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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 #stars within the ConMedNP library, along with the standard “drug-like”, “lead-like” and “fragment-like” subsets. Blue = ConMedNP library, red = “drug-like” subset, green = “lead-like” subset and violet = “fragment-like” subset.
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Fig1: Distribution curves for #stars within the ConMedNP library, along with the standard “drug-like”, “lead-like” and “fragment-like” subsets. Blue = ConMedNP library, red = “drug-like” subset, green = “lead-like” subset and violet = “fragment-like” subset.

Mentions: The 24 most relevant molecular descriptors calculated by QikProp are used to determine the #star parameter (Schrödinger 2011d). A plot of the #stars parameter (on x-axis) against the corresponding counts (on y-axis) in the ConMedNP is plotted within the same set of axes with those of the “drug-like”, “lead-like”, and “fragment-like” standard subsets (Figure 1). The criteria for the respective standard subsets were defined as (MW < 500; log P < 5; HBD ≤ 5; HBA ≤ 10) (Lipinski et al. 1997), (150 ≤ MW ≤ 350; log P ≤ 4; HBD ≤ 3; HBA ≤ 6) (Teague et al. 1999; Oprea 2002; Schneider 2002) and (MW ≤ 250; -2 ≤ log P ≤ 3; HBD < 3; HBA < 6; NRB < 3) (Verdonk et al. 2003). The ADMET descriptors for some 67 compounds in the total library were not computed by QikProp, probably due to some technical details related to the working of the software which was beyond our notice. Of the remaining 3,112 compounds, 45.31% showed #star = 0, while 68.93% had #star ≤ 2. Among the 1,696 compounds of the “drug-like” subset whose pharmacokinetic properties were predicted, 72.52% had pharmacokinetic descriptors within the acceptable range for 95% of known drugs, while 96.88% showed #stars ≤ 2. The “lead-like” and “fragment-like” subsets were respectively 80.68% and 65.58% compliant for all of the 24 most relevant computed descriptors. The mean values for 19 selected computed descriptors have been shown in Table 2 for all 4 compound libraries, while percentage compliances for 14 selected parameters are shown in Table 3. The mean values were used to assess the probability of finding drug leads within the ConMedNP compound library.Figure 1


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 #stars within the ConMedNP library, along with the standard “drug-like”, “lead-like” and “fragment-like” subsets. Blue = ConMedNP library, red = “drug-like” subset, green = “lead-like” subset and violet = “fragment-like” subset.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig1: Distribution curves for #stars within the ConMedNP library, along with the standard “drug-like”, “lead-like” and “fragment-like” subsets. Blue = ConMedNP library, red = “drug-like” subset, green = “lead-like” subset and violet = “fragment-like” subset.
Mentions: The 24 most relevant molecular descriptors calculated by QikProp are used to determine the #star parameter (Schrödinger 2011d). A plot of the #stars parameter (on x-axis) against the corresponding counts (on y-axis) in the ConMedNP is plotted within the same set of axes with those of the “drug-like”, “lead-like”, and “fragment-like” standard subsets (Figure 1). The criteria for the respective standard subsets were defined as (MW < 500; log P < 5; HBD ≤ 5; HBA ≤ 10) (Lipinski et al. 1997), (150 ≤ MW ≤ 350; log P ≤ 4; HBD ≤ 3; HBA ≤ 6) (Teague et al. 1999; Oprea 2002; Schneider 2002) and (MW ≤ 250; -2 ≤ log P ≤ 3; HBD < 3; HBA < 6; NRB < 3) (Verdonk et al. 2003). The ADMET descriptors for some 67 compounds in the total library were not computed by QikProp, probably due to some technical details related to the working of the software which was beyond our notice. Of the remaining 3,112 compounds, 45.31% showed #star = 0, while 68.93% had #star ≤ 2. Among the 1,696 compounds of the “drug-like” subset whose pharmacokinetic properties were predicted, 72.52% had pharmacokinetic descriptors within the acceptable range for 95% of known drugs, while 96.88% showed #stars ≤ 2. The “lead-like” and “fragment-like” subsets were respectively 80.68% and 65.58% compliant for all of the 24 most relevant computed descriptors. The mean values for 19 selected computed descriptors have been shown in Table 2 for all 4 compound libraries, while percentage compliances for 14 selected parameters are shown in Table 3. The mean values were used to assess the probability of finding drug leads within the ConMedNP compound library.Figure 1

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