RPR-SX-PDB
Analyzing PDB files
(Practical work with the PDB, the R bio3d package)
Abstract:
PDB structures are complex objects to which we can apply a number of measures - but doing so requires that we can read and analyze them in the computer. In this unit we explore computational analysis of PDB structures using bio3D::.
Objectives:
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Outcomes:
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Deliverables:
Prerequisites:
This unit builds on material covered in the following prerequisite units:
Contents
Evaluation
This learning unit can be evaluated for a maximum of 5 marks ...
- Create a new page on the student Wiki as a subpage of your User Page.
- Put all of your writing to submit on this one page.
- When you are done with everything, go to the Quercus Assignments page and open the first Learning Unit that you have not submitted yet. Paste the URL of your Wiki page into the form, and click on Submit Assignment.
Your link can be submitted only once and not edited. But you may change your Wiki page at any time. However only the last version before the due date will be marked. All later edits will be silently ignored.
- Short Report option
- 1. Create a new page on the student Wiki as a subpage of your User Page.
- 2. Select a unique set of fifteen representative PDB structures by issuing the command:
( myPDBs <- selectPDBrep(15) )
- 3. Analyze the distribution of H-bonds in helices and strands of your fifteen structures. Interpret your findings: what is the source of the difference, what seems to be the lowest energy distance between N...O in a Hydrogen bond, how does this appear in our data and why is this so? (Think! This question is a bit subtle, but can be answered by just thinking about it.)
- 4. Count the number of cis-peptide bonds in your structures. Do this separately for prolines, and for all other residues. Do you find that X-Pro cis-peptide bonds are more frequent than others? Why is that? (Think! Are you identifying the correct bonds? How do you know? How did you test?)
- 5. Plot chi1 torsion angles of amino acid sidechains againt chi2 torsion angles to analyze sidechain rotamer distributions. Aim for a publication quality plot and include the plot and its caption in your report. Randomly choose one amino acid for analysis by issuing the following command:
selectChi2()
- ... and paste the entire line of the output into your submission.
- When you have produced your plot, interpret the results.
- 6. Form matters. Be neat, and concise! Be sure to include the list of the PDB IDs you selected in your report! Make sure your process is documented, your results are presented, and that everything is interpreted. At the end of your report, include a section that contains all of the R script(s) you have written for your analysis. Make sure that your scripts are clean, error-free and commented. Also make absolutely sure that you have referenced all contributions that are not originally your own.
- 7. When you are done with everything, submit the page via Quercus as described above.
Contents
Task:
- Open RStudio and load the
ABC-units
R project. If you have loaded it before, choose File → Recent projects → ABC-Units. If you have not loaded it before, follow the instructions in the RPR-Introduction unit. - Choose Tools → Version Control → Pull Branches to fetch the most recent version of the project from its GitHub repository with all changes and bug fixes included.
- Type
init()
if requested. - Open the file
RPR-SX-PDB.R
and follow the instructions.
Note: take care that you understand all of the code in the script. Evaluation in this course is cumulative and you may be asked to explain any part of code.
About ...
Author:
- Boris Steipe <boris.steipe@utoronto.ca>
Created:
- 2017-08-05
Modified:
- 2020-09-22
Version:
- 1.2
Version history:
- 1.2 Edit policy update
- 1.1 Maintenance
- 1.0 First live version
- 0.1 First stub
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