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• W2023609562 startingPage "1092" @default.
• W2023609562 abstract "Improved methods are required to predict the position and orientation (pose) of binding to the target protein of low molecular weight compounds identified in fragment screening campaigns. This is particularly important to guide initial chemistry to generate structure–activity relationships for the cases where a high resolution structure cannot be obtained. We have assessed the benefit of an implicit solvent method for assessment of fragment binding poses generated by the Multiple Copy Simultaneous Search (MCSS) method in CHARMm. Additionally, the effect of using multiple receptor structures for a flexible receptor is investigated. The original MCSS performance -50% of fragment positions accurately predicted and scored - was increased up to 67% by scoring MCSS energy minima with a Molecular Mechanics Generalized Born approach with molecular volume integration and Surface Area model (MM-GBSA). The same increase in performance (but occasionally for different targets) was observed when using the docking program GOLD followed by MM-GBSA rescoring. The combined results from both methods resulted in a higher success rate emphasizing that a comparison of different docking methods can increase the correct identification of binding poses. For a receptor where multiple structures are available, Hsp90, the average performance on randomly adding receptor structures was also investigated. The results suggest that predictions using these docking methods can be used with some confidence to guide chemical optimization, if the structure of the target either remains relatively fixed on ligand binding, or if a number of crystal structures are available with diverse ligands bound and there is information on the positions of key water molecules in the binding site." @default.
• W2023609562 created "2016-06-24" @default.
• W2023609562 creator A5032307947 @default.
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• W2023609562 date "2011-04-29" @default.
• W2023609562 modified "2023-10-17" @default.
• W2023609562 title "Predicting Fragment Binding Poses Using a Combined MCSS MM-GBSA Approach" @default.
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• W2023609562 doi "https://doi.org/10.1021/ci100469n" @default.
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