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Q- SiteFinder : an energy-based method for the prediction of protein- ligand binding sites

Introducing Q-SiteFinder, a method for predicting ligand binding sites based on interaction energies, with comparisons to other techniques and detailed results analysis.

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Q- SiteFinder : an energy-based method for the prediction of protein- ligand binding sites

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  1. Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites Reporter: Yu Lun Kuo (D95922037) E-mail: sscc6991@gmail.com Date: June 5, 2008 Bioinformatics Vol. 21 no. 9 2005 (Pages 1908-1916)

  2. Motivation • 3D structure are available for protein whose interaction with small molecules (ligands) are not known • Describe a new method of ligand binding site prediction called Q-SiteFinder • Use the interaction energy

  3. Introduction • Goal • Given a protein structure, predicts its ligand bindings • Flexible ligand docking • Lead optimisation • Applicat ion • Function prediction • Drug discovery • etc.

  4. Docking Step

  5. SURFNET

  6. SURFNET

  7. Introduction • Detection and characterization of functional sites on protein • Identify functional sites • In addition de novo drug design • Lead to the creation of novel ligands not found in molecular databases

  8. Introduction • The ligand binding site is usually in the largest pocket • SURFNET (Laskowski et al., 1996) • The ligand binding site was found to be in the largest pocket in 83% of cases • LIGSITE (Hendlich et al., 1997) • The ligand binding site was found in the largest pocket in all 10 proteins tested • etc.

  9. Introduction • Q-SiteFinder • Defined only by energetic criteria • Calculates the van der Waals interaction energies of a methyl probe with the protein • Probes are ranked according to their total interaction energies

  10. Introduction • Several techniques have been developed for estimating the interaction energy • GRID (Wade and Goodford) • Identify the hydrogen bonding potential of drug-like molecules • The interaction energies • Using a conventional molecular mechanics function • Van der Waals, electrostatic, and solvation terms

  11. Introduction • Q-SiteFinder • Keep the predicted ligand binding site as small as possible without compromising accuracy • Provide a threshold for success

  12. Methods • Datasets • Consisted of 134 records obtained from the PDB • Correspond to the GOLD protein-ligand docking dataset (305 proteins) • Remove those with high levels of structural similarity • Which could bias the results • Solvent molecules were discarded • Phosphate, sulphate and metal ions • Q-SiteFinder is not designed to detect the binding site of small solvent molecules

  13. Q-SiteFinder • Simply uses the van der Waals interaction (of a methyl probe) and an interaction energy threshold to determine favourable binding clefts

  14. Results (Q-SiteFinder) • Define a successful prediction using a precision threshold • A threshold of 25% precision was used to define success in al the result here • A precision of 26% is considered a success • 17% is not

  15. Different Levels of Predicted Binding Site Precision 2gbp, 100% (Q-SiteFinder) 1bbp, 68% (Q-SiteFinder) 1glq, 17% (Q-SiteFinder). 1asc, 26% (Pocket-Finder)

  16. Results (Q-SiteFinder) • If a ligand is successfully predicted in more than one site on a protein • It is counted as a success only in the higher ranking site • If more than one ligand is found in the same site • Only the success with the highest precision is counted for this site

  17. Q-SiteFinder (Energy Threshold) Success rate was 71% in the first predicted Average precision was 68% Precision of 0% were excluded First predicted binding site It is desirable to have both a high rate of success and a high precision of binding site prediction a range of energy threshold values (−1.0 to −1.9 kcal/mol)

  18. Results (Pocket-Finder) • Use a variable, MINPSP • PSP (protein-site-protein) • A pocket is identified if an interaction occurs followed by a period of no interaction, followed by another interaction • Measure the extent to which each grid point is buried in the protein • Each grid point has seven scanning lines passing through it • x, y and z direction and the four cubic diagonals

  19. Results (Picket-Finder) • MINPSP (minimum number of PSP) • Thought of a burial threshold • PSP values for each grid point vary from 0 to 7 • 0: not a pocket • 7: deeply buried

  20. Pocket-Finder (PSP Threshold) Success rate: 48% Average precision: 29% Best success rate

  21. Results • Hendlich et al. (1997) • Recommend a MINPSP of 2 • Our implementation of Pocket-Finder • Low average precision: 8% • Large site volume: 8700 A3 (23% of the average protein volume) • No significant benefit in the success rate was observed on using a MINPSP of 2 rather than 5

  22. Results • Smaller sites have a higher average precision • Sites with high volume will usually incorporate locations on the protein surface • That are not part of binding site

  23. Comparison • Q-SiteFinder • Energy threshold value: -1.4 kcal/mol • Success rate: 71% average precision: 68% • At least one successful prediction in the • Top three predicted sites for 90% of the proteins • Top ten predicted sites for 96% of the proteins • Pocket-Finder • MINPSP threshold of 5 • Success rate: 48% average precision: 29% • At least one successful prediction in the • Top three predicted sites for 65% of the proteins • Top ten predicted sites for 74% of the proteins

  24. Comparison of the success rates • Q-SiteFinder has a higher success rate in each of the top three predicted binding sites

  25. Prediction in the first predicted site Pocket-Finder detects a subset of the ligand binding sites detected by Q-SiteFinder

  26. Application of Q-SiteFinder Success rate in the first predicted Unbound state: 51% Ligand-bound state: 80% • Q-SiteFinder for detecting binding sites on unbound protein The average precision of the first predicted binding site 71% for the unbound state 74% for the ligand-bound state. At least one success in the top 3 Unbound state: 86% Ligand-bound state: 97%

  27. Average Volume of Successfully Predicted Sites • Relax our threshold to allow any non-zero value (success requires a precision > 0%) Average precision of Pocket-Finder is 29% Q-SiteFinder is 68% Q-SiteFinder would appear to be more robust than Pocket-Finder, and better able to pinpoint the location of the ligand binding site

  28. Conclusion • Q-SiteFinder is better able to pinpoint the location of the ligand binding site than Pocket-Finder • High precision • Closely as possible to the actual binding site • Keep the predicted ligand binding site as small as possible without compromising accuracy • Given the high level of success in unbound protein sites • Do not have a ligand already bound

  29. CHIME Interface

  30. Java-Mage Interface

  31. Reference • Q-SiteFinder: Ligand Binding Site Prediction • http://bmbpcu36.leeds.ac.uk/qsitefinder/ • Pocket-Finder: Pocket Detection • http://bmbpcu36.leeds.ac.uk/pocketfinder/

  32. Thanks for your attention

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