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In silico drug metabolism and pharmacokinetic profiles of natural products from medicinal plants in the Congo basin.

Ntie-Kang F, Lifongo LL, Mbah JA, Owono Owono LC, Megnassan E, Mbaze LM, Judson PN, Sippl W, Efange SM - In Silico Pharmacol (2013)

Bottom Line: Material from some of the plant sources are currently employed in African Traditional Medicine.This survey demonstrated that about 45% of the compounds within the ConMedNP compound library are compliant, having properties which fall within the range of ADME properties of 95% of currently known drugs, while about 69% of the compounds have ≤ 2 violations.Moreover, about 73% of the compounds within the corresponding "drug-like" subset showed compliance.

View Article: PubMed Central - PubMed

Affiliation: CEPAMOQ, Faculty of Science, University of Douala, P.O. Box 8580, Douala, Cameroon ; Chemical and Bioactivity Information Centre, Department of Chemistry, Faculty of Science, University of Buea, P.O. Box 63, Buea, Cameroon ; Department of Pharmaceutical Sciences, Martin-Luther University of Halle-Wittenberg, Wolfgang-Langenbeck Str. 4, 06120 Halle (Saale), Germany.

ABSTRACT

Purpose: Drug metabolism and pharmacokinetics (DMPK) assessment has come to occupy a place of interest during the early stages of drug discovery today. The use of computer modelling to predict the DMPK and toxicity properties of a natural product library derived from medicinal plants from Central Africa (named ConMedNP). Material from some of the plant sources are currently employed in African Traditional Medicine.

Methods: Computer-based methods are slowly gaining ground in this area and are often used as preliminary criteria for the elimination of compounds likely to present uninteresting pharmacokinetic profiles and unacceptable levels of toxicity from the list of potential drug candidates, hence cutting down the cost of discovery of a drug. In the present study, we present an in silico assessment of the DMPK and toxicity profile of a natural product library containing ~3,200 compounds, derived from 379 species of medicinal plants from 10 countries in the Congo Basin forests and savannas, which have been published in the literature. In this analysis, we have used 46 computed physico-chemical properties or molecular descriptors to predict the absorption, distribution, metabolism and elimination and toxicity (ADMET) of the compounds.

Results: This survey demonstrated that about 45% of the compounds within the ConMedNP compound library are compliant, having properties which fall within the range of ADME properties of 95% of currently known drugs, while about 69% of the compounds have ≤ 2 violations. Moreover, about 73% of the compounds within the corresponding "drug-like" subset showed compliance.

Conclusions: In addition to the verified levels of "drug-likeness", diversity and the wide range of measured biological activities, the compounds from medicinal plants in Central Africa show interesting DMPK profiles and hence could represent an important starting point for hit/lead discovery.

No MeSH data available.


Related in: MedlinePlus

Distribution curves for predicted plasma-protein binding. Colour codes are as defined in Figure 1.
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Fig6: Distribution curves for predicted plasma-protein binding. Colour codes are as defined in Figure 1.

Mentions: The efficiency of a drug may be affected by the degree to which it binds to the proteins within blood plasma. It is noteworthy that binding of drugs to plasma proteins (like human serum albumin, lipoprotein, glycoprotein, α, ββ and γ globulins) greatly reduces the quantity of the drug in general blood circulation and hence the less bound a drug is, the more efficiently it can traverse cell membranes or diffuse. The predicted plasma-protein binding has been estimated by the prediction of binding to human serum albumin; the log KHSA parameter (recommended range is −1.5 to 1.5 for 95% of known drugs). Figure 6 shows the variation of this calculated parameter within the ConMedNP dataset, as well as for the standard subsets. This equally gave smooth Gaussian-shaped curves centred on −0.5 log KHSA units for the total and “drug-like” libraries and −1.5 log KHSA units for the “lead-like” and “fragment-like” datasets. In addition, our calculations reveal that > 81% of the compounds within the ConMedNP library are compliant to this parameter, indicating that a majority of the compounds are likely to circulate freely within the blood stream and hence have access to the target site.Figure 6


In silico drug metabolism and pharmacokinetic profiles of natural products from medicinal plants in the Congo basin.

Ntie-Kang F, Lifongo LL, Mbah JA, Owono Owono LC, Megnassan E, Mbaze LM, Judson PN, Sippl W, Efange SM - In Silico Pharmacol (2013)

Distribution curves for predicted plasma-protein binding. Colour codes are as defined in Figure 1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230438&req=5

Fig6: Distribution curves for predicted plasma-protein binding. Colour codes are as defined in Figure 1.
Mentions: The efficiency of a drug may be affected by the degree to which it binds to the proteins within blood plasma. It is noteworthy that binding of drugs to plasma proteins (like human serum albumin, lipoprotein, glycoprotein, α, ββ and γ globulins) greatly reduces the quantity of the drug in general blood circulation and hence the less bound a drug is, the more efficiently it can traverse cell membranes or diffuse. The predicted plasma-protein binding has been estimated by the prediction of binding to human serum albumin; the log KHSA parameter (recommended range is −1.5 to 1.5 for 95% of known drugs). Figure 6 shows the variation of this calculated parameter within the ConMedNP dataset, as well as for the standard subsets. This equally gave smooth Gaussian-shaped curves centred on −0.5 log KHSA units for the total and “drug-like” libraries and −1.5 log KHSA units for the “lead-like” and “fragment-like” datasets. In addition, our calculations reveal that > 81% of the compounds within the ConMedNP library are compliant to this parameter, indicating that a majority of the compounds are likely to circulate freely within the blood stream and hence have access to the target site.Figure 6

Bottom Line: Material from some of the plant sources are currently employed in African Traditional Medicine.This survey demonstrated that about 45% of the compounds within the ConMedNP compound library are compliant, having properties which fall within the range of ADME properties of 95% of currently known drugs, while about 69% of the compounds have ≤ 2 violations.Moreover, about 73% of the compounds within the corresponding "drug-like" subset showed compliance.

View Article: PubMed Central - PubMed

Affiliation: CEPAMOQ, Faculty of Science, University of Douala, P.O. Box 8580, Douala, Cameroon ; Chemical and Bioactivity Information Centre, Department of Chemistry, Faculty of Science, University of Buea, P.O. Box 63, Buea, Cameroon ; Department of Pharmaceutical Sciences, Martin-Luther University of Halle-Wittenberg, Wolfgang-Langenbeck Str. 4, 06120 Halle (Saale), Germany.

ABSTRACT

Purpose: Drug metabolism and pharmacokinetics (DMPK) assessment has come to occupy a place of interest during the early stages of drug discovery today. The use of computer modelling to predict the DMPK and toxicity properties of a natural product library derived from medicinal plants from Central Africa (named ConMedNP). Material from some of the plant sources are currently employed in African Traditional Medicine.

Methods: Computer-based methods are slowly gaining ground in this area and are often used as preliminary criteria for the elimination of compounds likely to present uninteresting pharmacokinetic profiles and unacceptable levels of toxicity from the list of potential drug candidates, hence cutting down the cost of discovery of a drug. In the present study, we present an in silico assessment of the DMPK and toxicity profile of a natural product library containing ~3,200 compounds, derived from 379 species of medicinal plants from 10 countries in the Congo Basin forests and savannas, which have been published in the literature. In this analysis, we have used 46 computed physico-chemical properties or molecular descriptors to predict the absorption, distribution, metabolism and elimination and toxicity (ADMET) of the compounds.

Results: This survey demonstrated that about 45% of the compounds within the ConMedNP compound library are compliant, having properties which fall within the range of ADME properties of 95% of currently known drugs, while about 69% of the compounds have ≤ 2 violations. Moreover, about 73% of the compounds within the corresponding "drug-like" subset showed compliance.

Conclusions: In addition to the verified levels of "drug-likeness", diversity and the wide range of measured biological activities, the compounds from medicinal plants in Central Africa show interesting DMPK profiles and hence could represent an important starting point for hit/lead discovery.

No MeSH data available.


Related in: MedlinePlus