Ligand-Based Structural Hypotheses for Virtual Screening

1. Ligand-Based Structural Hypotheses for Virtual Screening Ajay N. Jain Uses the tool described in the pervious paper

2. Agenda • To investigate adequacy of the utility of a model comprised by the overlap of known ligands for a given target in identifying novel ligands with high sensitivity and specificity • The target’s structure is not known • Justification: “Given a small number of potentially quite flexible molecules of diverse chemical structures, one must generate a hypothesis consisting of a single pose for each input molecule such that the joint superposition of all molecules will lead to predictive models of biological activity”

3. Molecules Used: Chose 4 therapeutically interesting targets with unknown three-dimensional structure, and identified ligands known to associate with those:

4. Positive Testing Set:

5. Control Test Sets HSV-1 Thymidine kinase inhibitors Estrogen Receptor Ligands

6. Control Test Sets Alignments

7. GPCR Models

8. GABAA Model

9. Serotonin Model Muscarinic Model Tanimoto Surflex-Sim Tanimoto Surflex-Sim Tanimoto Surflex-Sim Tanimoto Surflex-Sim Histamine Model GABAA Model ROC Curves

10. Examples of High Scoring Ligands

11. GABAA vs. GPCR GABAA vs. Random Musc. vs. Non Musc. vs. Random Hist. vs. Non Hist. vs. Random Selectivity of the Models

12. Serotonin Model Binding Affinity

13. Conclusions • “Offers a generally applicatble method for producing ligand-based binding site hypotheses, which can be used directly for high-throughput virtual screening or to form the basis on which to construct more detailed models of molecular activity” • “Performance in terms of screening utility is comparable to that of many structure-based molecular docking techniques, but the best docking methods are capable of better sensitivity and specificity”

14. Applicability • “where many existing ligands are known but where they share side-effects or biological properties that limit their biological utility” • “where a small number of ligands have been discovered for a target that has not been extensively probed and augmentation of the set is a primary goal of a medicinal chemistry effort”

15. Filler for Surflex Similarity Function