1. Ranking SS Prediction Using CA Overlap
Chester Shiu
CS273
May 31, 2005

2. Servers
ROBETTA
META-Basic
Shotgun-INBGU

3. ROBETTA Server Implementation of ROSETTA
Attempts Homology Modelling, then fills in gap with 3mers + simulated annealing
Does not handle extremes very well!

4. Why? ROBETTA performs poorly at extremes
Small – domain classification errors
Large – low contact order clustering?
Errors from poor homology identification and dependence on SA

5. META-Basic Not a Meta Server! Meta-Profile
Sequence AND Structure
6 PSI-BLAST iterations + RPS BLAST
High Specificity

6. Shotgun-INBGU Uses Consensus from linear weighing of parameters
Sequence
Multiple Alignment
Profiles of Fold Libraries
Consensus from linear weighing of parameters
Can pick out weak signal

7. Methodology Pair-wise compare top ranked model from each algorithm.
Select pair with highest score
Rationale: If ROBETTA suffers homology error then other two should outweigh

8. Scoring cRMSD Livebench 3D Score: exp(-ln(2)*d*d/(3*3))
But only got 2/10 correct
Number aligned Cα < 3A
9/10 correct!

9. The Erroneous Ranking 1rr9 – ATP-Dependent Protease
cRMSD roughly equidistant (15.9 vs 16.2)
Low Data: 4 versus 3 overlaps at <3A

10. Why is 3D Score so off?
Lower penalty for high distance than cRMSD, but still major
Sequence alignment issue?