Bioinformatics and Functional Genomics Student ID: 21485094

Lecturer: Dr. Obed Brew Beatriz Manso

PROTEIN STRUCTURE ANALYSIS AND MODELL ING

An important aspect of systems biology is the modelling of proteins. Such modeling can be used to

identify the genes and proteins that interact to generate a transformation, examine the instructions

or algorithms that modify the transformation or cause a cell to function in a particular way.

Modeling of proteins is part of an evolutionary cycle in which experimental biology also plays a key

role: a typical protein modelling cycle begins with the development of a model that represents the

biology of the thing that is being modelled, then the model is tested to see if it behaves the same

way as the biological protein. Alternatively, you could tweak the model until it closely resembles the

biological protein and repeat this cycle until your model accurately reflects reality.

Identify possible orthologs and or paralogs, and compare their 3D structure(s)

with that of the new protein.. Perform multiple sequence alignment,

phylogeny, and predict the protein’s structure and its function.

Part 1: Prediction of Primary Protein Structure

1. Predict the primary protein structure of the gene sequence in

“Practical08_UnnamedSequence” by uploading the FASTA sequence into the online program

AUGUSTUS (http://bioinf.uni-greifswald.de/augustus/submission.php).

2. Set the parameters in AUGUSTUS as follows:

a. Organism: ‘Homo sapiens’

b. Report genes on: both strands

c. Alternative transcripts: few.

3. Run AUGUSTUS and Click the link ‘graphical and text results’

4. View protein sequence by clicking “predicted amino acid sequences”

5. Save the predicted protein sequence as a FASTA file by copying the sequence into notepad.

In the file tab, select ‘save as’, save as type ‘all files’ and save the protein as a file with the

extension ‘.fa’ or ‘.fasta’.

6. Identify what protein FASTA file was predicted from the gene sequence by uploading the

protein FASTA file into BLASTp and assessing the matches.

>UnamedSequence

NNNGAAAAAAAANAACCTAGANAGTGGGNTGTTCANGGGGGGGGGGAGGAATCTTTGNTNCGCCAGGCCTCTTNGGCTTCAAAAGGAAGCTGCCTAA

GTACCTGCTCTTTACCAGCCCCCAGGAGAACCCCTGGGGCCACAAGCGCAGCTACCGCCTGCAGATCCACTCCATGGCCGACCAGGTGCTGCCCCCAGGC

TGGCAGGAGGAGCAGGCCATCACCTGGGCAAGGTACCCCCTGGCAGTGACCAAGTACCGGGAGTCGGAGCTGTGCAGCAGCAGCATCTACCACCAGAA

CGACCCCTGGCACCCGCCCGTGGTCTTCGAGCAGTTTCTTCACAACAACGAGAACATTGAAAATGAGGACCCGGTGGCCTGGGTGACGGTGGGCTTCCTG

CACATNCCCCACTCAGAGGACATTCCCAACACAGCCACACCTGGGAACTCCGTGGGCTTCCTGCTCCGGCCATTCAACTTCTTCCAGAGGACCCCTCCCTG

GCATCCAGAGACACTGGGGATCGTGTGGCCTCGGGACAACGGNCCCAACTACCGTTCCACGCTGGGATCCCTGANCAATCGAATCCCCGCGCCGCCATG

GCGNNCGGGANCATGCCAACTTCNNTCCAATTCCCTATAGCGAATCTNTNNTACAATTACTGCCCTCCGTTTACAACCNATCGAATNGGAAAACCTTTGG

CGTTCCCAACTTAATCGCCTTTNCANNCCAATCCCCTTCGCGTTNGCTGCAAAACAAAAAGCCCNANCCGATCCCTTCCNAAAANTTCCAACCTATGGCAT

GGACCCCCCTGATCGCGATAACCTNCGCTCTNCGTGNTACCCTCCAACNGACNTTNAATTNCANNNCTTAACNCCCNTCTNCG

Bioinformatics and Functional Genomics Student ID: 21485094

Lecturer: Dr. Obed Brew Beatriz Manso

BLAST results:

What is the name of the protein?

Amiloride binding protein 1 (amine oxidase (copper-containing))

Part 2: Acquire Orthologs of the Identified Protein Align Protein

Sequences

1. Enter the name of the protein identified in part 1 into the search bar in UniProt

(https://www.uniprot.org).

1. Select the human, pig, rat, and mouse entries, download the results, uncompressed in

format FASTA (canonical).

2. The sequences should open in a new tab, right click, select save as, and save the sequences

with the file extension ‘.fa’.

Bioinformatics and Functional Genomics Student ID: 21485094

Lecturer: Dr. Obed Brew Beatriz Manso

Part 3: Align Protein Sequences using MUSCLE

1. Insert the protein sequences into the query box in the EBI Multiple Sequence Alignment

MUSCLE Alignment tool (https://www.ebi.ac.uk/Tools/msa/muscle/).

2. Run the job and save the completed alignment as a FASTA file with the extension ‘.fa’.

Part 4: Determine the regions of conservation in the protein across

species

1. Import the MUSCLE aligned protein sequences imported into PFAAT from the ‘File’ tab, by

selecting ‘Open’, followed by ‘Alignment’.

2. Select the ‘Analysis’ tab, followed by ‘Conservation Scores’ and ‘Autocalculate Consensus’

and then ‘Information Score’ which resulted in a dialog box opening for selection of the

conservation score options.

3. The conserved regions of the protein sequence is by default determined using the von

Neuman Entropy (VNE) in PFAAT

4. To save the results of the conservation analysis, change the name of the outfile to a file

name with the extension ‘.tab’.

5. Import the tab-delimited output file which contained the conversation scores for each

alignment position into Excel using the text import wizard.

a. Open Excel

b. Select the output file to open in Excel

c. In the dialog box for the text import wizard, indicate the data has headers and the

text is delimited. Then go to next.

d. Indicate that the delimiter is ‘tab’. Go to next.

e. Change the format of the ‘Alignment’ column from ‘General’ to ‘text’. Then finish.

In the alignment score we can see that there are some positions that are highly conserved, which is

when VNE is ⩾ 0.85 (conservation score: Von Newman Entropy; Matrix:Blossum62)

Bioinformatics and Functional Genomics Student ID: 21485094

Lecturer: Dr. Obed Brew Beatriz Manso

Save conservation scores:

Part 5: Protein Secondary Structure Analysis

We’ll use the program Jalview (http://www.jalview.org/getdown/release/) .

1. Upload the protein FASTA alignment file used to determine the sequence conservation into

Jalview by clicking the ‘File’ tab, followed by ‘Input Alignment’, ‘From File’.

2. In the new alignment window, click ‘Web Service’, ‘Secondary Structure Prediction’,

followed by ‘JPred Secondary Structure Prediction’.

3. The results of the secondary structure prediction is shown in a new alignment window.

a. The consensus secondary structure predication can be observed in the ‘jnetpred’

row.

b. The secondary structure feature is reported as either helical ‘red tubes’ or strands

‘green arrows’. Higher values in the ‘JNETCONF’ row mean confidence in the

accuracy of the prediction.

c. Lupas rows annotate prediction of coiled-coils ‘c’, Jnet Burial row annotates a

prediction of Solvent Accessibility.

4. Results can optionally be exported by clicking ‘File’, ‘Export Annotations’ in format ‘Jalview’,

‘to File’ and saving a file.

Jalview Results:

Bioinformatics and Functional Genomics Student ID: 21485094

Lecturer: Dr. Obed Brew Beatriz Manso