Powered by natural selection, nature has spent almost 3 billion years creating a near-perfect natural product library of small molecule ligands, which targeted to specific macromolecules and their biological activities. The chemical complexity and functional diversity of nature’s natural product library is vast and when combined with the fact that nature has essentially performed countless high throughput screens to remove inactive- and retain active-compounds, “natural combinatorial libraries” will always be superior to any library that a team of pharmaceutical scientists can prepare.

These concomitant trends should come as no surprise, as it has long been recognized that natural products are the richest source of chemical diversity available and without doubt represent the most successful and validated strategy of small molecule drug discovery. Between 25% and 50% of approved drugs have their origins as natural products. In fact, one analysis has calculated that in excess of 60% of the 1073 new chemical entities (NCEs) approved between 1981 and 2010 are natural products, derivatives of natural products, or synthetic analogues of natural products.

Based on that trend, the OxAG team started to create its innovative Logi-biotic^® drug discovery platform, which relies on drug design rather than random discovery. The Logi-biotic^® profiling protocol uses various methods to identify certain common core elements that could be critical and needed for the desired activity. The identification of such a core centre, the definition of the active and free sites in the molecule and an early med-chem design makes the approach so successful.

The technology has progressed to successful proof-of-concept, in which chemical libraries mimicking natural product structures have been shown to exhibit bioactive hit rates significantly higher than with combinatorial libraries. This approach permits rapid access to active compounds but without the chemical complexity of the parent natural products.

The OxAGs Log-biotic^® platform has shown that it is an excellent approach that leads to a faster identification of new classes, like the first-in class antibiotic TetramOX^® or the novel Alzheimer and Parkinson lead candidate NeuroMETOX^® and allows the company to create valuable compound libraries for the future.