J Chem Inf Model - Maximum-score diversity selection for early drug discovery.

Tópicos

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Resumo

Diversity selection is a common task in early drug discovery. One drawback of current approaches is that usually only the structural diversity is taken into account, therefore, activity information is ignored. In this article, we present a modified version of diversity selection, which we term Maximum-Score Diversity Selection, that additionally takes the estimated or predicted activities of the molecules into account. We show that finding an optimal solution to this problem is computationally very expensive (it is NP-hard), and therefore, heuristic approaches are needed. After a discussion of existing approaches, we present our new method, which is computationally far more efficient but at the same time produces comparable results. We conclude by validating these theoretical differences on several data sets.

Resumo Limpo

divers select common task earli drug discoveri one drawback current approach usual structur divers taken account therefor activ inform ignor articl present modifi version divers select term maximumscor divers select addit take estim predict activ molecul account show find optim solut problem comput expens nphard therefor heurist approach need discuss exist approach present new method comput far effici time produc compar result conclud valid theoret differ sever data set

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