Quantifying biogenic bias in screening libraries

Abstract

In lead discovery, libraries of 10(6) molecules are screened for biological activity. Given the over 10(60) drug-like molecules thought possible, such screens might never succeed. The fact that they do, even occasionally, implies a biased selection of library molecules. We have developed a method to quantify the bias in screening libraries toward biogenic molecules. With this approach, we consider what is missing from screening libraries and how they can be optimized.

Figure 1

Overlap between commercially available molecules and the GDB gives the purchasable GDB.

Figure 2. Compounds in screening libraries are biased toward biogenic molecules

Percentage of the GDB and purchasable-GDB databases as a function of the Tanimoto similarity to their nearest neighbor in [a] the KEGG and [b] the Dictionary of Natural Compound databases. Percentage of the GDB, the purchasable-GDB, Asinex (360 042 compounds − 815 GDB compliant compounds), Chembridge (473 745 compounds − 389 GDB compliant compounds); IBS (424 806 compounds − 884 GDB compliant compounds), Life Chemicals (285 581 compounds − 172 GDB compliant compounds), Otava (121 657 compounds − 287 GDB compliant compounds) databases as a function of the Tanimoto similarity to their nearest neighbor to the [c] KEGG and the [d] Dictionary of Natural Products databases.

Figure 3

Ratio of the percentage of compounds in the purchasable-GDB and GDB databases that had a similarity ≥ 0.75 to their nearest neighbor in [a] the KEGG and [b] the Dictionary of Natural Products databases versus the number of heavy atoms up to which the database compound (in purchasable-GDB and GDB) are considered.