7 research outputs found
Qualitative prediction of bloodâbrain barrier permeability on a large and refined dataset
The prediction of bloodâbrain barrier permeation is vitally important for the optimization of drugs targeting the central nervous system as well as for avoiding side effects of peripheral drugs. Following a previously proposed model on bloodâbrain barrier penetration, we calculated the cross-sectional area perpendicular to the amphiphilic axis. We obtained a high correlation between calculated and experimental cross-sectional area (r = 0.898, n = 32). Based on these results, we examined a correlation of the calculated cross-sectional area with bloodâbrain barrier penetration given by logBB values. We combined various literature data sets to form a large-scale logBB dataset with 362 experimental logBB values. Quantitative models were calculated using bootstrap validated multiple linear regression. Qualitative models were built by a bootstrapped random forest algorithm. Both methods found similar descriptors such as polar surface area, pKa, logP, charges and number of positive ionisable groups to be predictive for logBB. In contrast to our initial assumption, we were not able to obtain models with the cross-sectional area chosen as relevant parameter for both approaches. Comparing those two different techniques, qualitative random forest models are better suited for blood-brain barrier permeability prediction, especially when reducing the number of descriptors and using a large dataset. A random forest prediction system (ntrees = 5) based on only four descriptors yields a validated accuracy of 88%
Chromatographic and computational screening of lipophilicity and pharmacokinetics of newly synthesized betulin-1,4-quinone hybrids
Lipophilicity is one of the most important parameters determining the pharmacodynamic and pharmacokinetic properties, as well as the toxicity of many compounds. The subject of the research was to determine the lipophilicity of betulin-1,4-quinone hybrids using thin layer chro-matography in reverse phase system and computer programs to calculate its theoretical models. The correlation between the experimental and theoretical values of lipophilicity was analyzed. Lipinskiâs and Veberâs rules, as well as penetration through the bloodâbrain barrier were also determined using computer programs. For all of the analyzed values, a similarity analysis was performed. The dendrograms for the experimental and theoretical lipophilicity show that there is a correlation between them. However, the dendrograms for the experimental lipophilicity and pharmacokinetic parameters indicate that there is no correlation between the structure and the pharmacological properties. Hybrids exhibit a high biological activity against cancer cell lines, with a high level of NAD[P]H-quinone oxidoreductase (NQO1) protein. The enzymatic assay used has shown that these compounds are good NQO1 substrates, as evidenced by the increasing metabolic rates relative to that of streptonigrin. The similarity analysis has also shown that there is no correlation between lipophilicity and biological activity for the tested compounds
Validacija topokemijskih modela za predviÄanje permeabilnosti kroz krvno-moĹždanu barijeru
Recently published topochemical models for permeability through the blood-brain barrier were validated and cross-validated in the present study. Five models based on three topochemical indices, Wienerâs topochemical index - a distance-based topochemical descriptor, molecular connectivity topochemical index - an adjacency-based topochemical descriptor and eccentric connectivity topochemical index - an adjacency-cum-distance based topochemical descriptor, for permeability of structurally and chemically diverse molecules through blood-brain barrier were used in the present investigation. A data set comprising 62 structurally and chemically diverse compounds was selected. This data set was divided into two sets of 31 compounds each - one to serve as the validation set and other as the cross-validation set. The values of all the three-topochemical indices in the original as well as in the normalized form for each of the 31 compounds of the validation set were computed using an in house computer program. Resultant data was analyzed and each compound was assigned a permeability characteristic using topochemical models, which was then compared with the reported permeability through the blood-brain barrier. Accuracy of prediction of these models was calculated. The same procedure was similarly followed for the cross-validation set. Studies revealed accuracy of prediction of the order of 7080% during validation. Surprisingly, very high predictability of the order of 7791% was observed during cross-validation. High predictability observed during validation as well as cross-validation authenticates topochemical models for prediction of permeability through the blood-brain barrier.U ovom radu su validirani i unakrsno validirani nedavno objavljeni topokemijski modeli za permeabilnost kroz krvno-moĹždanu barijeru. PredviÄanje prolaska kroz krvno-moĹždanu barijeru strukturno i kemijski razliÄitih molekula provedeno je na pet modela koji se temelje na tri topoloĹĄka indeksa, Wienerovom topoloĹĄkom indeksu, topoloĹĄkom indeksu molekularne povezanosti i topoloĹĄkom indeksu ekscentriÄne povezanosti. Ukupno 62 spoja podijeljena su u dva seta koji su sadrĹžavali 31 spoj. Jedan set upotrebljen je za validaciju, a drugi za unakrsnu validaciju. Vrijednosti svih triju topoloĹĄkih indeksa u poÄetnom setu i u normaliziranom setu su raÄunate pomoÄu kompjutorskog programa. Rezultati su analizirani i svakom spoju je pridruĹžena teorijska vrijednost permeabilnosti, koja je zatim usporeÄivana s objavljenim eksperimentalnim podacima za permeabilnost kroz krvno-moĹždanu barijeru. ToÄnost predviÄanja bila je izmeÄu 70 i 80%. Isti postupak je proveden za unakrsno validacijski set, a toÄnost je bila iznenaÄujeÄe velika (7791%), ĹĄto ukazuje da se upotrebljeni topokemijski modeli mogu upotrijebiti za predviÄanje permeabilnsot kroz krvno-moĹždanu barijeru
Lipophilicity, pharmacokinetic properties, and molecular docking study on SARS-CoV-2 target for betulin triazole derivatives with attached 1,4- quinone
A key parameter in the design of new active compounds is lipophilicity, which influences
the solubility and permeability through membranes. Lipophilicity affects the pharmacodynamic
and toxicological profiles of compounds. These parameters can be determined experimentally or
by using different calculation methods. The aim of the research was to determine the lipophilicity
of betulin triazole derivatives with attached 1,4-quinone using thin layer chromatography in a
reverse phase system and a computer program to calculate its theoretical model. The physiochemical
and pharmacokinetic properties were also determined by computer programs. For all obtained
parameters, the similarity analysis and multilinear regression were determined. The analyses showed
that there is a relationship between structure and properties under study. The molecular docking
study showed that betulin triazole derivatives with attached 1,4-quinone could inhibit selected
SARS-CoV-2 proteins. The MLR regression showed that there is a correlation between affinity scoring
values (DG) and the physicochemical properties of the tested compounds
Review of QSAR Models and Software Tools for predicting Biokinetic Properties
In the assessment of industrial chemicals, cosmetic ingredients, and active substances in pesticides and biocides, metabolites and degradates are rarely tested for their toxicologcal effects in mammals. In the interests of animal welfare and cost-effectiveness, alternatives to animal testing are needed in the evaluation of these types of chemicals. In this report we review the current status of various types of in silico estimation methods for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their metabolites/degradation products. The review was performed in a broad sense, with emphasis on QSARs and rule-based approaches and their applicability to estimation of oral bioavailability, human intestinal absorption, blood-brain barrier penetration, plasma protein binding, metabolism and. This revealed a vast and rapidly growing literature and a range of software tools.
While it is difficult to give firm conclusions on the applicability of such tools, it is clear that many have been developed with pharmaceutical applications in mind, and as such may not be applicable to other types of chemicals (this would require further research investigation). On the other hand, a range of predictive methodologies have been explored and found promising, so there is merit in pursuing their applicability in the assessment of other types of chemicals and products. Many of the software tools are not transparent in terms of their predictive algorithms or underlying datasets. However, the literature identifies a set of commonly used descriptors that have been found useful in ADME prediction, so further research and model development activities could be based on such studies.JRC.DG.I.6-Systems toxicolog