Application in combinatorial drug discovery

Part of the complexity of drug discovery is the sheer chemical diversity to explore combined to all requirements a compound must meet to become a commercial drug.

These steps can be part of an iterative drug discovery process that will have immediate use in both the pharmaceutical industry and academia.

Drug discovery faces important challenges in terms of cost, complexity and the amount of time required to yield promising compounds.

Hence, drug discovery is a combinatorial problem which, unfortunately, cannot be solved using combinatorial chemistry alone.

Indeed, this transforms the combinatorial drug discovery problem into an equally hard computational task.

Simulation of a drug discovery

They can be applied to molecular selection, in vitro evolution process, high throughput screening and virtual screening for drug discovery .

On the practical side, it is also under intensive investigations in drug discovery and pharmaceutical industry [3].

For the lead compound search in drug discovery , high specificity is often achieved by increasing the specific hydrophobic interactions between the ligand and the target [20], while high affinity often relies on some crucial interactions such as hydrogen-bonding.

When applies to drug screening, this suggests a multidimensional screening strategy using both affinity and specificity rather than affinity alone in the traditional drug discovery .

Remarkably, the comprehensive knowledge of the statistics of affinity distributions in many studies have led to a better understanding of molecular selection [59] , and in vitro evolution process such as combinatorial library panning, SELEX technology exploring the RNA/DNA-ligand interactions [60—64] , and high throughput screening for drug discovery to study the receptors or enzymes binding with the lead compounds [65, 66].

drug discovery .