The structure factor

Gerard Kleywegt does not take kindly to dodgy PDB files. I've been aware of his work in a general sense for a while, but after reading Practical Fragment's review of "Limitations and lessons in the use of X-ray structural information in drug design" by Andrew Davies, Stephen St-Gallay and Gerard Kleywegt I decided to read some of his papers. If you are looking for a broad overview (with excellent examples) of the issues to be considered if using PDB files, this paper is a good place to start.

The PDB is a wonderful resource, but it should be remembered that crystallography provides the electron density (at a specific resolution) not the structure, and everything from that point on is modelling. In other words, mistakes can be made due either due to ambiguities or incorrect assumptions. In most (?) PDB files, the electron density can be reconstructed to some extent from structure factors, and compared to the model to find regions where there is a lack of density, and hence a lack of evidence. In particular, the ligand can get very little love from the crystallographer (see references 43-48 in the paper).

I see that Kleywegt, after 15 years at Uppsala, has recently joined the Macromolecular Structure Database Group at the EBI as head of the PDBe, the European end of the PDB. Does this mean that dodgy PDB files will be a thing of the past?

Image credit: Ethan Hein

Mono, C# and OpenBabel

Matt Sprague and I have put in a bit of work making OpenBabel accessible on the .NET platform on Windows (see Matt's recent post, for example). .NET is like Microsoft's JVM. There are several .NET languages (e.g. C#, Visual Basic, IronPython), just like there are several languages for the JVM (e.g. Java, Jython, JRuby). If you write a program in any of the languages and compile it, the resulting classes can be used from any of the other languages.

Having finished the work for Windows, I started to look at Linux and MacOSX. There's an Open Source version of .NET called Mono, which is available cross-platform. After a bit of hacking around, I'm pleased to announce that the next release of OpenBabel will provide support for Mono on Linux and MacOSX. I've included an example C# and IronPython script that uses OpenBabel (see here).

One thing I was wondering though: anyone have any idea how widely Mono is used?

Cinfony paper published in Chemistry Central Journal

My Cinfony paper has just come out:
Cinfony - combining Open Source cheminformatics toolkits behind a common interface NM O'Boyle, GR Hutchison. Chem. Cent. J. 2008, 2, 24.

The paper describes the Why? and How? of Cinfony, shows some examples of use, and discusses performance. To download Cinfony, or for documentation on using Cinfony, please see the Cinfony web site.

Update (05/12/08): Table 3 in the paper caused a stir over at Chem-Bla-ics (Who Says Java is Not Fast and Cheminformatics Benchmark Project #1) and Depth-First (Choose Java for Speed).

Here's the abstract:

Background

Open Source cheminformatics toolkits such as OpenBabel, the CDK and the RDKit share the same core functionality but support different sets of file formats and forcefields, and calculate different fingerprints and descriptors. Despite their complementary features, using these toolkits in the same program is difficult as they are implemented in different languages (C++ versus Java), have different underlying chemical models and have different application programming interfaces (APIs).

Results

We describe Cinfony, a Python module that presents a common interface to all three of these toolkits, allowing the user to easily combine methods and results from any of the toolkits. In general, the run time of the Cinfony modules is almost as fast as accessing the underlying toolkits directly from C++ or Java, but Cinfony makes it much easier to carry out common tasks in cheminformatics such as reading file formats and calculating descriptors.

Conclusion

By providing a simplified interface and improving interoperability, Cinfony makes it easy to combine complementary features of OpenBabel, the CDK and the RDKit.

CrossRef + Ubiquity = Look up references without the pain

Imagine one of the following scenarios: you're reading a paper on your computer and want to look up a reference, or someone emails you the citation to an interesting paper, or you see some paper referenced on a website. If you want to read the paper that corresponds to the citation, you need to go to the website of the journal publisher, and enter all of the citation details or else click your way through years and journal issues to get to the paper you want. This is just the sort of tedious task that your computer should be doing for you instead.

And now, thanks to Geoffrey Bilder of CrossRef, it can. The details are described on the CrossTech blog. What it boils down to is that you can bring up the Ubiquity command window (CTRL+SPACE on Windows once Ubiquity is installed on Firefox), type "crossref" and use CTRL+V to paste a citation (or else select a citation on the webpage). After a couple of seconds, you'll see several hits for the paper in the CrossRef database, and clicking on Resolve will bring you directly to the online version of the paper. If you're feeling lucky you can just hit Enter after entering the citation and go directly to the first hit.

If you haven't already installed Ubiquity (see here for more info), I think it is worth it just to be able to use this particular CrossRef script.

Does my PNG look bad in this (journal)?

Did you ever submit a carefully-crafted image to a journal only to find that it looks terrible in the proofs from the publisher? This happened to me recently, and it took several iterations with the publisher to figure out what was happening.

The problem turned out to be transparency in PNGs. Basically, when you export a PNG from Inkscape, the background is left transparent and, more importantly, shading (e.g. to remove the jaggedness of diagonal lines) is done by mixing in a transparent layer called the alpha channel. Despite PNGs being around for years, it was only a couple of years ago that Internet Explorer finally got with the programme and handled transparency in PNGs. However, it seems it's still a problem with some publishers.

So, how to "fix" it? Open in Gimp, "Layer", "Transparency", "Remove Alpha Channel", "File", "Save". If you don't have an alpha channel, then the "Remove Alpha Channel" option will not be available.

Update 28/Nov/08: Pierre Lindenbaum suggested an alternative remedy: you can just draw a big white rectangle behind your image in Inkscape and everything will be okay. Paweł Szczęsny points out a better solution: in Inkscape, go to "File", "Document Properties", "Page", "Background", "RGB" and set the four values to 255 (white background, no alpha transparency).

Of OChRe, OSRA and OASA (but not OSCAR)

The field of Optical Chemical Recognition (OChRe) has been around a while with a number of well-established players (see Antony William's post on the subject). There's just a single open source program though, OSRA by Igor Filippov of the NIH, which was released in July 2007. Given an image containing one or several chemical structures, OSRA returns the SMILES string for the structures.

The dependencies of OSRA give an insight into the term "open source ecosystem". Rather than reinvent the wheel, OSRA makes use of open source libraries for optical character recognition (OCRAD, GOCR), bitmap to vector image conversion (POTRACE), messing about with images (ImageMagick, GREYstoration, ThinImage, CImg) and of course, cheminformatics (it uses either OpenBabel or RDKit). Luckily for Windows users, Igor provides a compiled version.

Back in July, I emailed Igor to request a new feature, the ability to output an SDF file containing the coordinates taken from the image. Three hours later he replied that he'd added it. And now, only four months later, I've gotten around to testing it (insert excuse here)...

Anyway, one nice way of testing conversion code is by roundtripping (or "There And Back Again"). So I took the now legendary depiction faceoff test file (see, for example, here), used the coordinates therein to create a PNG image using OASA (via Pybel or cinfony), ran OSRA on the resulting image to get some coordinates, and then used those coordinates to generate a PNG again. By eyeballing the two PNG images, it's possible to discover errors. So, here are the results of the OChRe.

Notes:
(1) If you notice any trends in the errors, comment below and Igor might fix them.
(2) Where there are missing images after the OChRe, this is where OSRA missed a bond (probably reasonably), generated two molecules, and caused OASA a headache (it only handles single molecules).

Here's the code:

import pybel
import popen2

odir = "images"
for mol in pybel.readfile("sdf", "onecomponent.sdf"):
    title = mol.title
    print title
    mol.draw(usecoords=True, show=False, filename=os.path.join(odir, "%s_oasa.png" % title))
    o, i, e = popen2.popen3("../osra-trunk/osra -f sdf %s/%s_oasa.png" % (odir, title))
    osrasdf = o.read()
    newmol = pybel.readstring("sdf", osrasdf)
    try:
        newmol.draw(usecoords=True, show=False, filename=os.path.join(odir, "%s_osra.png" % title))
    except AssertionError:
        print "Unconnected!"

Image credit: Jason.Hudson

Food for thought? Citations vs Accesses

Checking out the latest article in Chemistry Central Journal, I was surprised to see that in just 5 days after publication it had 5000 accesses. Today after 8 days, it has around 9000. This already makes it the most accessed paper ever from that journal. The article in question is by DP Naughton and A Petroczi, "Heavy metal ions in wines: meta-analysis of target hazard quotients reveal health risks".

At first, I couldn't figure out what was going on. A quick google, however, shows that the article has been picked up by several bloggers and news sites chasing the "wine is bad for you" angle. I also noticed that the paper is top of the BioMedCentral most viewed articles in the last 30 days. Of the other top 10, 6 are on nutrition or food-related topics.

I guess that this highlights a difference between the number of citations and the number of accesses. The number of citations reflects the impact of the paper within the scientific community, while the number of accesses also includes the impact within the broader community, arguably a more valid measure of its importance :-). Of course, for closed access journals only scientists will be able to access the papers and so the difference will not be so great (except in order of magnitude, that is).