A number of crystallographers have been studying macromolecules related to various aspects of cancer. How much has research in general reduced the mortality in the USA (unable to find world wide data) over the last 60 years? How was this graph made?
The above graph is from slide 6 of this powerpoint presentation by the Center of Disease Control and Prevention (CDC). (reference: www.cdc.gov/nchs/ppt/hpdata2010/focusareas/fa03_charts.ppt)
2000: 199.6
2001: 196.0
2002: 193.5
2003: 190.1
2004: 185.8
2005: 183.8
For the 2000-05 data, the closest link can be found here, after which select cancer in the top toggle.
The stability of the cancer mortality rate in the USA over about the last 60 years is fascinating. Before seeing this data, I would have assumed that with all the money spent on cancer research that we would have significantly reduced the mortality rate.
Implication, if you have cancer today, you have about the same chance of living as in 1950.
I had never seen this information by any news agency and thought it would be worth discussing, thoughts?
As a side note, thanks Norm for digging through the CDC website to find this information.
If you spend any significant amount of time searching for scientific articles then you may find this helpful.
My method for finding an article used to involve Googling my desired topic, only to realize I am not getting the publications needed. I then resort to searching with Google scholar.
Many of you may be familiar with PubMed, as it is a popular alternative. I haven’t been using PubMed because you can’t download full articles directly from their site. Although, sometimes I will search PubMed, find the article title and then search for that article specifically using Google.
After coming across this new program, I will never use PubMed again.
The answer…… is HubMed.
The site is easy to use: type in your desired topic, hit enter.
Why use HubMed?
1) HubMed tracks down the full article (unlike PubMed ) and allows you to view it easily.
3) Huge time saver when citing, especially with Endnote (detailed info here)
4) Has a Firefox search plugin so you don’t have to go to the site, just toggle to the symbol.
5) Rank Relations – select a number of articles, add to the clipboard, click rank, and a list of articles is generated that closely relate to the original selected articles (detailed info here)
6) TouchGraph Applet – select a number of articles, add to clipboard, click graph (detailed info here)
For example, I searched “lysozyme matthews” and decided to only select articles (by clicking on ‘Clip’) with ‘T4′ in their title. There is a counter located next to the ‘clipboard’ button found in the upper right. Everytime you select (by clicking on ‘Clip’), an article, the number increases.
Click on ‘clipboard’ followed by ‘Graph’ in blue, right side, below the article abstract. After clicking Graph, the following image appears showing how different topics are related to your search.
By clicking on a node (the floating boxes) you will be able to view articles described on that particular node.
Note: I didn’t have luck with 9 articles clipped in my clipboard, but did with 19. So there is a minimum number of articles that need to be added into your clipboard.
The documentation for HubMed explains their features in detail.
Naturally Obsessed is a movie that documents the trials and tribulations of a X-ray crystallographic laboratory (if you want to read the two page press release click here). I am doubtful that I will get the opportunity to view this film, but wanted to post about it in case the film ends up playing in your area.
Even if you won’t be able to see the movie, the website is worth looking at especially if you have everyone someone in your life that you have tried to explain what you do, but doesn’t really get it.
The site has a number of video clips, my favorite is under – the science -> X-ray Crystallography -> Prof. Richard Axel (first clip)
I still smile every time I see the student setting up crystal trays with the intense music in the background. I have come across a favorable review about the movie, but would love to hear from others that have seen it.
I realize using the term easy and PyMOL together (at least when dealing with the free version) is somewhat of an oxymoron. So there must be a coveat which is that if you want to make a movie with PyMOL you need to get eMovie. If you haven’t already wasted 6 hours trying to figure out how to make a movie with PyMOL alone feel free to comeback.
Welcome back, so once you have installed eMovie (make to put the files in the correct location as described on the download page) the next step is to start up PyMOL.
If installed correctly you should see an additional GUI (at right) as shown below:
My goal here is to give a basic introduction that will yield a movie that rotates a protein in a full circle. The eMovie website has more advanced examples, but they are not as step by step as shown here.
Usually during a presentation the protein is shown with a white background. This can be done in PyMOL via the PyMOL GUI under Display -> Background -> White
eMovie GUI click Scenes (views, appearances)
Create new scene/Save scene…
name: rotation
click on Rotation in the eMovie GUI (right below Scenes on the GUI)
Axis: y
Degrees: 360
Start Frame: 0
Action Length: 120 -click ok
click Add stop (in GUI)
Insert stop frame: 120
You can now view how the movie looks so far at this point by using the PyMOL GUI click Play (roughly the center button in the GUI)
Tip: save often because if PyMOL or eMovie freeze your settings will be lost (this happens quite frequently).
eMovie GUI click View Storyboard
click on Stop
Deleted selected action
*you must remove the stop before exporting*
eMovie GUI click Export eMovie
(set GUI viewing window to the size of the movie for viewing)
This notice is especially critical if you have different views. You need to make sure that the size of the PyMOL window is consistent. I would recommended making your entire movie in one sitting to avoid a sizing issue.
Tip: If you are going to do multiple views then name them in alphabetical order – in the order in which they appear. For example, you want to do a rotation then zoom – name the rotation frames arotation and bzoom for the zoom (r is before z therefore it would be the right order without the a/b prefix, but hopefully you get the idea).
As a personal preference, I set up a separate folder for each movie which I then export the frames from eMovie into.
Load the rendered images into Adobe ImageReady CS2
File -> Import then select the folder containing the images
You can highlight all the images and adjust the time to 0.1 seconds for smooth playing. Also if you want a delay such as from a rotation to a zoom you can increase the time on that particular frame.
File -> Export original document
Quicktime Movie (may want to consider the type of computer the presentation will be presented on)
Compression settings jpeg -> Best (quality)
Tip: Powerpoint reads the location of the movie files that have been inserted. Therefore you should load the frames on the flash drive with your talk and then save them. This should help avoid the ‘I am not sure why this movie isn’t working’ during your presentation.
P212121 is the most common space group in macromolecular crystallography. I have not yet found an explanation of why P212121 has resulted in more deposits than any other space group in the PDB. As you may already know there are a total of 65 possible space groups for macromolecular crystallography. P212121 comprises almost 25 percent of those deposited within the PDB. This strange occurrence inspired the naming of this blog.
Phil Evans is the programmer behind Scala which is used for scaling and merging. The presentation and slides were given at the Daresbury Laboratory, UK in 2001. This presentation gives a behind the scenes look at the various inputs and outputs of Scala. I would classify this as a though introduction to scaling and merging.
The presentation runs 52 minutes in length. Another aspect which is refreshing is that Phil simply states what he knows and does not. I for one have been to too many presentations that sidestep perplexing issues and questions.
Questions addressed:
Why are intensities on different scales?
What is the real resolution of your diffraction?
Why you should collect differently for phasing and scaling?
Notes of interest:
Turn B-factor on during Scala if you believe there is a large amount of radiation damage
Rmerge and multiplicity are inversely related
-the two references mentioned relating to this point are Weiss and Diederiches
My only compliant would be that the questions are difficult to hear at times.
Many people that are new to crystallography have a hard time ‘visualizing’ what is occurring between real and reciprocal space. The most intuitive and user friendly program that I have found to help with the problem is XRayView 3.0, which is free to educational institutions.
What concepts does XRayView touch upon?
The software uses an interactive gui to introduce the concepts of X-ray diffraction by crystals, including the reciprocal lattice, the Ewald sphere construction, the wavelength dependence of the reciprocal lattice, primitive and centered lattices, systematic extinctions, rotation photography, space group determination and the alignment of crystals by examination of reciprocal space. Laue cones, photography and group symmetry are also covered with this software.
XRayView is available for IRIX (is anyone still using SGI?), Windows, Linux and Macintosh.
Information about using XRayView can be found here.
The program comes with a number of exercises which are worth working through. In addition, I would recommend simply ‘playing around’ with different parameters, noting the effects of each adjustment. The citation for XRayView can be found here.
The process of indexing is determining the space group from your diffraction pattern. The points of intensity that are hopefully present in your diffraction pattern, I will refer to as spots.
The following are the very basic steps needed to index your diffraction pattern. You made need more advanced commands depending on your data in which you should refer to the ipmosflm documentation.
The process of indexing with ipmosflm loosely moves from top to bottom of the gui.
Initially, you should cover the beam stop or any other shadows on your diffraction image. Use Beam / mask images, which is the bottom button of the gui.
1) Find where the spots are located
-click Read Image (can select an image), Find Spots 2) Move to another image to find spots
-click Read Image (select a different image), Find Spots
(you may get better results by selecting images located away from each other)
(if you have between 200-700 spots then proceed to the next step) 3) Select images to index
-click Select images and select the images from the corresponding number listed
(the program usually detects which images it should use, but best to make sure) 4) Autoindex
-select the best solution, lets start with the default
(you need to type both the solution number and then enter the space group)
(I have found it best to select lower symmetry since it can be increased later) 5) Predict the location of where the spots should be located based on your autoindexing
-click Predict
(if they do not match then you could have a number of issues: 1) wrong space group 2) cracked crystal 3) wrong beam center 4) wrong rotational parameters)
-click Clear prediction (remove the spots that you just predicted) 6) Estimate mosiacity
-the lower this number the better (looking for number around .4-1.2) 7) Refine Cell Integration
(keep an eye on the integration despite it maybe boring sometimes the crystal may drift during collection or some other issue)
Rarely will you ever have to significantly vary from the default inputs. If you are new to using ipmosflm, I would recommend simply working with the default options to gain a sense of how the program functions. Followed by examining what each option means – ie. don’t become intimidated by all the options to the point of not giving it a try (as long as you have images you can always start over).
The world of graduate school is such a unique subculture that it maybe best described by comics. If you (undergraduate, graduate or professor) are involved in research at any academic institution, you should find something that you will enjoy.
I have included a link to the most popular 200 comics, here.
***see comments for now even a faster way*** Electron Density Server (EDS) provides the scientific community with a service for evaluating the electron density (and, indirectly, some aspects of the model quality) of crystal structures deposited in the Protein Data Bank. The reference for using the server can be found here.
Why would being able to quickly view electron density maps be helpful?
Allows others to gain a deeper understanding/appreciation of your interpretation of how the structure should be built. I have read papers which state something along the lines of “density was missing so I can’t build a given loop.”
Well, how much density was missing? Do you know the carbon alpha locations, but not the slide chains? etc…
Overall, this tool allows for a method to validate a give crystallographic structure. A more complete discussion of the need for the deposition of structure factors can be read in the above reference.
Here are the steps to use the server (it is not hard):
1) submit desired PDB ID into server
2) Left hand side is a ‘Downloads’ section
3) Click on ‘Download maps’
4) Select map format
-if you are using Coot then download either the ccp4 or cns format
5) Select type and download
6) Double click on .gz file, which will cause the files to open in a folder
7) Highlight desired file then click ‘extract’ usually in the upper part of the window
Finally, Open Coot -> File -> Open Map…
If you need the coordinates (where the atoms are located, sometimes called a pdb file since that is its extension) you can download it at the EDS.
There a number of neat options in the EDS, but they will have to wait for another post.
Stephen Curry summed up the real life application of the EDS quite well:
Thanks to the Electron Density Server, it took me all of 30 seconds to go from “Hmm, I’d like to check that out” to “Oh, I see what they mean.” On the EDS web-page you simply enter the PDB identifier for the structure (taken from the paper) and it immediately serves up a package of files that, once unzipped, lets you fire up the molecular graphics program O. You can then get straight to work: in the O session the structure coordinates and maps are already loaded. The EDS is a fantastic piece of work.
Kind of sounds like a clip from an infomercial.
As a side note you can check out Stephen’s blog here, which is an interesting blend of real and reciprocal space.
Integration