Supervised By: Dr.Habib Bokhari (Ass.Professor) Presented By: Shazia Sabir (FA04-BSB-005)

1. Supervised By: Dr.Habib Bokhari(Ass.Professor) Presented By: Shazia Sabir (FA04-BSB-005)

2. Introduction of GFP. • Strategy used for Modeling of HriGFP and HriCFP. • Tour of Database of GFP. • Tour of web-Interface of developed Database & developed tool.

3. Introduction of GFP • Existed for more than one hundred and sixty million years. • Found in one species of jellyfish, Aequorea victoria (monomeric) • First time clone in 1992. • Fluorescent GFP has been expressed in bacteria, yeast, slime mold, plants, , drosophila, zebrafish, and in mmmalian cells. • Since 1999, numerous GFP homologues have been discovered in Anthozoa, Hydrozo species • GFP as the microscope of the twenty-first century.

4. GFP found in Aqurea Victoria is comprised of 238 amino acids with mol.wt of w25 kDa. • Its wild-type absorbance/ excitation peak is at 395 nm with a minor peak at 475 nm. • The emission peak is at 508 nm. • Analysis of a hexapeptide derived by proteolysis of purified GFP led to the prediction that the fluorophore originates from an internal Ser-Tyr-Gly sequence.

5. Florophore Ref: Fan Yang, Larry G. Moss, and George N. Phillips, Jr. The Molecular Structure of Green Fluorescent Protein

6. Applications • Monitoring of gen expression • The gene encoding a FP is cloned under the control of the target promoter, whereby activity of the promoter can be monitored by the magnitude of the fluorescent signal • split FP->the fluorescent signal occurs only when both promoters are active. Ref: Dmitriy M. Chudakov, Sergey Lukyanov and Konstantin A. Lukyanov, Fluorescent proteins as a toolkit for in vivo imaging

7. HriGFP& HriCFP • Recently discovered proteins in Hydnophora rigida with emission maxima of 527nm & 495nm. • Have high similarity with each other while have very low similarity with related members. • Deletion of only one nucleotide in HriGFP at 446th position causes the shift in emission from green to cyan.

8. Goals of Project • Structural Modeling of HriGFP and HriCFP. • Development of Database of Green Flourescent Proteins. • Development of web-Interface of developed Database. • Development of Tool for prediction of Fluorophore in the protein sequence.

9. Strategies for Modeling of HriGFP& HriCFP

10. Introduction of Homology Modeling • Predicts the three-dimensional structure of a given protein sequence (TARGET) based on an alignment to one or more known protein structures (TEMPLATES) • Homology models are of great interest for planning and analyzing biological molecules when no experimental three dimensional structure is available.

11. Continue…. • The number of structurally characterized proteins (20,000) is small compared with the number of known protein sequences (1,000,000).(RefEswar et all, 2003) • Protein structures are more conserved than protein sequences, detectable levels of sequence similarity usually imply significant structural similarity

12. Steps In Homology Modeling

13. Step I & II i) Three regimes of the sequence-structure relationship • The easily detected relationships, characterized by >30% sequence identity • The “twilight zone”(with identities 10% to 30%) , corresponds to relationships with statistically significant sequence similarity • The “midnight zone” (less than 10%), corresponds to statistically insignificant sequence similarity,

14. Continue…. ii) Fold Recognition Approaches • Pairwise sequence alignment methods • Profile-Sequence alignment methods • Profile-Profile alignment methods • Sequence-Structure threading methods iii) Template Selection & Alignment

15. Step I & IIFold Assignment & alignment with template Ref: Sali, A., and Blundell, T.L. (1993). Comparative protein modelling by satisfaction of spatial restraints, J. Mol. Biol.

16. Step III (Model Building) • i) Modeling by Satisfaction of Spatial Restraints • Homology-derived restraints • Stereochemical restraints • Optimization of the objective function • Restraints derived from experimental data

17. Loop Modeling • Loops play an important role in defining the functional specificity of a given protein (e.g. forming active & Binding site). • important aspect of comparative modeling for 30% to 50% sequence identity

18. Step III (Model Building) Ref: Sali, A., and Blundell, T.L. (1993). Comparative protein modelling by satisfaction of spatial restraints, J. Mol. Biol.

19. Step IV(Predicting Model Errors) • Errors in side-chain packing • Distortions and shifts in correctly aligned regions • Errors in regions without a template • Errors due to misalignments

20. Ref: http://www.ncbi.nlm.nih.gov/gorf/orfig.cgi

21. Sequence of Template (1EMA) with 2D Structure Ref: http://www.rcsb.org/pdb/explore/explore.do?structureId=1EMA

22. 3D Structure of Template (1EmA) Ref:http://www.rcsb.org/pdb/explore/explore.do?structureId=1EMA

23. SWISS-MODEL • First Approach Mode - more than 25% seq similarity. - automatic template selection. • Alignment Mode - less than 25% seq similarity. - input alignment with template. • Project Mode - input file is deep view project file.

24. Alignment of HriGFP with Template Ref: http://www.ebi.ac.uk/Tools/clustalw2/index.html?

25. Alignment of HriCFP with Template Ref: http://www.ebi.ac.uk/Tools/clustalw2/index.html?

26. Alignment w.r.t structure Ref: http://swissmodel.expasy.org/workspace/index.php?func=modelling_align1

27. Model Generated by SWISS-MODEL

28. MODELLER • Input Files • Atom file (.pdb, .ent, .atm) • Alignment file (.ali) • Script file (.py) • Output Files • Log file (text file) • Output of Script

29. Atom file (Input file)

30. Alignment file (Input file)

31. Script file (Input file)

32. Log file (output file)

33. Alignment file (Output file)

34. Alignment Generated by MODELLER for HriGFPPap file (Output file)

35. Alignment Generated by MODELLER for HriCFPPap file (Output file)

36. Phase III (Model Generation) Five Models were generated DOPE score : -6536.567383 DOPE score : -6770.957031 DOPE score : -6814.932129 DOPE score : -7199.573242 DOPE score : -6945.205078 DOPE, or Discrete Optimized Protein Energy, is a statistical potential used to assess homology models in protein structure prediction.

37. Phase IV (Evaluation of Model) • The recognition of errors in experimental and theoretical models of protein structures is a major problem in structural biology. • If this score is outside a range characteristic for native proteins the structure probably contains errors. • A plot of local quality scores points to problematic parts of the model

38. GNUPLOT for HriCFP

39. GNLPLOT for HriCFP along with Template

40. Z-Score (Evaluation Criteria) • The z-score indicates overall model quality. • value is displayed in a plot that contains the z-scores of all experimentally determined protein chains in current PDB. • Can be used to check the input structure is within the range of scores typically found for native proteins of similar size.

41. Z-Score Ref: https://prosa.services.came.sbg.ac.at

42. Molecular Interactive View & Plot Generation Ref: https://prosa.services.came.sbg.ac.at

43. Ref: http://laboheme.df.ibilce.unesp.br/cluster/parmodel_mpi/

44. Ref: http://laboheme.df.ibilce.unesp.br/cluster/parmodel_mpi/

45. Root Mean Square & Root Mean Square Deviation

46. Conclusion • Both HriGFP and HriCFP are capable of forming only five beta-sheets that are not enough for formation of complete beta-can and hence may not provide full protection to fluorophore. So these gaps must be filled in order to give complete protection to fluorophore.

47. Future Prospects • Development of a Tool that would determine change in fluorescence upon mutagenesis.

48. Tour of • Database • Web-Interface • Tool

49. Thank You!