In silico models for nanotoxicity evaluation and prediction at the blood-brain barrier level: A mini-review

2017 ◽  
Vol 2 ◽  
pp. 20-27 ◽  
Author(s):  
Sergey Shityakov ◽  
Norbert Roewer ◽  
Jens-Albert Broscheit ◽  
Carola Förster
Keyword(s):  
Blood Brain Barrier ◽  
In Silico ◽  
Brain Barrier ◽  
Blood Brain ◽  
In Silico Models

Ligand and Structure-based Modeling of Passive Diffusion through the Blood-Brain Barrier

2018 ◽  
Vol 25 (9) ◽  
pp. 1073-1089 ◽  
Author(s):  
Santiago Vilar ◽  
Eduardo Sobarzo-Sanchez ◽  
Lourdes Santana ◽  
Eugenio Uriarte
Keyword(s):  
Blood Brain Barrier ◽  
In Silico ◽  
Passive Diffusion ◽  
Brain Barrier ◽  
Barrier Permeability ◽  
Blood Brain Barrier Permeability ◽  
Blood Brain ◽  
Brain Barrier Permeability ◽  
Different Types ◽  
The Brain

Background: Blood-brain barrier transport is an important process to be considered in drug candidates. The blood-brain barrier protects the brain from toxicological agents and, therefore, also establishes a restrictive mechanism for the delivery of drugs into the brain. Although there are different and complex mechanisms implicated in drug transport, in this review we focused on the prediction of passive diffusion through the blood-brain barrier. Methods: We elaborated on ligand-based and structure-based models that have been described to predict the blood-brain barrier permeability. Results: Multiple 2D and 3D QSPR/QSAR models and integrative approaches have been published to establish quantitative and qualitative relationships with the blood-brain barrier permeability. We explained different types of descriptors that correlate with passive diffusion along with data analysis methods. Moreover, we discussed the applicability of other types of molecular structure-based simulations, such as molecular dynamics, and their implications in the prediction of passive diffusion. Challenges and limitations of experimental measurements of permeability and in silico predictive methods were also described. Conclusion: Improvements in the prediction of blood-brain barrier permeability from different types of in silico models are crucial to optimize the process of Central Nervous System drug discovery and development.

scholarly journals COMPARATIVE ANALYSIS OF POTENTIALITY OF ESCULIN AND HINOKITOL (Β-THUJAPLICIN) AS ANTI-PARKINSONISM DRUGS: A PILOT IN SILICO STUDY

2016 ◽  
Vol 9 (1) ◽  
pp. 108
Author(s):  
Krishnapriya Madhu Varier ◽  
Sumathi Thangarajan ◽  
Arulvasu Chinnasamy ◽  
Gopalsamy Balakrishnan ◽  
Renjith Paulose
Keyword(s):  
Side Effects ◽  
Blood Brain Barrier ◽  
In Silico ◽  
Glycogen Synthase ◽  
Alpha Synuclein ◽  
Brain Barrier ◽  
Mao B ◽  
Blood Brain ◽  
In Silico Study ◽  
Dopamine D3

<p><strong>Objective: </strong>Parkinson’s disease (PD) is a leading cause of mental disability and death worldwide. Even though there are many advances in drug development against PD, a potent low dosage drug with fewer side effects are still in its nursery. This is a pioneer <em>in silico</em> attempt to test the anti-PD actions of esculin and hinokitol to act novel drugs.</p><p><strong>Methods: </strong>In this study, using Auto dock tools 4.2, esculin and hinokitol (β-Thujaplicin) were predicted for its inhibitory actions with Alpha-Synuclein (AS) Apo site, Dopamine D3 Receptor (D3R), Glycogen Synthase Kinase-3 Beta (GSK3β), Mono Oxidase B (MAO-B), Parkin and Tyrosine 3-Hydroxylase (TH) with levodopa standard. The reliability of the 3D predicted model of these proteins were analysed using RAMPAGE. Further, the blood-brain barrier (BBB) crossing ability of the natural compounds were analysed using cbligand. The <em>In silico </em>ADME (Absorption, Distribution, Metabolism, Excretion) properties of esculin and hinokitol were compared with that of levodopa using molinspiration and admetSAR @ LMMD software.<strong></strong></p><p><strong>Results: </strong>The predictions were that hinokitol, being blood-brain barrier positive (BBB+) with fewer side effects could be a potent anti-PD drug than esculin as it proved to be blood-brain barrier negative (BBB-). Hinokitol was predicted to be good inhibitors of AS, MAO-B and Parkin.</p><p><strong>Conclusion: </strong>The study revealed that hinokitol could be a potent anti-PD drug, being BBB+. Hinokitol was additionally predicted as a good inhibitor of AS, MAO-B and Parkin than levodopa standard.</p><p> </p>

scholarly journals Biomimetic Chromatographic Studies Combined with the Computational Approach to Investigate the Ability of Triterpenoid Saponins of Plant Origin to Cross the Blood–Brain Barrier

2021 ◽  
Vol 22 (7) ◽  
pp. 3573
Author(s):  
Katarzyna Stępnik
Keyword(s):  
Blood Brain Barrier ◽  
Computational Methods ◽  
In Silico ◽  
Brain Barrier ◽  
Plant Origin ◽  
Bacoside A ◽  
Triterpenoid Saponins ◽  
Platycodin D ◽  
Chromatographic Methods ◽  
Blood Brain

Biomimetic (non-cell based in vitro) and computational (in silico) studies are commonly used as screening tests in laboratory practice in the first stages of an experiment on biologically active compounds (potential drugs) and constitute an important step in the research on the drug design process. The main aim of this study was to evaluate the ability of triterpenoid saponins of plant origin to cross the blood–brain barrier (BBB) using both computational methods, including QSAR methodology, and biomimetic chromatographic methods, i.e., High Performance Liquid Chromatography (HPLC) with Immobilized Artificial Membrane (IAM) and cholesterol (CHOL) stationary phases, as well as Bio-partitioning Micellar Chromatography (BMC). The tested compounds were as follows: arjunic acid (Terminalia arjuna), akebia saponin D (Akebia quinata), bacoside A (Bacopa monnieri) and platycodin D (Platycodon grandiflorum). The pharmacokinetic BBB parameters calculated in silico show that three of the four substances, i.e., arjunic acid, akebia saponin D, and bacoside A exhibit similar values of brain/plasma equilibration rate expressed as logPSFubrain (the average logPSFubrain: −5.03), whereas the logPSFubrain value for platycodin D is –9.0. Platycodin D also shows the highest value of the unbound fraction in the brain obtained using the examined compounds (0.98). In these studies, it was found out for the first time that the logarithm of the analyte–micelle association constant (logKMA) calculated based on Foley’s equation can describe the passage of substances through the BBB. The most similar logBB values were obtained for hydrophilic platycodin D, applying both biomimetic and computational methods. All of the obtained logBB values and physicochemical parameters of the molecule indicate that platycodin D does not cross the BBB (the average logBB: 1.681), even though the in silico estimated value of the fraction unbound in plasma is relatively high (0.52). As far as it is known, this is the first paper that shows the applicability of biomimetic chromatographic methods in predicting the penetration of triterpenoid saponins through the BBB.

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