scholarly journals Applications of Multidimensional Space of Mathematical Molecular Descriptors in Large-Scale Bioactivity and Toxicity Prediction- Applications to Prediction of Mutagenicity and Blood-Brain Barrier Entry of Chemicals

2020 ◽  
Vol 93 (4) ◽  
Author(s):  
Subhash C. Basak ◽  
Subhabrata Majumdar ◽  
Claudiu Lungu
Keyword(s):  
Blood Brain Barrier ◽  
Large Scale ◽  
Molecular Descriptors ◽  
Brain Barrier ◽  
Multidimensional Space ◽  
Toxicity Prediction ◽  
Blood Brain

Preparation, Characterization, and Biodistribution of Glutathione PEGylated Nanoliposomal Doxorubicin for Brain Drug Delivery with A Post-insertion Approach

2021 ◽  
Author(s):  
Amin mehrabian ◽  
Roghayyeh Vakili-Ghartavol ◽  
Mohammad Mashreghi ◽  
Sara Shokooh Saremi ◽  
Ali Badiee ◽  
...  
Keyword(s):  
Blood Brain Barrier ◽  
Animal Studies ◽  
Large Scale ◽  
Fluorescent Microscopy ◽  
Pegylated Liposomal Doxorubicin ◽  
Brain Barrier ◽  
Pharmacokinetic Studies ◽  
Scale Production ◽  
Insertion Technique ◽  
Blood Brain

Abstract Brain cancer treatments have been largely unsuccessful due to the blood-brain barrier. Several publications support the presence of glutathione (GSH) receptors on the surface of the BBB and consequently the products such as the 2B3-101, which is almost 5% pre-inserted GSH PEGylated liposomal doxorubicin, is under process in clinical studies. Here we conducted the PEGylated nanoliposomal doxorubicin particles that are covalently attached to the glutathione using the post-insertion technique. The post-insertion methodology is noticeably simpler, faster, and more cost-effective compared to the pre-insertion method which makes it desirable for large-scale pharmaceutical manufacturing. The 25, 50, 100, 200, and 400 ligands of the DSPE PEG(2000) Maleimide-GSH complexes were incorporated into the available Caelyx. According to the animal studies such as biodistribution, fluorescent microscopy, and pharmacokinetic studies, the 200L and 400L treatment arms were the most promising formulations compared to the Caelyx. They proved that post-inserted nanocarriers with 40 times lower levels of GSH micelles compared to the 2B3-101 have significantly increased the penetrance through the blood-brain barrier. Other tissue analysis showed that the doxorubicin will likely accumulate in the liver, spleen, heart, and lung in comparison with the Caelyx due to the expressed GSH receptors on tissues as an endogenous antioxidant. In conclusion, as was expected, the post-insertion technique was found a successful approach with more pharmaceutical aspects for large-scale production. Moreover, it is highly recommended further investigations to determine the efficacy of 5% post-inserted GSH targeted nanoliposomes versus the 2B3-101 as a similar formulation with a different preparation method.

scholarly journals An Antivirulence Approach for Preventing Cryptococcus neoformans from Crossing the Blood-Brain Barrier via Novel Natural Product Inhibitors of a Fungal Metalloprotease

mBio ◽  
2020 ◽  
Vol 11 (4) ◽  
Author(s):  
Phylicia A. Aaron ◽  
Kiem Vu ◽  
Angie Gelli
Keyword(s):  
Cryptococcus Neoformans ◽  
Blood Brain Barrier ◽  
Cryptococcal Meningitis ◽  
Mammalian Cells ◽  
Large Scale ◽  
Fungal Infections ◽  
Antifungal Drugs ◽  
Brain Barrier ◽  
Content Type ◽  
Blood Brain

ABSTRACT Cryptococcus neoformans (Cn) is the leading cause of fungal meningitis, a deadly disease with limited therapeutic options. Dissemination to the central nervous system hinges on the ability of Cn to breach the blood-brain barrier (BBB) and is considered an attribute of Cn virulence. Targeting virulence instead of growth for antifungal drug development has not been fully exploited despite the benefits of this approach. Mpr1 is a secreted fungal metalloprotease not required for fungal growth, but rather, it functions as a virulence factor by facilitating Cn migration across the BBB. This central role for Mpr1, its extracellular location, and lack of expression in mammalian cells make Mpr1 a high-value target for an antivirulence approach aimed at developing therapeutics for cryptococcal meningitis. To test this notion, we devised a large-scale screen to identify compounds that prohibited Cn from crossing the BBB by selectively blocking Mpr1 proteolytic activity, without inhibiting the growth of Cn. A phytochemical natural product-derived library was screened to identify new molecular scaffolds of prototypes unique to a Cn microecosystem. Of the 240 pure natural products examined, 3 lead compounds, abietic acid, diosgenin, and lupinine inhibited Mpr1 proteolytic activity with 50% inhibitory concentration (IC50) values of <10 μM, displayed little to no mammalian cell toxicity, and did not affect Cn growth. Notably, the lead compounds blocked Cn from crossing the BBB, without damaging the barrier integrity, suggesting the bioactive molecules had no off-target effects. We propose that these new drug scaffolds are promising candidates for the development of antivirulence therapy against cryptococcal meningitis. IMPORTANCE Fungal infections like cryptococcal meningitis are difficult to resolve because of the limited therapies available. The small arsenal of antifungal drugs reflect the difficulty in finding available targets in fungi because like mammalian cells, fungi are eukaryotes. The limited efficacy, toxicity, and rising resistance of antifungals contribute to the high morbidity and mortality of fungal infections and further underscore the dire but unmet need for new antifungal drugs. The traditional approach in antifungal drug development has been to target fungal growth, but an attractive alternative is to target mechanisms of pathogenesis. An important attribute of Cryptococcus neoformans (Cn) pathogenesis is its ability to enter the central nervous system. Here, we describe a large-scale screen that identified three natural products that prevented Cn from crossing the blood-brain barrier by inhibiting the virulence factor Mpr1 without affecting the growth of Cn. We propose that compounds identified here could be further developed as antivirulence therapy that would be administered preemptively or serve as a prophylactic in patients at high risk for developing cryptococcal meningitis.

scholarly journals Prediction of Blood-Brain Barrier Penetration (BBBP) Based on Molecular Descriptors of the Free-Form and In-Blood-Form Datasets

Molecules ◽  
2021 ◽  
Vol 26 (24) ◽  
pp. 7428
Author(s):  
Hiroshi Sakiyama ◽  
Motohisa Fukuda ◽  
Takashi Okuno
Keyword(s):  
Blood Brain Barrier ◽  
Molecular Descriptors ◽  
Predictive Performance ◽  
Comparable Result ◽  
Brain Barrier ◽  
Free Form ◽  
Reliable Prediction ◽  
Blood Brain ◽  
Barrier Penetration ◽  
The Brain

The blood-brain barrier (BBB) controls the entry of chemicals from the blood to the brain. Since brain drugs need to penetrate the BBB, rapid and reliable prediction of BBB penetration (BBBP) is helpful for drug development. In this study, free-form and in-blood-form datasets were prepared by modifying the original BBBP dataset, and the effects of the data modification were investigated. For each dataset, molecular descriptors were generated and used for BBBP prediction by machine learning (ML). For ML, the dataset was split into training, validation, and test data by the scaffold split algorithm MoleculeNet used. This creates an unbalanced split and makes the prediction difficult; however, we decided to use that algorithm to evaluate the predictive performance for unknown compounds dissimilar to existing ones. The highest prediction score was obtained by the random forest model using 212 descriptors from the free-form dataset, and this score was higher than the existing best score using the same split algorithm without using any external database. Furthermore, using a deep neural network, a comparable result was obtained with only 11 descriptors from the free-form dataset, and the resulting descriptors suggested the importance of recognizing the glucose-like characteristics in BBBP prediction.

scholarly journals A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system

2010 ◽  
Vol 46 (4) ◽  
pp. 741-751 ◽  
Author(s):  
Matheus Malta de Sá ◽  
Kerly Fernanda Mesquita Pasqualoto ◽  
Carlota de Oliveira Rangel-Yagui
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Partition Coefficient ◽  
Blood Brain Barrier ◽  
Molecular Descriptors ◽  
Biological Data ◽  
Brain Barrier ◽  
Qspr Model ◽  
Blood Brain ◽  
The Central Nervous System

Drugs acting on the central nervous system (CNS) have to cross the blood-brain barrier (BBB) in order to perform their pharmacological actions. Passive BBB diffusion can be partially expressed by the blood/brain partition coefficient (logBB). As the experimental evaluation of logBB is time and cost consuming, theoretical methods such as quantitative structure-property relationships (QSPR) can be useful to predict logBB values. In this study, a 2D-QSPR approach was applied to a set of 28 drugs acting on the CNS, using the logBB property as biological data. The best QSPR model [n = 21, r = 0.94 (r² = 0.88), s = 0.28, and Q² = 0.82] presented three molecular descriptors: calculated n-octanol/water partition coefficient (ClogP), polar surface area (PSA), and polarizability (α). Six out of the seven compounds from the test set were well predicted, which corresponds to good external predictability (85.7%). These findings can be helpful to guide future approaches regarding those molecular descriptors which must be considered for estimating the logBB property, and also for predicting the BBB crossing ability for molecules structurally related to the investigated set.

scholarly journals Large-Scale Evaluation of Collision Cross Sections to Investigate Blood-Brain Barrier Permeation of Drugs

Pharmaceutics ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2141
Author(s):  
Armin Sebastian Guntner ◽  
Thomas Bögl ◽  
Franz Mlynek ◽  
Wolfgang Buchberger
Keyword(s):  
Drug Development ◽  
Blood Brain Barrier ◽  
Large Scale ◽  
Spatial Information ◽  
Collision Cross Section ◽  
Chemical Properties ◽  
Molecular Size ◽  
Brain Barrier ◽  
Early Evaluation ◽  
Blood Brain

Successful drug administration to the central nervous system requires accurate adjustment of the drugs’ molecular properties. Therefore, structure-derived descriptors of potential brain therapeutic agents are essential for an early evaluation of pharmacokinetics during drug development. The collision cross section (CCS) of molecules was recently introduced as a novel measurable parameter to describe blood-brain barrier (BBB) permeation. This descriptor combines molecular information about mass, structure, volume, branching and flexibility. As these chemical properties are known to influence cerebral pharmacokinetics, CCS determination of new drug candidates may provide important additional spatial information to support existing models of BBB penetration of drugs. Besides measuring CCS, calculation is also possible; but however, the reliability of computed CCS values for an evaluation of BBB permeation has not yet been fully investigated. In this work, prediction tools based on machine learning were used to compute CCS values of a large number of compounds listed in drug libraries as negative or positive with respect to brain penetration (BBB+ and BBB− compounds). Statistical evaluation of computed CCS and several other descriptors could prove the high value of CCS. Further, CCS-deduced maximum molecular size of BBB+ drugs matched the dimensions of BBB pores. A threshold for transcellular penetration and possible permeation through pore-like openings of cellular tight-junctions is suggested. In sum, CCS evaluation with modern in silico tools shows high potential for its use in the drug development process.

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