Protein Sequence Alignment

Primary Structure Analysis

Part 1

DNA takes us only so far

• DNA sequencing relatively fast & cheap; but to get meaningful information from sequence, need:

– to be able to distinguish genes from junk (a topic we’ll explore in some depth later on)

– to be able to identify regulatory sequences

– to be able to determine the function of a gene’s protein product – this will be our focus

Primary structure databases: nucleotides vs. proteins

• For nucleotide sequences, GenBank is primary repository for data

– source scientists have full authority over data

– strict historical/archival point of view

– companion database, RefSeq, is reviewed/corrected/annotated version of GenBank

• For protein sequences, there’s SwissProt(UniProt): an entirely different approach to database curation

The SwissProt Way

• SwissProt is not a primary repository like GenBank; instead, it is curated, primarily by a single person (Swiss scientist Amos Bairoch)– entries changed when new information available; flexible,

correctable– considered best-annotated protein database– lot of work for one person, or even team of experts

• URL: http://www.expasy.ch/sprot/

TrEMBL

• TrEMBL is SwissProt’s buffer database, similar in function (if not mechanics) to GenBank: GenBank is to RefSeq as TrEMBL is to SwissProt– consists of entries automatically derived from

translation of DNA ORFs; data goes here before it goes to SwissProt

– most of the protein sequences in both databases have never been isolated in nature; they are all derived from translated data

Searching SwissProt

• Like GenBank, provides variety of access points

• Starting point can be name of protein, or gene, or condition of interest

• Can limit search by specific field (organism, protein name, e.g.)

Example: HER-2 positive breast cancer

• We can start with a very general search:

• This produces almost 3000 hits; we can narrow this to our species:

Example continued

• But this only cuts out about 1000 entries

• Since we know (or think we know) the name of the protein, we can try adding another qualifier:

Example continued

• This results in one relevant entry:

A closer look

Proteomics

• Science of visualization & quantification of set of proteins present in given tissue or organism

• Points of reference:– gel electrophoresis: separation of protein molecules

by mass & charge

– ORF translation: derive AA chain from nucleotide chain

• These often don’t match: more to protein structure (even primary structure) than simple translation tells us

Post-translational modification

• Protein maturation process: modification(s) of primary structure that lead to ultimate tertiary/quaternary structure found in nature

• Includes some combination of:– cuts within AA chain– removal of AA fragments within chain– chemical modifications of single AAs– addition of lipid or sugar molecules

• Storage & retrieval of post-translational modification information is major role of protein databases

Location, location, location

• Protein function related to its location– translation process involves

exposing developing peptide chain to various chemical signals that specify location of mature protein

– translocation: transport of protein across one or more membranes

Final destinations include:

• attachment to cell membrane

• secretion outside cell

• transportation to mitochondria or other organelle

• transportation to nucleus

Folding

• Most important step in making mature protein– compacts peptide chain into stable 3D structure

– final structure usually consists of several relatively independent domains;thousand of known domains• most proteins contain up to 10

• identifiable by scaffolded sequence signatures, or motifs, recognizably preserved over millions of years of evolution

• domain architecture important because hints at 3D structure

Proteins vs. genes

• Protein primary structures relatively simple compared to genes

– AA sequences fairly short (average protein is 350 AAs)

– have clear start & end

– defined on single strand

– although modifications can & do occur between ORF & mature protein, AA order remains stable

Using bioinformatics to determine protein function

• CFTR protein serves as illustrative model:– Specific genetic defects can be identified in

specific CF patients

– Such genetic defects can be shown to lead to functional defects in CFTR

– Next step: develop specific drugs to target specific defects (still in experimental stage)

• Problem: given DNA sequence of gene, how do we find cellular function of protein product?

Model organisms

• Several organisms are known to have easily identifiable & mutable genes:

• These organisms can serve as model organisms for investigation of gene behavior in humans where human genes have recognizable counterparts in the model

Structural clues to protein function

• Proteins with similar primary structure (amino acid sequence) will likely have similar function

• Similarity doesn’t have to extend to entire protein; can be more localized, e.g. regions of unknown protein sequence may resemble functional regions of known protein

Aligning protein sequences

• Can be more effective for discovery than nucleotide sequence alignment

• Sequence similarity often provides clues in function of unknown protein

Alignment scoring & evolution

• Mutation is random process, but biological factors affect which mutations we actually see

• We are most likely to observe the substitution of an amino acid with one that is chemically similar, because drastic change that disrupts protein function is likely to be selected against

• Protein substitution matrix allows alignment algorithms to consider substitution likelihood to give better alignments

Protein similarity

• Proteins much more complex than DNA; this works in our favor in terms of making effective comparisons

• Amino acid similarity examples:– Aspartate and Glutamate have hydrophilic side

chains

– Leucine and Valine have hydrophobic side chains

– A hydrophobic – hydrophilic substitution is more likely to alter protein function than phobic-phobic

Protein similarity

• Can score not only exact matches but also conservative substitutions (mutations that result in functionally similar amino acids)

• Such substitutions are more likely because they wouldn’t be selected against in evolution

• Given all of the above, we can be confident of less ambiguity in protein alignment than in nucleotide alignment

Determining likelihood of substitution

• Method 1: Look at chemical properties of amino acids:– hydrophobic vs. hydrophilic

– charge

– size of side chains

• Method 2: look at frequency of actual substitution occurrence in known sequences based on comparison of similar proteins – this is basis for substitution matrix

• We will examine both methods

Method 1: Biochemical analysis of proteins

• The Swiss Institute of Bioinformatics maintains ExPASy, a set of online tools for protein structure & function analysis

• ExPASy stands for Expert Protein Analysis System

• Two of the tools at ExPASy are ProtParam and ProtScale

ProtParam

• Provides computation of physical & chemical properties of proteins from either user-entered raw sequence or from known entries in SwissProt/Trembl databases

• Analysis includes:– number of amino acids in sequence– molecular weight– amino acid composition (% of total)– extinction coefficient (used for spectrophotometic

analysis)– half-life: amount of time it takes for half of protein to

degrade after synthesis– instability index

Primary structure analysis

• Why analyze primary structure?– Need to take into account amino acid interactions

to get clearer picture of secondary, tertiary structural factors

– Segments with particular compositional types give clues to eventual conformation:• hydrophobic: potential transmembrane or core feature

• coiled-coil: potential protein-protein interaction site

• hydrophilic: potential surface structure

Primary structural analysis

• Sliding window technique– Oldest sequence analysis method– Uses tables of amino acid properties: scale values

• Method– Pick window size based on desired feature:

• for transmembrane feature: 19• for globular feature: 7-11

– With window centered on one amino acid, scale values associated with all amino acids in window are summed & averaged, then result is associated with central AA

– Shift window & continue until end of sequence– When finished, values associated with each AA are plotted

against sequence: property profile

ProtScale

• An example of an online tool for performing sliding-window technique on a protein is ProtScale, also found in the ExPASy suite

• The direct link to this resource is:http://www.expasy.org/cgi-bin/protscale.plNote the extension – this is a perl program

Using ProtScale

• Paste in FASTA sequence or type in accession number

• Choose scale/window size

• Click submit

Interpreting results

• Consider only strong signals• Check signal robustness by repeating comparison

using different scale

Sliding-window method: pros & cons

• Advantage: relatively robust (not sensitive to scale changes)

• Disadvantages:

– not precise

– window size is arbitrary

• Could go either way: does not interpret results for you

Testing for transmembrane segments in proteins

• What transmembrane segments indicate:

– One transmembrane segment at N-terminus of sequence suggests protein is secreted

– Several transmembrane segments suggests a channel

• Can perform analysis with ProtParam, but more precise tool is TMHMM, which uses hidden Markov models (a sophisticated computational technique) to predict transmembrane regions

TMHMM

Link: http://www.cbs.dtu.dk/services/TMHMM-2.0/

TMHMM results

• Predictions are precise

• Predicts segments inside/outside cell

Looking for coiled-coil segments

• Coiled-coils are regions formed by intertwining alpha-helices

• May indicate protein-protein interaction site

• May also lead to false results in database searches, so it’s good to know location in case you need to filter out

• Online tool available at:http://www.ch.embnet.org/software/COILS_form.html