作者: Craig R. MacNair , Jonathan M. Stokes , Shawn French , Cullen L. Myers , Kali R. Iyer
DOI: 10.1016/J.BMC.2016.09.053
关键词: Bacterial growth 、 Hit to lead 、 Nanotechnology 、 Antimicrobial 、 Chemistry 、 Antibiotics 、 Small molecule 、 Mechanism of action 、 Computational biology 、 Hit selection 、 High-throughput screening
摘要: Abstract The rapid spread of antibiotic resistance has created a pressing need for the development novel drug screening platforms. Herein, we report on use cell-based kinetic dose response curves small molecule characterization in discovery efforts. Kinetically monitoring bacterial growth at sub-inhibitory concentrations antimicrobial molecules generates unique profiles. We show that clustering profiles by characteristics can classify antibiotics mechanism action. Furthermore, changes kinetics have potential to offer insight into mechanistic action and be used predict off-target effects generated through structure–activity relationship studies. Kinetic also allows detection unstable compounds early lead process. propose this approach is cost-effective means gather critical information during hit selection pipeline.