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An experimentally validated approach to calculate the blood-brain barrier permeability of small molecules.

ABSTRACT: Drug development for the treatment of central nervous system (CNS) diseases is extremely challenging, in large part due to the difficulty in crossing the blood-brain barrier (BBB). Here we develop and experimentally validate a new in silico method to predict quantitatively the BBB permeability for small-molecule drugs. We show accurate prediction of solute permeabilities at physiological temperature using high-temperature unbiased atomic detail molecular dynamics simulations of spontaneous drug diffusion across BBB bilayers. These simulations provide atomic detail insights into the transport mechanisms, as well as converged kinetics and thermodynamics. The method is validated computationally against physiological temperature simulations for fast-diffusing compounds, as well as experimentally by direct determination of the compound permeabilities using a transwell assay as an in vitro BBB model. The overall agreement of the predicted values with both direct simulations at physiological temperatures and experimental data is excellent. This new tool has the potential to replace current semi-empirical in silico screening and in vitro permeability measurements in CNS drug discovery.

SUBMITTER: Wang Y

PROVIDER: S-EPMC6467875 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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An experimentally validated approach to calculate the blood-brain barrier permeability of small molecules.

Wang Yukun Y Gallagher Erin E Jorgensen Christian C Troendle Evan P EP Hu Dan D Searson Peter C PC Ulmschneider Martin B MB

Scientific reports 20190416 1

Drug development for the treatment of central nervous system (CNS) diseases is extremely challenging, in large part due to the difficulty in crossing the blood-brain barrier (BBB). Here we develop and experimentally validate a new in silico method to predict quantitatively the BBB permeability for small-molecule drugs. We show accurate prediction of solute permeabilities at physiological temperature using high-temperature unbiased atomic detail molecular dynamics simulations of spontaneous drug ...[more]

PMID: 30992465

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Project description:The blood-brain barrier plays a crucial role in regulating the passage of 98% of the compounds that enter the central nervous system (CNS). Compounds with high permeability must be identified to enable the synthesis of brain medications for the treatment of various brain diseases, such as Parkinson's, Alzheimer's, and brain tumors. Throughout the years, several models have been developed to solve this problem and have achieved acceptable accuracy scores in predicting compounds that penetrate the blood-brain barrier. However, predicting compounds with "low" permeability has been a challenging task. In this study, we present a deep learning (DL) classification model to predict blood-brain barrier permeability. The proposed model addresses the fundamental issues presented in former models: high dimensionality, class imbalances, and low specificity scores. We address these issues to enhance the high-dimensional, imbalanced dataset before developing the classification model: the imbalanced dataset is addressed using oversampling techniques and the high dimensionality using a non-linear dimensionality reduction technique known as kernel principal component analysis (KPCA). This technique transforms the high-dimensional dataset into a low-dimensional Euclidean space while retaining invaluable information. For the classification task, we developed an enhanced feed-forward deep learning model and a convolutional neural network model. In terms of specificity scores (i.e., predicting compounds with low permeability), the results obtained by the enhanced feed-forward deep learning model outperformed those obtained by other models in the literature that were developed using the same technique. In addition, the proposed convolutional neural network model surpassed models used in other studies in multiple accuracy measures, including overall accuracy and specificity. The proposed approach solves the problem inevitably faced with obtaining low specificity resulting in high false positive rate.

Project description:Cerebral small vessel disease (SVD) is a major cause of stroke and dementia. The underlying pathogenesis is poorly understood, but both neuroinflammation and increased blood-brain barrier permeability have been hypothesized to play a role, and preclinical studies suggest the two processes may be linked. We used PET magnetic resonance to simultaneously measure microglial activation using the translocator protein radioligand 11C-PK11195, and blood-brain barrier permeability using dynamic contrast enhanced MRI. A case control design was used with two disease groups with sporadic SVD (n = 20), monogenic SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, CADASIL), and normal controls (n = 20) were studied. Hotspots of increased glial activation and blood-brain barrier permeability were identified as values greater than the 95th percentile of the distribution in controls. In sporadic SVD there was an increase in the volume of hotspots of both 11C-PK11195 binding (P = 0.003) and blood-brain barrier permeability (P = 0.007) in the normal appearing white matter, in addition to increased mean blood-brain barrier permeability (P < 0.001). In CADASIL no increase in blood-brain barrier permeability was detected; there was a non-significant trend to increased 11C-PK11195 binding (P = 0.073). Hotspots of 11C-PK11195 binding and blood-brain barrier permeability were not spatially related. A panel of 93 blood biomarkers relating to cardiovascular disease, inflammation and endothelial activation were measured in each participant; principal component analysis was performed and the first component related to blood-brain barrier permeability and microglial activation. Within the sporadic SVD group both hotspot and mean volume blood-brain barrier permeability values in the normal appearing white matter were associated with dimension 1 (β = 0.829, P = 0.017, and β = 0.976, P = 0.003, respectively). There was no association with 11C-PK11195 binding. No associations with blood markers were found in the CADASIL group. In conclusion, in sporadic SVD both microglial activation and increased blood-brain barrier permeability occur, but these are spatially distinct processes. No evidence of increased blood-brain barrier permeability was found in CADASIL.

Project description:Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improve the accuracy and shorten the time for new drug development. The primary goal of this research is to develop artificial intelligence (AI) computing models and novel deep learning architectures capable of predicting whether molecules can permeate the human blood-brain barrier (BBB). The in silico (computational) and in vitro (experimental) results were validated by the Natural Products Research Laboratories (NPRL) at China Medical University Hospital (CMUH). The transformer-based MegaMolBART was used as the simplified molecular input line entry system (SMILES) encoder with an XGBoost classifier as an in silico method to check if a molecule could cross through the BBB. We used Morgan or Circular fingerprints to apply the Morgan algorithm to a set of atomic invariants as a baseline encoder also with an XGBoost classifier to compare the results. BBB permeability was assessed in vitro using three-dimensional (3D) human BBB spheroids (human brain microvascular endothelial cells, brain vascular pericytes, and astrocytes). Using multiple BBB databases, the results of the final in silico transformer and XGBoost model achieved an area under the receiver operating characteristic curve of 0.88 on the held-out test dataset. Temozolomide (TMZ) and 21 randomly selected BBB permeable compounds (Pred scores = 1, indicating BBB-permeable) from the NPRL penetrated human BBB spheroid cells. No evidence suggests that ferulic acid or five BBB-impermeable compounds (Pred scores < 1.29423E-05, which designate compounds that pass through the human BBB) can pass through the spheroid cells of the BBB. Our validation of in vitro experiments indicated that the in silico prediction of small-molecule permeation in the BBB model is accurate. Transformer-based models like MegaMolBART, leveraging the SMILES representations of molecules, show great promise for applications in new drug discovery. These models have the potential to accelerate the development of novel targeted treatments for disorders of the central nervous system.

Project description:BackgroundThe blood-brain barrier (BBB) is a semipermeable interface that prevents the non-selective transport into the central nervous system. It controls the delivery of macromolecules fueling the brain metabolism and the immunological surveillance. The BBB permeability is locally regulated depending on the physiological requirements, maintaining the tissue homeostasis and influencing pathological conditions. Given its relevance in vertebrate CNS, it is surprising that little is known about the BBB in Amphibians, some of which are capable of adult CNS regeneration.ResultsThe BBB size threshold of the anuran Xenopus laevis (African clawed toad), as well as two urodele species, Ambystoma mexicanum (axolotl) and Pleurodeles waltl (Iberian ribbed newt), was evaluated under physiological conditions through the use of synthetic tracers. We detected important differences between the analyzed species. Xenopus exhibited a BBB with characteristics more similar to those observed in mammals, whereas the BBB of axolotl was found to be permeable to the 1 kDa tracer. The permeability of the 1 kDa tracer measured in Pleurodeles showed values in between axolotl and Xenopus vesseks. We confirmed that these differences are species-specific and not related to metamorphosis. In line with these results, the tight junction protein Claudin-5 was absent in axolotl, intermediate in Pleurodeles and showed full-coverage in Xenopus vessels. Interestingly, electron microscopy analysis and the retention pattern of the larger tracers (3 and 70 kDa) demonstrated that axolotl endothelial cells exhibit higher rates of macropinocytosis, a non-regulated type of transcellular transport.ConclusionsOur study demonstrated that, under physiological conditions, the blood-brain barrier exhibited species-specific variations, including permeability threshold, blood vessel coverage, and macropinocytosis rate. Future studies are needed to test whether the higher permeability observed in salamanders could have metabolic and immunological consequences contributing to their remarkable regenerative capacity.

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An experimentally validated approach to calculate the blood-brain barrier permeability of small molecules.

Publications

An experimentally validated approach to calculate the blood-brain barrier permeability of small molecules.

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