1. Finding Functionally Significant Structural Motifs in Proteins
Jennifer Hicks

2. Introduction Goal of Protein Classification: Techniques Trypsin
Evolutionary Relationships
Functional Similarities
Techniques
Sequence Matching
Whole Structure Matching
Motif Matching
Trypsin
Active Site

3. Project Goal Find structural motif in an example protein
INPUT: 3D, labeled coordinates
Known Motif or Pattern
Example Protein
Output: Best Match
Optimal Transform and Correspondence Set
Partial Match RMSD

4. Algorithm Overview
Generate small set of interest regions and correspondences from the example protein
Align the input pattern to each interest region
Choose the alignment with the lowest RMSD

5. Regions of Interest Input: Output: 3 pivot elements of pattern motif
Error Threshold
Output:
Correspondence sets that satisfy constraints and labels

6. Alignment: Approach 1 Find an initial transform
Create a full correspondence set using a closest neighbor method
Find the optimal transform by aligning small random subsets of the current correspondence set
Repeat steps 2 and 3 until RMSD stabilizes

7. Alignment: Approach 2
Find transform for current Correspondence Set with SVD
Transform motif and update Correspondence Set to include sufficiently close elements
Repeat steps 1 and 2 until Correspondence Set stops growing

8. Partial Match RMSD
Approach 2: Penalty for items not included in final correspond. set
Approach 1: Tukey function to allow for outliers
T(x)

9. Running Time Let m = # Pattern Elements
Let n = # Example Protein Elements
Regions of Interest:
Cubic in number of example protein elements that match pivot label
Each iteration of Alignment:
O(m) to compute transform
O(mn) to update correspondences

10. Testing Generated 3D, labeled motif Randomly perturbed motif
Aligned motif to generated proteins with and without the perturbed motif

11. Results

12. Future Work Regions of Interest: Protein Description: Partial Match:
Grid Method
Choose pivots based on biological significance
Initial Alignment
Protein Description:
Labeling technique
Orientation vectors
Partial Match:
Determine biological significance

13. References
Singh, Rohit. Computational study of protein structure and folding: some interesting problems. Masters Thesis, Stanford University, 2002.
Umcyama, Shinji. Least-Squares Estimation of Transformation Parameters Between Two Point Patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1991, 13(4).
Protein Data Bank