BIO Assignment Week 8

Assignment for Week 7
Predictions: Homology Modeling

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Assignment 8 >

Note! This assignment is currently inactive. Major and minor unannounced changes may be made at any time.

 
 

Concepts and activities (and reading, if applicable) for this assignment will be topics on next week's quiz.

Introduction

How could the search for ultimate truth have revealed so hideous and visceral-looking an object?

Max Perutz (on his first glimpse of the Hemoglobin structure)

   

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 discovered 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 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 (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 and the following assignment you will (1) construct a molecular model of the APSES domain from the Mbp1 orthologue in your assigned species, (2) identify similar structures of distantly related domains for which protein-DNA complexes are known, (3) assemble a hypothetical complex structure and (4) consider whether the available evidence allows you to distinguish between different modes of ligand binding.

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.

 

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 find useful or interesting.

 

Warm-up: a minimal change

Minimal changes to structure models can be done directly in Chimera. This illustrates the principle of full-scale modeling quite nicely. For an example, let us consider the residue A 42 of the 1BM8 structure. It is oriented twards the core of the protein, but most other Mbp1 orthologs have a larger amino acid in this position, V, or even I.

Task:

1. Open 1BM8 in Chimera, hide the ribbons and show all atoms as a stick model.
2. Color the protein white.
3. Open the sequence window and select A 42. Color it red. Choose Actions → Set pivot. Then study how nicely the alanine sidechain fits into the cavity formed by its surrounding residues.
4. To emphasize this better, hide the solvent molecules and select only the protein atoms. Display them as a sphere model to better appreciate the packing, i.e. the Van der Waals contacts we discussed in class. Use the Favorites → Side view panel to move the clipping plane and see a section through the protein. Study the packing, in particular, note that the additional methyl groups of a valine or isoleucine would not have enough space in the structure. Then restore the clipping planes so you can see the whole molecule.
5. Lets simplify the view: choose Actions → Atoms/Bonds → backbone only → chain trace. Then select A 42 again in the sequence window and choose Actions → Atoms/Bonds → show.
6. Add the surrounding residues: choose Select → Zone.... In the window, see that the box is checked that selects all atoms at a distance of less then 5Å to the current selection, and check the lower box to select the whole residue of any atom that matches the distance cutoff criterion. Click OK and choose Actions → Atoms/Bonds → show.
7. Select A 42 again: left-click (control click) on any atom of the alanine to select the atom, then up-arrow to select the entire residue. Now let's mutate this residue to isoleucine.
8. Choose Tools → Structure Editing → Rotamers and select ILE as the rotamer type. Click OK, a window will pop up that shows you the possible rotamers for isoleucine together with their database-derived probabilities; you can select them in the window and cycle through them with your arrow keys. But note that the probabilities are very different - and thus show you high-energy and low-energy rotamers to choose from. Therefore, unless you have compelling reasons to do otherwise, try to find the highest-probability rotamer that may fit. This is where your stereo viewing practice becomes important, if not essential. It is really, really hard to do this reasonably in a 2D image! It becomes quite obvious in 3D. Btw: I find such "quantitative" work - where the real distances are important - easier in orthographic than in perspective view (cf. the Camera panel).
9. I find that the first rotamer is actually not such a bad fit. The CD atom comes close to the sidechains of I 25 and L 96. But we can assume that these are somewhat mobile and can accommodate a denser packing, because - as you can easily verify in your Jalview alignment - it is NOT the case that sequences that have I 42, have a smaller residue in position 25 and/or 96. So let's accept the most frequent ILE rotamer by selecting it in the rotamer window and clicking OK (while existing side chain(s): replace is selected).
10. Done.

If you want to go over this in more detail, check the video tutorial on YouTube published by the NIAID bioinformatics group here. I would also encourage you to go over Part 2 of the video tutorial that discusses how to check for and resolve (by energy minimization) steric clashes. But do remember that it is not clear whether energy minimization will make your structure more correct in the sense of a smaller overall RMSD with the real, mutated protein.

What we have done here with one residue is exactly the way homology modeling works with entire sequences. Let's now build a homology model for YFO Mbp1.

Preparation

Target sequence

The first step of homology modelling is to determine which sequence to model. We have determined the putative orthologue with conserved function in YFO by reciprocal best match with saccharomyces cervisiae Mbp1. Your sequence was initially found with an APSES domain search in YFO and the alignments with the yeast sequence are straightforward for the most part.

There are two exceptions however: the alignment of ASPFU gene XP_754232 and the CAPCO gene XP_007722875 both are missing part of the domin's N-terminus. This is odd, because this may imply the APSES domain of these genes might not be properly folded. When such surprising results of alignement occurr, you must consider whether there could be an error in the published sequence, perhaps stemming from an erroneous gene model. This is not absolutely germane to this assignment, so I have placed the process into the collapsible section below - optional reading. However it may be useful for you to understand what the issue is here and how to address it.

Correcting the ASPFU Mbp1 gene model.

An alignment of APSES domain sequence shows the shortened N-terminus of the ASPFU and the CAPCOprotein, relative to SACCE and e.g. the closely related aspergillus nidulans, ASPNI:

APSES domains:
Mbp1_SACCE  QIYSARYSGVDVYEFIHSTGSIMKRKKDDWVNATHILKAA...
Mbp1_ASPNI  NVYSATYSSVPVYEFKIGTDSVMRRRSDDWINATHILKVA...
Mbp1_ASPFU  ----------------------MRRRGDDWINATHILKVA...
Mbp1_CAPCO  ----------------------MRRRSDDWVNATHILKVA...

We analyse this for the ASPFU gene.

Working from the possibility that this may be a gene model error - e.g. a false translational start, a frameshift due to a sequencing error, or an erroneously modelled intron, we check whether the translation of the genomic sequence supports the presence of the expected amino acids. This is easily done running TBLASTN - BLASTing the protein query against the six reading frames of the ASPFU genome. We find the following:

Aspergillus fumigatus Af293 chromosome 3, whole genome shotgun sequence
Sequence ID: ref|NC_007196.1|Length: 4079167Number of Matches: 2
[...]
Query  10       VDVYEFIHSTGSIMKRKKDDWVNATHILKAANFAKAKRTRILE ...
                V VYEF     S+M+R+ DDW+NATHILK A F K  RTRILE ...
Sbjct  3691193  VPVYEFKVDGESVMRRRGDDWINATHILKVAGFDKPARTRILE ...

Indeed, there is sequence upstream of the gene's published translation start that matches well with our query! But where is the correct translation start? For that we need to look at the actual nucleotide sequence and translate it. Remember: BLAST is a local sequence alignment algorithm and it won't retrieve everything that matches to our query, just the best matching segment. ASPFU chromosome 3 is over 4 megabases large, so let us try to obtain only the region we are actually interested in: downstream of bases 3691193, lets say 3691100 (make sure this offset is divisible by three, to stay in the same reading frame) and upstream to, say, 3691372.

1. At the NCBI genome project site we search for aspergillus fumigatus.
2. At the aspergillus fumigatus genome project site we click on chromosome 3 to access the map viewer.
3. Hovering over the Download/View sequence link shows us how an URL to access sequence data is structured:

http://www.ncbi.nlm.nih.gov/projects/mapview/seq_reg.cgi?taxid=746128&chr=3&from=1&to=4079167

We can easily adapt this to the sequence range we need ...

4. ... and follow: http://www.ncbi.nlm.nih.gov/nuccore/NC_007196.1?from=3691003&to=3691243&report=fasta to yield:

>gi|71025130:3691003-3691243 Aspergillus fumigatus Af293 chromosome 3, whole genome shotgun sequence
ACGGTTTGCGGAGACGGGCATTATGGCGGCGGTGGATTTCTCAAAAATCTATTCTGCTACATACAGCAGC
GTAAGTCTCTTCTAATTGCGTATCTCTGTTTTCCCTACAGCCTCAAATTTTCCCCAATGCCTCTTTCCAT
CCATTTTGCCCCTTCCTTCGCCGCGAAGCCAATCTAACGCAGTTCAATAGGTTCCAGTTTACGAGTTCAA
AGTCGATGGCGAAAGTGTTATGCGCCGACGA

5. To translate this, we navigate to any of the EMBOSS tools servers and use "remap" - we want to see the translation matched to the nucleotide sequence. We turn restriction sites off, translate all three forward frames and paste and manually align the SACCE Mbp1 sequence into the output to see what we expect and what we got. I have selected only the frame(s) that actually give a match, and I have pasted the homologous CAPCO and SACCE sequences (lower case) to demonstrate their similarity:

ASPFU     ACGGTTTGCGGAGACGGGCATTATGGCGGCGGTGGATTTCTCAAAAATCTATTCTGCTACATACAGCAGC
                                                                        
ASPFU      R  F  A  E  T  G  I  M  A  A  V  D  F  S  K  I  Y  S  A  T  Y  S  S  
CAPCO                           m  -  a  f  d  -  k  e  i  y  s  a  t  y  s  n  
SACCE                           m  s  -  -  -  -  n  q  i  y  s  a  r  y  s  g

         
ASPFU     GTAAGTCTCTTCTAATTGCGTATCTCTGTTTTCCCTACAGCCTCAAATTTTCCCCAATGCCTCTTTCCAT
 
ASPFU     V  S  L  F  *  ... 
CAPCO     v  a  -  -     ...
SACCE     v  d  -  -     ...
         
ASPFU     CCATTTTGCCCCTTCCTTCGCCGCGAAGCCAATCTAACGCAGTTCAATAGGTTCCAGTTTACGAGTTCAA
                                                             ...  V  Y  E  F  K 
CAPCO                                                        ...  v  y  e  l  k 
SACCE                                                        ...  v  y  e  f  i
         
ASPFU      AGTCGATGGCGAAAGTGTTATGCGCCGACGAGGCGATGATTGGATCAATGCTACACATATTCTTAAA

ASPFU       V  D  G  E  S  V  M  R  R  R  G  D  D  W  I  N  A  T  H  I  L  K ...
CAPCO       v  a  g  d  h  i  m  r  r  r  s  d  d  w  v  n  a  t  h  i  l  k ...
SACCE       h  s  t  g  s  i  m  k  r  k  k  d  d  w  v  n  a  t  h  i  l  k ...

This clearly shows us that there is N-terminal sequence that ought to be added to the gene model, upstream of the reported translational start of MRRR.... The sequences thus most likely begin as follows:

ASPFU   MAAVDFSKIYSATYSSVSLFVYEFKVDGE-----SVMRRRGDDWINATHILK...
CAPCO   ma-fd-keiysatysnva--vyelkvagd-----himrrrsddwvnathilk...
SACCE   ms----nqiysarysgvd--ysgvdvyefihstgsimkrkkddwvnathilk...

The fact that the truncated N-terminus appears in both closely related genes and species suggests that what we see here is a mis-annotated intron. The take-home lesson is: if your retrieved protein sequence does not conform to your expectations, it may be worthwhile to follow up with the actual nucleotide sequence.

 

Template choice and template sequence

The SWISS-MODEL server provides several different options for constructing homology models. The easiest option requires only a target sequence as input. In this mode the program will automatically choose suitable templates and create an input alignment. I would argue however that that is not the best way to use such a service: template choice and alignment both may be significantly influenced by biochemical reasoning, and an automated algorithm cannot make the necessary decisions. Should you use a structure of reduced resolution that however has a ligand bound? Should you move an indel from an active site to a loop region even though the sequence similarity score might be less? Questions like that may yield answers that are counter to the best choices an automated algorithm could make. But Swiss Model is flexible and allows us to upload an explicit alignment between target and template. Please note: the model you will produce is "easy" - the sequence similarity is high and there are no indels to consider, the automated mode would have done just as well. But the strategy we pursue here is suitable also for much more difficult problems. The automated strategy probably is not.

Template choice is the first step. Often more than one related structure can be found in the PDB. We have touched on principles of selecting template structures in the lectures; please refer to the template choice principles page on this Wiki where I have reviewed the principles and discussed more details and alternatives. 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 the BLAST search is probably the method of choice: after all, the most important measure of the probability of success for homology modeling is sequence similarity.

In Assignment 3, you have defined the extent of the APSES domain in yeast Mbp1. In Assignment 6, you have used PSI-BLAST to search for APSES domains in YFO. In Assignment 7 you have confirmed by Reciprocal Best Match which of these APSES domain sequences is the closest related orthologue to yeast Mbp1. This sequence is the best candidate for having a conserved function similar to yeast Mbp1. Therefore, this sequence is the one you will model: it is called the target for the homology modeling procedure. In the same assignment you have also computed a multiple sequence alignment that includes the sequence of Mbp1 with YFO.

Defining a template means finding a PDB coordinate set that has sufficient sequence similarity to your target that you can build a model based on that template. In Assignment 2 you have used a keyword search at the PDB to find "Mbp1" structures - but some of these structures were not homologs: keyword searches are notoriously unreliable. To find suitable PDB structures, we will perform a BLAST search at the PDB instead.

Task:

1. Retrieve your YFO Mbp1-like APSES domain sequence. You can find the domain boundaries for the yeast protein in the Mbp1 annotation reference page, and you can get the aligned sequence from your Jalview alignment, or simply recompute it with the needle program of the EMBOSS suite. This YFO sequence is your target sequence.
2. Navigate to the PDB.
3. Click on Advanced to enter the advanced search interface.
4. Open the menu to Choose a Query Type:
5. Find the Sequence features section and choose Sequence (BLAST...)
6. Paste your target sequence into the Sequence field, select not to mask low-complexity regions and Submit Query. Since the E-value is set rather high by default, you will get a number of low-confidence hits as well as the actual homologs, these have very low E-values.

All hits that are homologs are potentially suitable templates, but some are more suitable than others. Consider how the coordinate sets differ and which features would make each more or less suitable for creating a homology model: you should consider ...

• 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

Sequence similarity is the most important, but we can have the PDB tabulate the other features concisely for this task.

1. There is a menu to create Reports: - select customizable table.
2. Select (at least) the following information items:

Structure Summary

• Experimental Method

Sequence

• Chain Length

Ligands

• Ligand Name

Biological details

• Macromolecule Name

refinement Details

• Resolution
• R Work
• R free

1. click: Create report.

Unfortunately you don't get the E-values into the report, and those should strongly influence your final decision. However in our case the sequences and therefore the E-values of the top three hits are all the same. Neither of the structures has a bound DNA ligand, but the experimental methods and structure quality are different. Two of the sequences have a longer chain-length ... but those are only disordered residues (otherwise these would be better suited templates; regrettably, you'd need to check that in the real world, there is no automatic tool to evaluate disorder and its effects on template choice). In my opinion that leaves pretty much only one unambiguous choice: 1BM8. In case you don't agree, please let me know.

Finally

Click on the 1BM8 ID to navigate to the structure page for the template and save the FASTA sequence to your computer. This is the template sequence.

 

Sequence numbering

 

It is not straightforward at all how to number sequence in such a project. A "natural" numbering starts with the start-codon of the full length protein and goes sequentially from there. However, this does not map exactly to other numbering schemes we have encountered. As you know the first residue of the APSES domain (as defined by CDD) is not Residue 1 of the Mbp1 protein. The first residue of the 1BM8 FASTA file (one of the related PDB structures) is the fourth residue of the Mbp1 protein. The first residue in the structure is GLN 3, therefore Q is the first residue in a FASTA sequence derived from the cordinate section of the PDB file (the ATOM records. In the 1MB1 structure, the original N-terminal amino acids are present in the molecule, therefore they are present in the FASTA file which starts with MSNQIY..., but they are disordered in the structure and no coordinates are present for M and S. A sequence derived explicitly from the coordinates is therefore different from the reported FASTA sequence, which is really bad because that is what the modeling program has to work with ... and so on. It can get complicated. You need to remember: a sequence number is not absolute, but assigned in a particular context and you need to be careful how to do this.

Fortunately, the numbering for the residues in the coordinate section of our target structure corresponds not to its FASTA sequence, but to the numbering of the gene. Otherwise we would need to renumber the sequence (e.g. by using the bio3D R package). If we would not do this, the sequence numbers in the model might not correspond to the sequence numbers of our target.

 

The input alignment

  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 just 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 most of the Mbp1 orthologues, we do not observe 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. To obtain an alignment between the template sequence and the target sequence from your species, proceed as follows.

 

Task:
Choose on of the following options to align your target and template sequence.

In Jalview...

• Load your Jalview project with aligned APSES domain sequences or recreate it from the Mbp1 orthologue sequences from the Mbp1 protein orthologs page that I prepared for Assignment 7. Include the sequence of your template protein and re-align.
• Delete all sequence you no longer need, i.e. keep only the APSES domains of the target (from your species) and the template (from the PDB) and choose Edit → Remove empty columns. This is your input alignment.
• Choose File→Output to textbox→FASTA to obtain the aligned sequences. They should both have exactly the same length, i.e. N- or C- termini have to be padded by hyphens if the original sequences had different length. Save the sequences in a text-file.

Using a different MSA program

• Copy the FASTA formatted sequences of the Mbp1 proteins in the reference species from the Reference APSES domain page.
• Access e.g. the MSA tools page at the EBI.
• Paste the Mbp1 sequence set, your target sequence and the template sequence into the input form.
• Run the alignment and save the output.

Using the EMBOSS explorer

• Use the needle tool for the alignment ... but remember that pairwise alignments will only be suitable in case the alignment is absolutely unambiguous (such as here) . If there are any indels, an MSA will give much more reliable information.

By hand

APSES domains are strongly conserved and have few if any indels. You could also simply align by hand.

• Copy the CLUSTAL formatted reference alignment of the Mbp1 proteins in the reference species from the Reference APSES domain page.
• Open a new file in a text editor.
• Paste the Mbp1 sequence set, your target sequence and the template sequence into the file.
• Align by hand, replace all spaces with hyphens and save the output.

Whatever method you use: the result should be a two sequence alignment in multi-FASTA format, that was constructed from a number of supporting sequences and that contains your aligned target and template sequence. This is your input alignment for the homology modeling server. For a Schizosaccharomyces pombe model, which I am using as an example here, it looks like this:

>1BM8_A 
QIYSARYSGVDVYEFIHSTGSIMKRKKDDWVNATHILKAANFAKAKRTRI
LEKEVLKETHEKVQGGFGKYQGTWVPLNIAKQLAEKFSVYDQLKPLFDF
>Mbp1_SCHPO 2-100 NP_593032
AVHVAVYSGVEVYECFIKGVSVMRRRRDSWLNATQILKVADFDKPQRTRV
LERQVQIGAHEKVQGGYGKYQGTWVPFQRGVDLATKYKVDGIMSPILSL

 

Homology model

 

SwissModel

 

Access the Swissmodel server at http://swissmodel.expasy.org and click on Start Modelling. Then, under the Supported Inputs, click on Target-Template Alignment.

Task:

• Paste your alignment for target and model into the form field. Click on the question mark next to "Supported Inputs" if you are not sure about the format. SwissModel will analyse the sequences and ask you to identify target and template. The YFO sequence is your target. The 1BM8 sequence is the template.

• Click Validate Target Template Alignment and check that the returned alignment is correct.

• Click Build Model to start the modeling process.

• The resulting page returns information about the resulting model. Mouse over the Model 01, open the PDB file and save the coordinates to your computer. Read the information on what is being returned by the server (click on the question mark icon). Study the quality measures.

• Also save:

• • The output page as pdf (for reference)
  • The modeling report (as pdf)

Model analysis

   

The PDB file

 

Task:
Open your model coordinates in a text-editor (make sure you view the PDB file in a fixed-width font (like "courier") so all the columns line up correctly) and consider the following questions:

• 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 your model correspond to that region?

R code: renumbering the model

As you have seen, SwissModel numbers the first residue "1" and does not keep the numbering of the template. We should renumber the model so we can compare the model and the template with the same residue numbers. Fortunately there is a very useful R package that will help us with that.

Task:

1. Navigate to the bio3D home page. bio3d is not available for installation via CRAN, but needs to be installed from source. Instructions for the different platforms are here http://thegrantlab.org/bio3d/tutorials/installing-bio3d Follow the instructions and install bio3d for R on your platform.

1. Explore and execute the following R script. I am assuming that your model is in your working directory, change paths and filenames as required.

# renumberPDB.R

# This is a simple renumbering script that uses the bio3D 
# package. We simply set the first residue number to what it
# should be and renumber all residues based on the first one.
# The script assumes your input PDBfile is in your working
# directory.

# To run this, you must have installed the bio3D R package; instructions
# are here: http://thegrantlab.org/bio3d/tutorials/installing-bio3d

setwd("~/my/working/directory")
PDBin      <- "YFO_model.pdb"
PDBout     <- "YFO_model_ren.pdb"

first <- 4  # residue number that the first residue should have
 
# ================================================
#    Read coordinate file
# ================================================
 
# read PDB file using bio3D function read.pdb()
library(bio3d)
pdb  <- read.pdb(PDBin) # read the PDB file into a list

pdb            # examine the information
pdb$atom[1,]   # get information for the first atom

# you can explore ?read.pdb and study the examples.

# ================================================
#    Change residue numbers
# ================================================


resNum <- as.numeric(pdb$atom[,"resno"])  # get residue numbers for all atoms
resNum <- resNum + (first - resNum[1])         # calculate offset
pdb$atom[,"resno"] <- resNum             # replace old numbers with new
pdb$atom[1,]                                   # check result


# ================================================
#    Write output to file
# ================================================

write.pdb(pdb=pdb,file=PDBout)

# Done. Open the PDB file you have written in a text editor and confirm
# that this has worked.

 

First visualization

 

Since a homology model inherits its structural details from the template, your model of the YFO sequence should look very similar to the original 1BM8 structure.

Task:

1. Start Chimera and load the model coordinates that you have just renumbered.
2. From the PDB, also load the template structure. (Use File → Fetch by ID ...)
3. In the Favourites → Model Panel window you can switch between the two molecules.
4. Hide the ribbon and choose backbone only → full. You will note that the backbone of the two structures is virtually identical.
5. Next, choose Actions → Atoms/Bonds → show to display display the two molecules in a stick style and note how the sidechains have been modeled. Note especially how sidechain coordinates have been guessed, where the template had shorter sidechains than the target. It may be more clear if you hide H-atoms: Select → Chemistry → Element → H and Actions → Atoms/Bonds → hide
6. Display only residue 50 to 74 to focus on the putative helix-turn-helix domain. Choose Favourites → Sequence, select the residues for one model, then Select → Invert (selected model) and Actions → Atoms/Bonds → hide.
7. Study the result. A model of the HTH domain of YFO Mbp1.

 
 

Coloring the model by energy

SwissModel calculates energies for each residue of the model with a molecular mechanics forcefield. The SwissModel modeling summary page contains a plot of these energies as a function of sequence number like. The values - between 0.0 and 1.0 - are stored in the PDB files B-factor field.

Task:

1. Back in Chimera, use the model panel to close the 1BM8 structure.
2. Choose Tools → Depiction → Render by attribute and select attributes of atoms, Attribute: bfactor, check color atoms and click OK.
3. Study the result: It seems that residues in the core of the protein have better energies than residues at the surface. Why could that be the case?

Study the options of this window a bit, rendering by attribute is a powerful way to store and depict all manners of information with the molecule. Simply write a little R script that uses bio3D to replace the B-factor or occupancy values with any value you might be interested in: energies, conservation scores, information ... whatever. The rewnder this property to map it on the 3D structure of your molecule. If you want to experience with this a bit, you could apply the information scores from the previous assignment to your model, using a script that is easy to derive from the renumbering R-script you have studied above.

Introduction

One of the really interesting questions we can discuss with reference to our homology model is how sequence variation might result in changed DNA recognition sites, and then lead to changed cognate DNA binding sequences. In order to address this, we would need to generate a plausible structural model for how DNA is bound to APSES domains.

Since there is currently no software available that would reliably model such a complex from first principles, we will base a model of a bound complex on homology modelling as well. This means we need to find a similar structure for which the position of bound DNA is known, then superimpose that structure with our model. This places the DNA molecule into the spatial context of the model we are studying. 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 an APSES domain-DNA complex. How can we find a coordinate set of a structurally similar protein-DNA complex?

This assignment is based on the homology model you built. You will (1) identify similar structures of distantly related domains for which protein-DNA complexes are known, (2) assemble a hypothetical complex structure and (3) consider whether the available evidence allows you to distinguish between different modes of ligand binding,

Modeling a DNA ligand

 

 

Finding a similar protein-DNA complex

 

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. Just like with sequence searches, we might not want to search with the entire protein, if 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.

At the NCBI, VAST is provided as a search tool for structural similarity search.

Task:

1. Navigate to the VAST search interface page.
2. Enter 1bm8 as the PDB ID to search for and click Go.
3. Follow the link to Related Structures.
4. Study the result.

You will see that VAST finds more than 3,000 partially similar structures, but it would be almost impossibly tedious to manually search through the list for structures of protein DNA complexes that are similar to the interacting core of the APSES domain. It turns out that our search is not specific enough in two ways: we have structural elements in our PDB file that are unnecessary for the question at hand, and thus cause the program to find irrelevant matches. But, if we constrain ourselves to just a single helix and strand (i.e. the 50-74 subdomain that has been implicated in DNA binding, the search will become too non-specific. Also we have no good way to retrieve functional information from these hits: which ones are DNA-binding proteins, that bind DNA through residues of this subdomain and for which the structure of a complex has been solved? It seems we need to define our question more precisely.

Task:

1. Open VMD and load the 1BM8 structure or your YFO homology model.
2. Display the backbone as a Trace (of CA atoms) and color by Index
3. In the sequence viewer, highlight residues 50 to 74.
4. In the representations window, find the yellow representation (with Color ID 4) that the sequence viewer has generated. Change the Drawing Method to NewCartoon.
5. Now (using stereo), study the topology of the region. Focus on the helix at the N-terminus of the highlighted subdomain, it is preceded by a turn and another helix. This first helix makes interactions with the beta hairpin at the C-terminal end of the subdomain and is thus important for the orientation of these elements. (This is what is referred to as a helix-turn-helix motif, or HtH motif, it is very common in DNA-binding proteins.)
6. Holding the shift key in the alignment viewer, extend your selection until you cover all of the first helix, and the residues that contact the beta hairpin. I think that the first residue of interest here is residue 33.
7. Again holding the shift key, extend the selection at the C-terminus to include the residues of the beta hairpin to where they contact the helix at the N-terminus. I think that the last residue of interest here is residue 79.
8. Study the topology and arrangement of this compact subdomain. It contains the DNA-binding elements and probably most of the interactions that establish its three-dimensional shape. This subdomain even has a name: it is a winged helix DNA binding motif, a member of a very large family of DNA-binding domains. I have linked a review by Gajiwala and Burley to the end of this page; note that their definition of a canonical winged helix motif is a bit larger than what we have here, with an additional helix at the N-terminus and a second "wing". )

Armed with this insight, we can attempt again to find meaningfully similar structures. At the EBI there are a number of very well designed structure analysis tools linked off the Structural Analysis page. As part of its MSD Services, PDBeFold provides a convenient interface for structure searches for our purpose

Task:

1. Navigate to the PDBeFold search interface page.
2. Enter 1bm8 for the PDB code and choose Select range from the drop down menu. Select the residues you have defined above.
3. Note that you can enter the lowest acceptable match % separately for query and target. This means: what percentage of secondary structure elements would need to be matched in either query or target to produce a hit. Keep that value at 80 for our query, since we would want to find structures with almost all of the elements of the winged helix motif. Set the match to 10 % for the target, since we are interested in such domains even if they happen to be small subdomains of large proteins.
4. Keep the Precision at normal. Precision and % query match could be relaxed if we wanted to find more structures.
5. Finally click on: Submit your query.
6. On the results page, click on the index number (in the left-hand column) of the top hit that is not one of our familiar Mbp1 structures to get a detailed view of the result. Most likely this is 1wq2:a, an enzyme. Click on View Superposed. This will open a window with the structure coordinates superimposed in the Jmol molecular viewer. Control-click anywhere in the window area to open a menu of viewing options. Select Style → Stereographic → Wall-eyed viewing. Select Trace as the rendering. Then study the superposition. You will note that the secondary structure elements match quite well, but does this mean we have a DNA-binding domain in this sulfite reductase?

All in all this appears to be well engineered software! It gives you many options to access result details for further processing. I think this can be put to very good use. But for our problem, we would have to search through too many structures because, once again, we can't tell which ones of the hits are DNA binding domains, especially domains for which the structure of a complex has been solved.

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) and the "wing" is clearly seen as the green pair of beta-strands, extending to the right of the helix-turn-helix motif.

 

APSES domains represent one branch of the tree of helix-turn-helix (HTH) DNA binding modules. (A 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 a beta-strand binding into the minor groove. 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 compare our model to a structure of a protein-DNA complex. Superfamilies of such structural domains are compiled in the CATH database. Unfortunately CATH itself does not provide information about whether the structures have been determined as complexes. But we can search the PDB with CATH codes and restrict the results to complexes. Essentially, this should give us a list of all winged helix domains for which the structure of complexes with DNA have been determined. This works as follows:

Task:

• For reference, access CATH domain superfamily 1.10.10.10; this is the CATH classification code we will use to find protein-DNA complexes. Click on Superfamily Superposition to get a sense of the structural core of the winged helix domain.

1. Navigate to the PDB home page and follow the link to Advanced Search
2. In the options menu for Choose a Query Type select Structure Features → CATH Classification Browser. A window will open that allows you to navigate down through the CATH tree. You can view the Class/Architecture/Topology names on the CATH page linked above. Click on the triangle icons (not the text) for Mainly Alpha → Orthogonal Bundle → ARC repressor mutant, subunit A then click on the link to winged helix repressor DNA binding domain. Or, just enter "winged helix" into the search field. This subquery should match more than 550 coordinate entries.
3. Click on the (+) button behind Add search criteria to add an additional query. Select the option Structure Features → Macromolecule type. In the option menus that pop up, select Contains Protein→Yes, Contains DNA→Yes, Contains RNA→Ignore, Contains DNA/RNA hybrid→Ignore. This selects files that contain Protein-DNA complexes.
4. Check the box below this subquery to Remove Similar Sequences at 90% identity and click on Submit Query. This query should retrieve more than 100 complexes.
5. Scroll down to the beginning of the list of PDB codes and locate the Reports menu. Under the heading View select Gallery. This is a fast way to obtain an overview of the structures that have been returned. Adjust the number of Results to see all 100 images and choose Options→Resize medium.
6. Finally we have a set of winged-helix domain/DNA complexes, for comparison. Scroll through the gallery and study how the protein binds DNA.

First of all you may notice that in fact not all of the structures are really different, despite having requested only to retrieve dissimilar sequences, and not all images show DNA. This appears to be a deficiency of the algorithm. But you can also easily recognize how in most of the the structures the recognition helix inserts into the major groove of B-DNA (eg. 1BC8, 1CF7) and the wing - if clearly visible at all in the image - appears to make accessory interactions with the DNA backbone.. There is one exception: the structure 1DP7 shows how the human RFX1 protein binds DNA in a non-canonical way, through the beta-strands of the "wing". This is interesting since it suggests there is more than one way for winged helix domains to bind to DNA. We can therefore use structural superposition of your homology model and two of the winged-helix proteins to decide whether the canonical or the non-canonical mode of DNA binding seems to be more plausible for Mbp1 orthologues.

 

Preparation and superposition of a canonical complex

 

The structure we shall use as a reference for the canonical binding mode is the Elk-1 transcription factor.

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 (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.

The 1DUX coordinate-file contains two protein domains and two B-DNA dimers in one asymmetric unit. For simplicity, you should delete the second copy of the complex from the PDB file. (Remember that PDB files are simply text files that can be edited.)

Task:

1. Find the 1DUX structure in the image gallery and open the 1DUX structure explorer page in a separate window. Download the coordinates to your computer.
2. Open the coordinate file in a text-editor (TextEdit or Notepad - NOT MS-Word!) and delete the coordinates for chains D,E and F; you may also delete all HETATM records and the MASTER record. Save the file with a different name, e.g. 1DUX_monomer.pdb .
3. Open VMD and load your homology model. Turn off the axes, display the model as a Tube representation in stereo, and color it by Index. Then load your edited 1DUX file, display this coordinate set in a tube representation as well, and color it by ColorID in some color you like. It is important that you can distinguish easily which structure is which.
4. You could use the Extensions→Analysis→RMSD calculator interface to superimpose the two strutcures IF you would know which residues correspond to each other. Sometimes it is useful to do exactly that: define exact correspondences between residue pairs and superimpose according to these selected pairs. For our purpose it is much simpler to use the Multiseq tool (and the structures are simple and small enough that the STAMP algorithm for structural alignment can define corresponding residue pairs automatically). Open the multiseq extension window, select the check-boxes next to both protein structures, and open the Tools→Stamp Structural Alignment interface.
5. In the "'Stamp Alignment Options'" window, check the radio-button for Align the following ... Marked Structures and click on OK.
6. In the Graphical Representations window, double-click on all "NewCartoon" representations for both molecules, to undisplay them.
7. You should now see a superimposed tube model of your homology model and the 1DUX protein-DNA complex. You can explore it, display side-chains etc. and study some of the details of how a transcription factor recognizes and binds to its cognate DNA sequence. However, remember that your model's side-chain orientations have not been determined experimentally but inferred from the template, and that the template's structure was determined in the absence of bound DNA ligand.

1. Orient and scale your superimposed structures so that their structural similarity is apparent, and the recognition helix can be clearly seen inserting into the DNA major groove. You may want to keep a copy of the image for future reference. Consider which parts of the structure appear to superimpose best. Note whether it is plausible that your model could bind a B-DNA double-helix in this orientation.

 
 

Preparation and superposition of a non-canonical complex

The structure displaying a non-canonical complex between a winged-helix domain and its cognate DNA binding site is the human Regulatory Factor X.

Stereo-view of a non-canonical wHTH-DNA complex, discovered in with the stucture of human Regulatory Factor X (hRFX) binding its cognate X-box DNA sequence (1DP7). Note how the helix that coresponds to the recognition helix in the canonical domain lies across the minor groove whereas the beta-"wing" inserts into the major groove. The color gradient ramps from blue (18) to green (68).

Before we can work with this however, we have to fix an annoying problem. If you download and view the 1DP7 structure in VMD, you will notice that there is only a single strand of DNA! Where is the second strand of the double helix? It is not in the coordinate file, because it happens to be exactly equivalent to the frist starnd, rotated around a two-fold axis of symmetry in the crystal lattice. We need to download and work with the so-called Biological Assembly instead. But there is a problem related to the way the PDB stores replicates in biological assemblies. The PDB generates the additional chains as copies of the original and delineates them with MODEL and ENDMDL records, just like in a multi-structure NMR file. The chain IDs and the atom numbers are the same as the original. The PDB file thus contains the same molecule in two different orientations, not two independent molecules. This is an important difference regarding how such molecules are displayed by VMD. If you try to use the biological unit file of the PDB, VMD does not recognize that there is a second molecule present and displays only one chain. And that looks exactly like the one we have seen before. We have to edit the file, extract the second DNA molecule, change its chain ID and then append it to the original 1DP7 structure...

Task:

1. On the structure explorer page for 1DP7, select the option Download Files → PDB File.
2. Also select the option Download Files → Biological Assembly.
3. Uncompress the biological assembly file.
4. Open the file in a text editor.
5. Delete everything except the second DNA molecule. This comes after the MODEL 2 line and has chain ID D. Keep the TER and END lines. Save this with a new filename (e.g. 1DP7_DNAonly.pdb).
6. Also delete all HETATM records for HOH, PEG and EDO, as well as the entire second protein chain and the MASTER record. The resulting file should only contain the DNA chain and its copy and one protein chain. Save the file with a new name, eg. 1DP7_BDNA.PDB.
7. Use a similar procedure as BIO_Assignment_Week_8#R code: renumbering the model in the last assignment to change the chain ID.

PDBin <- "1DP7_DNAonly.pdb"
PDBout <- "1DP7_DNAnewChain.pdb"

pdb  <- read.pdb(PDBin)
pdb$atom[,"chain"] <- "E"
write.pdb(pdb=pdb,file=PDBout)

1. Use your text-editor to open both the 1DP7.pdb structure file and the 1DP7_DNAnewChain.pdb. Copy the DNA coordinates, paste them into the original file before the END line and save.
2. Open the edited coordinate file with VMD. You should see one protein chain and a B-DNA double helix. (Actually, the BDNA helix has a gap, because the R-library did not read the BRDU nucleotide as DNA). Switch to stereo viewing and spend some time to see how amazingly beautiful the complementarity between the protein and the DNA helix is (you might want to display protein and nucleic in separate representations and color the DNA chain by Position → Radial for clarity) ... in particular, appreciate how not all positively charged side chains contact the phosphate backbone, but some pnetrate into the helix and make detailed interactions with the nucleobases!
3. Then clear all molecules
4. In VMD, open Extensions→Analysis→MultiSeq. When you run MultiSeq for the first time, you will be asked for a directory in which to store metadata. You can use the default, or a directory of your choice; you may subsequently skip all steps that ask you to install "required" databases locally since we will not need them for this task.
5. Choose File→Import Data, browse to your directory and load one by one:

-Your model;

-The 1DUX complex;

-The 1DP7 complex.

1. Mark all three protein chains by selecting the checkbox next to their name and choose Tools→ STAMP structural alignment.
2. Align the Marked Structures, choose a scanscore of 2 and scanslide of 5. Also choose Slow scan. You may have to play around with the setting to get the molecules to superimpose: but the can be superimposed quite well - at least the DNA-binding helices and the wings should line up.
3. In the graphical representations window, double-click on the cartoon representations that multiseq has generated to undisplay them, also undisplay the Tube representation of 1DUX. Then create a Tube representation for 1DP7, and select a Color by ColorID (a different color that you like). The resulting scene should look similar to the one you have created above, only with 1DP7 in place of 1DUX and colored differently.
4. Orient and scale your superimposed structures so that their structural similarity is apparent, and the differences in binding elements is clear. Perhaps visualizing a solvent accessible surface of the DNA will help understand the spatial requirements of the complex formation. You may want to keep a copy of the image for future reference. Note whether it is plausible that your model could bind a B-DNA double-helix in the "alternative" conformation.

 

Interpretation

Task:

1. Spend some time studying the complex.
2. Recapitulate in your mind how we have arrived at this comparison, in particular, how this was possible even though the sequence similarity between these proteins is low - none of these winged helix domains came up as a result of our previous BLAST search in the PDB.
3. You should clearly think about the following question: considering the position of the two DNA helices relative to the YFO structural model, which binding mode appears to be more plausible for protein-DNA interactions in the YFO Mbp1 APSES domains? Is it the canonical, or the non-canonical binding mode? Is there evidence that allows you to distinguish between the two modes?
4. Before you quit VMD, save the "state" of your session so you can reload it later. We will look at residue conservation once we have built phylogenetic trees. In the main VMD window, choose File→Save State....

Links and resources

Altenhoff & Dessimoz (2012) Inferring orthology and paralogy. Methods Mol Biol 855:259-79. (pmid: 22407712)

[ PubMed ] [ DOI ] The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases, and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments.

• PDB file format (see the Coordinate Section if you are unsure about chain identifiers)
• Wikipedia on Structural Superposition (although the article is called "Structural Alignment")

Reference sequences

• Mbp1 ortholog sequences (all fungi)

 

Footnotes and references

 

Ask, if things don't work for you!

If anything about the assignment is not clear to you, please ask on the mailing list. You can be certain that others will have had similar problems. Success comes from joining the conversation.

• Do consider how to ask your questions so that a meaningful answer is possible:
  • How to create a Minimal, Complete, and Verifiable example on stackoverflow and ...
  • How to make a great R reproducible example are required reading.

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