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<table width="40%"><tr><td class="l1">&nbsp;</td><td>
  
__TOC__
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===Hardware===
&nbsp;
+
<table width="100%">
&nbsp;
+
<tr class="s1"><td class="l1">High performance computing <!-- (... at the bench: GPUs, FPGAs, Clusters) --></td></tr>
 +
<tr class="s2"><td class="l1">Cloud computing</td></tr>
 +
<tr><td class="sp">&nbsp;</td></tr>
 +
</table>
  
<div style="padding: 5px; background: #A6AFD0;  border:solid 1px #AAAAAA; font-size:200%;font-weight:bold;">
+
===Systems and Tools===
Assignment 4 - Homology modeling
+
<table width="100%">
</div>
 
 
 
<div style="padding: 15px; background: #F0F1F7;  border:solid 1px #AAAAAA; font-size:125%;color:#444444">
 
;How could the search for ultimate truth have revealed so hideous and visceral-looking an object?
 
::''<small>Max Perutz (on his first glimpse of the Hemoglobin structure)</small>''
 
</div>
 
&nbsp;
 
&nbsp;
 
 
 
Where is the hidden beauty in structure, and where, the "ultimate truth"? In the previous assignments we have studied sequence conservation in APSES family domains and we have seen homologues in all fungal species. This is an ancient protein family that had already duplicated to several paralogues at the time the cenancestor of all fungi lived, more than 600,000,000 years ago, in the [http://www.ucmp.berkeley.edu/fungi/fungifr.html Vendian period] of the Proterozoic era of Precambrian times.
 
 
 
In order to understand how specific residues in the sequence contribute to the putative function of the protein, and why and how they are conserved throughout evolution, we would need to study an explicit molecular model of an APSES domain protein, bound to its cognate DNA sequence. Explanations of a protein's observed properties and functions can't rely on the general fact that it binds DNA, we need to consider details in terms of specific residues and their spatial arrangement. In particular, it would be interesting to correlate the conservation patterns of key residues with their potential to make specific DNA binding interactions. Unfortunately, no APSES domain structures in complex with bound DNA has been solved up to now, and the experimental evidence we have considered in Assignment 2 ([http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=10747782 Taylor ''et al.'', 2000]) is not sufficient to unambiguously define the details of how a DNA double helix might be bound. Moreover, at least two distinct modes of DNA binding are known for proteins of the winged-helix superfamily, of which the APSES domain is a member.
 
 
 
''In this assignment you will (1) construct a molecular model of the Mbp1 orthologue in your assigned organism, (2) identify similar structures of distantly related domains for which protein-DNA complexes are known, (3) define whether the available evidence allows you to distinguish between different modes of ligand binding, and (4) assemble a hypothetical complex structure.''
 
 
 
For the following, please remember the following terminology:
 
 
 
;Target
 
:The protein that you are planning to model.
 
;Template
 
:The protein whose structure you are using as a guide to build the model.
 
;Model
 
:The structure that results from the modeling process. It has the '''Target sequence''' and is similar to the '''Template structure'''.
 
&nbsp;
 
 
 
A brief overview article on the construction and use of homology models is linked to the resource section at the bottom of this page. That section also contains links to other sites and resources you might require.
 
 
 
{{Template:Preparation|
 
care=Be sure you have understood all parts of the assignment and cover all questions in your answers! Sadly, we see too many assignments which, arduously effected, nevertheless intimate nescience of elementary tenets of molecular biology. If the sentence above did not trigger an urge to open a dictionary, you are trying to guess, rather than confirm possibly important information.|
 
num=4|
 
ord=fourth|
 
due = Monday, November 12 at 10:00 in the morning}}
 
 
 
 
 
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
 
==(1) Preparation==
 
</div>
 
 
 
 
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
===Template choice and sequence (1 marks)===
 
</div>
 
&nbsp;<br>
 
Often more than one related structure can be found in the PDB. We have touched on principles of selecting template structures in the lecture and there is a short summary of [[Template_choice_principles|template choice principles]] on this Wiki. One can either search the PDB itself through its '''Advanced Search''' interface; for example one can search for sequence similarity with a BLAST search, or search for structural similarity by accessing structures according to their CATH or SCOP classification. But one can always also use the BLAST interface at the NCBI, since the sequences contained in PDB files are accessible as a database subsection on the BLAST menu.
 
 
 
<div style="padding: 5px; background: #DDDDEE;">
 
*Use the NCBI BLAST interface to identify all PDB files that are clearly homologous to your target APSES domain, if you haven't already done so in Assignment 2. Document that you have searched in the correct subsection of the database by selecting "pdb" on the database choice menu. For the hits you find, consider how these coordinate sets differ and which features would make each more or less suitable for your task by commenting briefly on
 
:*sequence similarity to your target
 
:*size of expected model (length of alignment)
 
:*presence or absence of ligands
 
:*experimental method and quality of the data set
 
Then choose the '''template''' you consider the most suitable and note why you have decided to use this template.
 
 
 
* Retrieve the most suitable template structure coordinate file from the PDB.
 
</div>
 
 
 
It is not straightforward at all how to number sequence in such a project. The "natural" numbering is to start a sequential numbering from the start-codon of the full length protein and go sequentially from there. However, this does not map well with other numbering schemes we have encountered. As you know the first residue of the APSES domain as the CDD defines it is not Residue 1 of the Mbp1 protein. The first residue of the e.g. 1MB1 FASTA file '''is''' the first residue of Mbp1 protein, but the last five residues are an artifical His tag. Is H125 of 1MB1 thus equivalent to R125 in MBP1_SACCE? The N-terminus of the Mbp1 crystal structure is disordered. The first residue in the structure is ASN 3, therefore N is the first residue in a FASTA sequence derived from the cordinate section of the PDB file (the <code>ATOM  </code> records; whereas the SEQRES records start with MET ... and so on. You need to remember: a sequence number is not absolute, but derived from a particular context.
 
 
 
The homology model will be based on an alignment of target and template. Thus we have to define the target sequence. As discussed in class, PDB files have an explicit  and an implied sequence and these do not necessarily have to be the same. To compare the implied and the explicit sequence for the template, you need to extract sequence information from coordinates. One way to do this is via the Web interface for [http://swift.cmbi.ru.nl/servers/html/index.html '''WhatIf'''], a crystallography and molecular modeling package that offers many useful tools for coordinate manipulation tasks.
 
 
 
<div style="padding: 5px; background: #DDDDEE;">
 
*Navigate to the '''Administration''' sub-menu of the [http://swift.cmbi.ru.nl/servers/html/index.html WhatIf Web server]. Follow the link to '''Make sequence file from PDB file'''. Enter the PDB-ID of your template into the form filed and '''Send''' the request to the server. The server accesses the PDB file and extracts sequence information directly from the <code>ATOM&nbsp;&nbsp;</code> records of the file. The results will be returned in PIR format. Copy the results, edit them to FASTA format and save them in a text-only file. Make sure you create a valid FASTA formatted file! Use this '''implied''' sequence to check if and how it differs from the sequence ...
 
 
 
:*... listed in the <code>SEQRES</code> records of the coordinate file;
 
:*... given in the FASTA sequence for the template, which is provided by the PDB;
 
:*... stored in the protein database of the NCBI.
 
: and record your results.
 
 
 
* In a table, establish how the sequence numbers in the coordinate section of your template(*) correspond to your target sequence numbering.
 
</div>
 
 
 
:(*) <small>These residue numbers are important, since they are referenced e.g. by VMD when you visualize the structure. The easiest way to list them is via the ''Sequence Viewer'' extension of VMD.</small>.
 
:<small>Don't do this for every residue individually but define ranges. Look at the correspondence of the first and last residue of target and template sequence and take indels into account. Establishing sequence correspondence precisely is crucially important! For example, when a publication refers to a residue by its sequence number, you have to be able to relate that number to the residue numbers of the model as well as your target sequence.</small>.
 
&nbsp;
 
&nbsp;
 
 
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
=== The input alignment  (1 mark)===
 
</div>
 
&nbsp;<br>
 
 
 
The sequence alignment between target and template is the single most important factor that determines the quality of your model.
 
 
 
No comparative modeling process will repair an incorrect alignment; it is useful to consider a homology model rather like a three-dimensional map of a sequence alignment rather than a structure in its own right. In a homology modeling project, typically the largest amount of time should be spent on preparing the best possible alignment. Even though automated servers like the SwissModel server will align sequences and select template structures for you, it would be unwise to use these only because they are convenient. You should take advantage of the much more sophisticated alignment methods available. Analysis of wrong models can't be expected to produce right results.
 
 
 
The best possible alignment is usually constructed from a multiple sequence alignment that includes at least '''the target and template sequence''' and other related sequences as well. The additional sequences are an important aid in identifying the correct placement of insertions and deletions. Your alignment should have been carefully reviewed by you and wherever required, manually adjusted to move insertions or deletions between target and template out of the secondary structure elements of the template structure.
 
 
 
In the case of Mbp1 genes however, all orthologues we have considered have no indels in the APSES domain regions. Evolutionary pressure on the APSES domains has selected against indels in the more than 600 million years these sequences have evolved independently in their respective species.
 
 
 
Accordingly, all we need to do is to write the APSES domain sequences one under the other.
 
 
 
<div style="padding: 5px; background: #DDDDEE;">
 
* Copy the FASTA formatted sequence for the APSES domain of your organism's Mbp1 orthologue from [[All_APSES_domains|file used in Assignment 3]] and save it as a text file. This is your '''target''' sequence. Compare this with the FASTA formatted file you have extracted from the PDB coordinate set. This is your '''template''' sequence. Then generate a multi-FASTA formatted file that contains both sequences, and '''pad''' the shorter sequence with hyphens as gap characters so it has exactly the same length as the template and is aligned.  Refer to the [[Assignment_4_fallback_data|'''Fallback data''']] if you are not sure about the format. (1 mark)
 
</div>
 
&nbsp;<br>
 
&nbsp;
 
 
 
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
 
 
 
==(2) Homology model==
 
</div>
 
&nbsp;
 
&nbsp;
 
 
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
=== (2.1) SwissModel (1 mark)===
 
</div>
 
&nbsp;<br>
 
 
 
Access the Swissmodel server at [http://swissmodel.expasy.org '''http://swissmodel.expasy.org'''] . Navigate to the '''Alignment Interface'''.
 
 
 
&nbsp;<br><div style="padding: 5px; background: #EEEEEE;">
 
*Copy from the alignment above the 1MB1 sequence and the sequence from your organism, and paste it into the form field. Refer to the [[Assignment_5_fallback_data|'''Fallback Data file''']] if you are not sure about the format.
 
:(You have to choose the correct format, and, if e.g. you choose a CLUSTAL format, you have to include a header line and a blank line. Other common problems uploading your alignment may include uploading a file that has not been saved as "text only" and periods i.e.  "."  in sequence names. Underscores appear to be safe.)
 
 
 
* Click '''submit''' and define your '''target''' and '''template''' sequence. For the '''template sequence''' define the coordinate file and chain. (In our case the coordinate file is <code>'''1MB1'''</code> and the chain is "<code>'''A'''</code>". Recently the PDB has revised all coordinate sets and assigned chain "A" to those that did not have a chain designation previously, becuase there was only one chain in the file.
 
 
 
*Click '''submit''' and request the construction of a homology model: Enter your e-mail address and check the button for '''Normal Mode''', not "Swiss-PDB Viewer mode. (Important, since there will be problems with the output otherwise). Click '''submit'''. You should receive four files files by e-mail within half an hour or so. (1 mark)
 
 
 
(You do not need to submit the actual coordinate files with your assignment.)
 
 
 
</div>
 
&nbsp;<br>
 
In case you do not wish to submit the modelling job yourself, or have insurmountable problems using the SwissModel interface, you can access the result files from the  [[Assignment_5_fallback_data|'''Fallback Data file''']]. Note this in your assignment.
 
 
 
 
 
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
 
 
 
==(3) Model analysis==
 
</div>
 
&nbsp;
 
&nbsp;
 
 
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
=== (3.1) The PDB file (1 mark)===
 
</div>
 
&nbsp;<br>
 
 
 
Open your '''model''' coordinates in a text-editor (make sure you view the PDB file in a fixed-width font) and consider the following questions: (Alternatively, view the coordinates linked to the [[Assignment_5_fallback_data|'''Fallback Data file''']].)
 
 
 
&nbsp;<br><div style="padding: 5px; background: #EEEEEE;">
 
*What is the residue number of the first residue in the '''model'''? What should it be, based on the alignment? If the putative DNA binding region was reported to be residues 50-74 in the Mbp1 protein, which residues of the '''model''' correspond to that? (1 mark)
 
</div>
 
 
 
<!-- discuss flagging of loops - setting of B-factor to 99.0 -->
 
 
 
[...]
 
 
 
&nbsp;
 
&nbsp;
 
 
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
===(3.2) first visualization (3 marks)===
 
</div>
 
&nbsp;<br>
 
 
 
In assignment 2 you have already studied the 1MB1 coordinate file and compared it to your organism's Mbp1 APSES domain, Since a homology model inherits its structural details from the '''template''', the model should look very similar to the original structure but contain the sequence of the '''target'''.
 
 
 
&nbsp;<br><div style="padding: 5px; background: #EEEEEE;">
 
*Save the attachment of your '''model''' coordinates to your harddisk and visualize it in RasMol. (Alternatively, copy and save the coordinates from the  [[Assignment_5_fallback_data|'''Fallback Data file''']] to your harddisk.) Make an informative view, divergent stereo and paste it into your assignment. (3 marks)
 
  
 +
<tr class="s1"><td class="l1 mw-collapsible mw-collapsed" data-expandtext="Expand subtopics" data-collapsetext="Collapse">[[Unix]]
 +
<div class="mw-collapsible-content">
 +
<table width="100%"><tr class="s2"><td class="l2">[[Unix system administration]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Unix automation]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Program installation]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[wget]]</td></tr></table>
 
</div>
 
</div>
&nbsp;<br>
+
</td></tr>
 
 
 
 
[[Image:A5_Mbp1_subdomain.jpg|frame|none|Stereo-view of a subdomain within the 1MB1 structure that includes residues 36 to 76. The color gradient ramps from blue (36) to green (76).]]
 
 
 
&nbsp;
 
&nbsp;
 
  
 +
<tr class="s2"><td class="l1">[[Network Configuration]]</td></tr>
 +
<tr class="s1"><td class="l1">[[Apache]]</td></tr>
 +
<tr class="s2"><td class="l1">[[MySQL]]</td></tr>
 +
<tr class="s1"><td class="l1">[[Tools for the bioinformatics lab]]</td></tr>
 +
<tr class="s2"><td class="l1">[[GBrowse|GBrowse and LDAS]]</td></tr>
 +
<tr><td class="sp">&nbsp;</td></tr>
 +
</table>
  
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
+
===Programming===
 +
<table width="100%" >
 +
<tr class="s1"><td class="l1">[[IDE|IDE (Integrated Development Environment)]]</td></tr>
 +
<tr class="s2"><td class="l1">[[Regular Expressions]]</td></tr>
 +
<tr class="s1"><td class="l1">[[Screenscraping]]</td></tr>
  
===(3.3) modeling a DNA ligand (4 marks)===
+
<tr class="s2"><td class="l1 mw-collapsible mw-collapsed" data-expandtext="Expand subtopics" data-collapsetext="Collapse">[[Perl]]
 +
<div class="mw-collapsible-content">
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl basic programming]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Perl hash example]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl LWP example]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Perl MySQL introduction]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl OBO parser]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Perl basic programming]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl programming exercises 1]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Perl programming exercises 2]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl programming Data Structures]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Perl references]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl simulation]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Perl: Object oriented programming]]</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[Perl: Ugly programming]]</td></tr></table>
 
</div>
 
</div>
&nbsp;<br>
+
</td></tr>
 
 
The really interesting question we could begin to address with our model is how sequence variation might be converted into changing DNA recognition sites, and then lead to changed cognate DNA binding sequences. But in order to address this, we would need to add a plausible model for a bound DNA molecule to our model.
 
 
 
Since there is currently no software available that would accurately model such a complex from first principles, we will base this on homology modeling as well. This means we need to find a similar structure for which the complex structure is known. However, you may remember from the third assignment that the APSES domains in fungi seem to be a relatively small family. And there is no structure available of a protein-DNA complex.  Now what?
 
 
 
Remember that homologous sequences can have diverged to the point where their sequence similarity is no longer recognizable, however their structure may be quite well conserved. Thus if we could find similar structures in the PDB, these might provide us with some plausible hypotheses for how DNA is bound by APSES domains. We thus need a tool similar to BLAST, but not for the purpose of sequence alignment, but for structure alignment. A kind of BLAST for structures.
 
 
 
However, very similar to BLAST, we might not want to search with the entire protein, if all we are interested in is a subdomain that binds to DNA. Attempting to match all structural elements in addition to the ones we are actually interested in is likely to make the search less specific - we would find false positives that are similar to some irrelevant part of our structure. However, defining too small of a subdomain would also lead to a loss of specificity: in the extreme it is easy to imagine that the search for e.g. a single helix would retrieve very many hits that would be quite meaningless. The arrangement of the residues from 50 to 74 that we have already discussed in Assignment 2 suggests that the compact subdomain from 36 to 76 (see the image above) might be a useful structure to search with: it contains the residues we are interested in and enough of connected secondary structure elements to be structurally meaningful.
 
 
 
At the '''NCBI''', [http://www.ncbi.nlm.nih.gov/Structure/VAST/vast.shtml VAST] is a search tool for structural similarity search tool for this purpose. Unfortunately it does not seem to be able to handle a query with such a structural subdomain (the process did not finish after several days) but at least you can get a list of structural neighbors of the 1MB1 full-length template structure, by entering the PDB ID in a small form field on the VAST home page, and then clicking on the colored bar labeled "Chain" on the MMDB structure summary page. This precomputed page for the 1MB1 structure shows a number of diverse proteins matching to various helices and strands of the structure.
 
  
At the '''EBI''' there are a number of very well designed structure analysis tools linked off the [http://www.ebi.ac.uk/Tools/structural.html '''Structural Analysis''' page]. As part of its MSD Services, the SSM (Secondary Structure Matching service) provides a well thought out interface for searching files from the PDB or uploading coordinates.
+
<tr class="s1"><td class="l1">[[BioPerl]]</td></tr>
 +
<tr class="s2"><td class="l1">[[PHP]]</td></tr>
 +
<tr class="s1"><td class="l1">[[Data modelling]]</td></tr>
 +
<tr class="s2"><td class="l1">BioPython <!-- (scope, highlights, installation, use, support) --></td></tr>
 +
<tr class="s1"><td class="l1">Graphical output <!-- (PNG and SVG) --></td></tr>
 +
<tr class="s2"><td class="l1">[[Autonomous agents]]</td></tr>
 +
</table>
  
After uploading the coordinates for residues 36 to 76 of the 1MB1 structure running the search and sorting the results by alignment length, the top hits include a number of nucleotide binding proteins such as a replication terminator (1F4K), the LexA repressor (1MVD) and a "Winged Helix" protein (1KQ8). These are all members of a much larger superfamily, the "winged helix" DNA binding domains ([http://cathwww.biochem.ucl.ac.uk/cgi-bin/cath/GotoCath.pl?cath=1.10.10.10 CATH 1.10.10.10]), of which hundreds of structures have been solved. They represent one branch of the tree of helix-turn-helix (HTH) DNA binding modules. (A recent review on HTH proteins is linked from the resources section at the bottom of this page). Winged Helix domains typically bind their cognate DNA with a "recognition helix" which precedes the beta hairpin and binds into the major groove; additional stabilizing interactions are provided by the edge of the beta strand binding into the minor groove.
+
===Algorithms===
 +
<table width="100%" >
 +
<tr class="sh"><td class="l1">Algorithms on Sequences</td></tr>
 +
<tr class="s1"><td class="l2">[[Dynamic Programming]]</td></tr>
 +
<tr class="s2"><td class="l2">[[Multiple Sequence Alignment]]</td></tr>
 +
<tr class="s1"><td class="l2">[[Genome Assembly]]</td></tr>
  
<!-- The other service the EBI structure links to is the DALI server. DALI was one of the first algorithms capable of large-scale protein structure searches; it was developed by Liisa Holm and is now hosted by her group in Helsinki. Submitting our search domain generates the e-mailed result linked to here. Both results (there are only two) are also found in the top 100 list of the SSM service. The winged helix domain 1DP7 merits some comment though: its structure shows a novel mode of binding for DNA. Here, it is the beta-wing, not the "recognition helix" that inserts into the major groove! We will consider this in more detail below.
+
<tr><td class="sp">&nbsp;</td></tr>
  
First we shall explore some of the structures that SSM has returned. The SSM server presents its result details in Web pages, but it also allows to download the entire result set in an XML formatted file. This is a common method of data-interchange in bioinformatics but you would not want to actually read such a file and manually extract information (even though you could, in principle). Thus I have prepared a summary file of the alignment details of the SSM results. This should allow you to rapidly find the exact aligned residues in the matched domains. While I have derived this file from the output through a computer program I have written, you could easily have accessed the same information on the Web, had you run the query yourself. -->
+
<tr class="sh"><td class="l1">Algorithms on Structures</td></tr>
 +
<tr class="s1"><td class="l2">[[Docking]]</td></tr>
 +
<tr class="s2"><td class="l2">Protein Structure Prediction <!-- ''ab initio'' --></td></tr>
  
This is good news: once we have determined that the APSES domain is actually an example of a larger group of transcription factors, we can pick one of these for which a DNA complex structure is known. I have picked one such structure from the list of hits that were returned by SSM: it is the Elk-1 transcription factor.
+
<tr><td class="sp">&nbsp;</td></tr>
  
[[Image:A5_canonical_wHTH.jpg|frame|none|Stereo-view of the canonical DNA binding mode of the Winged Helix domain family. Shown here is the Elk-1 transcription factor - an ETS DNA binding domain - in complex with a high-affinity binding site (pdb|1DUX). Note how the "recognition helix" inserts into the major groove of the DNA molecule. The color gradient ramps from blue (34) to green (84). Note how the first helix of the "helix-turn-helix" architecture serves only to position the recognition helix and makes few interactions by itself.]]
+
<tr class="sh"><td class="l1">Algorithms on Trees</td></tr>
 +
<tr class="s1"><td class="l2">Computing with trees <!-- Bayesian approaches for phylogenetic trees, tree comparison) --></td></tr>
  
Now all that is left to do is to bring the DNA molecule  into the correct orientation for our '''model''' and then to combine the two files. We need to superimpose the Elk-1 protein/DNA complex onto our '''model'''.
+
<tr><td class="sp">&nbsp;</td></tr>
  
;Structure superposition
+
<tr class="sh"><td class="l1">Algorithms on Networks</td></tr>
There are quite a number of superposition servers available on the Web, a remarkably comprehensive overview can be found in [http://en.wikipedia.org/wiki/Structural_alignment Wikipedia]. However, overengineering and black-box mentality makes our task more difficult than it need be: most tools do not allow users to specify particular alignment zones but attempt to automatically define the zones of residues to be supoerimposed according to some geometric target function. Almost none return the actual rotation matrix and translation vector that is used for the superposition. And almost none transform the coordinates of heteratoms such as solvent, ligands or DNA molecules along with the protein coordinates. An exception that I have found to be very useable is the [http://www.predictioncenter.org/local/lga/lga.html Local-Global Alignment server ('''LGA''')], written by Adam Zemla. The procedure is quite straightforward:
+
<tr class="s1"><td class="l2">Network metrics <!-- (Degree distributions, Centrality metrics, other metrics on topology, small-world- vs. random-geometric controversy) --></td></tr>
 +
<tr class="s2"><td class="l3">[[Dijkstras Algorithm]]</td></tr>
 +
<tr class="s1"><td class="l3">[[Floyd Warshall Algorithm]]</td></tr>
 +
</table>
  
*Define the structure to be rotated (1DUX in this case). This is a dimer, so download the file from the PDB and manually edit to contain only DNA chains A and B and protein chain C.
 
*Define the structure to be held constant (1MB1 in this case). Download from PDB.
 
*Use the "browse" option to define both files as input on the LGA inpput form
 
*Use the option to have both coordinate sets included in your output: <code>-o2</code>
 
*Submit
 
 
The results arrive per e-mail. I have linked the resulting PDB file to the [[Assignment_5_fallback_data|'''Fallback Data page''']]. <small>If you run this analysis on your own, you may want to review the types of edits the edits I made to the PDB file to get it displayed correctly in Rasmol.</small>
 
 
 
&nbsp;<br><div style="padding: 5px; background: #EEEEEE;">
 
*Save the superimposed  coordinates in a file, open and view in Rasmol and note how well the "recognition helix" and adjacent beta strands superimpose! (Alternatively, copy and save the coordinates from the c to your harddisk.) Make an informative view, divergent stereo and paste it into your assignment. (4 marks)
 
</div>
 
&nbsp;<br>
 
&nbsp;
 
  
 +
===Communication and collaboration===
 +
<table width="100%" >
 +
<tr class="s1"><td class="l1">[[MediaWiki]]</td></tr>
 +
<tr class="s2"><td class="l1">[[HTML essentials]]</td></tr>
 +
<tr class="s1"><td class="l1">[[HTML 5]]</td></tr>
 +
<tr class="s2"><td class="l1">[[SADI|SADI Semantic Automated Discovery and Integration]]</td></tr>
 +
<tr class="s1"><td class="l1">[[CGI]]</td></tr>
 +
<tr><td class="sp">&nbsp;</td></tr>
 +
</table>
  
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
+
===Statistics===
 +
<table width="100%" >
 +
<tr class="s1"><td class="l1">[[Pattern discovery]]</td></tr>
 +
<tr class="s2"><td class="l1">Correlation <!-- (Covariance matrices and their interpretation, application to large problems, collaborative filtering, MIC and MINE) --></td></tr>
 +
<tr class="s1"><td class="l1">Clustering methods <!-- (Algorithms and choice (including: hierarchical, model-based and partition clustering, graphical methods (MCL), flow based methods (RRW) and spectral methods). Implementation in R if possible) --></td></tr>
 +
<tr class="s2"><td class="l1">Cluster metrics <!-- (Cluster quality metrics (Akaike, BIC)–when and how) --></td></tr>
 +
<tr class="s1"><td class="l1">[[Map equation|The Map Equation]] </td></tr>
 +
<tr class="s2"><td class="l1">Machine learning <!-- (Classification problems: Neural Networks, HMMs, SVM..) --></td></tr>
  
==(4) Summary of Resources==
+
<tr class="s1"><td class="l1 mw-collapsible mw-collapsed" data-expandtext="Expand subtopics" data-collapsetext="Collapse">[[R]]
 +
<div class="mw-collapsible-content">
 +
<table width="100%"><tr class="s2"><td class="l2">R plotting</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">[[R programming]]</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">R EDA</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">R regression</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">R PCA</td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">R Clustering</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">R Classification <!-- Phrasing inquiry as a classification problem, dealing with noisy data, machine learning approaches to classification, implementation in R) --></td></tr></table>
 +
<table width="100%"><tr class="s1"><td class="l2">R hypothesis testing</td></tr></table>
 +
<table width="100%"><tr class="s2"><td class="l2">[[Bioconductor]]</td></tr></table>
 
</div>
 
</div>
&nbsp;<br>
+
</td></tr>
 
 
;Links
 
:* [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/Peitsch_2002_UseOfModels.pdf '''Review (PDF, restricted)''' Manuel Peitsch on Homology Modeling]
 
:* [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/Aravind_2005_HTHdomains.pdf '''Review (PDF, restricted)''' Aravind ''et al.'' Helix-turn-helix domains] (background reading, not required reading)
 
:* [[Organism_list_2006|Assigned Organisms]]
 
:* [http://www.rcsb.org/pdb/file_formats/pdb/pdbguide2.2/guide2.2_frame.html '''PDB file format''']
 
:* [http://en.wikipedia.org/wiki/Structural_alignment Wikipedia on '''Structural Superposition'''] <small>(although the article is called "Structural Alignment")</small>
 
  
:* [[Assignment_5_fallback_data|'''Fallback Data page''']]
+
<tr><td class="sp">&nbsp;</td></tr>
 +
</table>
  
;Alignments
+
===Applications===
:* [[All_Mbp1_T-COFFEE|Mbp1 proteins '''T-Coffee''' aligned (text version)]]
+
<table width="100%" >
 +
<tr class="s1"><td class="l1">[[Data integration]] <!-- Add BioMart: Biodata integration, and data-mining of complex, related, descriptive data --></td></tr>
 +
<tr class="s2"><td class="l1">Text mining <!-- (Use cases, tasks and metrics, taggers, vocabulary mapping, Practicals: R-support, Python/Perl support, others...) --></td></tr>
 +
<tr class="s1"><td class="l1">[[HMMER]]</td></tr>
 +
<tr class="s2"><td class="l1">High-throughput sequencing</td></tr>
 +
<tr class="s1"><td class="l1">Functional annotation <!-- GFF --></td></tr>
 +
<tr class="s2"><td class="l1">Microarray analysis <!-- (... in R: differential expression and multiple testing; Loading and normalizing data, calculating differential expression, LOWESS, the question of significance, FWERs: Bonferroni and FDR; SAM and LIMMA) --></td></tr>
 +
<tr><td class="sp">&nbsp;</td></tr>
 +
</table>
 +
</td></tr></table>
  
&nbsp;
 
&nbsp;
 
 
<div style="padding: 5px; background: #D3D8E8;  border:solid 1px #AAAAAA;">
 
[End of assignment]
 
 
</div>
 
</div>
 
If you have any questions at all, don't hesitate to mail me at [mailto:boris.steipe@utoronto.ca boris.steipe@utoronto.ca] or post your question to the [mailto:bch441_2006@googlegroups.com Course Mailing List]
 
 
 
<Tasks: review location of fallback files; rewrite SwissModel interface section ...>
 

Latest revision as of 12:44, 27 September 2015

 

Hardware

High performance computing
Cloud computing
 

Systems and Tools

Unix
Network Configuration
Apache
MySQL
Tools for the bioinformatics lab
GBrowse and LDAS
 

Programming

IDE (Integrated Development Environment)
Regular Expressions
Screenscraping
Perl
BioPerl
PHP
Data modelling
BioPython
Graphical output
Autonomous agents

Algorithms

Algorithms on Sequences
Dynamic Programming
Multiple Sequence Alignment
Genome Assembly
 
Algorithms on Structures
Docking
Protein Structure Prediction
 
Algorithms on Trees
Computing with trees
 
Algorithms on Networks
Network metrics
Dijkstras Algorithm
Floyd Warshall Algorithm


Communication and collaboration

MediaWiki
HTML essentials
HTML 5
SADI Semantic Automated Discovery and Integration
CGI
 

Statistics

Pattern discovery
Correlation
Clustering methods
Cluster metrics
The Map Equation
Machine learning
R
R plotting
R programming
R EDA
R regression
R PCA
R Clustering
R Classification
R hypothesis testing
Bioconductor
 

Applications

Data integration
Text mining
HMMER
High-throughput sequencing
Functional annotation
Microarray analysis