Pharmacophore Analysis and Target Expansion
A compound series developed for one target often has activity — known or unexplored — against related targets. This is simultaneously a risk (off-target activity) and an opportunity (additional indications, combination strategies, rescue of programs from competitive crowding).
AI-assisted pharmacophore analysis and target expansion enables systematic exploration of both.
Pharmacophore analysis
A pharmacophore is the 3D arrangement of features required for biological activity. Pharmacophore modeling — determining what spatial arrangement of hydrogen bond donors, acceptors, hydrophobic groups, and charged centers drives binding — is a core tool in structure-based drug design.
AI adds two capabilities to classical pharmacophore analysis:
Large-scale pharmacophore matching. Given a defined pharmacophore, AI can screen virtual libraries of millions of compounds to identify structures that match the pharmacophore. This enables rapid identification of scaffold hops — structurally diverse compounds that maintain the binding geometry — which is critical when IP position or ADMET liabilities require moving away from the lead scaffold.
Reverse pharmacophore mapping. Given an active compound, AI can identify all targets in the proteome for which the compound's pharmacophore might have affinity. This is the entry point for target expansion — systematic identification of new indications or combination opportunities.
Target expansion strategy
The question target expansion answers: "We have 1,000 compounds with SAR data. Which of them might have clinically meaningful activity against targets we haven't tested?"
AI-assisted target expansion works by:
- Building pharmacophore models for each compound based on structural analysis.
- Comparing these pharmacophores against the binding site features of all characterized targets in ChEMBL and PDB.
- Ranking predicted off-target activity by structural similarity and published binding data.
- Prioritizing experimental follow-up on the highest-probability off-target hits.
For a company with a maturing oncology series, this process has frequently revealed meaningful activity against additional cancer types, ADMET targets (hERG, CYP isoforms), or combination partner opportunities — turning a single-indication program into a platform.