James,
I had in fact just come to the conclusion that the indexing was
consistent with 3dko for 'possible' but not for 'impossible',
which I suppose was logical.
George
Woops! sorry folks. I made a mistake with the I(+)/I(-) entry. They
had the wrong axis convention relative to 3dko and the F in the same
file. Sorry about that.
The files on the website now should be right.
http://bl831.als.lbl.gov/~jamesh/challenge/possible.mtz
http://bl831.als.lbl.gov/~jamesh/challenge/impossible.mtz
md5 sums:
c4bdb32a08c884884229e8080228d166 impossible.mtz
caf05437132841b595be1c0dc1151123 possible.mtz
-James Holton
MAD Scientist
On 1/12/2013 8:25 AM, James Holton wrote:
Fair enough!
I have just now added DANO and I(+)/I(-) to the files. I'll be very
interested to see what you can come up with! For the record, the
phases therein came from running mlphare with default parameters but
exactly the correct heavy-atom constellation (all the sulfur atoms in
3dko), and then running dm with default parameters.
Yes, there are other ways to run mlphare and dm that give better
phases, but I was only able to determine those parameters by
"cheating" (comparing the resulting map to the right answer), so I
don't think it is "fair" to use those maps.
I have had a few questions about what is "cheating" and what is not
cheating. I don't have a problem with the use of sequence
information because that actually is something that you realistically
would know about your protein when you sat down to collect data. The
sequence of this molecule is that of 3dko:
http://bl831.als.lbl.gov/~jamesh/challenge/seq.pir
I also don't have a problem with anyone actually using an
automation program to _help_ them solve the "impossible" dataset as
long as they can explain what they did. Simply putting the above
sequence into BALBES would, of course, be cheating! I suppose one
could try eliminating 3dko and its "homologs" from the BALBES search,
but that, in and of itself, is perhaps relevant to the challenge:
"what is the most distance homolog that still allows you to solve the
structure?". That, I think, is also a stringent test of
model-building skill.
I have already tried ARP/wARP, phenix.autobuild and
buccaneer/refmac. With default parameters, all of these programs
fail on both the "possible" and "impossible" datasets. It was only
with some substantial tweaking that I found a way to get
phenix.autobuild to crack the "possible" dataset (using 20 models in
parallel). I have not yet found a way to get any automation program
to build its way out of the "impossible" dataset. Personally, I
think that the breakthrough might be something like what Tom
Terwilliger mentioned. If you build a good enough starting set of
atoms, then I think an automation program should be able to take you
the rest of the way. If that is the case, then it means people like
Tom who develop such programs for us might be able to use that
insight to improve the software, and that is something that will
benefit all of us.
Or, it is entirely possible that I'm just not running the current
software properly! If so, I'd love it if someone who knows better
(such as their developers) could enlighten me.
-James Holton
MAD Scientist
On 1/12/2013 3:07 AM, Pavol Skubak wrote:
Dear James,
your challenge in its current form ignores an important source
of information for model building that is available for your
simulated data - namely, it does not allow to use anomalous
phase information in the model building. In difficult cases on
the edge of success such as this one, this typically makes
the difference between building and not building.
If you can make the F+/F- and Se substructure available, we
can test whether this is the case indeed. However, while I
expect this would push the challenge further significantly,
most likely you would be able to decrease the Se incorporation
of your simulated data further to such levels that the anomalous
signal is again no longer sufficient to build the structure. And
most likely, there would again exist an edge where a small
decrease in the Se incorporation would lead from a model built
to no model built.
Best regards,
--
Pavol Skubak
Biophysical Structural Chemistry
Gorleaus Laboratories
Einsteinweg 55
Leiden University
LEIDEN 2333CC
the Netherlands
tel: 0031715274414 <tel:0031715274414>
web: http://bsc.lic.leidenuniv.nl/people/skubak-0
--
Prof. George M. Sheldrick FRS
Dept. Structural Chemistry,
University of Goettingen,
Tammannstr. 4,
D37077 Goettingen, Germany
Tel. +49-551-39-3021 or -3068
Fax. +49-551-39-22582
