1. Proteins  Proteins control the biological functions of cellular organisms  e.g. metabolism, blood clotting, immune system amino acids  Building blocks – amino acids  amino group (NH 2 ), carboxyl group (COOH), side chain R

2. The Protein Data Bank

3. Protein sequence and structure  Protein alphabet consists of 20 amino acids Sequence viewStructure view ADKELKFLVVDDFSTMRRIV.....

4. Protein structure and function  Function is determined by 3D shape/structure Thrombin Facilitates blood clotting Hirudin Anticoagulant (blocks active site)

5. Protein structure and function  Structure conserves better evolution information 1MBC: VLSEGEWQLVLHVWAKVE..... 2FAL: XSLSAAEADLAGKSWAPV..... Myoglobin family

6. Structural Bioinformatics  Pairwise alignment algorithms  DALI (Holm and Sander, Journal of Molecular Biology, 1993)  LOCK (Singh and Brutlag, ISMB, 1997)  CE (Shindyalov and Bourne, Protein Engineering, 1998)  SSM (Krissinel and Henrick, Acta Cryst., 2004)  Ye et al. JBCB, 2004  Multiple alignment algorithms  Gerstein and Levitt, ISMB, 1996: Iterative dynamic programming  SSAP (Orengo and Taylor, Methods Enymol., 1996): Two-level DP  Leibowitz et al., ISMB, 1999): Geometric hashing  CE-MC (Guda et al., PSB, 2001)  MAMMOTH (Lupyan et al., Bioinformatics, 2005)  MAPSCI (Ye at al., WABI, 2006)

7. Structural Bioinformatics  Homology detection  Hidden Markov models (Jaakola et al., JCB, 2000)  Spectrum, Mismatch kernel (Leslie et al., Bioinformatics, 2002)  Structure kernel (Qiu et al., Bioinformatics, 2007)  Protein structure prediction  Jones and Hadley, Bioinformatics: Sequence, structure and databanks. 2000.  FUGUE (Shi et al., J. Mol. Biol., 2001)  SCOP (Andreeva, Nucleic Acids Res., 2004)  Protein docking  Shoichet et al., J. Comput. Chem., 1992.  Choi et al., WABI, 2004.  Wang et al., PSB, 2005.  Sousa et al., Proteins, 2006.

8. Pairwise Structure Alignment  Given two proteins represented by the C α atoms (backbone)  find 3D transformation that superimposes a large number of the C α atoms  ensure that overall distance between matched pairs is as small as possible  Trade-off between number of matches and total distance between

9. Pairwise Structure Alignment Ye et al. JBCB 2004  Uses orientation independent representation of proteins based on the fact that C α atoms are ~4 Ǻ apart

10. Pairwise Structure Alignment Ye et al. JBCB 2004  The protein is represented as a sequence of angle triplets {(α 1, β 1, γ 1 ), (α 2, β 2, γ 2 ), …, (α n, β n, γ n ) }

11. Pairwise Structure Alignment Ye et al. JBCB 2004  Compute a local alignment based on angle representation  Find maximal subset of runs with similar transformation matrices

12. Pairwise Structure Alignment Ye et al. JBCB 2004  The main algorithm  Compute the angle based representation  Align the angle based representation  Identify runs with similar transformation matrices  Compute initial structural alignment  Refine the alignment iteratively  Running time is ~(m+n) 2 where m, n are the protein lengths

13. Multiple Structure Alignment  Given a set of proteins represented by the C α atoms (backbone)  find a simultaneous alignment of all structures  find a consensus structure that represents all of them

14. Multiple Structure Alignment  The main algorithm  find initial consensus structure (one of the given proteins)  pairwise align the consensus and each of the proteins  merge the pairwise alignments from previous step  recompute the consensus protein; repeat from step 2  Merging the pairwise alignments similar to sequence case P 1 = BBCA, P 2 = CBBA, P 3 = BCCA P 1 : -BBCA, P 1 := BBCAP: -BBCA P 2 : CBB-A, P 3 := BCCAP: CBB-A P: -BCCA

15. Multiple Structure Alignment  Computation of consensus structure (after merging alignments)

16. Multiple Structure Alignment  Algorithm flowchart