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Growing problems with resistance to existing antimalarials makes identification of new drugs a high priority.We modeled quantitative structure-activity relationships(QSARs)for potential target enzymes,then used those models to predict activities for the 13,533 compounds identified as active in a high-throughput antimalarial screening program recently made public by GlaxoSmithKline(Pubchem biossay AID 2306) [1].Applying these models and the class generation technology in MedChem StudioTM to data from AID 2306 enabled us to identify one particular class of chemistry as likely to inhibit one of our chosen targets.