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ADMET & DMPK ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 267-281
Author(s):  
Lucia Grumetto ◽  
Giacomo Russo

56 compounds, whose log BB values were known from the scientific literature, were considered and their phospholipophilicity values were calculated in silico. These values, along with either experimentally determined or calculated lipophilicity values, were used to extract cΔ/Δ’log kwIAM parameters. cΔ/Δ’log kwIAM values were found inversely related to data of blood-brain barrier passage, especially in the < -0.20 log BB range and on the IAM.PC.DD2 phase (r2 = 0.79). In multiple linear regression, satisfactory statistic models (r2 (n-1) = 0.76), based on cD/D’log kwIAM.MG along with other in silico calculated descriptors, were achieved. This method brings the potential to be applied, along with other methodologies, to filter out solutes whose BBB permeation is foreseen to be substandard, thus allowing pharmaceutical companies/research institutes to focus on candidates that are more likely to concentrate in the brain.


Molecules ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 487 ◽  
Author(s):  
Małgorzata Janicka ◽  
Małgorzata Sztanke ◽  
Krzysztof Sztanke

The permeation of the blood-brain barrier is a very important consideration for new drug candidate molecules. In this research, the reversed-phase liquid chromatography with different columns (Purosphere RP-18e, IAM.PC.DD2 and Cosmosil Cholester) was used to predict the penetration of the blood-brain barrier by 65 newly-synthesized drug-like compounds. The linear free energy relationships (LFERs) model (log BB = c + eE + sS + aA + bB + vV) was established for a training set of 23 congeneric biologically active azole compounds with known experimental log BB (BB = Cblood/Cbrain) values (R2 = 0.9039). The reliability and predictive potency of the model were confirmed by leave-one-out cross validation as well as leave-50%-out cross validation. Multiple linear regression (MLR) was used to develop the quantitative structure-activity relationships (QSARs) to predict the log BB values of compounds that were tested, taking into account the chromatographic lipophilicity (log kw), polarizability and topological polar surface area. The excellent statistics of the developed MLR equations (R2 > 0.8 for all columns) showed that it is possible to use the HPLC technique and retention data to produce reliable blood-brain barrier permeability models and to predict the log BB values of our pharmaceutically important molecules.


2019 ◽  
Vol 15 ◽  
Author(s):  
Shalu Singh ◽  
Alka Bali ◽  
Tania Peshin

Background: Schizophrenia is a disorder with complex etiology with hyperdopaminergia as the main underlying cause. Atypical antipsychotics are the agents which do not give rise to significant extrapyramidal side effects and are more effective against negative symptoms of schizophrenia. Introduction: A new series of chloro-substituted substituted aryloxypiperazine derivatives and their indole based derivatives was designed and evaluated for atypical antipsychotic activity based on established models for combined dopaminergic and serotonergic antagonism. Method: The present series of compounds were designed based on 3D similarity studies, synthesized and evaluated for atypical antipsychotic activity in animal models for combined dopaminergic and serotonergic antagonism. The blood brain barrier penetration potential was assessed from theoretical log BB values computed through an online software program. Results: Theoretical ADME profiling of the designed compounds based on selected physicochemical parameters suggested an excellent compliance with Lipinski’s rules. The log BB values obtained for the compounds suggested a good potential for brain permeation. Indole substitution contributed towards an improved efficacy over aryloxy analogs. Lead compounds showed a potential for combined dopaminergic and serotonergic antagonism. Conclusion: The 5-methoxy indole based compounds 16 and 17 were identified as the lead compounds displaying a potential atypical antipsychotic profile.


2015 ◽  
Vol 13 (1) ◽  
pp. 7-14
Author(s):  
Lubica Havranova Sichrovska ◽  
Ivan Malik ◽  
Eva Sedlarova ◽  
Jozef Csollei ◽  
Lukas Stanzel ◽  
...  

The present study deals with blood-brain barrier (BBB) passive penetration of the substances labelled as 7a–7d and chemically referred to as 1-[3-(Y-alkoxyphenylcarbamoyloxy)-2-hydroxypropyl]-4-(2-methylphenyl) piperazinium chlorides. Following their chemical structures, they could be classified as prospective ?-/?-adrenoceptor blockers. Such groups are known, among others, by their adverse reactions on central nervous system due to their transport across the BBB. The lipophilicity as the main parameter of the BBB permeability predictions is presented by the values of partition coefficient which was experimentally estimated using shake-flask method in two different partitions, i.e. in octan-1-ol/buffer and cyclohexane/buffer as well. The in silico models which were used are based on the correlation between the log BB and the ? log P readouts (the log P value estimated in octan-1-ol/buffer minus the one estimated in cyclohexane/buffer) whereby log BB is primary transfer marker for such compounds entering brain from blood. Besides the log BB outputs, some other molecular physicochemical descriptors have to be generated. According to the results obtained by using Young, Kaliszan, Kelder, Clarks, Pan, Abraham, Feher and van de Waterbeemd models, probably none of the currently investigated compounds will permeate across the BBB. DOI: http://dx.doi.org/10.3329/dujps.v13i1.21854 Dhaka Univ. J. Pharm. Sci. 13(1): 7-14, 2014 (June)


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