Drug Delivery Systems to Treat Brain Cancer, with a Focus on Glioblastoma

Glioblastoma multiforme (GBM) is a highly aggressive malignant tumor, and the most prevalent primary malignant tumor affecting the brain and central nervous system. Recent research indicates that the genetic profile of GBM makes it resistant to drugs and radiation. However, the main obstacle in treating GBM is transporting drugs through the blood-brain barrier (BBB). Albumin is a versatile biomaterial for the synthesis of nanoparticles. The efficiency of albumin-based delivery systems is determined by their ability to improve tumor targeting and accumulation. In this review, we will discuss the prevalence of human glioblastoma and the currently adopted treatment, as well as the structure and some essential functions of the BBB, to transport drugs through this barrier. We will also mention some aspects related to the blood-tumor brain barrier (BTBB) that lead to poor treatment efficacy. The properties and structure of serum albumin were highlighted, such as its role in targeting brain tumors, as well as the progress made until now regarding the techniques for obtaining albumin nanoparticles and their functionalization, in order to overcome the BBB and treat cancer, especially human glioblastoma. The albumin drug delivery nanosystems mentioned in this paper have improved properties and can overcome the BBB to target brain tumors.

TIMP-1 Protects Tight Junctions of Brain Endothelial Cells From MMP-Mediated Degradation

OBJECTIVE

The blood-brain barrier (BBB) plays a critical role in central nervous system homeostasis, and the integrity of BBB is disrupted in many neurodegenerative diseases. Matrix metalloproteinases (MMPs) degrade the tight junctions (TJs) of endothelial cells and basement membrane components essential to BBB integrity, which leads to increased BBB permeability and allows inflammatory cells and neurotoxic substances to enter the brain. Tissue inhibitors of metalloproteinases (TIMPs), endogenous inhibitors of MMPs, regulate MMP activity, thereby maintaining BBB integrity.

METHODS

The disruptive impacts of MMP-3 and MMP-9 on BBB and protective effect of TIMP-1 were investigated in a simplified in vitro model of the BBB, which was generated using rat brain microvascular endothelial cells (RBMEC). The main features of BBB formation, including permeability and the trans-endothelial electrical resistance (TEER), were monitored over time after the addition of MMP-3 and MMP-9 and their complexes with TIMP-1 inhibitor.

RESULTS

Our results indicated that MMP-3 and MMP-9 caused a dose-dependent disruption of the BBB, with 1.5 µM MMPs resulting in an over threefold increase in permeability, while TIMP-1 inhibition protected the integrity of the BBB model and recovered TEER and permeability of RBMECs. The disruption and recovery of tight junction proteins of RBMECs after MMP and TIMP treatment were also detected using fluorescent microscopy.

CONCLUSION

MMP-9 and MMP-3 disrupt the BBB by degrading tight junctions in endothelial cells, and TIMP-1 could inhibit the disruptive effect of MMP-3 and MMP-9 by showing potential as therapeutic protein against MMP-related diseases where BBB disruption plays a role.

Neuroprotective mechanism of Ajugarin-I against Vincristine-Induced neuropathic pain via regulation of Nrf2/NF-κB and Bcl2 signalling

Vincristine (VCR) is a well-known chemotherapeutic agent that frequently triggers neuropathic pain. Ajugarin-I (Aju-I) isolated from Ajuga bracteosa exerts antioxidant, anti-inflammatory, and neuroprotective properties. The present study was designed to investigate the ameliorative potential of Aju-I against VCR-induced neuropathic pain and explored the underlying mechanism involved. The neuroprotective potential of Aju-I was first confirmed against hydrogen peroxide (H₂O₂)-induced cytotoxicity and oxidative stress in PC12 cells. For neuropathic pain induction, vincristine was given intraperitoneally (i.p.) into adult male albino mice (BALB/c) of the same age (8-12 weeks old) for 10 days (days 1-10). Aju-I (1 and 5 mg/kg) doses were administered from day 11 to 21 intraperitoneally (i.p.) after the neuropathic induction. Initially, behavioral tests such as thermal hyperalgesia, mechanical allodynia, and cold allodynia were performed to investigate the antinociceptive potential of Ajugarin-I (1 and 5 mg/kg, b.w). The nuclear factor-erythroid factor 2-related factor 2(Nrf2), nuclear factor-κB (NF-κB), BCL2-associated × protein (Bax), and B-cell-lymphoma-2 (Bcl-2) signaling proteins were determined by immunohistochemistry and western blot. Additionally, inflammatory cytokines, antioxidant, and oxidative stress parameters were also measured in the spinal cord and sciatic nerve. The behavioral results demonstrated that Aju-I (5 mg/kg) markedly alleviated VCR-induced neuropathic pain behaviors including hyperalgesia and allodynia. It reversed the histological alterations caused by VCR in the sciatic nerve, spinal cord, and brain. It significantly alleviated oxidative stress and inflammation by regulating the immunoreactivity of Nrf2/NF-κB signaling. It suppressed apoptosis by regulating the immunoreactivity of Bcl-2/Bax and Caspase-3. The flow cytometry and comet analysis also confirmed its anti-apoptotic potential. It considerably improved the antioxidant status and mitigated VCR-induced inflammatory cytokines. High-performance liquid chromatography (HPLC) analysis indicated that Aju-I crosses the blood-brain barrier (BBB) and penetrated the brain tissue. These findings suggest that Aju-I treatment inhibited vincristine-induced neuropathy via regulation of Nrf2/NF-κB and Bcl2 signaling.

Angiotensin II receptor blockers (ARBs) and manufacturing contamination: A retrospective National Register Study into suspected associated adverse drug reactions

AIMS

The aim of this study was to determine if any suspected adverse drug reactions (ADRs) observed with the use of angiotensin II receptor blockers (ARBs) could be linked to either (a) their unique respective physicochemical and pharmacological profiles and (b) the recently disclosed suspected carcinogenic manufacturing contaminants found in certain sartan drug class batches.

METHODS

The pharmacology profiles of ARBs were data-mined from the Chemical Database of bioactive molecules with drug-like properties, European Molecular Biology Laboratory (ChEMBL). Suspected ADR data (from 01/2016-10/2022, inclusive) and prescribing rates of ARBs over a 5-year prescribing window (from 09/2016 to 08/2021, inclusive) were obtained via analysis of the United Kingdom Medicines and Healthcare products Regulatory Authority (MHRA) Yellow Card drug analysis profile and Open prescribing databases, respectively.

RESULTS

The overall suspected ADRs and fatalities per 100 000 prescriptions identified across the ARBs studied were found to be different between the sartan drug class members (chi-squared test, P < .05). There is a greater relative rate of reports for valsartan across all investigated organ classes of ADRs, than other ARBs, despite valsartan's more limited pharmacological profile and similar physicochemical properties to other sartans. The disparity in ADR reporting rates with valsartan vs other ARBs could be due to the dissimilarity in formulation excipients, patient factors and publicity surrounding batch contaminations, amongst others. Cancer-related ADRs and fatalities per 100 000 prescriptions identified across the ARBs studied are not statistically significant (chi-squared test, P > .05) based on the datasets used over the 5-year period.

CONCLUSION

No connection between ARB pharmacology and their suspected ADRs could be found. No conclusion between sartan batch contaminations and increased suspected cancer-related ADRs was found.

Development of QSAR models to predict blood-brain barrier permeability

Assessing drug permeability across the blood-brain barrier (BBB) is important when evaluating the abuse potential of new pharmaceuticals as well as developing novel therapeutics that target central nervous system disorders. One of the gold-standard in vivo methods for determining BBB permeability is rodent log BB; however, like most in vivo methods, it is time-consuming and expensive. In the present study, two statistical-based quantitative structure-activity relationship (QSAR) models were developed to predict BBB permeability of drugs based on their chemical structure. The in vivo BBB permeability data were harvested for 921 compounds from publicly available literature, non-proprietary drug approval packages, and University of Washington's Drug Interaction Database. The cross-validation performance statistics for the BBB models ranged from 82 to 85% in sensitivity and 80-83% in negative predictivity. Additionally, the performance of newly developed models was assessed using an external validation set comprised of 83 chemicals. Overall, performance of individual models ranged from 70 to 75% in sensitivity, 70-72% in negative predictivity, and 78-86% in coverage. The predictive performance was further improved to 93% in coverage by combining predictions across the two software programs. These new models can be rapidly deployed to predict blood brain barrier permeability of pharmaceutical candidates and reduce the use of experimental animals.

Pharmacophore Modeling Using Machine Learning for Screening the Blood-Brain Barrier Permeation of Xenobiotics

Daily exposure to xenobiotics affects human health, especially the nervous system, causing neurodegenerative diseases. The nervous system is protected by tight junctions present at the blood-brain barrier (BBB), but only molecules with desirable physicochemical properties can permeate it. This is why permeation is a decisive step in avoiding unwanted brain toxicity and also in developing neuronal drugs. In silico methods are being implemented as an initial step to reduce animal testing and the time complexity of the in vitro screening process. However, most in silico methods are ligand based, and consider only the physiochemical properties of ligands. However, these ligand-based methods have their own limitations and sometimes fail to predict the BBB permeation of xenobiotics. The objective of this work was to investigate the influence of the pharmacophoric features of protein-ligand interactions on BBB permeation. For these purposes, receptor-based pharmacophore and ligand-based pharmacophore fingerprints were developed using docking and Rdkit, respectively. Then, these fingerprints were trained on classical machine-learning models and compared with classical fingerprints. Among the tested footprints, the ligand-based pharmacophore fingerprint achieved slightly better (77% accuracy) performance compared to the classical fingerprint method. In contrast, receptor-based pharmacophores did not lead to much improvement compared to classical descriptors. The performance can be further improved by considering efflux proteins such as BCRP (breast cancer resistance protein), as well as P-gp (P-glycoprotein). However, the limited data availability for other proteins regarding their pharmacophoric interactions is a bottleneck to its improvement. Nonetheless, the developed models and exploratory analysis provide a path to extend the same framework for environmental chemicals, which, like drugs, are also xenobiotics. This research can help in human health risk assessment by a priori screening for neurotoxicity-causing agents.

Cheminformatics Identification and Validation of Dipeptidyl Peptidase-IV Modulators from Shikimate Pathway-Derived Phenolic Acids towards Interventive Type-2 Diabetes Therapy

Recently, dipeptidyl peptidase-IV (DPP-IV) has become an effective target in the management of type-2 diabetes mellitus (T2D). The study aimed to determine the efficacy of shikimate pathway-derived phenolic acids as potential DPP-IV modulators in the management of T2D. The study explored in silico (molecular docking and dynamics simulations) and in vitro (DPP-IV inhibitory and kinetics assays) approaches. Molecular docking findings revealed chlorogenic acid (CA) among the examined 22 phenolic acids with the highest negative binding energy (−9.0 kcal/mol) showing a greater affinity for DPP-IV relative to the standard, Diprotin A (−6.6 kcal/mol). The result was corroborated by MD simulation where it had a higher affinity (−27.58 kcal/mol) forming a more stable complex with DPP-IV than Diprotin A (−12.68 kcal/mol). These findings were consistent with in vitro investigation where it uncompetitively inhibited DPP-IV having a lower IC₅₀ (0.3 mg/mL) compared to Diprotin A (0.5 mg/mL). While CA showed promising results as a DPP-IV inhibitor, the findings from the study highlighted the significance of medicinal plants particularly shikimate-derived phenolic compounds as potential alternatives to synthetic drugs in the effective management of T2DM. Further studies, such as derivatisation for enhanced activity and in vivo evaluation are suggested to realize its full potential in T2D therapy.

Metabolite Profiling of the Environmental-Controlled Growth of Marsilea crenata Presl. and Its In Vitro and In Silico Antineuroinflammatory Properties

This study was aimed to evaluate the metabolite contents and antineuroinflammatory potential of Marsilea crenata Presl. grown under a controlled environmental condition. The antineuroinflammatory test has been carried out in vitro using ethanolic extract of M. crenata leaves on HMC3 microglia cells. An in silico approach was applied to predict the active compounds of the extract. The HMC3 microglia cells were induced with IFNγ to create prolonged inflammatory conditions and then treated with 96% ethanolic extract of the M. crenata leaves of 62.5, 125, and 250 μg/mL. The expression of MHC II was analyzed using the ICC method with the CLSM instrument. Metabolites of the extract were profiled using UPLC-QToF-MS/MS instrument and MassLynx 4.1 software. In silico evaluation was conducted with molecular docking on 3OLS protein using PyRx 0.8 software, and physicochemical properties of the compounds were analyzed using SwissADME webtool. The ethanolic extract of M. crenata leaves could reduce the MHC II expression in HMC3 microglia cells in all concentrations with the values 97.458, 139.574, and 82.128 AU. The result of metabolite profiling found 79 compounds in the extract. In silico evaluation showed that 19 compounds gave agonist interaction toward 3OLS, and three met all parameters of physicochemical analysis. The ethanolic extract of the environmental-controlled growth of M. crenata leaves antineuroinflammatory activity on HMC3 microglia cells. The extract was predicted to contain some phytoestrogen compounds which act as 3OLS agonists.

Quantitative Retention (Structure)–Activity Relationships in Predicting the Pharmaceutical and Toxic Properties of Potential Pesticides

The micellar liquid chromatography technique and quantitative retention (structure)–activity relationships method were used to predict properties of carbamic and phenoxyacetic acids derivatives, newly synthesized in our laboratory and considered as potential pesticides. Important properties of the test substances characterizing their potential significance as pesticides as well as threats to humans were considered: the volume of distribution, the unbonded fractions, the blood–brain distribution, the rate of skin and cell permeation, the dermal absorption, the binding to human serum albumin, partitioning between water and plants’ cuticles, and the lethal dose. Pharmacokinetic and toxicity parameters were predicted as functions of the solutes’ lipophilicities and the number of hydrogen bond donors, the number of hydrogen bond acceptors, and the number of rotatable bonds. The equations that were derived were evaluated statistically and cross-validated. Important features of the molecular structure influencing the properties of the tested substances were indicated. The QSAR models that were developed had high predictive ability and high reliability in modeling the properties of the molecules that were tested. The investigations highlighted the applicability of combined chromatographic technique and QS(R)ARs in modeling the important properties of potential pesticides and reducing unethical animal testing.

Novel mitoNEET ligand NL-1 improves therapeutic outcomes in an aged rat model of cerebral ischemia/reperfusion injury

Cerebral ischemic stroke is a leading cause of mortality and disability worldwide. Currently, there are a lack of drugs capable of reducing neuronal cell loss due to ischemia/reperfusion-injury after stroke. Previously, we identified mitoNEET, a [2Fe-2S] redox mitochondrial protein, as a putative drug target for ischemic stroke. In this study, we tested NL-1, a novel mitoNEET ligand, in a preclinical model of ischemic stroke with reperfusion using aged female rats. Using a transient middle cerebral artery occlusion (tMCAO), we induced a 2 h ischemic injury and then evaluated the effects of NL-1 treatment on ischemic/reperfusion brain injury at 24 and 72 h. Test compounds were administered at time of reperfusion via intravenous dosing. Results of the study demonstrated that NL-1 (10 mg/kg) treatment markedly improved survival and reduced infarct volume and hemispheric swelling in the brain as compared aged rats treated with vehicle or a lower dose of NL-1 (0.25 mg/kg). Interestingly, the protective effect of NL-1 was significantly improved when encapsulated in PLGA nanoparticles, where a 40-fold lesser dose (0.25 mg/kg) of NL-1 produced an equivalent effect as the 10 mg/kg dose. Evaluation of changes in blood-brain barrier permeability and lipid peroxidation corroborated the protective actions of NL-1 (10 mg/kg) or NL-1 NP treatment demonstrated a reduced accumulation of parenchymal IgG, decreased levels of 4-hydroxynonenal (4-HNE) and a decreased TUNEL positive cells in the brains of aged female rats at 72 h after tMCAO with reperfusion. Our studies indicate that targeting mitoNEET following ischemia/reperfusion-injury is a novel drug target pathway that warrants further investigation.

Point-specific interactions of isovitexin with the neighboring amino acid residues of the hACE2 receptor as a targeted therapeutic agent in suppressing the SARS-CoV-2 influx mechanism

Objective:

Despite the development of several vaccines against severe acute respiratory syndrome coronavirus-2, the need for an additional prophylactic agent is evident. In recent in silico studies, isovitexin exhibited a higher binding affinity against the human angiotensin converting-enzyme 2 (hACE2) receptor than existing antiviral drugs. The research aimed to find out the point specificity of isovitexin for the hACE2 receptor and to assess its therapeutic potential, depending on the stability of the isovitexin–hACE2 complex.

Materials and Methods:

The pharmacokinetic profile of isovitexin was analyzed. The crystal structure of the hACE2 receptor and the ligand isovitexin were docked to form a ligand–protein complex following molecular optimization. To determine the isovitexin–hACE2 complex stability, their binding affinity, hydrogen bonding, and hydrophobic interactions were studied. Lastly, the root mean square deviation (RMSD), root mean square fluctuation, solvent accessible surface area, molecular surface area, radius of gyration (Rg), polar surface area, and principal component analysis values were found by simulating the complex with molecular dynamic (MD).

Results:

The predicted Lethal dose₅₀ for isovitexin was 2.56 mol/kg, with an acceptable maximum tolerated dose and no hepatotoxicity or AMES toxicity. Interactions with the amino acid residues Thr371, Asp367, Glu406, Pro346, His345, Phe274, Tyr515, Glu375, Thr347, Glu402, and His374 of the hACE2 protein were required for the high binding affinity and specificity of isovitexin. Based on what was learned from the MD simulation, the hACE2 receptor-blocking properties of isovitexin were looked at.

Conclusions:

Isovitexin is a phytochemical with a reasonable bioactivity and safety profile for use in humans, and it can potentially be used as a hACE2-specific therapeutic to inhibit COVID-19 infection.

Biological Membrane-Penetrating Peptides: Computational Prediction and Applications

Peptides comprise a versatile class of biomolecules that present a unique chemical space with diverse physicochemical and structural properties. Some classes of peptides are able to naturally cross the biological membranes, such as cell membrane and blood-brain barrier (BBB). Cell-penetrating peptides (CPPs) and blood-brain barrier-penetrating peptides (B3PPs) have been explored by the biotechnological and pharmaceutical industries to develop new therapeutic molecules and carrier systems. The computational prediction of peptides’ penetration into biological membranes has been emerged as an interesting strategy due to their high throughput and low-cost screening of large chemical libraries. Structure- and sequence-based information of peptides, as well as atomistic biophysical models, have been explored in computer-assisted discovery strategies to classify and identify new structures with pharmacokinetic properties related to the translocation through biomembranes. Computational strategies to predict the permeability into biomembranes include cheminformatic filters, molecular dynamics simulations, artificial intelligence algorithms, and statistical models, and the choice of the most adequate method depends on the purposes of the computational investigation. Here, we exhibit and discuss some principles and applications of these computational methods widely used to predict the permeability of peptides into biomembranes, exhibiting some of their pharmaceutical and biotechnological applications.

Design, Synthesis, and Biological Evaluation of 4,4’-Difluorobenzhydrol Carbamates as Selective M1 Antagonists

Due to their important role in mediating a broad range of physiological functions, muscarinic acetylcholine receptors (mAChRs) have been a promising target for therapeutic and diagnostic applications alike; however, the list of truly subtype-selective ligands is scarce. Within this work, we have identified a series of twelve 4,4’-difluorobenzhydrol carbamates through a rigorous docking campaign leveraging commercially available amine databases. After synthesis, these compounds have been evaluated for their physico–chemical property profiles, including characteristics such as HPLC-logD, tPSA, logBB, and logPS. For all the synthesized carbamates, these characteristics indicate the potential for BBB permeation. In competitive radioligand binding experiments using Chinese hamster ovary cell membranes expressing the individual human mAChR subtype hM1-hM5, the most promising compound 2 displayed a high binding affinitiy towards hM1R (1.2 nM) while exhibiting modest-to-excellent selectivity versus the hM2-5R (4–189-fold). All 12 compounds were shown to act in an antagonistic fashion towards hM1R using a dose-dependent calcium mobilization assay. The structural eligibility for radiolabeling and their pharmacological and physico–chemical property profiles render compounds 2, 5, and 7 promising candidates for future position emission tomography (PET) tracer development.

Active site-specific quantum tunneling of hACE2 receptor to assess its complexing poses with selective bioactive compounds in co-suppressing SARS-CoV-2 influx and subsequent cardiac injury

Objective:

This research aims to study the target specificity of selective bioactive compounds in complexing with the human angiotensin-converting enzyme (hACE2) receptor to impede the severe acute respiratory syndrome coronavirus 2 influx mechanism resulting in cardiac injury and depending on the receptor’s active site properties and quantum tunneling.

Materials and Methods:

A library of 120 phytochemical ligands was prepared, from which 5 were selected considering their absorption, distribution, metabolism, and excretion (ADMET) and quantitative structure–activity relationship (QSAR) profiles. The protein active sites and belonging quantum tunnels were defined to conduct supramolecular docking of the aforementioned ligands. The hydrogen bond formation and hydrophobic interactions between the ligand–receptor complexes were studied following the molecular docking steps. A comprehensive molecular dynamic simulation (MDS) was conducted for each of the ligand–receptor complexes to figure out the values – root mean square deviation (RMSD) (Å), root mean square fluctuation (RMSF) (Å), H-bonds, Cα, solvent accessible surface area (SASA) (Ų), molecular surface area (MolSA) (Ų), Rg (nm), and polar surface area (PSA) (Å). Finally, computational programming and algorithms were used to interpret the dynamic simulation outputs into their graphical quantitative forms.

Results:

ADMET and QSAR profiles revealed that the most active candidates from the library to be used were apigenin, isovitexin, piperolactam A, and quercetin as test ligands, whereas serpentine as the control. Based on the binding affinities of supramolecular docking and the parameters of molecular dynamic simulation, the strength of the test ligands can be classified as isovitexin > quercetin > piperolactam A > apigenin when complexed with the hACE2 receptor. Surprisingly, serpentine showed lower affinity (−8.6 kcal/mol) than that of isovitexin (−9.9 kcal/mol) and quercetin (−8.9 kcal/mol). The MDS analysis revealed all ligands except isovitexin having a value lower than 2.5 Ǻ. All the test ligands exhibited acceptable fluctuation ranges of RMSD (Å), RMSF (Å), H-bonds, Cα, SASA (Ų), MolSA (Ų), Rg (nm), and PSA (Å) values.

Conclusion:

Considering each of the parameters of molecular optimization, docking, and dynamic simulation interventions, all of the test ligands can be suggested as potential targeted drugs in blocking the hACE2 receptor.

The novel BET inhibitor UM-002 reduces glioblastoma cell proliferation and invasion

Bromodomain and extraterminal domain (BET) proteins have emerged as therapeutic targets in multiple cancers, including the most common primary adult brain tumor glioblastoma (GBM). Although several BET inhibitors have entered clinical trials, few are brain penetrant. We have generated UM-002, a novel brain penetrant BET inhibitor that reduces GBM cell proliferation in vitro and in a human cerebral brain organoid model. Since UM-002 is more potent than other BET inhibitors, it could potentially be developed for GBM treatment. Furthermore, UM-002 treatment reduces the expression of cell-cycle related genes in vivo and reduces the expression of invasion related genes within the non-proliferative cells present in tumors as measured by single cell RNA-sequencing. These studies suggest that BET inhibition alters the transcriptional landscape of GBM tumors, which has implications for designing combination therapies. Importantly, they also provide an integrated dataset that combines in vitro and ex vivo studies with in vivo single-cell RNA-sequencing to characterize a novel BET inhibitor in GBM.

The cognitive effect of anticholinergics for patients with overactive bladder

Overactive bladder (OAB) is often treated with medications that block the cholinergic receptors in the bladder (known as anticholinergics). The effect of this medication class on cognition and risk of dementia has been increasingly studied over the past 40 years after initial studies suggested that the anticholinergic medication class could affect memory. Short-term randomized clinical trials demonstrated that the administration of the anticholinergic oxybutynin leads to impaired memory and attention, and large, population-based studies showed associations between several different anticholinergic medications and dementia. However, trials involving anticholinergics other than oxybutynin have not shown such substantial effects on short-term cognitive function. This discordance in results between short-term cognitive safety of OAB anticholinergics and the long-term increased dementia risk could be explained by the high proportion of patients using oxybutynin in the OAB subgroups of the dementia studies, or a study duration that was too short in the prospective clinical trials on cognition with other OAB anticholinergics. Notably, all studies must be interpreted in the context of potential confounding factors, such as when prodromal urinary symptoms associated with the early stages of dementia lead to an increase in OAB medication use, rather than the use of OAB medication causing dementia. In patients with potential risk factors for cognitive impairment, the cautious use of selected OAB anticholinergic agents with favourable physicochemical and pharmacokinetic properties and clinical trial evidence of cognitive safety might be appropriate.

Physiologically Based Pharmacokinetic (PBPK) Modeling for Predicting Brain Levels of Drug in Rat

One of the main obstacles in neurological disease treatment is the presence of the blood-brain barrier. New predictive high-throughput screening tools are essential to avoid costly failures in the advanced phases of development and to contribute to the 3 Rs policy. The objective of this work was to jointly develop a new in vitro system coupled with a physiological-based pharmacokinetic (PBPK) model able to predict brain concentration levels of different drugs in rats. Data from in vitro tests with three different cells lines (MDCK, MDCK-MDR1 and hCMEC/D3) were used together with PK parameters and three scaling factors for adjusting the model predictions to the brain and plasma profiles of six model drugs. Later, preliminary quantitative structure-property relationships (QSPRs) were constructed between the scaling factors and the lipophilicity of drugs. The predictability of the model was evaluated by internal validation. It was concluded that the PBPK model, incorporating the barrier resistance to transport, the disposition within the brain and the drug-brain binding combined with MDCK data, provided the best predictions for passive diffusion and carrier-mediated transported drugs, while in the other cell lines, active transport influence can bias predictions.

Blood-brain barrier models: Rationale for selection

Brain delivery is a broad research area, the outcomes of which are far hindered by the limited permeability of the blood-brain barrier (BBB). Over the last century, research has been revealing the BBB complexity and the crosstalk between its cellular and molecular components. Pathologically, BBB alterations may precede as well as be concomitant or lead to brain diseases. To simulate the BBB and investigate options for drug delivery, several in vitro, in vivo, ex vivo, in situ and in silico models are used. Hundreds of drug delivery vehicles successfully pass preclinical trials but fail in clinical settings. Inadequate selection of BBB models is believed to remarkably impact the data reliability leading to unsatisfactory results in clinical trials. In this review, we suggest a rationale for BBB model selection with respect to the addressed research question and downstream applications. The essential considerations of an optimal BBB model are discussed.

Neutrophil Delivered Hollow Titania Covered Persistent Luminescent Nanosensitizer for Ultrosound Augmented Chemo/Immuno Glioblastoma Therapy

Glioblastoma (GBM) is the most malignant brain tumor with unmet therapeutic demand. The blood-brain-barrier (BBB) and tumor heterogeneity limit the treatment effectiveness of various interventions. Here, an ultrasound augmented chemo/immuno therapy for GBM using a neutrophil-delivered nanosensitizer, is developed. The sensitizer is composed of a ZnGa2 O4 :Cr3+ (ZGO) core for persistent luminescence imaging and a hollow sono-sensitive TiO2 shell to generate reactive oxygen species (ROS) for controlled drug release. Immune checkpoint inhibitor (Anti-PD-1 antibody) is trapped in the interior of the porous ZGO@TiO2 with paclitaxel (PTX) loaded liposome encapsulation to form ZGO@TiO2 @ALP. Delivered by neutrophils (NEs), ZGO@TiO2 @ALP-NEs can penetrate through BBB for GBM accumulation. After intravenous injection, ultrasound irradiation at GBM sites initiates ROS generation from ZGO@TiO2 @ALP, leading to liposome destruction for PTX and anti-PD-1 antibody release to kill tumors and induce local inflammation, which in-turn attractes more ZGO@TiO2 @ALP-NEs to migrate into tumor sites for augmented and sustained therapy. The treatment enhances the survival rate of the GBM bearing mice from 0% to 40% and endows them with long-term immuno-surveillance for tumor recurrence, providing a new approach for precision therapy against GBM and other cancers.

First-in-Class Isonipecotamide-Based Thrombin and Cholinesterase Dual Inhibitors with Potential for Alzheimer Disease

Recently, the direct thrombin (thr) inhibitor dabigatran has proven to be beneficial in animal models of Alzheimer’s disease (AD). Aiming at discovering novel multimodal agents addressing thr and AD-related targets, a selection of previously and newly synthesized potent thr and factor Xa (fXa) inhibitors were virtually screened by the Multi-fingerprint Similarity Searching aLgorithm (MuSSeL) web server. The N-phenyl-1-(pyridin-4-yl)piperidine-4-carboxamide derivative 1, which has already been experimentally shown to inhibit thr with a K_i value of 6 nM, has been flagged by a new, upcoming release of MuSSeL as a binder of cholinesterase (ChE) isoforms (acetyl- and butyrylcholinesterase, AChE and BChE), as well as thr, fXa, and other enzymes and receptors. Interestingly, the inhibition potency of 1 was predicted by the MuSSeL platform to fall within the low-to-submicromolar range and this was confirmed by experimental K_i values, which were found equal to 0.058 and 6.95 μM for eeAChE and eqBChE, respectively. Thirty analogs of 1 were then assayed as inhibitors of thr, fXa, AChE, and BChE to increase our knowledge of their structure-activity relationships, while the molecular determinants responsible for the multiple activities towards the target enzymes were rationally investigated by molecular cross-docking screening.

Conjugation with Phospholipids as a Modification Increasing Anticancer Activity of Phenolic Acids in Metastatic Melanoma-In Vitro and In Silico Studies

Phenolic acids possess many beneficial biological activities, including antioxidant and anti-inflammatory properties. Unfortunately, their low bioavailability restricts their potential medical uses, as it limits the concentration of phenolic acids achievable in the organism. The conjugation with phospholipids constitutes one of the most effective strategies to enhance compounds bioavailability in biological systems. In the present study, the conjugates of anisic (ANISA) and veratric acid (VA) with phosphatidylcholine (PC) were investigated. Since both ANISA and VA are inhibitors of tyrosinase, a melanocyte enzyme, the expression of which increases during tumorigenesis, anticancer potential of the conjugates was tested in several metastatic melanoma cell lines. The conjugates proved to be antiproliferative, apoptosis-inducing and cell-cycle-affecting agents, selective for cancerous cells and not affecting normal fibroblasts. The conjugates substituted by ANISA and VA, respectively, at both the sn-1 and sn-2 positions of PC, appeared the most promising, since they were effective against the vast majority of metastatic melanoma cell lines. Additionally, the conjugation of phenolic acids to PC increased their antioxidant activity. Molecular modeling was employed for the first time to estimate the features of the investigated conjugates relevant to their anticancer properties and membrane permeation. Again, the conjugates substituted by phenolic acid at both the sn-1 and sn-2 positions of PC seemed to be presumably most bioavailable.

Chemical tools for epichaperome-mediated interactome dysfunctions of the central nervous system

Diseases are a manifestation of how thousands of proteins interact. In several diseases, such as cancer and Alzheimer’s disease, proteome-wide disturbances in protein-protein interactions are caused by alterations to chaperome scaffolds termed epichaperomes. Epichaperome-directed chemical probes may be useful for detecting and reversing defective chaperomes. Here we provide structural, biochemical, and functional insights into the discovery of epichaperome probes, with a focus on their use in central nervous system diseases. We demonstrate on-target activity and kinetic selectivity of a radiolabeled epichaperome probe in both cells and mice, together with a proof-of-principle in human patients in an exploratory single group assignment diagnostic study (ClinicalTrials.gov Identifier: NCT03371420). The clinical study is designed to determine the pharmacokinetic parameters and the incidence of adverse events in patients receiving a single microdose of the radiolabeled probe administered by intravenous injection. In sum, we introduce a discovery platform for brain-directed chemical probes that specifically modulate epichaperomes and provide proof-of-principle applications in their use in the detection, quantification, and modulation of the target in complex biological systems.

Here, the authors show structural, biochemical, and functional insights into the discovery of epichaperome‐ directed chemical probes for use in central nervous system diseases. Probes emerging from this work have translated to human clinical studies in Alzheimer’s disease and cancer.

Evolution of blood-brain barrier in brain diseases and related systemic nanoscale brain-targeting drug delivery strategies

Blood–brain barrier (BBB) strictly controls matter exchange between blood and brain, and severely limits brain penetration of systemically administered drugs, resulting in ineffective drug therapy of brain diseases. However, during the onset and progression of brain diseases, BBB alterations evolve inevitably. In this review, we focus on nanoscale brain-targeting drug delivery strategies designed based on BBB evolutions and related applications in various brain diseases including Alzheimer's disease, Parkinson's disease, epilepsy, stroke, traumatic brain injury and brain tumor. The advances on optimization of small molecules for BBB crossing and non-systemic administration routes (e.g., intranasal treatment) for BBB bypassing are not included in this review.

The New PI3K/mTOR Inhibitor GNE-477 Inhibits the Malignant Behavior of Human Glioblastoma Cells

The most common primary central nervous system tumor in adults is glioblastoma multiforme (GBM). The high invasiveness of GBM cells is an important factor leading to inevitable tumor recurrence and a poor prognosis of patients. GNE-477, a novel PI3K/mTOR inhibitor, has been reported to exert antiproliferative effects on other cancer cells. However, researchers have not clearly determined whether GNE-477 produces antitumor effects on GBM. In the present study, GNE-477 significantly inhibited the proliferation, migration and invasion of U87 and U251 cells. In addition, GNE-477 also induced apoptosis of GBM cells, arresting the cell cycle in G0/G1 phase. More importantly, GNE-477 also reduced the levels of AKT and mTOR phosphorylation in the AKT/mTOR signaling pathway in a concentration-dependent manner. An increase in AKT activity induced by SC79 rescued the GNE-477-mediated inhibition of GBM cell proliferation and apoptosis. The antitumor effects of GNE-477 and the regulatory effects on related molecules were further confirmed in vivo using a nude mouse intracranial xenograft model. In conclusion, our study indicated that GNE-477 exerted significant antitumor effects on GBM cells in vitro and in vivo by downregulating the AKT/mTOR pathway.

A Review of Mathematics Determining Solute Uptake at the Blood-Brain Barrier in Normal and Pathological Conditions

The blood-brain barrier (BBB) limits movement of solutes from the lumen of the brain microvascular capillary system into the parenchyma. The unidirectional transfer constant, K_in, is the rate at which transport across the BBB occurs for individual molecules. Single and multiple uptake experiments are available for the determination of K_in for new drug candidates using both intravenous and in situ protocols. Additionally, the single uptake method can be used to determine K_in in heterogeneous pathophysiological conditions such as stroke, brain cancers, and Alzheimer's disease. In this review, we briefly cover the anatomy and physiology of the BBB, discuss the impact of efflux transporters on solute uptake, and provide an overview of the single-timepoint method for determination of K_in values. Lastly, we compare preclinical K_in experimental results with human parallels.

Development of an a priori computational approach for brain uptake of compounds in an insect model system

Delivery of compounds to the brain is critical for the development of effective treatment therapies of multiple central nervous system diseases. Recently a novel insect-based brain uptake model was published utilizing a locust brain ex vivo system. The goal of our study was to develop a priori, in silico cheminformatic models to describe brain uptake in this insect model, as well as evaluate the predictive ability. The machine learning program Orange® was used to evaluate several machine learning (ML) models on a published data set of 25 known drugs, with in vitro data generated by a single laboratory group to reduce inherent inter-laboratory variability. The ML models included in this study were linear regression (LR), support vector machines (SVN), k-nearest neighbor (kNN) and neural nets (NN). The quantitative structure-property relationship models were able to correlate experimental logCtot (concentration of compound in brain) and predicted brain uptake of r² > 0.5, with the descriptors log(P*MW^-0.5) and hydrogen bond donor used in LR, SVN and KNN, while log(P*MW^-0.5) and total polar surface area (TPSA) descriptors used in the NN models. Our results indicate that the locust insect model is amenable to data mining chemoinformatics and in silico model development in CNS drug discovery pipelines.

Application of RP-18 TLC Retention Data to the Prediction of the Transdermal Absorption of Drugs

Several chromatographic parameters (R_M⁰ and S obtained from RP-18 TLC with methanol—pH 7.4 phosphate buffer mobile phases by extrapolation to zero concentration of methanol; R_f and R_M obtained from RP-18 TLC with acetonitrile—pH 7.4 phosphate buffer 70:30 v/v as a mobile phase) and calculated molecular descriptors (molecular weight—M_W; molar volume—V_M; polar surface area—PSA; total count of nitrogen and oxygen atoms—(N+O); H-bond donor count—HD; H-bond acceptor count—HA; distribution coefficient—log D; total energy—E_T; binding energy—E_b; hydration energy—E_h; energy of the highest occupied molecular orbital—E_HOMO; energy of the lowest unoccupied orbital—E_LUMO; electronic energy—E_e; surface area—S_a; octanol-water partition coefficient—log P; dipole moment—DM; refractivity—R, polarizability—α) and their combinations (R_f/PSA, R_M/M_W, R_M/V_M) were tested in order to generate useful models of solutes’ skin permeability coefficient log K_p. It was established that neither R_M⁰ nor S obtained in the conditions used in this study is a good predictor of the skin permeability coefficient. The chromatographic parameters R_f and R_f/PSA were also unsuitable for this purpose. A simple and potentially useful, purely computational model based on (N+O), log D and HD as independent variables and accounting for ca. 83% of total variability was obtained. The evaluation of parameters derived from R_M (R_M, R_M/M_W, R_M/V_M) as independent variables in log K_p models proved that R_M/V_M is the most suitable descriptor belonging to this group. In a search for a reliable log K_p model based on this descriptor two possibilities were considered: a relatively simple model based on 5 independent variables: (N+O), log D, R_M/V_M, E_T and E_h and a more complex one, involving also E_b, M_W and PSA.

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.

Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development

In drug development, preclinical safety and pharmacokinetics assessments of candidate drugs to ensure the safety profile are a must. While in vivo and in vitro tests are traditionally used, experimental determinations have disadvantages, as they are usually time-consuming and costly. In silico predictions of these preclinical endpoints have each been developed in the past decades. However, only a few web-based tools have integrated different models to provide a simple one-step platform to help researchers thoroughly evaluate potential drug candidates. To efficiently achieve this approach, a platform for preclinical evaluation must not only predict key ADMET (absorption, distribution, metabolism, excretion and toxicity) properties but also provide some guidance on structural modifications to improve the undesired properties. In this review, we organized and compared several existing integrated web servers that can be adopted in preclinical drug development projects to evaluate the subject of interest. We also introduced our new web server, Virtual Rat, as an alternative choice to profile the properties of drug candidates. In Virtual Rat, we provide not only predictions of important ADMET properties but also possible reasons as to why the model made those structural predictions. Multiple models were implemented into Virtual Rat, including models for predicting human ether-a-go-go-related gene (hERG) inhibition, cytochrome P450 (CYP) inhibition, mutagenicity (Ames test), blood-brain barrier penetration, cytotoxicity and Caco-2 permeability. Virtual Rat is free and has been made publicly available at https://virtualrat.cmdm.tw/.

Focused Ultrasound for Noninvasive, Focal Pharmacologic Neurointervention

A long-standing goal of translational neuroscience is the ability to noninvasively deliver therapeutic agents to specific brain regions with high spatiotemporal resolution. Focused ultrasound (FUS) is an emerging technology that can noninvasively deliver energy up the order of 1 kW/cm² with millimeter and millisecond resolution to any point in the human brain with Food and Drug Administration-approved hardware. Although FUS is clinically utilized primarily for focal ablation in conditions such as essential tremor, recent breakthroughs have enabled the use of FUS for drug delivery at lower intensities (i.e., tens of watts per square centimeter) without ablation of the tissue. In this review, we present strategies for image-guided FUS-mediated pharmacologic neurointerventions. First, we discuss blood–brain barrier opening to deliver therapeutic agents of a variety of sizes to the central nervous system. We then describe the use of ultrasound-sensitive nanoparticles to noninvasively deliver small molecules to millimeter-sized structures including superficial cortical regions and deep gray matter regions within the brain without the need for blood–brain barrier opening. We also consider the safety and potential complications of these techniques, with attention to temporal acuity. Finally, we close with a discussion of different methods for mapping the ultrasound field within the brain and describe future avenues of research in ultrasound-targeted drug therapies.

Protein-Based Artificial Nanosystems in Cancer Therapy

Proteins, like actors, play different roles in specific applications. In the past decade, significant achievements have been made in protein-engineered biomedicine for cancer therapy. Certain proteins such as human serum albumin, working as carriers for drug/photosensitizer delivery, have entered clinical use due to their long half-life, biocompatibility, biodegradability, and inherent nonimmunogenicity. Proteins with catalytic abilities are promising as adjuvant agents for other therapeutic modalities or as anticancer drugs themselves. These catalytic proteins are usually defined as enzymes with high biological activity and substrate specificity. However, clinical applications of these kinds of proteins remain rare due to protease-induced denaturation and weak cellular permeability. Based on the characteristics of different proteins, tailor-made protein-based nanosystems could make up for their individual deficiencies. Therefore, elaborately designed protein-based nanosystems, where proteins serve as drug carriers, adjuvant agents, or therapeutic drugs to make full use of their intrinsic advantages in cancer therapy, are reviewed. Up-to-date progress on research in the field of protein-based nanomedicine is provided.

Discovery of 3-alkyl-5-aryl-1-pyrimidyl-1H-pyrazole derivatives as a novel selective inhibitor scaffold of JNK3

3-alkyl-5-aryl-1-pyrimidyl-1H-pyrazole derivatives were designed and synthesised as selective inhibitors of JNK3, a target for the treatment of neurodegenerative diseases. Following previous studies, we have designed JNK3 inhibitors to reduce the molecular weight and successfully identified a lead compound that exhibits equipotent activity towards JNK3. Kinase profiling results also showed high selectivity for JNK3 among 38 kinases. Among the derivatives, the IC₅₀ value of 8a, (R)-2-(1-(2-((1-(cyclopropanecarbonyl)pyrrolidin-3-yl)amino)pyrimidin-4-yl)-5-(3,4-dichlorophenyl)-1H-pyrazol-3-yl)acetonitrile exhibited 227 nM, showing the highest inhibitory activity against JNK3.

Collision cross sections obtained with ion mobility mass spectrometry as new descriptor to predict blood-brain barrier permeation by drugs

Evaluating the ability of a drug to permeate the blood-brain barrier is not a trivial task due to the structural complexity of the central nervous system. Nevertheless, it is of immense importance to identify related properties of the drugs either to be able to produce a desired effect in the brain or to avoid unwanted side effects there. In the past, multiple methods have been used for that purpose. However, these are sometimes methodologically problematic and do not claim universal validity. Therefore, additional new methods for judging blood-brain barrier penetration by drugs are advantageous. Accordingly, within the scope of this study, we tried to introduce a new structure-derived parameter to predict the blood-brain barrier permeation of small molecules based on ion mobility mass spectrometry experiments – the collision cross section, as an illustration of the branching and the molecular volume of a molecule. In detail, we used ion mobility quadrupole time-of-flight mass spectrometric data of 46 pharmacologically active small-molecules as well as literature-derived permeability and lipophilicity data to set up our model. For the first time we were able to show a strong correlation between the brain penetration of pharmacologically active ingredients and their mass spectrometric collision cross sections.