Multiple Sequence Alignments. Multiple Alignments Generating multiple alignments Web servers...
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Transcript of Multiple Sequence Alignments. Multiple Alignments Generating multiple alignments Web servers...
Multiple Sequence Alignments
Multiple Alignments
Generating multiple alignments Web servers
Analyzing a multiple alignment what makes a ‘good’ multiple alignment? what can it tell us, why is it useful?
Adjusting a multiple alignment Alignment editors and HowTo Demonstration and practice
What is a Multiple Alignment?
A comparison of sequences “multiple sequence alignment”
A comparison of equivalents: Structurally equivalent positions Functionally equivalent residues Secondary structure elements Hydrophobic regions, polar residues
Generating multiple alignments
Pairwise sequence alignment is easy with sufficiently closely related sequences.
Below a certain level of identity sequence alignment may become uncertain : twilight zone for aa sequences ~ 30%.
In or below the twilight zone it is good to make use of additional information, eg, from evolution.
A multiple alignment of diverse sequences is more informative than a pairwise alignment: residues conserved over longer period of time are under
stronger evolutionary constraints.
Multiple Sequence Alignments Algorithms
Multiple sequence alignment uses heuristic methods only: With dynamic programming, computational
time quickly explodes as the number of sequences increases.
Different methods/algorithms: Segment-based (DiAlign, …). Iterative (HMMs, DiAlign, PRRP, …). Progressive (Clustalw, T-Coffee, MUSCLE,
…).
Progressive Alignment
Step1: Calculate all pairwise alignments and calculate distances for all pairs of sequences.
Step 2: Construct guide tree joining the most similar sequences using Neighbour Joining.
A B C D EB 2C 4 4D 6 6 6E 6 6 6 4F 8 8 8 8 8
Step 1 Step 2
Progressive Alignment
Step 3: From the tree assign weights for each sequence: We want to down-weight nearly identical sequences
and up-weight the most divergent ones. Step 4: Align sequences, starting at the leaves
of the guide tree: Pairwise comparisons as well as comparison of single
sequence with a group of sequences (Profile)
Caveat: errors introduced early cannot be corrected by subsequent information
Web servers
ClustalW: http://www.ebi.ac.uk/Tools/clustalw2/
T-Coffee: http://www.ebi.ac.uk/Tools/t-coffee/ MUSCLE: http://www.ebi.ac.uk/Tools/muscle/
DiAlign: http://dialign.gobics.de/
... and more at http://helix.nih.gov/apps/bioinfo/msa.html.
Clustalw features Amino acid substitution matrices are varied at different
alignment stages according to the divergence of the sequences to be aligned.
Reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure.
Insertions and deletions are more common in loop regions than in the core of the protein!
T-Coffee featuresMore accurate than ClustalWInstead of amino acid substitution matrices,
uses consistency in a library of pairwise alignments
i
j
Vertices represent positions in protein
sequence. Edges represent pairwise
alignments between protein sequences.
If residues I and J have many common
neighbours, their consistency is high.
MUSCLE
Fast implementationSometimes more accurate than ClustalW
or T-Coffee
Example Let’s build a multiple alignment for the following
sequences :>query
MKNTLLKLGVCVSLLGITPFVSTISSVQAERTVEHKVIKNETGTISISQLNKNVWVHTELGYFSGEAVPSNGLVLNTSKGLVLVDSSWDDKLTKELIEMVEKKFKKRVTDVIITHAHADRIGGMKTLKERGIKAHSTALTAELAKKNGYEEPLGDLQSVTNLKFGNMKVETFYPGKGHTEDNIVVWLPQYQILAGGCLVKSASSKDLGNVADAYVNEWSTSIENVLKRYGNINLVVPGHGEVGDRGLLLHTLDLLK>gi|2984094 MGGFLFFFLLVLFSFSSEYPKHVKETLRKITDRIYGVFGVYEQVSYENRGFISNAYFYVADDGVLVVDALSTYKLGKELIESIRSVTNKPIRFLVVTHYHTDHFYGAKAFREVGAEVIAHEWAFDYISQPSSYNFFLARKKILKEHLEGTELTPPTITLTKNLNVYLQVGKEYKRFEVLHLCRAHTNGDIVVWIPDEKVLFSGDIVFDGRLPFLGSGNSRTWLVCLDEILKMKPRILLPGHGEALIGEKKIKEAVSWTRKYIKDLRETIRKLYEEGCDVECVRERINEELIKIDPSYAQVPVFFNVNPVNAYYVYFEIENEILMGE>gi|115023|sp|P10425|MKKNTLLKVGLCVSLLGTTQFVSTISSVQASQKVEQIVIKNETGTISISQLNKNVWVHTELGYFNGEAVPSNGLVLNTSKGLVLVDSSWDNKLTKELIEMVEKKFQKRVTDVIITHAHADRIGGITALKERGIKAHSTALTAELAKKSGYEEPLGDLQTVTNLKFGNTKVETFYPGKGHTEDNIVVWLPQYQILAGGCLVKSAEAKNLGNVADAYVNEWSTSIENMLKRYRNINLVVPGHGKVGDKGLLLHTLDLLK>gi|115030|sp|P25910|MKTVFILISMLFPVAVMAQKSVKISDDISITQLSDKVYTYVSLAEIEGWGMVPSNGMIVINNHQAALLDTPINDAQTEMLVNWVTDSLHAKVTTFIPNHWHGDCIGGLGYLQRKGVQSYANQMTIDLAKEKGLPVPEHGFTDSLTVSLDGMPLQCYYLGGGHATDNIVVWLPTENILFGGCMLKDNQATSIGNISDADVTAWPKTLDKVKAKFPSARYVVPGHGDYGGTELIEHTKQIVNQYIESTSKP>gi|282554|pir||S25844 MTVEVREVAEGVYAYEQAPGGWCVSNAGIVVGGDGALVVDTLSTIPRARRLAEWVDKLAAGPGRTVVNTHFHGDHAFGNQVFAPGTRIIAHEDMRSAMVTTGLALTGLWPRVDWGEIELRPPNVTFRDRLTLHVGERQVELICVGPAHTDHDVVVWLPEERVLFAGDVVMSGVTPFALFGSVAGTLAALDRLAELEPEVVVGGHGPVAGP EVIDANRDYLRWVQRLAADAVDRRLTPLQAARRADLGAFAGLLDAERLVANLHRAHEELLGGHVRDAMEIFAELVAYNGGQLPTCLA
ClustalW at EBI
Many options: CPU mode, full/fast alignment, window length in
fast mode, … gap penalties.
ClustalW at EBI Automatic display of:
Score table Alignment (optional
colouring) Tree guide
Link to Jalview alignment editor!
A note on the example
It is atypical: It uses only three sequences. One should use more in order to extract reliable
informations.
It illustrates a common mistake: It uses too closely related sequences. One should use as divergent and diverse sequences
as possible in order to extract relevant informations.
A Good Multiple Alignment?
Difficult to define…
Good ones look pretty! Aligned secondary structures Strongly conserved residues / regions Comparison with known structure helps
Bad ones look chaotic and random.
A Good Multiple Alignment?
☻ ?
conservation
quality
consensus
Multiple Alignment Features
Barton (1993) “The position of insertions and deletions suggests
regions where surface loops exist…
Multiple Alignment Features
Multiple Alignment Features
Barton (1993) “The position of insertions and deletions suggests
regions where surface loops exist…
Conserved glycine or proline suggests a β-turn...
Multiple Alignment Features
Multiple Alignment Features
Barton (1993) “The position of insertions and deletions suggests
regions where surface loops exist…
Conserved glycine or proline suggests a β-turn…
Residues with hydrophobic properties conserved at i, i+2, i+4 (etc) separated by unconserved or hydrophilic residues suggests a surface β-strand…
Multiple Alignment Features
Multiple Alignment Features
Barton (1993) “The position of insertions and deletions suggests
regions where surface loops exist…
Conserved glycine or proline suggests a β-turn…
Residues with hydrophobic properties conserved at i, i+2, i+4 (etc) separated by unconserved or hydrophilic residues suggests a surface β-strand…
A short run of hydrophobic amino acids (4 or 5 residues) suggests a buried β-strand…
Multiple Alignment Features
Multiple Alignment Features
Barton (1993) Pairs of conserved hydrophobic amino acids separated by
pairs of unconserved or hydrophilic residues suggests an α-helix with one face packed in the protein core. Similarly, an i, i+3, i+4, i+7 pattern of conserved residues.”
Multiple Alignment Features
Multiple Alignment Features
Cysteine is a rare amino acid, and is often used in disulphide bonds ( pairs of conserved cysteines )
Charged residues ( histidine, aspartate, glutamate, lysine, arginine ) and other polar residues embedded in a conserved region indicate functional importance
Multiple Alignment Features
Quality Assessment
Bad residues Large distance from column consensus
Bad columns Average distance from consensus is high
– “entropy”
Bad regions Profile scores
Bad quality doesn’t always mean badly aligned!
RINAIEVMAKLIQ
LI
MIILVEIVLAM
PERMKIDQGQNMW
DLVTWDYAASLDF
DNPGGACRTTLID
Quality Assessment
Profiles A profile holds scores for each residue type (plus gaps)
over every column of a multiple alignment Concepts:
• Consensus sequence• Amino acid similarity
Some multiple alignment programs use profiles to build or add to an alignment
Any alignment, or even one sequence, can be a profile (one sequence isn’t a very good one…)
What can we do with a multiple alignment?
Identify subgroups (phylogeny) Intra-group sequence conservation Evolutionary relatedness (view tree)
Identify motifs (functionality) Evolutionary signals Highly conserved residues indicate
functional or structural significance!
Widen search for related proteins MA better than single sequence Consensus sequence / profile useful
RPDDWHLHLRGGIDTHVHFIGFTLTHEHICPFVEPHIHLDPKVELHVHLD
What do we want to do?
Build a homology model? Accuracy
Perform phylogenetic analysis? Completeness
Functional analysis of a protein family? Diversity
Building the initial alignment
Fetch related sequences and run alignment Clustal, Dialign, TCoffee, Muscle …
Fetch a multiple alignment from a database and add sequences of interest Pfam, ProDom, ADDA …
Start from a motif-finding procedure MEME, Pratt, Gibbs Sampler …
Adjusting the alignment
1. Filter alignment: Remove any redundancy Remove unrelated sequences Remove unwanted domains Recalculate alignment if necessary
2. Look for conserved motifs, adjust any misalignments. Try different colour schemes and thresholds.
3. One step at a time…
Jalview Alignment Editor
Clamp, M., Cuff, J., Searle, S. M. and Barton, G. J. (2004), "The Jalview Java Alignment Editor", Bioinformatics, 20, 426-7.
Colouring your alignment
HYDROPHOBIC/ POLAR hydrophobic polar
BURIED INDEX buried surface
β-STRAND LIKELIHOOD probable unlikely
HELIX LIKELIHOOD probable unlikely
Colouring your alignment
By conservation thresholds:
Colouring your alignment
Conservation index
Amino Acid Property Classification Schema, eg: Livingstone & Barton 1993
Sequence Features
Check PDB Structures
Load MA with sequence(s) for known PDB structure View >> Feature Settings >> Fetch DAS Features (wait...)
OR Right-click >> Associate Structure with Sequence >> Discover
PDB ids (quicker)
Right-click sequence name >> View PDB Entry
Structure opens in new window – residues acquire MA colours
Highlight residues by hovering mouse over alignment or structure
Label residues by clicking on structure
Compare Alignment to Structure
Compare Alignment to Structure
Crucial way of checking alignment!
Where are gaps / insertions /deletions ? In secondary structures: bad In surface loops: okay
Where are our key / functional residues? Are they in probable active site? Check they are clustered Check they are accessible, not buried
Demonstration and Practice
1. Start Jalview (click here)2. Tools >> Preferences >>
Visualselect Maximise Window, unselect Quality, set Font Size to 8 or 9, Colour >> Clustal, uncheck Open File
Editingcheck Pad Gaps When Editing
3. File >> Input Alignment >> from URL (use this one)4. Get used to the controls – selecting and deselecting
sequences/groups (drag mouse), dragging sequences/groups (use shift/ctrl), selecting sequence regions, hiding sequences/groups, removing columns and regions… Then explore menus and tools.
5. Now load this alignment – I’ve messed up a good alignment, and now I’d like you to correct it! There are two groups of sequences and one single sequence to adjust.
Demonstration and Practice
6. View >> Feature Settings >> DAS Settings select Uniprot, dssp, cath, Pfam, PDBsum_ligands, PDBsum_DNAbinding,
then click ‘Save as default’ click Fetch DAS Features (then click yes at prompt) ... Move mouse over alignment and read information about features Move mouse over sequence names to check for PDB ids
7. Open a PDB structure (choose any)
8. View >> uncheck Show All Chains, then use up-arrow key to increase structure size.
9. Hover mouse over structure (see how residues are highlighted in the sequence), then do same for sequence. Select residues in the structure by clicking them – a label will appear. Click again to remove label.
10. Check position of insertions & deletions using this method.