“The instructions for assembling every organism on the planet--slugs and sequoias, peacocks and

1. “The instructions for assembling every organism on the planet--slugs and sequoias, peacocks and parasites, whales and wasps--are all specified in DNA sequences that can be translated into digital information and stored in a computer for analysis. As a consequence of this revolution, biology in the 21st century is rapidly becoming an information science... ...hypotheses will arise as often in silico as in vitro.” Eric Lander, Science 287 (5459), 1777-1782

3. The Problem…analysis of native state assembly of proteins. • Protein function and folding are highly cooperative processes, • Amino acids that interact in these processes can be close, or relatively distant in the 1o structure, • identifying interacting residues in active sites, or identifying interacting residues that yield discrete 3o structure is difficult, • these interactions are not obvious by scanning primary sequence.

4. Labor intensive. Doesn’t indicate residue interactions. A Partial Solution • Mutational analysis, • clone the gene, • alter the DNA sequence that codes for specific residues, • express the gene, • check for function or conformational fidelity.

5. Labor intensive. Presently impossible to accomplish on a large scale. A Better SolutionThermodynamic Mutant Cycling AnalysisMore later…but briefly… Double mutation analysis, • used to determine if two different residues (or peptide fragments) interact.

6. Multiple Sequence Alignment (globins) A Bioinformatic Alternative…...let Evolution do the dirty work.

7. “Entropy” in a MSA…the key to this paper. • Think of amino acids as parts of a system that follows the rules of thermodynamics, • if there were no constraints, amino acid frequency and distribution would tend to randomness, • however, natural selection constrains primary sequence in living systems.

8. MSA and Entropy

9. Genomic SequencesDNA Sequence:Reagent for the 21st Century

10. PDZ Domains (n = 274) “Model” Protein Domain Family • Evolutionarily conserved, especially in tertiary structure, • Ca atoms: root mean square deviation = 1.4 angstroms*, • More diverged in sequence homology, • averaging 24% AA sequence similarity. • *Four high resolution crystal structures of distantly related family members. Post synaptic density protein (PSD95), Drosophila disc large tumor suppressor (DlgA), and Zonula occludens-1 protein (zo-1)

11. Structural Classification of Proteins domains PDZ domains are found in diverse signaling proteinsin bacteria, yeasts, plants, insects and vertebrates. They bind either the carboxyl-terminal sequences of proteins or internal peptide sequences PDZ domains consist of 80 to 90 amino acids comprising six beta-strands (betaA to betaF) and two alpha-helices, A and B, compactly arranged in a globular structure. Peptide binding of the ligand takes place in an elongated surface groove as an antiparallel beta-strand interacts with the betaB strand and the B helix. The structure of PDZ domains allows binding to a free carboxylate group at the end of a peptide through a carboxylate-binding loop between the betaA and betaB strands. Google: SCOP Pfam

12. Don’t Sweat the Formulas! …English Translation: a measure of conservation can be made by comparing the frequency of amino acids in the column of a MSA, to a randomly filled column… …expressed as a change in free energy.

13. Figure 1A Black: amino acid frequency in a database of 36,498 proteins. Gray: amino acid frequency in a database of 274 PDZ domains.

14. PDZ domain AA 76 • AA 76 is known to be important in determining ligand specificity, - S/T - X- V/I - COO- - or -- F/Y - X- V/A - COO- Antepenultimate AA in the ligand.

15. Figure 1B,CPDZ MSA DGstat Highly conserved. DGstat = 3.83 kT* Poorly conserved. DGstat = 0.1 kT*

16. 76 99 Figure 1D

17. Figure 1E, F

18. Coupled Sites? …English Translation: you change the MSA by removing a subset of peptides that have similar (or identical) amino acids in a specific column… …if the amino acid in the original column interacts with another part of the peptide, you might expect to see a change in DGstat (DDGstat ) in another column of the new MSA.

19. Perturbing the MSA…extract subsets of low-entropy alignments. Re-calculate DGstat in the new MSA, look for columns that had a change in DGstat.

20. AA 76 • removed all of the peptides that had a histidine at AA 76 in the MSA, • Calculated the change in DGstat (D DGstat) at all positions.

21. AA 76 AA 34 AA 63 Figure 2 B

22. 29, 26 other side of ligand binding 33, 34, 80, 84 local 66, 57, 51 unexpected Figure 2C-F

23. in Silica, So Far, So What? Show me the money...

24. H76Y Statistical DDGstat Experimental DDGstat Fig. 3

25. FRET Fluorescence Resonance Energy Transfer

26. Mutant Cycling Analysis (General)…with FRET (Fluorescence Resonance Energy Transfer) 476/527 ratiom1 If not equal, then sites are coupled. 476/527 ratio m1:m2 Please Note: this was a general presentation, see slide 33 for the application used in this paper.

27. Fig. 3 Fig. D: What is it, why is it included? ?

28. Figure 4 Attempt to map connectivity through the peptide. Also performed analysis on POZ domain.

29. Conclusion With growing sequence data from evolutionary distant genomes, the mapping of energetic connectivity for many fold families should be a realistic goal.

30. Figure 4

31. Coupling Coefficient(Mutant Cycling Analysis) • k (wt:wt) x k (mut:mut) • k (wt:mut) x k (mut:wt) coupling coefficient = ...if there is no coupling, then the coupling coefficient would approach unity.