Prioritizing multiple therapeutic targets in parallel using automated DNA-encoded library screening

Autor: Carl A. Machutta, Christopher S. Kollmann, Kenneth E. Lind, Xiaopeng Bai, Pan F. Chan, Jianzhong Huang, Lluis Ballell, Svetlana Belyanskaya, Gurdyal S. Besra, David Barros-Aguirre, Robert H. Bates, Paolo A. Centrella, Sandy S. Chang, Jing Chai, Anthony E. Choudhry, Aaron Coffin, Christopher P. Davie, Hongfeng Deng, Jianghe Deng, Yun Ding, Jason W. Dodson, David T. Fosbenner, Enoch N. Gao, Taylor L. Graham, Todd L. Graybill, Karen Ingraham, Walter P. Johnson, Bryan W. King, Christopher R. Kwiatkowski, Joël Lelièvre, Yue Li, Xiaorong Liu, Quinn Lu, Ruth Lehr, Alfonso Mendoza-Losana, John Martin, Lynn McCloskey, Patti McCormick, Heather P. O’Keefe, Thomas O’Keeffe, Christina Pao, Christopher B. Phelps, Hongwei Qi, Keith Rafferty, Genaro S. Scavello, Matt S. Steiginga, Flora S. Sundersingh, Sharon M. Sweitzer, Lawrence M. Szewczuk, Amy Taylor, May Fern Toh, Juan Wang, Minghui Wang, Devan J. Wilkins, Bing Xia, Gang Yao, Jean Zhang, Jingye Zhou, Christine P. Donahue, Jeffrey A. Messer, David Holmes, Christopher C. Arico-Muendel, Andrew J. Pope, Jeffrey W. Gross, Ghotas Evindar
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Nature Communications, Vol 8, Iss 1, Pp 1-11 (2017)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/ncomms16081
Popis: Encoded Library Technology (ELT) has streamlined the identification of chemical ligands for protein targets in drug discovery. Here, the authors optimize the ELT approach to screen multiple proteins in parallel and identify promising targets and antibacterial compounds forS. aureus, A. baumannii and M. tuberculosis.
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