Department of Computer Science, University of California, Santa Barbara August 11-14, 2003 CTSS: A Robust and Efficient Method for Protein Structure Alignment Based on Local Geometrical and Biological Features Tolga Can and Yuan-Fang Wang

2 CSB2003, August 11-14, 2003 Introduction Importance of discovering structural relationships between proteins Structural Alignment: NP-Hard Protein structure representation: no standard as in sequence alignment Many algorithms  Inter-atomic Distances (CE, DALI)  SSE vectors (VAST, 3D-Lookup) Different similarity measures  RMSD, p-value, etc.

3 CSB2003, August 11-14, 2003 Problem Definition Given a protein structure, find similar protein structures from a database of protein structures. 1fse:A 1jek:B 1alu:_ 2spc:A 1l3l:C 1k61:D 1kzu:B 1et1:A 1jig:A 1wdc:A 1nkd:_ 1fmh:A 1gl2:A ? 1l3l:C1kzu:B1jig:A1nkd:_ =

4 CSB2003, August 11-14, 2003 Protein Structure? HEADER PHEROMONE 20-DEC-95 2ERL SEQRES 1 40 ASP ALA CYS GLU GLN ALA ATOM 1 N ASP ATOM 2 CA ASP ATOM 3 C ASP ATOM 4 O ASP ATOM 5 CB ASP ATOM 6 N ALA ATOM 7 CA ALA ATOM 8 C ALA ATOM 9 O ALA ATOM 10 CB ALA ATOM 11 N CYS ATOM 12 CA CYS ATOM 13 C CYS ATOM 14 O CYS ATOM 15 CB CYS ATOM 16 SG CYS We use C α coordinates to represent the protein structure. PDB File

5 CSB2003, August 11-14, 2003 Protein Structure HEADER PHEROMONE 20-DEC-95 2ERL SEQRES 1 40 ASP ALA CYS GLU GLN ALA ATOM 1 N ASP ATOM 2 CA ASP ATOM 3 C ASP ATOM 4 O ASP ATOM 5 CB ASP ATOM 6 N ALA ATOM 7 CA ALA ATOM 8 C ALA ATOM 9 O ALA ATOM 10 CB ALA ATOM 11 N CYS ATOM 12 CA CYS ATOM 13 C CYS ATOM 14 O CYS ATOM 15 CB CYS ATOM 16 SG CYS The C α coordinates of a protein define a curve in 3D space. PDB File

6 CSB2003, August 11-14, 2003 Spline Approximation HEADER PHEROMONE 20-DEC-95 2ERL SEQRES 1 40 ASP ALA CYS GLU GLN ALA ATOM 1 N ASP ATOM 2 CA ASP ATOM 3 C ASP ATOM 4 O ASP ATOM 5 CB ASP ATOM 6 N ALA ATOM 7 CA ALA ATOM 8 C ALA ATOM 9 O ALA ATOM 10 CB ALA ATOM 11 N CYS ATOM 12 CA CYS ATOM 13 C CYS ATOM 14 O CYS ATOM 15 CB CYS ATOM 16 SG CYS We smooth the C α curve based on secondary structure information. PDB File

7 CSB2003, August 11-14, 2003 Spline Approximation HEADER PHEROMONE 20-DEC-95 2ERL SEQRES 1 40 ASP ALA CYS GLU GLN ALA ATOM 1 N ASP ATOM 2 CA ASP ATOM 3 C ASP ATOM 4 O ASP ATOM 5 CB ASP ATOM 6 N ALA ATOM 7 CA ALA ATOM 8 C ALA ATOM 9 O ALA ATOM 10 CB ALA ATOM 11 N CYS ATOM 12 CA CYS ATOM 13 C CYS ATOM 14 O CYS ATOM 15 CB CYS ATOM 16 SG CYS We smooth the C α curve based on secondary structure information. HelixTurn PDB File

8 CSB2003, August 11-14, 2003 Matching Two Curves Are they similar?

9 CSB2003, August 11-14, 2003 Curvature and Torsion Curvature: Torsion: If two single-valued continuous functions  (s) and  (s) are given for s > 0, then there exists exactly one space curve, determined except for orientation and position in space (i.e., up to a Euclidian motion), where s is the intrinsic arc length,  is the curvature, and  is the torsion. Fundamental Theorem of Space Curves: Measure of how far the curve deviates from being planar Measure of how far the curve deviates from being linear

10 CSB2003, August 11-14, 2003 Curvature and Torsion They are invariant to rotation and translation. They are localized. Curvature Torsion

11 CSB2003, August 11-14, 2003 Feature Extraction For each amino acid a (Curvature, Torsion) tuple is computed and Secondary Structure assignment information from PDB web site is gathered This constitutes a 3D feature vector of length n, where n is the number of amino acids in the protein + Curvature Torsion Secondary Structure Information (3 rd dimension not shown above)

12 CSB2003, August 11-14, 2003 Indexing the Features Why is indexing necessary? Hash Table (show in 2D below, 3 rd Dimension is the SSE type) Torsion Curvature A Hash Bin

13 CSB2003, August 11-14, 2003 Query Execution Hierarchical approach:  Pruning before detailed pairwise alignment hash table  Accumulate vote  vote protein ++  Normalize vote  vote protein /length protein  Threshold

14 CSB2003, August 11-14, 2003 Query Execution Pairwise alignment by Smith-Waterman dynamic programming technique performed after screening process: Distance Matrix SW 1fse:A 1l3l:C Gap length:63 RMSD:1.61 A o

15 CSB2003, August 11-14, 2003 SW Alignment Result 1fse:A 1l3l:C

16 CSB2003, August 11-14, 2003 Sample Query Results Query: 1faz:A, database: 1938 protein chains Screening time: 18 seconds Pairwise Alignment time: 29 seconds length:42 RMSD:2.8 A o 1faz:A & 1ytf:D length:38 RMSD:3.68 A o 1faz:A & 1dj7:A

17 CSB2003, August 11-14, 2003 Sample Query Results Query: 1b16:A, database: 1938 protein chains Screening time: 25 seconds Pairwise Alignment time: 68 seconds length:35 RMSD:3.26 A o 1b16:A & 1h05:A length:35 RMSD:1.58 A o 1b16:A & 1qp8:A

18 CSB2003, August 11-14, 2003 Current and Future Work Evaluation of  Accuracy  Comparison with SCOP classification  Efficiency  Comparison with other techniques like CE, or DALI Better index structures  Faster and more accurate screening of candidates Incorporating biological, chemical properties of amino acids to the structure signatures of proteins.

19 CSB2003, August 11-14, 2003 Conclusions A new method for protein structure alignment is presented:  Extracted structural features are:  Compact: O(n)  Localized: computed for each amino acid  Robust: error handling by spline approximation  Invariant: suitable for indexing  Meaningful: Biological, chemical properties can be incorporated easily  An indexing technique is deployed to avoid exhaustive scan of the structure database Experiment results show that this method is suitable for finding structural motifs.

20 CSB2003, August 11-14, 2003 Thank you for your attention! Tolga Can Department of Computer Science University of California at Santa Barbara Santa Barbara, CA 93106, U.S. URL: For More Information: