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

Research output: Contribution to journalArticlepeer-review


  • Carl A Machutta
  • Christopher S Kollmann
  • Kenneth E Lind
  • Xiaopeng Bai
  • Pan F Chan
  • Jianzhong Huang
  • Lluis Ballell
  • Svetlana Belyanskaya
  • 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

Colleges, School and Institutes

External organisations

  • GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, USA.
  • GlaxoSmithKline, 830 Winter Street, Waltham, Massachusetts 02451, USA.
  • GlaxoSmithKline
  • University of Birmingham


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.


Original languageEnglish
Article number16081
JournalNature Communications
Early online date17 Jul 2017
Publication statusE-pub ahead of print - 17 Jul 2017

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