Multiple AlignmentsMotifs/Profiles

• What is multiple alignment?• HOW does one do this?• WHY does one do this?• What do we mean by a motif or

profile?

BIO520 Bioinformatics Jim Lund

Prev. reading: Ch 1-5Assigned reading: Ch 6.4, 6.5, 6.6

Information from Alignments

• Infer biological function– Conserved elements critical for function– Divergent elements relate to divergent

function

• Infer structure (2°, 3°)• Infer phylogeny

– History– Evolutionary forces (selection…)

How do I find similar sequences?

Multiple Alignment

•Global, Optimal

•Theory

•Computation

•Progressive Alignment

Multiple Alignment: better alignments

Alignment Methods/Programs

• GAP (GCG suite)– Optimal Alignment

• MSA– (nearly) Optimal Alignment

• Clustal W/X – Progressive Alignment

• PSI-BLAST– Searches for matching sequences iteratively– Search seq is invariant master for the

alignment.

MSA Strategy

c(A)=c(Ai,j)Minimize score!

• HUGE matrix(aa# of seqs) CRASH computer– time~product of sequence length– 1000x10,000 OK, but 200x200x200x200 NOT

• Alignment procedure– nearly optimal--only considers a subset of all

alignment)– weight sequences via distance– branch-and-bound algorithm

Running MSA

• Download and run it locally (UNIX):– http://www.ncbi.nlm.nih.gov/CBBresearch/S

chaffer/genetic_analysis.html

• On the internet:– http://searchlauncher.bcm.tmc.edu/multi-

align/multi-align.html

• Rerun on segments AFTER Clustal...

Clustal Strategy

1. Rapid pairwise alignments each-to-each

2. Calculate distance matrix– Create guide tree (neighbor joining)

3. Align– Closest pairs first

– Add pairs or align sub-alignments

– Adjust similarity matrix as alignment proceeds

4. Add sequences– introduce gaps

• gaps at loops, not inside known 2° structures

• Dynamic gap weighting

Clustal Strategy

Pairwise alignments Guide tree Align

Clustal W(X) Strategy1. Pairwise alignments

The pairwise alignment number here is a dissimilarity measure.

Clustal W(X) Strategy2. Unrooted neighbor tree

(dendrogram)

Clustal W(X) Strategy3. Guide tree

Clustal W(X) Strategy4. Progressive alignment

using guide tree

Running Clustal W/X• WWW, Win, Mac, UNIX

– http://www2.ebi.ac.uk/clustalw/

• Input– Multiple sequence file (PIR, FASTA,…)

• Can FORCE alignments

• Specify secondary structures

• Considerations– Fast, easy, widely used

– Divergent proteins OK (trees misleading)

“The Right Proteins”GAPDH

Rabbit KAENGKLVING-KAITIFQERDPANIKWGDAGAEYVVESTGVFTTMEKAGAHLKGGAKRV 117

Chick KAENGKLVING-HAITIFQERDPSNIKWADAGAEYVVESTGVFTTMEKAGAHLKGGAKRV 117

*********** :**********.:***.*******************************

“The Right Proteins”GAPDH

Rabbit KAENGKLVING-KAITIFQERDPANIKWGDAGAEYVVESTGVFTTMEKAGAHLKGGAKRV 117

Chick KAENGKLVING-HAITIFQERDPSNIKWADAGAEYVVESTGVFTTMEKAGAHLKGGAKRV 117

Human KAEDGKLVIDG-KAITIFQERDPENIKWGDAGTAYVVESTGVFTTMEKAGAHLKGGAKRI 118

Tobacco KVKDEKTLLFGEKSVRVFGIRNPEEIPWAEAGADFVVESTGVFTDKDKAAAHLKGGAKKV 110

Entamoeba EAGENAIIVNGHKIV-VKAERDPAQIGWGALGVDYVVESTGVFTTIPKAEAHIKGGAKKV 105

:. : :: * : : :*:* :* *. *. :********* ** **:*****::

Alignment Interpretation

• DNA sequences– >50% “worth looking at” (eyeball test)– ~75% needed for phylogeny

• Polypeptide sequences– 80% similar=SAME tertiary structure– 30-80% domains=similar structure– 15-30% ????– <15% short motifs

Uses of Alignment

• Understanding or predicting mutant function

• Finding motifs in DNA or polypeptides

• Directing experiments--e.g. PCR primers

• Phylogeny

“The Right Proteins”

Rabbit KAENGKLVING-KAITIFQERDPANIKWGDAGAEYVVESTGVFTTMEKAGAHLKGGAKRV 117

Chick KAENGKLVING-HAITIFQERDPSNIKWADAGAEYVVESTGVFTTMEKAGAHLKGGAKRV 117

Human KAEDGKLVIDG-KAITIFQERDPENIKWGDAGTAYVVESTGVFTTMEKAGAHLKGGAKRI 118

Tobacco KVKDEKTLLFGEKSVRVFGIRNPEEIPWAEAGADFVVESTGVFTDKDKAAAHLKGGAKKV 110

Entamoeba EAGENAIIVNGHKIV-VKAERDPAQIGWGALGVDYVVESTGVFTTIPKAEAHIKGGAKKV 105

:. : :: * : : :*:* :* *. *. :********* ** **:*****::

Viewing and interpreting alignments

•Color residues by property•Conservation in the alignment•Known properties

•Substitution groups: STA, HY•Physiochemical property

•charge•hydrophobicity

•Programs for visualization•Jalview•AMAS•Alscript

Viewing alignments

JalView alignment viewer

How to build multiple alignments

1. Find sequences to align (db search).

2. Choose which regions of each protein to include.

• Sequences should be of similar lengths.

3. Run multiple alignment program.

4. Inspect multiple alignment for problems.• Regions with many gaps have aligned poorly.

5. Remove disruptive sequences and re-run alignment.

6. Add back remaining sequences avoiding disruption.

Interpro

• Pfam 7.3 (3865 domains), • PRINTS 33.0 (1650 fingerprints), • PROSITE 17.5 (1565 and 252

preliminary profiles), • ProDom 2001.3 (1346 domains), • SMART 3.1 (509 domains), • TIGRFAMs 1.2 (814 domains), • SWISS-PROT 40.27 (113470 entries), • TrEMBL 21.12 (685610 entries).

InterproA database of protein families, domains

and functional sites

• PROSITE, home of regular expressions and profiles;

• Pfam, SMART, TIGRFAMs, PIRSF, and SUPERFAMILY keepers of hidden Markov models(HMMs);

• PRINTS, provider of fingerprints (groups of aligned, un-weighted motifs);

Interpro

NCBI CDD (Conserved Domain Database

Domains from:• Pfam (Protein families)

– A database of protein families that currently contains > 7973 entries.

• SMART (a Simple Modular Architecture Research Tool)– More than 500 domain families found in signalling,

extracellular and chromatin-associated proteins are detectable.

– Domains are extensively annotated with respect to phyletic distributions, functional class, tertiary structures and functionally important residues.

• COGs (Clusters of Orthologous Groups)– Proteins or groups of paralogs from at least 3 lineages that

correspond to an ancient conserved domain