‹ back to 2026-09-18

Development of a random background to understand ligand optimization

Nature Drug Discovery Xinyu Xu, Olivier Mailhot, Galen J. Correy, Xi-Ping Huang, Joao M. Braz, Da Shi, Karthik Srinivasan, Kara Zielinski, Yuliia Holota, Yuliia Kuziv, Christos Iliopoulos-Tsoutsouvas, Nathan D. Levinzon, Yagmur U. Doruk, Moira M. Rachman, Morgan E. Diolaiti, Maisie G. V. Stevens, Fangyu Liu, Katie L. Holland, Harald Hübner, Jing Wang, Yujin Wu, Alan Ashworth, Alexandros Makriyannis, Yuqi Zhang, Yurii S. Moroz, Peter Gmeiner, Robert Abel, Aashish Manglik, Allan I. Basbaum, Bryan L. Roth, James S. Fraser, Brian K. Shoichet 2026-09-16

TL;DR - This Nature paper describes an approach for establishing a random-background expectation for ligand potency optimization. The framework could improve optimization efficiency by providing a baseline against which progress can be assessed.

Focuses on ligand potency optimization in drug discovery.
Introduces a random background for interpreting optimization outcomes.
Aims to improve efficiency and distinguish meaningful gains from baseline expectations.
The provided abstract is too brief to specify the method, benchmarks, or quantitative results.

view merged work →