Year: 2026
Type: article
Abstract: Ligand optimization is central to drug discovery, with hundreds of analogues often designed and synthesized between an initial hit and a therapeutic candidate 1,2 . The efficiency of this process is unclear, partly because there is no random background for optimization to compare against. Such a random background might emerge from systematic random small substitutions across starting ligands, measuring the likelihood of achieving a substantial improvement in affinity or potency, or other property by any single perturbation. Recent literature has suggested that perhaps 10% of analogues with minor modifications improve upon the potency of a parent by tenfold or more 3,4 , but this number is clouded by reporting bias, intentional improvement and inter-group variability. To begin to establish a background expectation for ligand optimization, here we systematically modified 18 lead molecules across six targets with single-atom changes; 257 compounds were synthesized. Unexpectedly, 11.3% of these random small perturbation analogues improved potency by tenfold or more. Conversely, they typically had worse in vitro pharmacokinetics. Although it was possible to find analogues where the potency increase compensated for inferior exposure and half-life, resulting in more potent compounds in vivo, overall, a frustrated landscape for ligand optimization is revealed. This study begins to establish a background expectation for ligand potency optimization and offers a simple strategy to do so. It also begins to quantify the challenges confronting the field in moving beyond in vitro potency.
Source: Nature
Authors: 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
Institutions: University of California, San Francisco, University of North Carolina at Chapel Hill, Schrodinger (United States), Enamine (Ukraine), Northeastern University, University of Utah, UCSF Helen Diller Family Comprehensive Cancer Center, Friedrich-Alexander-Universität Erlangen-Nürnberg, Taras Shevchenko National University of Kyiv, National Institute of Mental Health
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $12,690
Awards: G1557483336, Glacios™ Cryo Transmission Electron Microscope with 200 kV XFEG optics, G2515541506, G328662883, Rational prioritization algorithm for docking-based virtual screening of trillion-scale make-on-demand small molecule libraries, Acquisition of an electron microscope for high-resolution single particle cryo-EM, G386734474, G420478540, Linux cluster for near atomic resolution single particle cryo-EM, G8436568139, G8917620550, Development and Testing of New Computational Methods for Ligand Discovery and Mechanism
OpenAlex ID: W7213392602