Methods of Protein Structure Alignment

1
Methods of Protein Structure Alignment

• David Hoksza
• Charles University in Prague Department of
  Software Engineering Czech Republic

2
Presentation Outline

• Biological background
• Protein databases
• Protein structure
• Similarity measures
• Algorithms

3
Terminology

• DNA (deoxyribonucleic acid)
• sequence of nucleotides (A, C, G, T)
• double-helix
• RNA (ribonucleic acid)
• single-helix sequence of nucleotides (A, C, G, U)
• messenger RNA (mRNA)
• transfer RNA (tRNA)
• ribosomal RNA (rRNA)
• Proteins
• molecules
• translated from mRNA in ribosomes
• sequence of amino acids (20 AAs)
• coded by codon (triplet of nucleotides)
• genetic code
• DNA ? RNA ? protein

central dogma
transcription
translation
4
Protein Similarity

• Interaction of proteins determines biological
  functions
• Function of protein derived from its three
  dimensional structure
• similar proteins (many common amino acids on
  appropriate places) have similar structure
• ? similar proteins have similar functions
• similar proteins have a common ancestor
• Identifying protein sequence
• ? finding similar proteins
• ? getting clue to the function

5
Protein Databases

• Finding similar proteins
• even among different species
• Prominent non-structural databases
• GenBank
• EMBL (European Molecular Biology Laboratory Data)
• DDBJ (DNA Data Bank of Japan)
• UniProt
• Swissprot trEMBL (translated EMBL) PIR
  (Protein Information Resource)
• Prominent structural databases
• PDB (Protein Data Bank)
• SCOP (Structural Classification of Proteins)
• ASTRAL Compendium (for Sequence and Structure
  Analysis)

not moderated
moderated
6
Databases Growth
7
Databases Growth (PDB)
8
Levels of complexity of protein structure

• Primary structure
• linear sequences of amino acids
• Secondary structure
• local three-dimensional segments which are folded
  into specific repeated structures
• alpha helices, beta sheets (strands)
• Tertiary structure
• the atomic coordinates - spatial relations among
  the secondary structure elements
• Quaternary structure
• multiple polypeptide chains

9
Protein structure

• Amino-acids differ in their side chains
  (R-groups)
• Connection peptide bonds
• Protein sequence ? sequence of rigid planes
• Degrees of freedom
• Planes
• R-groups

• 3D conformation described by dihedral angles
• Only a-carbons usually considered

10
Protein structure cont.

• SSE Secondary Structural Elements
• Repetitive structures arising by H bonds
• Alpha helices
• ith amino-acids is connected to (i4)th
  amino-acid
• f and ? angles are constant
• peptide units per turn is 3,6
• Beta sheets (strands)
• multiple strands connected to each other by H
  bonds
• parallel/antiparallel
• Motifs
• Combinations (second form) of SSEs
• beta ribbon, beta-barrel, beta-hairpin,
  helix-loop-helix, greek key,

11
Similarity measures

• RMSD Root Mean Square deviation/difference/dista
  nce
• Summarizes partial distances of aligned residue
  pairs
• Evaluates quality of a matching (superposition)
• cRMSD (core RMSD)
• inter-residue
• dRMSD (distance RMSD)
• intra-residue
• elastic similarity score
• disregarding outliers
• fragmented dRMSD
• aimed to recognition of similar substructures

12
Algorithms

• Goals
• Alignment
• direct similarity
• Classification
• indirect similarity
• Methods
• Incremental extension
• extending initial partial alignment
• Dynamic programming
• dynamic programming matrix of (usually) distances
• Indexing
• using features to be indexed by
• trees
• geometric hashing

13
Algorithms - Incremental Extension

• DALI
• Elastic similarity score
• Matrix of inter-residual distances
• Similar proteins similar inter-residual
  distances similar distance matrices
• Contatct pattern (CP) - submatrix of fixed size
  (hexapeptides)
• Similar pairs of CPs are stored and one is used
  as a seed
• Monte-Carlo optimization is used for extend the
  already created alignment

• CE
• AFP Aligned Fragment Pair (constant length
  portions local structures)
• Fragmented dRMSD
• Joining of AFPs based on three different distance
  measures
• Several path are computed and best of them is
  optimized by Smith-Waterman (on the distance
  matrix)

14
Algorithms Dynamic Programming

• SAP
• Double dynamic programming
• View vector of distances to other resiudes
• Between pairs of views, optimal alignments
  (Smith-Waterman) are computed which are used to
  fill up final DP matrix ? final alignment
• PROSUP
• Identification of seed fragments
• Expand seed fragments to initial alignments
• Apply DP (Needleman-Wunsch) to refine initial
  alignments
• Evaluate refined alignments
• STRUCTAL
• Evaluated as the best structural algorithm in
  Kolodny, R., Koehl, P., Levitt, M. Comprehensive
  evaluation of protein structure alignment
  methods scoring by geometric measures. J. Mol.
  Biol. 346 (2005), 1173-88.
• Initial alignment based on several rules (match
  beginning of structures, match ends, match pairs
  based on sequence alignment, )
• Refine the alignments by DP (Needleman-Wunsch)
• Exposure weighting
• Position dependent gap penalties
• TALI
• Incorporates torsion angles ? mutual distances
  form DP matrix ? Smith-Waterman

15
Algorithms Indexing - Trees

• PSIST
• Features
• sliding window of size w
• distance
• angle
• Suffix-tree

• PSI
• Represenatation
• SSE approximation
• amino-acids ? centers of masses
• defining local neighborhood for each SSE
• features (9 dimensions)
• distances in triplets
• angles between pairs in triplets
• R-tree

16
Algorithms Indexing - Hashing

• ProGreSS
• Combines structure and sequence
• Features (sliding window of size w)
• structure
• curvature (dim w)
• torsion angles (dim w)
• Haar wavelet transormation ? dim dt
• normalization ? 0,1 dt space
• sequence
• line in scoring matrix (PAM, BLOSUM, ..) ?
  scoring vector ? chaining scoring vectors ? dim
  20w
• Haar wavelet transormation ? dim dq
• normalization ? 0,1 dq space
• SSE type

• CTSS
• Theory of differential geometry
• Structure 3D spline
• Features
• torsion angle
• curvature
• SSE type
• Pairwise comparison
• Smith-Waterman
• scoring matrix
• based on features
• For each pair

17
End
18
PDB record

• HEADER HYDROLASE(O-GLYCOSYL) 25-JAN-94
  149L
• TITLE CONSERVATION OF SOLVENT-BINDING SITES
• ..
• REMARK 1
  
• REMARK 1 REFERENCE 1
  
• REMARK 1 AUTH M.MATSUMURA,W.J.BECKTEL,
  
• ..
• REMARK 2 RESOLUTION. 2.60 ANGSTROMS.
  
• REMARK 3
  
• REMARK 3 REFINEMENT.
  
• REMARK 3 PROGRAM TNT
  
• REMARK 3 AUTHORS TRONRUD,TEN EYCK
  
• ...
• SEQRES 1 A 164 MET ASN LEU PHE GLU MET LEU
  ARG
• SEQRES 2 A 164 ARG LEU LYS ILE TYR LYS ASP
  THR
• ..
• HELIX 1 H1 LEU A 3 GLU A 11 1
  9
• HELIX 2 H2 LEU A 39 ILE A 50 1
  12
• ..

• HELIX 10 H10 PRO A 143 THR A 155 1
  13
• SHEET 1 A 3 TYR A 18 LYS A 19 0
  
• SHEET 2 A 3 TYR A 25 ILE A 27 -1 N THR
  A 26 O TYR A 18
• ..
• SHEET 3 A 3 HIS A 31 THR A 34 -1 N HIS
  A 31 O ILE A 27
• TURN 1 T1 ASP A 20 GLY A 23
• ..
• ATOM 1 N MET A 1 29.360 -4.880
  38.742 1.00 65.91 N
• ATOM 2 CA MET A 1 29.892 -6.057
  38.096 1.00 60.68 C
• ATOM 3 C MET A 1 30.674 -5.673
  36.863 1.00 56.33 C
• ..
• ATOM 302 CG PRO A 37 51.531 -30.219
  18.738 1.00 78.60 C
• ATOM 303 CD PRO A 37 52.005 -28.775
  18.641 1.00 78.61 C
• ATOM 304 N SER A 38 53.483 -28.405
  22.129 1.00 70.92 N
• ATOM 305 CA SER A 38 54.604 -28.517
  23.043 1.00 67.86 C
• ..
• ATOM 1309 OXT LEU A 164 25.719 -18.888
  43.195 1.00 25.30 O
• TER 1310 LEU A 164
• ..

19
Similarity Measures (primary structure)

• two strings of amino-acids
• hamming distance
• sequences of equal length
• number of non-identical positions
• edit distance
• minimal number of operations insert/update/delete
  to convert one sequence to the other
• weighted edit distance
• takes into account probability of updating one
  letter to the other
• scoring (substitution) matrices
• PAM, BLOSUM,
• different costs for opening/extending a gap
• global/local alignment