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GAUK 174615
Adaptive virtual screening
2015 - 2017

Biological screening is used to detect the ability of small molecules to trigger a response in a macromolecular target by binding to it. The main disadvantage of physical screening is its price and the need to own the tested molecules. An alternative to the physicial screening is its in-silico variant - virtual screening (VS). VS commonly takes place in the early stages of drug discovery as a molecular filter before physical screening. One of the similarity principle-based types of VS is the ligand-based VS (LBVS). The similarity principle correlates function of a molecule with its structural and physico-chemical properties. If there exist known active molecules (ligands) to given target we can utilize molecular similarity to identify novel ligands. LBVS requires a suitable molecular representation and similarity function. Then the candidate molecules can be sorted based on similarity to known ligand(s) and thus, by association, by activity. The parameters of LBVS (similarity, representation and its parametrization) greatly influence its effectivity. The parameters are often static despite the fact that they are target dependent. A wrong parametrizations results in sub-optimal efficiency. Our goal is to develop a modular LBVS framework with generic representation and automated parameterization based on existing information about target.

Principal investigator : Petr Škoda
Co-Investigator : Jan Jelinek, Radoslav Krivak