1. An efficient visualization tool for the analysis of protein mutation matrices Maria Pamela C. David, Carlo M. Lapid and Vincent Ricardo M. Daria Computational Science Research Center University of the Philippines, Diliman

2. Outline Visualization A crash course on protein structure, function and engineering Protein mutation matrices  Generation  Data  Visualization Applications of visualization

3. Visualization

6. “Our species relies on vision over all other senses” (about half of the human brain is devoted directly or indirectly to vision) “We learn about 11% audibly and 83% visually” ~50% of our brain gets involved in visual processing Other perceptual channels can be used : - They work in parallel as long as they don’t conflict - In a conflict, the visual channel will dominate

7. Crash course on protein structure and engineering

8. Protein mutations?

9. Analysis of evolving sequences/sequences with high variability Would have applications in artificial protein design Protein mutation/substitution matrices

10. Matrix generation A D R TS W G G G E G E K K L T I D Y R

11. Note: 1.Alignment should be good 2.Primer-derived sequences should be removed A D R TS W G G G E G E K K L T I D Y R Size and Polarizability D → G S → K Charge and polarity R → E W → R T → D Hydrophilicity T → I S → L Physico-chemical properties

12. Sample mutation matrix WLFIMVYPATCQGKSHNERD W000013730360214003525000 L20592251557602673363711040414924110776 F36601033046000792438373903 I4192701482353500143003949241740732 M36327215050003303726105021644 V1843602073015410143943266756000 Y036020101532238039974135437 P01000020000100166003620 A08684734130010740043668001193791 T03735008023551003044035979512 C001260363500000002604500 Q03036138361302401342391501370 G2577539007908722530374433241139 K05549472943600290114810704714039440 S21030504401101129613551144200239563111 H0004288402021940620333708 N016024332301843299015910015176124 E114916438203750411591373928509135 R043392011015482972369307849058 D43723394763273111259312241234440 Replacement residues, increasing hydrophilicity Replaced residues, increasing hydrophilicity

13. Image equivalent Lower hydrophilicity Higher hydrophilicity

14. Tool 1: Matrix scaling W L F I M V Y P A T C Q G K S H N E R D

15. Tool 2: Matrix comparison Matrix 1 Matrix 2 Find mutations exclusive to either matrix W L F I M V Y P A T C Q G K S H N E R D

16. Tool 2: Matrix comparison Matrix 1 only Matrix 2 only W L F I M V Y P A T C Q G K S H N E R D

17. Application 1: antibody engineering FRamework Complementarity Determining Region

18. Application 1: antibody engineering CDR mutations FR mutations W L F I M V Y P A T C Q G K S H N E R D

19. Application 1: antibody engineering A D R TS W G G G E G E K K L T I D Y R D K IT D R Engineered antibody

20. Application 2: vaccine design

21. Lower hydrophilicity Higher hydrophilicity

22. Application 3: biosensor design

23. Smaller residues Larger residues

24. Other advantages of visualization

25. Conclusion Visualization plays a key role in analysis  Quicker elucidation of patterns  Find those that were not immediately obvious Key applications of protein mutation matrix visualization  Evolution studies  Protein engineering Image manipulation and analysis techniques may be applied to images

26. Current activities + future targets Matrix generation tool development  Prototype hosted at the CSRC site Migrate from Matlab to open source software (i.e. Scilab/Octave + PERL/Tcl/Tk) Offer full matrix generation + visualization package online

27. THANK YOU!Q UESTI ONS??