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Stratégies de docking-scoring assistées par analyse de données.
Application au criblage virtuel des cibles thérapeutiques COX-2 et PPAR gamma

Abstract : Virtual screening is a strategy able to pick up high affinity or activity compounds for a given pharmacological target. We have developed a methodology which involves three dimensional data of COX-2 and PPARγ receptors. First, we have compared the available structures but we have also studied the different scoring functions (able to predict the binding of a molecule within a protein). Moreover, we have tested consensus techniques but also multivariate data analysis methodologies to treat the information from the scoring functions. We have also studied the incorporation of pharmacophoric constraints prior to docking, acting as a filter to remove undesirable compounds. This pharmacophoric model has also improved the choice of the first pose. Another investigation has been to assist the docking procedure with molecular dynamic. The aim of this task has been to take into consideration the flexibility of the active site of the protein. We have shown that a gain can be expected with such a strategy. Finally, consensus and multivariate data analysis has been applied to the data generated by all the conformers.
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https://tel.archives-ouvertes.fr/tel-00275585
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Submitted on : Thursday, April 24, 2008 - 2:48:19 PM
Last modification on : Thursday, March 5, 2020 - 6:48:59 PM
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  • HAL Id : tel-00275585, version 1

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Alban Arrault. Stratégies de docking-scoring assistées par analyse de données.
Application au criblage virtuel des cibles thérapeutiques COX-2 et PPAR gamma. Autre. Université d'Orléans, 2007. Français. ⟨tel-00275585⟩

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