RT-RICO - Identifying Non-Independent Patterns in Protein Motif Sequence Data

Useful Links

• Wikipedia Secondary Structure
• Wikipedia Secondary Structure Prediction
• Pfam database of protein families and HMMs
• The PSIPRED protein structure prediction server
• CASP, Critical Assessment of Techniques for Protein Structure Prediction
• EVA Results for Secondary Structure, other methods/servers
• SCOP: Structural Classification of Proteins
• NCBI
• PDB ----- PDB Secondary Structure Download

Something new ...

For proteins with NO homologous protein with known structure in PDB.
:: www.pdb.org => Advanced Search => Sequence (Blast/Fasta/PSI_BLAST); Blast => Sequence search (E Cut Off 10.0, or 30.0 or use Fasta, depending on output, need a algorithm for this)
(Fasta search may return different results; some proteins may use Fasta search, because Blast returned nothing)

What I am doing...

1. SCOP: Structural Classification of Proteins

2. scope parseable files follow the structure of scope hierarchy

3. get data from scope
--- http://scop.mrc-lmb.cam.ac.uk/scop/ref/nar2002.pdf
--- http://scop.mrc-lmb.cam.ac.uk/scop/ref/nar2007.pdf
--- http://scop.mrc-lmb.cam.ac.uk/scop/ref/1995-jmb-scop.pdf

4. Pfam database of protein families and HMMs - it has some good links to other databases

5. A MSD example

6. Beginning Perl in Bioinformatics Book Exercises & Examples, PDB file format (secondary structure) explanation. PDB downloads ss.txt.

Proposed Steps

0. Do steps 1 to 5 manually to prove it can be done before coding.

1. Parse SCOPE file, get proteins names divided into 4 structures. (dir.cla.scop.txt_1.xx)

2. Use step 1 results to parse PDB or NCBI protein data file, get amino acid sequence and corresponding secondary structure sequence.

3. Use (part of) step 2 results to build data file ready for RT-RICO, e.g. (5 amino acids + 1 secondary structure ) x 3 secondary structures + decide the format of the data file (e.g. is it suitable to use 5 amino acids? or 9 amino acids?)

4. Use step 3 results, modify RT-RICO code, generate rules e.g. from 5 amino acids -> 1 secondary structure (slightly different for beginning and end). Use the rules generated to predict secondary structure (probability).

5. Use (part of) step 2 results to generate Q3 score, use step 3 results & newly developed algorithm to generate Q3 score

6. If step 5 works, write a paper. (And it works !!! Yeh !!!)

Notes

• (Wiki) Secondary structure is formally defined by the hydrogen bonds of the biopolymer, as observed in an atomic-resolution structure. In proteins, the secondary structure is defined by patterns of hydrogen bonds between backbone amide groups (sidechain-mainchain and sidechain-sidechain hydrogen bonds are irrelevant), where the DSSP definition of a hydrogen bond is used.

• (Wiki) Secondary structure prediction is a set of techniques in bioinformatics that aim to predict the local secondary structures of proteins and RNA sequences based only on knowledge of their primary structure - amino acid or nucleotide sequence, respectively. For proteins, a prediction consists of assigning regions of the amino acid sequence as likely alpha helices, beta strands (often noted as "extended" conformations), or turns. The success of a prediction is determined by comparing it to the results of the DSSP algorithm applied to the crystal structure of the protein; for nucleic acids, it may be determined from the hydrogen bonding pattern.

• The accuracy of current protein secondary structure prediction methods is assessed in weekly benchmarks such as LiveBench and EVA.

• * G = 3-turn helix (310 helix). Min length 3 residues.
  * H = 4-turn helix (alpha helix). Min length 4 residues.
  * I = 5-turn helix (pi helix). Min length 5 residues.
  * T = hydrogen bonded turn (3, 4 or 5 turn)
  * E = beta sheet in parallel and/or anti-parallel sheet conformation (extended strand). Min length 2 residues.
  * B = residue in isolated beta-bridge (single pair beta-sheet hydrogen bond formation)
  * S = bend (the only non-hydrogen-bond based assignment)

• DSSP:
  * H: alpha helix
  * B: residue in isolated beta-bridge
  * E: extended strand, participates in beta ladder
  * G: 3-helix (3/10 helix)
  * I: 5-helix (pi helix)
  * T: hydrogen bonded turn
  * S: bend
  * .: no assigned structure

• (G, H, I) => Helix H
  (E, B) => Sheet E
  (T, S) => Coil C

• All-alpha: consist almost entirely (at least 90%) of alpha-helices
  All-beta: composed mostly of beta-sheets (at least 90%) in their secondary structure
  Alpha/beta: alternating, mainly parallel segments of alpha-helices and beta-sheets
  Alpha+beta: mixture of all-alpha and all-beta regions, mostly in an anti-parallel fashion

Reading

• Fadime Üney Yüksektepea, Özlem Yılmaza and Metin Türka, Prediction of secondary structures of proteins using a two-stage method, Computers & Chemical Engineering Volume 32, Issues 1-2, January 2008, Pages 78-88
• DSSP Program. Kabsch W, Sander C (1983). "Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features". Biopolymers 22 (12): 2577-637.
• U¨ ney, F., & Tu¨rkay, M. (2006). A mixed-integer programming approach to multi-class data classification problem. European Journal of Operational Research, 173(3), 910–920.
• I start using hardcopy paper readings... so I won't put them here.
• Tu¨rkay, M., U¨ ney, F., & Yılmaz, O. (2005). L. Puigjaner & A. Espuna (Eds.), Prediction of folding type of proteins using mixed-integer linear programming, computer-aided chemical engineering: ESCAPE-15 (pp. 523–528). Amsterdam: Elsevier.
• Baker, D., & Sali, A. (2001). Protein structure prediction and structural genomics. Science, 294(5540), 93–96. (. pdf file)
• Altschul, S., Madden, T., Shaffer, A., Zhang, J., Zhang, Z., Miller, W., et al. (1997). Gapped Blast and PSI-Blast: A new generation of protein database search programs. Nucleic Acids Research, 25, 3389–3402.
• Bradley, P., Chivian, D., Meiler, J., Misura, K. M., Rohl, C., Schief, W., et al. (2003). Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation. Proteins: Structure Function, and Genetics, 53, 457–468. (.pdf file)
  

Other Readings (Mainly for Data)

• Cuff, J. A., & Barton, G. (1999). Evaluation and improvement of multiple sequence methods for protein secondary structure prediction. Proteins, 34, 508–519. (.pdf file) - good data
• Rost, B. (2003). Rising accuracy of protein secondary structure prediction. In D. Chasman (Ed.), Protein structure determination, analysis, and modeling for drug discovery (pp. 207–249). New York: Dekker. (.ppt presentation)