AfroDb: a select highly potent and diverse natural product library from African medicinal plants

Abstract

Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We assess the bioactivity and "drug-likeness" of a relatively small but structurally diverse dataset (containing >1,000 compounds) from African medicinal plants, which have been tested and proven a wide range of biological activities. The geographical regions of collection of the medicinal plants cover the entire continent of Africa, based on data from literature sources and information from traditional healers. For each isolated compound, the three dimensional (3D) structure has been used to calculate physico-chemical properties used in the prediction of oral bioavailability on the basis of Lipinski's "Rule of Five". A comparative analysis has been carried out with the "drug-like", "lead-like", and "fragment-like" subsets, as well as with the Dictionary of Natural Products. A diversity analysis has been carried out in comparison with the ChemBridge diverse database. Furthermore, descriptors related to absorption, distribution, metabolism, excretion and toxicity (ADMET) have been used to predict the pharmacokinetic profile of the compounds within the dataset. Our results prove that drug discovery, beginning with natural products from the African flora, could be highly promising. The 3D structures are available and could be useful for virtual screening and natural product lead generation programs.

Figure 1. Bar chart showing the distribution of the compounds within AfroDb by region of collection.

Figure 2. Graph distribution of features that determine “drug-likeness”.

(A, B) Histogram of Lipinski violations as a percentage of the AfroDb data set and molar weight distribution, respectively. (C, D, E, F) Distribution curves of the log P, HBA, HBD and NRB, respectively for the 1,008 compounds currently in AfroDb. For subfigure B, the x-axis label is the lower limit of binned data, e.g. 0 is equivalent to 0 to 100.

Figure 3. 2D structures of the three compounds with log P values >14, included in AfroDb.

Figure 4. Pairwise comparison of mutual relationships between molecular descriptors.

(A) The distribution of the calculated log P versus MW, (B) HBA against MW, (C) HBD against MW and (D) NRB versus MW. LCR represents the Lipinski compliant regions.

Figure 5. Comparison of property distribution for the two datasets by percentage distributions.

(A) MW, (B) log P, (C) HBA and (D) HBD. DNP in red and AfroDb in blue. For subfigure B, the x-axis label is the lower limit of binned data, e.g. −2 is equivalent to −2 to −1.

Figure 6. Distribution curves for #stars within the AfroDb library, along with the standard “drug-like”, “lead-like” and “fragment-like” subsets.

Blue = AfroDb library, red = “drug-like” subset, green = “lead-like” subset and violet = “fragment-like” subset.

Figure 7. Distibution curves for some computed ADME parameters.

(A) logB/B, (B) logK _HSA, (C) logHERG. For subfigure B, the x-axis label is the lower limit of binned data, e.g. −2 is equivalent to −2 to −1. The colour codes are according to Figure 5.

Figure 8. A simple descriptor-based comparison of the AfroDb database and the ChemBridge Diversity database.

Comparison of typical physico-chemical property distributions (MW, HBA, HBD, NCC, NO, NRB, log P, NR and TPSA) in the AfroDb (green) and ChemBridge Diverset (red) database. All histograms and scatterplots were generated with the R software .

Figure 9. A principal component analysis (PCA) plot, showing the comparison of the chemical space defined by the NPs in AfroDb (green) and the chemical space represented by NPs in the ChemBridge Diversity (red) databases.

Figure 10. MCSS panel in AfroDb, featuring the most common cyclic structures included in the database.

Figure 11. 2D structures of selected promising compounds derived from the African flora and included in AfroDb.