Protein Disordered Regions and the Evolution of Eukaryotes Allan Wu Phar 201 Phil Bourne

Initial motivation for project: The Number of New Folds are Decreasing wthChart.do?content=fold-scop

Introduction to protein disordered regions They are regions of proteins without an inherent structure (though they might have transient structure). Many studies have found that they evolve faster than ordered regions. (Kim et. al, Dunker et. al, Brown et al.)‏ Amount of disordered regions in prokaryotes:  2-4% Amount of disordered regions in eukaryotes:  33%  In addition, much of these disordered regions appear to be in kinase targets, and proteins in signaling pathways. (Kim et. al.)‏ What are the advantage of having so much disordered regions?

Binding affinity variability and multiple ligand model Easy way to adjust binding affinity for proteins and ligand specificity independently Multiple proteins can bind to the same target (Dunker et. al.)‏

Example of protein staying disordered upon binding to ligand Sic1 (cyclin dependent kinase inhibitor)‏ However, the conformations In which the Protein exists mybe limited. (Mittag et. al.)‏

Hypothesis Why do disordered regions evolve faster? Reason protein disordered regions evolve faster is that they are more tolerant of the types of mutations which they could take and still remain functional. Idea of a greater mutation range, or range of amino acid replacement which would preserve function.

Preliminary study to prove hypothesis: Mapping Human SNPs onto Disordered Regions Method: Used Disprot as a database of protein disordered regions, and LS-SNP as a database of human SNPs Mapped all human SNPs onto Disprot, see what percentage falls on disordered regions and what percentage falls on ordered regions Calculate a “conservation” score based on BLOSUM62 matrix of SNPs that are in disordered vs. ordered regions using the equation S s in S and w in W score(w,s)/number of SNPs, where score(w,s) is the BLOSUM62 score between the wildtype amino acid and the amino acid in the SNP.

Results of preliminary study Percentage of disordered regions in 122 proteins: 23% Percentage of SNPs in disordered region: 31% Conservation score of SNPs in ordered regions: -0.4 Conservation score of SNPs in disordered regions: Redid the work of Brown et. al. and Kim et. al., but confirms that what happens on an evolutionary time- scale between two different species also occurs on a time-scale within a species. Interesting to note that the change in conservation score is more dramatic than change in the number of SNPs between ordered and disordered regions.

Implication of my preliminary study Difference in conservation score between ordered and disordered regions more dramatic than change in number of SNPs in number of SNPs in ordered vs. disordered regions. Disordered regions can evolve faster because they could substitute for a wider range of amino acids. Suggests an comparative genomic method of discovering protein disordered regions.

Mutation range of disordered regions is greater than ordered regions We could think of the mutation range as the range of amino acids that can be replaced without loosing function, which is greater in disordered than ordered regions.

Further experiments to confirm the hypothesis Find even more SNPs and see if their pattern of evolution is similar to this more limited study, and also include allelic requencies. Better methods for detection of protein disordered regions. Mutagenesis studies of protein disordered regions  Create SNPs using induced mutagenesis to compare how well ordered vs. disordered regions retain their functions after mutagenesis Test if ability to mutate more freely than ordered region give rise to new functions.

Implications of Study: Better method for detecting disordered regions in proteins Suggests an comparative genomic method of discovering protein disordered regions There is a signature pattern of evolution for protein disorder regions one could use this to determine disordered regions. Could take advantage of cheap sequencing, which may be cheaper than determining structure

Impact on Understanding Evolution of Eukaryotes It has been shown that the three kingdom uses different protein folds We could consider disorder regions to be “folds” which are used only by eukaryotes The use of disordered regions, and perhaps other adaptations, allowed them to evolve beyond prokaryotes

Evidence that disordered region allowed development of multicellularity Suggested by Ward et. al. Disordered regions evolve faster than ordered regions Disordered proteins tend to be involved in cell cycle, transcriptional and translational regulation (Fink 2005)‏ Many of them are kinases  Kinases are involved in differentiation  Many protooncogenes are kinases

Advantages of fast evolution of signaling networks Fast  Kinases cascades work at a time scale much faster than control at the transcription level Faster degradation of signaling proteins?  Since disordered proteins tend to be degraded faster in proteasomes, maybe it's easier to do it this way?

Citations Tanja Mittaga, Stephen Orlickyb, Wing-Yiu Choyc, Xiaojing Tangb, Hong Lina, Frank Sicherib, Lewis E. Kay Mike Tyers and Julie D. Forman-Kaya (2008) Dynamic equilibrium engagement of a polyvalent ligand with a single-site receptor. PNAS 105:17772– Philip M Kim1,5,*, Andrea Sboner1,5, Yu Xia2 and Mark Gerstein1,3,4 (2008) The role of disorder in interaction networks: a structural analysis. Molecular Systems Biology 4. K. DUNKER, E. GARNER, S. GUILLIOT. PROTEIN DISORDER AND THE EVOLUTION OF MOLECULAR RECOGNITION: THEORY, PREDICTIONS AND OBSERVATIONS (1998) Pac Symp Biocomput J. J. Ward, J. S. Sodhi, L. J. McGuffin, B. F. Buxton and D. T. Jones. Prediction and Functional Analysis of Native Disorder in Proteins from the Three Kingdoms of Life. (2004) J. Mol. Biol. 337: 635–645. Brown CJ, Takayama S, Campen AM, Vise P, Marshall TW, Oldfield CJ, Williams CJ, Dunker AK (2002) Evolutionary rate heterogeneity in proteins with long disordered regions. J Mol Evol 55: 104–110. Anthony L Fink. Natively unfolded proteins. Current Opinion in Structural Biology 2005, 15:35–41.