Virtual Screening and Hit Prioritization
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This document discusses virtual ligand screening (VLS) as an alternative to high-throughput screening for identifying potential drug candidates. It describes the VLS process, which involves selecting a target and compound library, preparing the target and ligands, running a docking simulation to analyze ligand-target binding, and prioritizing hits. The document outlines advantages of computational methods like VLS compared to experimental screening, as well as some limitations. It also provides examples of free and commercial docking engines that can be used and highlights challenges in VLS like accounting for receptor flexibility.
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Virtual Screening and Hit Prioritization
- 1. Virtual Screening and Hit Prioritization Dr. Puneet Kacker Amity University Uttar Pradesh pkacker@amity.edu
- 3. What Medicinal Chemists Want? Experiment Identification Binding
- 4. The Experimental Method High-throughput screening (HTS) Expensive Time Consuming Skill Intensive
- 5. Why Computational Methods? Accuracy as good as experimental (not always!) Can provide insights at molecular level Fast Easy to access Can easily be automated Economical
- 6. Computational Limitations It only can simulate real conditions if programmed Larger systems are less accurate then smaller systems Need to be experimentally tested for accuracy. Does not look at the whole picture
- 7. VLS: alternative of HTS V L S Millions of Compounds Few Potential Binders
- 8. The Detailed VLS Process Select a Target Select a Compound Library Prepare Target Prepare Ligand set Select a Docking Engine Analyze the Results
- 9. Target Selection Take one Disease Search Therapeutic Targets known for that particular disease 1 2
- 10. Selecting a Compound Library
- 11. Receptor Preparation Add Hydrogen Assign Charges Assign Protonation States Complete Missing Atoms
- 12. Ligand Preparation and VLS Filters Preparation Assign charges Generate possible Tautomers and Stereoisomers (LigPrep) Assign right protonation states Filters Physico-Chemical Filters (Lipinski Rule of Five) Similarity-based filters (take only diverse set of compounds)
- 15. VLS Hits Prioritization Clustering Score based
- 18. The Target
- 19. ArgusLab Procedure Defining a Binding Site Defining a Ligand Running Docking Simulation Pose Energy 1 2 3 4
- 20. Challenges Receptor Flexibility can be tackled effectively by exploiting Multiple diverse Conformations of proteins Multiple ways to construct the ensemble: Multiple crystal entries Snapshots taken from MD simulations Figure: Hong and Tang, Biochemistry, Vol. 43, No. 16, 2004
- 22. Writing Manuscript/Report Stand on the shoulders of giants Take suggestions and ideas from experts (poster presentation) Check Consistency Select an appropriate journal “Copyright” does not mean “right to copy” (Check plagiarized material)
- 23. Reading Material
- 24. Journals Publishing Papers on VLS IF: 4.67IF: 1.79 IF:3.15 IF:5.25