Protein Sequence Alignment. Primary Structure Analysis Part 1

Transcription

1 Protein Sequence Alignment Primary Structure Analysis Part 1

2 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

3 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

4 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:

5 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

6 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.)

7 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:

8 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:

9 Example continued This results in one relevant entry:

10 A closer look

11 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

12 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

13 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

14 Final destinations include: attachment to cell membrane secretion outside cell transportation to mitochondria or other organelle transportation to nucleus

15 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

16 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

17 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?

18 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

19 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

20 Aligning protein sequences Can be more effective for discovery than nucleotide sequence alignment Sequence similarity often provides clues in function of unknown protein

21 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

22 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

23 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

24 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

25 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

26 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

27 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

28 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

29 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: Note the extension this is a perl program

30 Using ProtScale Paste in FASTA sequence or type in accession number Choose scale/window size Click submit

31 Interpreting results Consider only strong signals Check signal robustness by repeating comparison using different scale

32 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

33 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

34 TMHMM Link:

35 TMHMM results Predictions are precise Predicts segments inside/outside cell

36 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: