Incorporating partial matches within multiobjective pharmacophore identification |
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Authors: | Simon J Cottrell Valerie J Gillet Robin Taylor |
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Institution: | Department of Information Studies, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield, S1 4DP, UK. |
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Abstract: | This paper describes the extension of our earlier multiobjective method for generating plausible pharmacophore hypotheses
to incorporate partial matches. Diverse sets of molecules rarely adopt exactly the same binding mode, and so allowing the
identification of partial matches allows our program to be applied to larger and more diverse datasets. The method explores
the conformational space of a series of ligands simultaneously with their alignment using a multiobjective genetic algorithm
(MOGA). The principles of Pareto ranking are used to evolve a diverse set of pharmacophore hypotheses that are optimised on
conformational energy of the ligands, the goodness of the overlay and the volume of the overlay. A partial match is defined
as a pharmacophoric feature that is present in at least two, but not all, of the ligands in the set. The number of ligands
that map to a given pharmacophore point is taken into account when evaluating an overlay. The method is applied to a number
of test cases extracted from the Protein Data Bank (PDB) where the true overlay is known. |
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Keywords: | Pharmacophore Molecular alignment MOGA Multiobjective optimisation Multiobjective genetic algorithm Partial matches |
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