Hongjian Li Department of Computer Science and Engineering Chinese University of Hong Kong

1. Hongjian Li Department of Computer Science and Engineering Chinese University of Hong Kong 12 September 2013JackyLeeHongJian@Gmail.com http://www.cse.cuhk.edu.hk/~hjli

2. Virtual Screening • Structure based • Docking • Protein structure required • Homology modeling • Ligand based • Similarity search • Active ligand required • Assumption • Structure -> functions • Consensus

3. Structural Similarity • Alignment based • Molecular superposition • Precise geometric comparison • Polarity • Hydrophobicity • Chirality • Computationally expensive • e.g. ROCS • Similarity score = volume overlap • Descriptor based • Encode shape by geometrical descriptors

4. Structural Similarity • Moment based: USR • Four reference points • ctd: molecular centroid • cst: closest atom to ctd • fct: farthest atom to ctd • ftf: farthest atom to fct • Moments • μ1ctd: size • μ2ctd: variance • μ3ctd: skewness • Applicable to different number of atoms • Dimension reduction: ligand -> 12D

5. Similarity Score • Dissimilarity transformed into a normalized similarity score • Inverse monotonic

6. Results • 2,433,493 compounds, no ground truth • USR vsESshape3D 17 25 30 consistent very inconsistent 33 diverse 38 consistent

7. Conformer Test • 292 conformers of (b) USR ESshape3D

8. Efficiency Comparison • USR is 1,546 and 2,038 times faster than ESshape3D and Shape Signatures Descriptor based

9. Efficiency Comparison • USR is 14,238 times faster than ROCS, the fastest alignment-based method • USR screens 3.5B molecules in 4 min Alignment based

10. Ligand Clustering

11. Conclusion • No protein structure required • Retrieve topologically dissimilar compounds • 1,546 times faster • No alignment required • Ligand -> 12D, clustering algorithms apply • Independence of orientation or position • Extensible: reference points, moments • Applications • Internet search engines for 3D geometrical objects • Protein similarity search

12. USR Variants • (Edward Cannon, 2008) • USR + MACCS • 4th and 5th moments Edward Cannon, Florian Nigsch, and John Mitchell. A novel hybrid ultrafast shape descriptor method for use in virtual screening. Chemistry Central Journal, 2(1):3, 2008.

13. USR Variants • (M. Armstrong, 2009), (Ting Zhou, 2010) • Chirality M. Stuart Armstrong, Garrett M. Morris, Paul W. Finn, Raman Sharma, and W. Graham Richards. Molecular similarity including chirality. Journal of Molecular Graphics and Modelling, 28(4):368–370, 2009. Ting Zhou, KarineLafleur, and AmedeoCaflisch. Complementing ultrafast shape recognition with an optical isomerism descriptor. Journal of Molecular Graphics and Modelling, 29(3):443–449, 2010.

14. USR Variants • (M. Armstrong, 2010), (M. Armstrong, 2011) • ElectroShape • Shape, chirality, electrostatics, lipophilicity • (Shave S., 2010) • UFSRAT • (Adrian Schreyer, 2012) • USRCAT • USR-like methods are patented by University of Oxford M. Armstrong, Garrett Morris, Paul Finn, Raman Sharma, Loris Moretti, Richard Cooper, and W. Richards. ElectroShape: fast molecular similarity calculations incorporating shape, chirality and electrostatics. Journal of Computer-Aided Molecular Design, 24(9):789–801, 2010. M. Armstrong, Paul Finn, Garrett Morris, and W. Richards. Improving the accuracy of ultrafast ligand-based screening: incorporating lipophilicity into ElectroShape as an extra dimension. Journal of Computer-Aided Molecular Design, 25(8):785–790, 2011. Shave S. Development of high performance structure and ligand based virtual screening techniques. PhD thesis. 2010. Adrian Schreyer and Tom Blundell. USRCAT: real-time ultrafast shape recognition with pharmacophoric constraints. Journal of Cheminformatics, 4(1):27, 2012.

15. Q & A