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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 compliance to Jorgensen’s “Rule of Three”. (A) calculated logSwat against count, (B) predicted BIPcaco–2 against count. Colour codes are as defined in Figure 1.
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Fig2: Distribution curves for compliance to Jorgensen’s “Rule of Three”. (A) calculated logSwat against count, (B) predicted BIPcaco–2 against count. Colour codes are as defined in Figure 1.

Mentions: where S is the similarity, and Pexp and PQP are the respective experimental and QikProp predictions for the most similar molecule within the training set. In equation (1), if S = 1, then the predicted property is equal to the measured experimental property of the training set compound. According to Jorgensen’s ro3, if a compound complies to all or some of the rules (logSwat > −5.7, BIPcaco–2 > 22 nm/s and # Primary Metabolites < 7), then it is more likely to be orally available. The distribution curves for two of the three determinants for the ro3 (logSwat and BIPcaco–2) are shown in Figure 2. In general 43.57% of the ConMedNP library was compliant to the ro3, while the respective % compliances for the various subsets were 73.52%, 93.56% and 100% for the “drug-like”, “lead-like” and “fragment-like” libraries. Among the individual computed parameters, the most remarkable was logSwat. This was met by 72.46% of the compounds within the ConMedNP library, while this property showed a Gaussian distribution for the “drug-like” and “lead-like” subsets. Only 37.28% of the compounds fell within the respected range for the BIPcaco–2 criterion. The predicted apparent Caco-2 cell permeability, BIPcaco–2 (in nm s-1), model the permeability of the gut-blood barrier (for non-active transport), even though this parameter is not often correctly predicted computationally (Veber et al. 2002). The histograms of the predicted qualitative human oral absorption parameter (in the scale 1 = low, 2 = medium and 3 = high) are shown in Figure 3. It was observed 48.65% of the compounds in ConMedNP were predicted to have high human oral absorption. The predicted % human oral absorption (on 0 to 100% scale) shows a similar trend, 42.09% of the compounds being predicted to be absorbed at 100% and 57.81% of the compounds predicted to be absorbed at > 90%.Figure 2


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 compliance to Jorgensen’s “Rule of Three”. (A) calculated logSwat against count, (B) predicted BIPcaco–2 against count. 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

Fig2: Distribution curves for compliance to Jorgensen’s “Rule of Three”. (A) calculated logSwat against count, (B) predicted BIPcaco–2 against count. Colour codes are as defined in Figure 1.
Mentions: where S is the similarity, and Pexp and PQP are the respective experimental and QikProp predictions for the most similar molecule within the training set. In equation (1), if S = 1, then the predicted property is equal to the measured experimental property of the training set compound. According to Jorgensen’s ro3, if a compound complies to all or some of the rules (logSwat > −5.7, BIPcaco–2 > 22 nm/s and # Primary Metabolites < 7), then it is more likely to be orally available. The distribution curves for two of the three determinants for the ro3 (logSwat and BIPcaco–2) are shown in Figure 2. In general 43.57% of the ConMedNP library was compliant to the ro3, while the respective % compliances for the various subsets were 73.52%, 93.56% and 100% for the “drug-like”, “lead-like” and “fragment-like” libraries. Among the individual computed parameters, the most remarkable was logSwat. This was met by 72.46% of the compounds within the ConMedNP library, while this property showed a Gaussian distribution for the “drug-like” and “lead-like” subsets. Only 37.28% of the compounds fell within the respected range for the BIPcaco–2 criterion. The predicted apparent Caco-2 cell permeability, BIPcaco–2 (in nm s-1), model the permeability of the gut-blood barrier (for non-active transport), even though this parameter is not often correctly predicted computationally (Veber et al. 2002). The histograms of the predicted qualitative human oral absorption parameter (in the scale 1 = low, 2 = medium and 3 = high) are shown in Figure 3. It was observed 48.65% of the compounds in ConMedNP were predicted to have high human oral absorption. The predicted % human oral absorption (on 0 to 100% scale) shows a similar trend, 42.09% of the compounds being predicted to be absorbed at 100% and 57.81% of the compounds predicted to be absorbed at > 90%.Figure 2

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