Back to Search Start Over

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

Authors :
Todd L. Graybill
John D. Martin
Jason W. Dodson
Hongfeng Deng
Christopher P. Davie
Christopher C. Arico-Muendel
Minghui Wang
Hongwei Qi
Sandy S. Chang
David J. Holmes
Karen A. Ingraham
Kenneth E Lind
Heather O’Keefe
Carl A. Machutta
David Barros-Aguirre
Christine Patricia Donahue
Christina S. Pao
Jeffrey W. Gross
Ghotas Evindar
Jean Zhang
Bing Xia
Juan Wang
Patti McCormick
Xiaorong Liu
Jianzhong Huang
Joël Lelièvre
Quinn Lu
Pan F. Chan
Matt S. Steiginga
Lynn McCloskey
Christopher S. Kollmann
Taylor L. Graham
Xiaopeng Bai
Jing Chai
Yue Li
Walter P. Johnson
Ruth Lehr
Lawrence M. Szewczuk
Jingye Zhou
Lluis Ballell
Genaro S. Scavello
Robert H. Bates
Anthony E. Choudhry
Aaron Coffin
Sharon Sweitzer
Christopher R. Kwiatkowski
Andrew J. Pope
Enoch Gao
Christopher B. Phelps
David T. Fosbenner
Keith Rafferty
Thomas O’Keeffe
Gang Yao
Bryan W. King
Svetlana L. Belyanskaya
May Fern Toh
Gurdyal S. Besra
Amy N. Taylor
Devan J. Wilkins
Alfonso Mendoza-Losana
Paolo A. Centrella
Flora S. Sundersingh
Jeffrey A. Messer
Yun Ding
Jianghe Deng
Source :
Nature Communications, Nature Communications, Vol 8, Iss 1, Pp 1-11 (2017)
Publication Year :
2016

Abstract

The identification and prioritization of chemically tractable therapeutic targets is a significant challenge in the discovery of new medicines. We have developed a novel method that rapidly screens multiple proteins in parallel using DNA-encoded library technology (ELT). Initial efforts were focused on the efficient discovery of antibacterial leads against 119 targets from Acinetobacter baumannii and Staphylococcus aureus. The success of this effort led to the hypothesis that the relative number of ELT binders alone could be used to assess the ligandability of large sets of proteins. This concept was further explored by screening 42 targets from Mycobacterium tuberculosis. Active chemical series for six targets from our initial effort as well as three chemotypes for DHFR from M. tuberculosis are reported. The findings demonstrate that parallel ELT selections can be used to assess ligandability and highlight opportunities for successful lead and tool discovery.<br />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 for S. aureus, A. baumannii and M. tuberculosis.

Details

ISSN :
20411723
Volume :
8
Database :
OpenAIRE
Journal :
Nature communications
Accession number :
edsair.doi.dedup.....6fd5399c3ed244a244dc84c19085f169