Toward a Random Background for Ligand Optimization

Area of Science:

• Medicinal Chemistry
• Drug Discovery
• Pharmacology

Background:

• Ligand optimization is crucial for drug discovery, involving synthesizing numerous analogs.
• The efficiency of optimization is unclear due to a lack of a random background for comparison.
• Existing data on analog improvement is clouded by reporting bias and reproducibility issues.

Purpose of the Study:

• To establish a background expectation for ligand potency optimization.
• To systematically assess the impact of small, random modifications on ligand properties.
• To quantify the challenges in improving drug candidates beyond in vitro potency.

Main Methods:

• Systematically modified 18 lead molecules across six targets using single atom changes.
• Synthesized 257 unique analog compounds.
• Evaluated potency, in vitro pharmacokinetics (metabolic stability, plasma free fraction), and in vivo efficacy.

Main Results:

• 11.2% of analogs with small perturbations showed a ≥10-fold increase in potency.
• More potent analogs often exhibited poorer in vitro pharmacokinetic properties.
• Some analogs compensated for reduced exposure with increased potency, leading to improved in vivo compounds.

Conclusions:

• Ligand optimization presents a frustrated landscape, with potency gains often offset by pharmacokinetic liabilities.
• This study provides a baseline expectation for ligand optimization efficiency.
• Moving beyond in vitro potency requires addressing complex trade-offs between efficacy and drug-like properties.