I mentioned, in a previous post , a documentary called Naturally Obsessed. I expressed an interest in viewing the movie and encouraged readers to take advantage should such an opportunity present itself. Soon after the post, I received an email from one of the movie’s producers offering to send me a copy of the movie. You guys ROCK!
I’ll start on that positive note and, after viewing the movie, it looks like I’ll be ending on one as well.
Initially (before I received the movie), I thought it would simply be a good way to educate family and friends about the life of a crystallographer or graduate student in this field. Turns out, the movie is not only a great way to introduce people to this line of work, but a beneficial tool that can be used to recruit new students to this area of science.
The movie does not disappoint. It has some very entertaining characters who easily capture and hold the viewers attention.
The movie helped me realize a few things. First, how caught up I can get in my projects. Second, I gained an appreciation for the other researchers out there, as we are all going through the same ups and downs. We may work in separate labs but, ultimately, we all have the same goal: to understand how nature works. Finally, we all eat pizza on synchrotron trips.
Important note:
If you’re having difficulty getting your crystals to diffract properly, try setting up your trays to ‘Yoshimi Battles the Pink Robots’ by the Flaming Lips. Seems as though our little proteins have an affinity for good music.
Favorite quote by Kil(partick) Carroll:
“Science is not done in a vacuum. Everything, in some sense or another, is a collaboration…eventually everyone gets stuck. The only way to do it is by talking to other people who have been where you are and can give a relatively logical approach to solve that problem.”
Final note: Naturally Obsessed will be playing at the ACA this year. DEFINITELY worth checking out. I will update you when I hear a specific time and location.
The program COOT by Paul Emsley and Kevin Cowtan is simply, awesome (pdf paper citation). I usually read the ‘tips’ that appear when starting the program and wanted to compile a comprehensive list:
Note: if this is difficult to read try pressing ‘ctrl then +’ as needed
To centre on a particular atom, click it with middle mouse (if that doesn’t seem to work it may be because the molecule is not active).
+ and – on the keyboard change the contour level
To move just one atom (in Regularize, RS Refine, or Rotate/Translate mode) use Ctrl Left-mouse to pick an atom (you have to be accurate).
There is a mailing list for Coot development and discussion at http://www.jiscmail.ac.uk/lists/coot.html
Use Ctrl Left-mouse to drag (for example) a blob of density to the the pointer
Slow recentering? Try Draw -> Smooth Recentering and reduce the number of steps
Want distance of the atoms to the pointer? Use Measures -> Pointer Distances…
To label an atom: Shift Left-mouse on it
To make atoms be insensitive to clicking, deactivate it by unclicking that molecule’s "Active" button in the Display Control window
Can’t label or centre on some symmetry atoms? It’s a known bug. (For now, drag that atom closer to the centre of the screen).
Use function key ‘F8′ to make a rendered snapshot.
Use the Ctrl to rotate the view when changing Chi angles.
Too many cis peptides when using dragged refinement? Use the
Planar Peptide Restraints’ suggested in the Coot FAQ.
Use the Ctrl to rotate the view when using Delete.
When in skeleton mode, new skeleton can be displayed around the current point using the ‘S’ key.
When in baton mode, the baton can be rotated independently from the Guide Points by using the ‘B’ key (it’s a toggle).
When Editing Chi Angles, switch between the angles quickly using the ‘1′, ‘2′, ‘3′, ‘4′ keys.
Use "refmac-extra-params" to pass refmac your personal parameters.
Use "(poly-ala imol)" to turn molecule number imol into poly-ALA. Use "(poly-ala imol ‘SER)" to turn it into poly-SER."
Use "(fit-protein imol)" to rotamer search and real-space refine all residue of molecule number imol."
Shift Ctrl right-mouse rotates round screen Z.
Ctrl + right-mouse + horizontal (left to right) mouse movement moves the view in screen Z.
Ctrl right-mouse up-down drag changes the slab.
Use "(set-idle-function-rotate-angle 0.05)" to change the spin speed.
(ligand-expert)" enables the GUI editting of some ligand-fitting parameters.
Use keyboard + and – to zoom in Ramachandran and Kleywegt Plots
The ‘U’ key undoes last nagivation (e.g. re-centering on new pdb file).
The ‘D’ and ‘F’ keys change the clipping/slabbing.
(view-matrix)" prints the current view matrix, useful for molscript, perhaps.
Baton-building low resolution maps is better done with maps that have increased sampling rate (2.0 or 2.5).
Coot can read SHELXL .res files. (It can write them too.)
Clear All Atom Labels" can be found under Measures -> Distances & Angles. Obviously.
Esc and Return are keyboard accelerators for Reject/Accept for Refinement and Regularization.
Restraints for alpha helical and beta-strand structure can in the Refinement/Regularization Control Panel
To disable coot tips: add "(no-coot-tips)" to your ~/.coot file.
It is possible to accidently invert chiral centres. Use Validate -> Chiral Centre to check.
The following is a rearrangement of articles primarily by Philip E. Bourne. I have also included videos and a couple of additional articles which were not found in the original link above. Professor Bourne is the founding editor-in-chief of the open access journal PLoS Computational Biology.
I have mentioned the Zhang server before and so thought I would share 2 ways this server can be helpful to crystallographers.
The Zhang Server (I-TASSER server) uses the amino acid sequence of a protein to predict its structure. The server is simple to use– enter in your desired amino acid sequence and email.
Note: You need to have an academic email address to use the server freely. (more information about the server).
Good:
1) Great resource: the server allows users to submit their sequences to be analyzed
2) Free to all academic users
Bad:
1) Turn around time: it took about two weeks before my predictions were complete (this will vary greatly depending on how many proteins are in the queue upon submission)
The two ways this server could be helpful:
First
I was able to find another protein that may have a similar fold to the one I am working on. Were it not for this server, this protein would have gone unnoticed. The Zhang server searches through the PDB looking for homology that you may miss.
Second: In silicomolecular replacement? Could the coordinates from the Zhang server then be used for molecular replacement? This idea is being explored by MR-CAFASP. I have not heard of many crystallographers testing whether in silico molecular replacement would work.
Has a novel protein been published using in silico predictions? In the future, I will play around with the coordinate file from the Zhang server to determine whether or not the results are robust enough to yield reasonable crystallographic statistics.
CASP stands for the Critical Assessment of Techniques for Protein Structure Prediction. A number of other blogs have discussed various aspects of CASP:
In short, CASP holds a competition every other year with the goal of attaining an objective measurement of the current capabilities in protein structure prediction. The competition was started in 1994 and the results have shown improvement, however, they have begun to level off.
A number of ‘assessments’ (categories) have been examined over the years which include: high-accuracy, template based and template free modeling (more details here and at the CASP wiki).
Fold It is a game in which users compete to determine the most likely (stable) protein structure (see blog post above for details). Another approach to the protein folding problem has been the Folding@Home project that allows you to download software that bans together many computers to act as a single supercomputer (similar to Seti@Home).
TED: Ideas worth spreading. The slogan really exemplifies what occurs at this conference, namely: high quality topics, speakers and presentations.
I have not seen all the presentations, but wanted to include 3 that I thought would be relevant to this site (each presentation is about 20 minutes in length).
Dr. James Watson: The double helix and today’s DNA mysteries
-How he (and others) discovered the structure of DNA and current DNA research
-I really get a kick out of seeing our founding members still active in research
Bill Gates: How I’m trying to change the world now
-He presents scientific work related to malaria as well as a number of fascinating statistics related to education
Kevin Kelly: The first 5,000 days of the web, and the next 5,000
-Although this presentation is not crystallographic in nature, it is too good to miss
-I enjoy when people make a compelling case regarding what they think will occur in the future
The two books that are mentioned in the above talks are available through Amazon:
If there are any other talks you enjoyed, please feel free to leave a comment!
2) Download the coordinates, followed by the map in CCP4 format
3) Extract the files that you downloaded
(7-zip will work for windows if you do not already have it installed) **Rename using the term map: example) 1c8u.ccp4 renamed to 1c8u.map.ccp4
4) Start PyMol and open the pdb and map files (File -> Open)
5) Display the map by clicking on the ‘A’ for actions then mesh followed by selecting your desired mesh level – as shown above (I did 2.0 in this example)
-Below: if you look at the upper right corner you can see what is displayed by if it is highlighted (light gray) in the PyMol window (in this case 1c8u.map is off)
6) Enter the information available on the PyMol Wiki into the command line (enter everything left of the # symbol)
select site, resi 39-50 # residues that are displayed for viewing
isomesh map, 1c8u.map, 2.0, site, carve=1.6 #display the map around the selected residues (change 1c8u.map to correspond to how you named your .map file)
color grey30, map # sets map to 30% gray
bg_color white #sets background to white
set ray_trace_fog, 0 #turns off raytrace fog–optional
set depth_cue, 0 # turns off depth cueing–optional
set ray_shadows, off #turns off ray-tracing shadows
I then zoomed in on one of the selections then showed ‘S’ ’sticks’ in the PyMol window.
7) Click on ‘ray’ for ray tracing then followed with ‘color grey30, map’ since the mesh looked black (note again what is toggle on and off in the upper right)
Finally, you can add labels using GIMP or Photoshop
Don’t forget to cite PyMol
If you would like to learn how to easily make a movie using PyMol check this post out.
I previously mentioned the Protein Data Bank (PDB). In brief, it is the world wide depository of macromolecular structures. Currently, 150,000 scientists from more than 150 countries visit the PDB each month. I am grateful that the PDB is freely available as it has served as an invaluable resource. A number of items have come to mind regarding the search feature in the PDB. I do not have the background to properly gauge the feasibility of these 10 search improvements, so please think of the following as a wish list rather than demands.
1) Eliminate the need for pop-up windows
-most browsers block pop-up windows, making these searches mildly annoying.
2) Have an option to simplify the results
-such as eliminating the images of the proteins (faster loading)
-reduced space would allow for more macromolecules to be displayed on each page (perhaps allowing 15 macromolecules to be shown, rather than 10)
3) List residues that are not within electron densities as a percentage
-residues at the termini or in flexible loops may not be within the electron density, however this may not be noticed by researchers who are unfamiliar with crystallographic models
-by seeing a percentage, a researcher may become aware that he or she should be examining the coordinate file with the electron density (like that which can be generated using the electron density server)
4) Eliminate separate ‘Evaluate Subquery’ toggles
-so it resembles a Google search
5) Save the original search
-it is frustrating having to toggle 5 ‘Evaluate Subquery’ entries and then, should you want to adjust one, have to completely re-enter all of them.
6) Provide an entry of when the structure factors will be available on the structure summary page
7) Ability to automatically load the structure factors with electron density
-similar to what can be done using the electron density server
Be able to search using metals
-instead of using a separate database
9) Be able to receive an email notification if/when a structure is deposited by a colleague
-this will allow you to monitor labs that are working on similar projects
-you’ll know when to send a colleague an ‘even a blind squirrel will eventually find a nut’ note
10) Have a ‘Find Related Articles’ button
-if applicable, auto enter the title of the article into Hubmed
I was searching through the PDB last night and was amazed at the range of B-factors there were at a 3 Å resolution.
I then wondered, at what point should we not model the location of an atom?
First, a reminder:
The B-factor is a measure of the effective diameter of an atom’s electron density. Static (think crystal packing) and thermal motion can effectively disperse the electron density of a given atom, causing an increase in it’s B-factor. The B-factor is related to the rms error in an atom’s position (u) by the equation: B=79*u2. For this reason, B-factors are related to resolution (reference).
Similar definitions of the B-factor can be found here and here.
If you end up searching through the PDB, you will find 1036 proteins (this number will change over time) deposited that have a 3.0 Å resolution.
First example: PDB entry 2D7H, with the space group H32 and a unit cell, is as follows:
Length [Å] a 111.15 b 111.15 c 260.48
Angles [°] alpha 90.00 beta 90.00 gamma 120.00
Low B-factor
ATOM 759 CB ALA A 99 77.336 -1.412 30.730 1.00 21.08 C
High B-factor
ATOM 975 N MET B 24 38.372 12.422 49.773 1.00200.00 N
ATOM 976 CA MET B 24 39.225 11.256 49.976 1.00200.00 C
ATOM 977 C MET B 24 40.626 11.792 50.257 1.00200.00 C
ATOM 978 O MET B 24 41.131 12.633 49.511 1.00200.00 O
ATOM 1068 CB PHE B 36 45.647 -1.156 36.281 1.00200.00 C
ATOM 1069 CG PHE B 36 47.091 -1.333 35.905 1.00200.00 C
ATOM 1070 CD1 PHE B 36 48.100 -0.752 36.669 1.00200.00 C
ATOM 1071 CD2 PHE B 36 47.445 -2.085 34.788 1.00200.00 C
ATOM 1072 CE1 PHE B 36 49.442 -0.919 36.327 1.00200.00 C
ATOM 1073 CE2 PHE B 36 48.783 -2.257 34.436 1.00200.00 C
ATOM 1074 CZ PHE B 36 49.782 -1.673 35.209 1.00200.00 C
ATOM 1178 N GLU B 54 51.227 15.579 34.700 1.00200.00 N
ATOM 1179 CA GLU B 54 51.753 15.584 33.337 1.00200.00 C
ATOM 1180 C GLU B 54 50.633 15.768 32.310 1.00200.00 C
ATOM 1181 O GLU B 54 50.707 16.659 31.463 1.00200.00 O
ATOM 1187 N LEU B 55 49.599 14.932 32.381 1.00200.00 N
ATOM 1188 CA LEU B 55 48.477 15.043 31.448 1.00200.00 C
ATOM 1189 C LEU B 55 47.326 15.859 32.072 1.00200.00 C
ATOM 1190 O LEU B 55 47.344 16.161 33.269 1.00200.00 O
(I suspect that 200 is the maximum value allowed during data processing)
Second example: PDB entry 3CSM in the same space group with a larger unit cell:
Length [Å] a 203.50 b 203.50 c 128.70
Angles [°] alpha 90.00 beta 90.00 gamma 120.00
Low B-factor
HETATM 4160 CH2 TRP A 300 60.946 11.402 30.293 1.00 2.00 C
High B-factor
HETATM 4192 O4 TSA A 400 35.340 17.976 38.640 1.00 96.69 O
(this is the last residue in the peptide, so it will often have a higher B-factor)
A number of other variables could effect the B-factor such as crystal packing, radiation damage or the use of partial occupancy. I find the difference between these two structures fascinating. Taking the B-factor into consideration is important, especially if a cartoon is presented without any crystallographic information.
Though not perfectly accurate, this scattering factor calculator can be used to examine the mean atom displacement for a carbon with a B-factor of 200.
The result is a 1.59 Å mean atom displacement which, as I mentioned in the introduction, makes one wonder at what point should we not model the location of an atom?
Marjorie Harding, at the University of Edinburgh, has a resource that can be helpful in learning about coordination sites in metalloproteins that have been deposited within the PDB. In addition to coordination number, there are also statistics related to geometry, distances, model resolution and donor group preferences (such as Asp usually donates to Mg instead of His).
In addition, Dr. Harding has been involved in the development of a database dedicated to ‘Metal Sites in Proteins’ — MESPEUS database. This database is current as of January 2007 and allows you to search by PDB code, specific metals, coordination groups and numbers. Regular updates are expected in the future. The citation for the database can be found at the bottom of this page.
Finally, you can add labels using GIMP or Photoshop