GDNF and cAMP significantly enhance in vitro blood-brain barrier integrity in a humanized tricellular transwell model.

Blood-brain barrier (BBB) is a crucial membrane safeguarding neural tissue by controlling the molecular exchange between blood and the brain. However, assessing BBB permeability presents challenges for central nervous system (CNS) drug development. In vitro studies of BBB-permeable agents before animal testing are essential to mitigate failures. Improved in vitro models are needed to mimic physiologically relevant BBB integrity. Here, we established an in vitro human-derived triculture BBB model, coculturing hCMEC/D3 with primary astrocytes and pericytes in a transwell format. This study found that the triculture BBB model exhibited significantly higher paracellular tightness (TEER 147.6 ± 6.5 Ω × cm2) than its monoculture counterpart (106.3 ± 1.0 Ω × cm2). Additionally, BBB permeability in the triculture model was significantly lower. While GDNF and cAMP have been shown to promote BBB integrity in monoculture models, their effect in our model was previously unreported. Our study demonstrates that both GDNF and cAMP increased TEER values (around 200 Ω × cm2 for each; 237.6 ± 17.7 Ω × cm2 for co-treatment) compared to untreated control, and decreased BBB permeability, mediated by increased claudin-5 expression. In summary, this humanized triculture BBB model, enhanced by GDNF and cAMP, offers an alternative for exploring in vitro drug penetration into the human brain.

Design of RNA Polymerase Inhibitors as Therapeutics for Tuberculous Meningitis.

BACKGROUND: Tuberculosis is an infectious disease caused by Mycobacterium tuber-culosis. The current treatment protocols for pulmonary tuberculosis are quite effective, even though the treatment requires 3-6 months. The current treatment protocols for extrapulmonary tuberculosis are based on the same drugs that are used for pulmonary tuberculosis. However, the success rates are much lower for certain types of extrapulmonary tuberculosis, such as tubercu-lous meningitis. Tuberculous meningitis is one of the very few diseases attributable to bacteria that have a very high short-term mortality rate among diagnosed patients, even after treatment with antibiotics that are effective for pulmonary tuberculosis. For example, rifampicin is highly effective for the treatment of pulmonary tuberculosis, but its effectiveness for the treatment of tuberculous meningitis is much lower. The reason for the lower effectiveness of rifampicin against tuberculous meningitis is that it has low Blood-Brain Barrier (BBB) permeability, which results in lower concentrations of the drug at the required sites in the central nervous system. METHODS: In this work, ligands having improved BBB permeability and pharmacokinetic and pharmacodynamic properties, either similar to or better than that of rifampicin, have been designed. The BBB permeability of the designed molecules was assessed by using pkCSM, a machine-learning model. Pharmacokinetic properties, drug-likeness, and synthesizability were assessed by using SWISS-MODEL. The binding affinity of the designed drugs was assessed by using AutoDock Vina. A customized scoring function, StWN score, was used for a quantitative weighted assessment of all the properties of interest to rank the designed molecules. RESULTS: In this study, drug-like ligands have been designed that have been predicted to have high BBB permeability as well as high affinity for RNA polymerase ß of Mycobacterium tuberculosis. CONCLUSION: The best ligands generated by the tools employed were selected as potential drugs to address the current need for better options for the treatment of tuberculous meningitis.

Exploring the Pharmacological Effects of Bioactive Peptides on Human Nervous Disorders: A Comprehensive Review.

A family of peptides known as bioactive peptides has unique physiological properties and may be used to improve human health and prevent illness. Because bioactive peptides impact the immunological, endocrine, neurological, and cardiovascular systems, they have drawn a lot of interest from researchers. According to recent studies, bioactive peptides have a lot to offer in the treatment of inflammation, neuronal regeneration, localized ischemia, and the blood-brain barrier. It investigates various peptide moieties, including antioxidative properties, immune response modulation, and increased blood-brain barrier permeability. It also looks at how well they work as therapeutic candidates and finds promising peptide-based strategies for better outcomes. Furthermore, it underscores the need for further studies to support their clinical utility and suggests that results from such investigations will enhance our understanding of the pathophysiology of these conditions. In order to understand recent advances in BPs and to plan future research, academic researchers and industrial partners will find this review article to be a helpful resource.

In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy.

Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and significant challenge. Drug repurposing emerges as a cost-effective and efficient strategy to combat this disorder. This study leverages the transformer-based deep learning methods coupled with molecular binding affinity calculation to develop a novel in-silico drug repurposing pipeline for epilepsy. The number of candidate inhibitors against 24 target proteins encoded by gain-of-function genes implicated in epileptogenesis ranged from zero to several hundreds. Our pipeline has repurposed the medications with most anti-epileptic drugs and nearly half psychiatric medications, highlighting the effectiveness of our pipeline. Furthermore, Lomitapide, a cholesterol-lowering drug, first emerged as particularly noteworthy, exhibiting high binding affinity for 10 targets and verified by molecular dynamics simulation and mechanism analysis. These findings provided a novel perspective on therapeutic strategies for other central nervous system disease.

Alterations in brain fluid physiology during the early stages of development of ischaemic oedema.

Oedema occurs when higher than normal amounts of solutes and water accumulate in tissues. In brain parenchymal tissue, vasogenic oedema arises from changes in blood-brain barrier permeability, e.g. in peritumoral oedema. Cytotoxic oedema arises from excess accumulation of solutes within cells, e.g. ischaemic oedema following stroke. This type of oedema is initiated when blood flow in the affected core region falls sufficiently to deprive brain cells of the ATP needed to maintain ion gradients. As a consequence, there is: depolarization of neurons; neural uptake of Na+ and Cl- and loss of K+; neuronal swelling; astrocytic uptake of Na+, K+ and anions; swelling of astrocytes; and reduction in ISF volume by fluid uptake into neurons and astrocytes. There is increased parenchymal solute content due to metabolic osmolyte production and solute influx from CSF and blood. The greatly increased [K+]isf triggers spreading depolarizations into the surrounding penumbra increasing metabolic load leading to increased size of the ischaemic core. Water enters the parenchyma primarily from blood, some passing into astrocyte endfeet via AQP4. In the medium term, e.g. after three hours, NaCl permeability and swelling rate increase with partial opening of tight junctions between blood-brain barrier endothelial cells and opening of SUR1-TPRM4 channels. Swelling is then driven by a Donnan-like effect. Longer term, there is gross failure of the blood-brain barrier. Oedema resolution is slower than its formation. Fluids without colloid, e.g. infused mock CSF, can be reabsorbed across the blood-brain barrier by a Starling-like mechanism whereas infused serum with its colloids must be removed by even slower extravascular means. Large scale oedema can increase intracranial pressure (ICP) sufficiently to cause fatal brain herniation. The potentially lethal increase in ICP can be avoided by craniectomy or by aspiration of the osmotically active infarcted region. However, the only satisfactory treatment resulting in retention of function is restoration of blood flow, providing this can be achieved relatively quickly. One important objective of current research is to find treatments that increase the time during which reperfusion is successful. Questions still to be resolved are discussed.

Exploration of the Molecular Mechanism by Which Caveolin-1 Regulates Changes in Blood-Brain Barrier Permeability Leading to Eosinophilic Meningoencephalitis.

Angiostrongylus cantonensis, a zoonotic parasite, can invade the human central nervous system (CNS) and cause acute eosinophilic meningitis or eosinophilic meningoencephalitis. Mice infected with A. cantonensis show elevated levels of pro-inflammatory cytokines, plasminogen activators, and matrix metalloproteinase-9, resulting in disruption of the blood-brain barrier (BBB) and immune cell infiltration into the CNS. Caveolin-1 (Cav-1) regulates the permeability of the BBB, which affects immune cells and cerebrospinal fluid. This intricate interaction ultimately fuels the progression of brain damage and edema. This study aims to investigate the regulatory role of Cav-1 in the pathogenesis of meningoencephalitis induced by A. cantonensis infection. We investigated pathological alterations by triphenyl-tetrazolium chloride, brain water content, BBB permeability, Western blot analysis, and gelatin zymography in BALB/c mice after A. cantonensis. The study evaluates the critical role of Cav-1 regulation through the TLR4/MyD88 signaling pathway, modulates tight junction proteins, influences BBB permeability, and contributes to brain damage in A. cantonensis-induced meningoencephalitis.

Amelioration of Neurochemical Alteration and Memory and Depressive Behavior in Sepsis by Allopurinol, a Tryptophan 2,3-Dioxygenase Inhibitor.

BACKGROUND: In response to inflammation and other stressors, tryptophan is catalyzed by Tryptophan 2,3-Dioxygenase (TDO), which leads to activation of the kynurenine pathway. Sepsis is a serious condition in which the body responds improperly to an infection, and the brain is the inflammation target in this condition. OBJECTIVE: This study aimed to determine if the induction of TDO contributes to the permeability of the Blood-Brain Barrier (BBB), mortality, neuroinflammation, oxidative stress, and mitochondrial dysfunction, besides long-term behavioral alterations in a preclinical model of sepsis. METHODS: Male Wistar rats with two months of age were submitted to the sepsis model using Cecal Ligation and Perforation (CLP). The rats received allopurinol (Allo, 20 mg/kg, gavage), a TDO inhibitor, or a vehicle once a day for seven days. RESULTS: Sepsis induction increased BBB permeability, IL-6 level, neutrophil infiltrate, nitric oxide formation, and oxidative stress, resulting in energy impairment in 24h after CLP and Allo administration restored these parameters. Regarding memory, Allo restored short-term memory impairment and decreased depressive behavior. However, no change in survival rate was verified. CONCLUSION: In summary, TDO inhibition effectively prevented depressive behavior and memory impairment 10 days after CLP by reducing acute BBB permeability, neuroinflammation, oxidative stress, and mitochondrial alteration.

Feasibility of measuring blood-brain barrier permeability using ultra-short echo time radial magnetic resonance imaging.

BACKGROUND AND PURPOSE: The purpose of this study is to evaluate the feasibility of using 3-dimensional (3D) ultra-short echo time (UTE) radial imaging method for measurement of the permeability of the blood-brain barrier (BBB) to gadolinium-based contrast agent. In this study, we propose to use the golden-angle radial sparse parallel (GRASP) method with 3D center-out trajectories for UTE, hence named as 3D UTE-GRASP. We first examined the feasibility of using 3D UTE-GRASP dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) for differentiating subtle BBB disruptions induced by focused ultrasound (FUS). Then, we examined the BBB permeability changes in Alzheimer's disease (AD) pathology using Alzheimer's disease transgenic mice (5xFAD) at different ages. METHODS: For FUS experiments, we used four Sprague Dawley rats at similar ages where we compared BBB permeability of each rat receiving the FUS sonication with different acoustic power (0.4-1.0 MPa). For AD transgenic mice experiments, we included three 5xFAD mice (6, 12, and 16 months old) and three wild-type mice (4, 8, and 12 months old). RESULTS: The result from FUS experiments showed a progressive increase in BBB permeability with increase of acoustic power (p < .05), demonstrating the sensitivity of DCE-MRI method for detecting subtle changes in BBB disruption. Our AD transgenic mice experiments suggest an early BBB disruption in 5xFAD mice, which is further impaired with aging. CONCLUSION: The results in this study substantiate the feasibility of using the proposed 3D UTE-GRASP method for detecting subtle BBB permeability changes expected in neurodegenerative diseases, such as AD.

Evaluation of lipophilicity and drug-likeness of donepezil-like compounds using reversed-phase thin-layer chromatography.

Fourteen donepezil-like acetylcholinesterase (AChE) inhibitors from our library were analyzed using reversed-phase thin-layer chromatography to assess their lipophilicity and blood-brain barrier permeability. Compounds possessed N-benzylpiperidine and N,N-diarylpiperazine moieties connected via a short carboxamide or amine linker. Retention parameters RM 0, b, and C0 were considered as the measures of lipophilicity. Besides, logD of the investigated compounds was determined chromatographically using standard compounds with known logPow and logD values at pH 11. Experimentally obtained lipophilicity parameters correlated well with in silico generated results, and the effect of the nature of the linker between two pharmacophores and substituents on the arylpiperazine part of the molecule was observed. As a result of drug-likeness analysis, both Lipinski's rule of five and Veber's rule parameters were determined, suggesting that examined compounds could be potential candidates for further drug development. Principal component analysis was performed to obtain an insight into a grouping of compounds based on calculated structural descriptors, experimentally obtained values of lipophilicity, and AChE inhibitory activity.

Molecular Mechanisms of Neuroprotection after the Intermittent Exposures of Hypercapnic Hypoxia.

The review introduces the stages of formation and experimental confirmation of the hypothesis regarding the mutual potentiation of neuroprotective effects of hypoxia and hypercapnia during their combined influence (hypercapnic hypoxia). The main focus is on the mechanisms and signaling pathways involved in the formation of ischemic tolerance in the brain during intermittent hypercapnic hypoxia. Importantly, the combined effect of hypoxia and hypercapnia exerts a more pronounced neuroprotective effect compared to their separate application. Some signaling systems are associated with the predominance of the hypoxic stimulus (HIF-1α, A1 receptors), while others (NF-κB, antioxidant activity, inhibition of apoptosis, maintenance of selective blood-brain barrier permeability) are mainly modulated by hypercapnia. Most of the molecular and cellular mechanisms involved in the formation of brain tolerance to ischemia are due to the contribution of both excess carbon dioxide and oxygen deficiency (ATP-dependent potassium channels, chaperones, endoplasmic reticulum stress, mitochondrial metabolism reprogramming). Overall, experimental studies indicate the dominance of hypercapnia in the neuroprotective effect of its combined action with hypoxia. Recent clinical studies have demonstrated the effectiveness of hypercapnic-hypoxic training in the treatment of childhood cerebral palsy and diabetic polyneuropathy in children. Combining hypercapnic hypoxia with pharmacological modulators of neuro/cardio/cytoprotection signaling pathways is likely to be promising for translating experimental research into clinical medicine.

Post-endovascular treatment, blood-brain barrier disruption, predicts patient outcomes better than pre-treatment status.

OBJECTIVES: Blood-brain barrier (BBB) disruption is an important pathological change after cerebral infarction that exacerbates brain injury. We aimed to investigate and compare the predictive utility of pre-treatment BBB permeability (BBBP) and BBBP within 1 h after endovascular treatment (EVT) for hemorrhagic transformation (HT) and 90-day prognosis. METHODS: Patients underwent preoperative computed tomography perfusion (CTP) and non-contrast CT (NCCT) within 1 h after EVT. Preoperative BBBP was determined by the relative permeability surface area product (rPS) in the hypoperfusion area. Postoperative BBBP was determined by the post-EVT Alberta Stroke Program Early CT Score (Post-ASPECTS), which is based on brain parenchymal hyperdensity on the postoperative NCCT. OUTCOMES: We included 100 patients. Univariate logistic regression analysis revealed correlations of preoperative rPS with HT, poor outcomes, and death. However, these correlations were not observed in multivariate logistic regression. A Post-ASPECTS ≤7 and could independently predict poor outcomes, while Post-ASPECTS ≤6 could independently predict death and HT. The baseline National Institutes of Health Stroke Scale (NIHSS) score could independently predict poor outcomes and death but not HT. A combined model using the baseline NIHSS and Post-ASPECTS scores had better predictive performance for poor outcomes and death than baseline NIHSS score alone; however, it was not superior to the predictive performance of the Post-ASPECTS score. CONCLUSION: The preoperative rPS cannot independently predict clinical outcomes in EVT-treated patients; contrastingly, the Post-ASPECTS score could independently predict poor outcomes, death, and HT. This parameter could inform prompt postoperative treatment decisions.

Multifunctional Liposomes Targeting Amyloid-ß Oligomers for Early Diagnosis and Therapy of Alzheimer's Disease.

Early detection and treatment are crucial for Alzheimer's disease (AD) management. Current diagnostic and therapeutic methods focus on late-stage amyloid fibrils and plaques, overlooking toxic soluble amyloid ß oligomers (AßOs) accumulating early in AD. A multifunctional liposome-based platform is designed for early diagnosis and therapy of AD, leveraging a novel self-assembled cyclic d,l-α-peptide (CP-2) that selectively targets AßOs. Biocompatible CP-2 conjugated liposomes (CP-2-LPs) effectively disrupt Aß aggregation and mitigate Aß-mediated toxicity in human neuroblastoma cells. In transgenic Caenorhabditis elegans AD models, CP-2-LPs significantly outperformed free CP-2 by improving cognitive and behavioral functions, extending lifespan, and reducing toxic AßO levels. Intravenous injection of fluorescently labeled CP-2-LPs reveals effective blood-brain barrier penetration, with significantly higher brain fluorescence in transgenic mice than WT, enabling precise diagnosis. These findings underscore CP-2-LPs as a valuable tool for early detection and targeted therapy in AD.

METTL3 Mediates Microglial Activation and Blood-Brain Barrier Permeability in Cerebral Ischemic Stroke by Regulating NLRP3 Inflammasomes Through m6A Methylation Modification.

Cerebral ischemic stroke (CIS) is the main cause of disability. METTL3 is implicated in CIS, and we explored its specific mechanism. Middle cerebral artery occlusion (MCAO) rat model and oxygen-glucose deprivation/reperfusion (OGD/R) HAPI cell model were established and treated with LV-METTL3 or DAA, oe-METTL3, miR-335-3p mimics, or DAA, to assess their effects on MCAO rat neurological and motor function, cerebral infarction area, brain water content, microglial activation, blood-brain barrier (BBB) permeability, and NLRP3 inflammasome activation. METTL3, pri-miR-335-3p, mature miR-335-3p, and miR-335-3p mRNA levels were assessed by RT-qPCR; M1/M2 microglial phenotype proportion and M1/M2 microglia ratio, inflammatory factor levels, and m6A modification were assessed. MCAO rats manifested cerebral ischemia injury. METTL3 was under-expressed in CIS. METTL3 overexpression inhibited microglial activation and M1 polarization and BBB permeability in MCAO rats and inhibited OGD/R-induced microglial activation and reduced M1 polarization. METTL3 regulated miR-335-3p expression and inhibited NLRP3 inflammasome activation. m6A methylation inhibition averted METTL3's effects on NLRP3 activation, thus promoting microglial activation in OGD/R-induced cells and METTL3's effects on BBB permeability in MCAO rats. Briefly, METTL3 regulated miR-335-3p expression through RNA m6A methylation and inhibited NLRP3 inflammasome activation, thus repressing microglial activation, BBB permeability, and protecting against CIS.

Novel Pitolisant-Derived Sulfonyl Compounds for Alzheimer Disease.

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disorder characterized by cognitive decline, memory loss, behavioral changes, and other neurological symptoms. Considering the urgent need for new AD therapeutics, in the present study we designed, synthesized, and evaluated multitarget compounds structurally inspired by sulfonylureas and pitolisant with the aim of obtaining multitarget ligands for AD treatment. Due to the diversity of chemical scaffolds, a novel strategy has been adopted by merging into one structure moieties displaying H3R antagonism and acetylcholinesterase inhibition. Eight compounds, selected by their binding activity on H3R, showed a moderate ability to inhibit acetylcholinesterase activity in vitro, and two of the compounds (derivatives 2 and 7) were also capable of increasing acetylcholine release in vitro. Among the tested compounds, derivative 2 was identified and selected for further in vivo studies. Compound 2 was able to reverse scopolamine-induced cognitive deficits with results comparable to those of galantamine, a drug used in clinics for treating AD. In addition to its efficacy, this compound showed moderate BBB permeation in vitro. Altogether, these results point out that the fragment-like character of compound 2 leads to an optimal starting point for a plausible medicinal chemistry approach for this novel strategy.

Blood-brain barrier permeability by CT perfusion predicts parenchymal hematoma after recanalization with thrombectomy.

BACKGROUND AND PURPOSE: Parenchymal hematoma is a dreaded complication of mechanical thrombectomy after acute ischemic stroke. This study evaluated whether blood-brain barrier permeability measurements based on CT perfusion could be used as predictors of parenchymal hematoma after successful recanalization and compared the predictive value of various permeability parameters in patients with acute ischemic stroke. METHODS: We enrolled 53 patients with acute ischemic stroke who underwent mechanical thrombectomy and achieved successful recanalization. Each patient underwent CT, CT angiography, and CT perfusion imaging before treatment. We used relative volume transfer constant (rKtrans ) values, relative permeability-surface area product (rP·S), and relative extraction fraction (rE) to evaluate preoperative blood-brain barrier permeability in the delayed perfusion area. RESULTS: Overall, 22 patients (37.7%) developed hemorrhagic transformation after surgery, including 10 patients (16.9%) with hemorrhagic infarction and 11 patients (20.8%) with parenchymal hematoma. The rP·S, rKtrans , and rE of the hypoperfusion area in the parenchymal hematoma group were significantly higher than those in the hemorrhagic infarction and no-hemorrhage transformation groups (p < .01). We found that rE and rP·S were superior to rKtrans in predicting parenchymal hematoma transformation after thrombectomy (P·S area under the curve [AUC] .844 vs. rKtrans AUC .753, z = 2.064, p = .039; rE AUC .907 vs. rKtrans AUC .753, z = 2.399, p = .017). CONCLUSIONS: Patients with parenchymal hematoma after mechanical thrombectomy had higher blood-brain barrier permeability in hypoperfusion areas. Among blood-brain barrier permeability measurement parameters, rP·S and rE showed better accuracy for parenchymal hematoma prediction.

Self-Assembly Driven Formation of Functional Ultralong "Artificial Fibers" to Mitigate the Neuronal Damage Associated with Alzheimer's Disease.

Fibrillation of amyloid beta (Aß) is the key event in the amyloid neurotoxicity process that induces a chain of toxic events including oxidative stress, caspase activation, poly(ADP-ribose) polymerase cleavage, and mitochondrial dysfunction resulting in neuronal loss and memory decline manifesting as clinical dementia in humans. Herein, we report the development of a novel, biologically active supramolecular probe, INHQ, and achieve functional nanoarchitectures via a self-assembly process such that ultralong fibers are achieved spontaneously. With specifically decorated functional groups on INHQ such as imidazole, hydroxyquinoline, hydrophobic chain, and hydroxyquinoline molecules, these ultralong fibers coassembled efficiently with toxic Aß oligomers and mitigated the amyloid-induced neurotoxicity by blocking the aforementioned biochemical events leading to neuronal damage in mice. These functional ultralong "Artificial Fibers" morphologically resemble the amyloid fibers and provide a higher surface area of interaction that improves its clearance ability against the Aß aggregates. The efficacy of this novel INHQ molecule was ascertained by its high ability to interact with Aß. Moreover, this injectable, ultralong INHQ functional "artificial fiber" translocates through the blood-brain barrier and successfully attenuates the amyloid-triggered neuronal damage and pyknosis in the cerebral cortex of wild-type mouse. Utilizing various spectroscopic techniques, morphology analysis, and in vitro, in silico, and in vivo studies, these ultralong INHQ fibers are proven to hold great promise for treating neurological disorders at all stages with a potential to replace the existing medications, reduce complications in the brain, and eradicate the amyloid-triggered neurotoxicity implicated in numerous disorders in human through a rare synergistic mechanism.

[Resampling combined with stacking learning for prediction of blood-brain barrier permeability of compounds].

It is a significant challenge to improve the blood-brain barrier (BBB) permeability of central nervous system (CNS) drugs in their development. Compared with traditional pharmacokinetic property tests, machine learning techniques have been proven to effectively and cost-effectively predict the BBB permeability of CNS drugs. In this study, we introduce a high-performance BBB permeability prediction model named balanced-stacking-learning based BBB permeability predictor(BSL-B3PP). Firstly, we screen out the feature set that has a strong influence on BBB permeability from the perspective of medicinal chemistry background and machine learning respectively, and summarize the BBB positive(BBB+) quantification intervals. Then, a combination of resampling algorithms and stacking learning(SL) algorithm is used for predicting the BBB permeability of CNS drugs. The BSL-B3PP model is constructed based on a large-scale BBB database (B3DB). Experimental validation shows an area under curve (AUC) of 97.8% and a Matthews correlation coefficient (MCC) of 85.5%. This model demonstrates promising BBB permeability prediction capability, particularly for drugs that cannot penetrate the BBB, which helps reduce CNS drug development costs and accelerate the CNS drug development process.

Discovery of blood-brain barrier permeable and orally bioavailable caffeine-based amide derivatives as acetylcholinesterase inhibitors.

Caffeine is one of the privileged natural products that shows numerous effects on the central nervous system. Herein, thirty-one caffeine-based amide derivatives were synthesized and evaluated in vitro for their anticholinesterase activity. The introduction of the amide group to the caffeine core augmented its anticholinesterase activity from an IC50 value of 128 to 1.32 µM (derivative, 6i). The SAR study revealed that N7 substitution on caffeine core is favorable over N1, and the presence of amide 'carbonyl' as a part of the linker contributes to the biological activity. The caffeine core of 6i exhibits interactions with the peripheral anionic site, whereas the N-benzyl ring fits nicely inside the catalytic anionic site. Analog 6i inhibits AChE in a mixed-type mode (Ki 4.58 µM) and crosses the BBB in an in-vitro PAMPA assay. Compound 6i has a descent metabolic stability in MLM (>70% remaining after 30 min) and favorable oral pharmacokinetics in Swiss albino mice.

Honokiol in glioblastoma recurrence: a case report.

Glioblastoma is the most common and aggressive primary tumor in the central nervous system. There is no standard of care for patients with recurrent GBM. Honokiol is a pleiotropic lignan and has the potential to be a potent and safe anticancer agent in human GBM when it is encapsulated by liposomes. We report an efficient and safe response to three phases of treatment with liposomal honokiol in a patient with recurrent glioblastoma.

Machine learning based dynamic consensus model for predicting blood-brain barrier permeability.

The blood-brain barrier (BBB) is an important defence mechanism that restricts disease-causing pathogens and toxins to enter the brain from the bloodstream. In recent years, many in silico methods were proposed for predicting BBB permeability, however, the reliability of these models is questionable due to the smaller and class-imbalance dataset which subsequently leads to a very high false positive rate. In this study, machine learning and deep learning-based predictive models were built using XGboost, Random Forest, Extra-tree classifiers and deep neural network. A dataset of 8153 compounds comprising both the BBB permeable and BBB non-permeable was curated and subjected to calculations of molecular descriptors and fingerprints for generating the features for machine learning and deep learning models. Three balancing techniques were then applied to the dataset to address the class-imbalance issue. A comprehensive comparison among the models showed that the deep neural network model generated on the balanced MACCS fingerprint dataset outperformed with an accuracy of 97.8% and a ROC-AUC score of 0.98 among all the models. Additionally, a dynamic consensus model was prepared with the machine learning models and validated with a benchmark dataset for predicting BBB permeability with higher confidence scores.