Computational Approaches for Fragment Optimization
Fragment based screening has become a valuable tool to complement traditional lead finding methods like high throughput screening in drug discovery. Fragments are low molecular mass compounds and are usually screened using high sensitivity biophysical methods which are suitable for the detection of weakly binding ligands. Because fragments have a low affinity, efficient methods to improve their affinity are required. Structure based methods, i.e. methods which make use of a three dimensional structure of the protein have been applied in most of the cases for fragment optimization programs which are reported in the literature. De novo design, combinatorial docking and interactive optimization fell in this category and belong to the computer-aided drug design field. While de novo design is a computational method where a ligand is build completely de novo, combinatorial docking is applied to evaluate easily accessible or physically existing compound libraries around a previously identified core and interactive optimization alternates computational, biological and structural experiments to progress towards a drug. The principles, advantages, drawbacks of the different methods are being discussed together with examples of applications taken from the literature. At the end of the article we define a new metric to express the efficiency of optimization and show that small molecular molecules, i.e. fragments with a molecular mass below 250 Da, tend to be more easily optimized than larger molecules, thus reinforcing the interest of the fragment approach in the drug discovery process.
Keywords: Fragment optimization, de novo design, combinatorial docking, structure based drug design, hit to lead optimization
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