<div dir="ltr">Hi Pavel,<div><br></div><div style>The maximum entropy maps look wonderful and it looks like they might be useful in the doubtful cases. It is however hard to compare them to the standard 2Fo-Fc when the grid sampling isn't the same.</div>
<div style><br></div><div style>Cheers,</div><div style>Morten</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">On 14 February 2013 19:46, Nathaniel Echols <span dir="ltr"><<a href="mailto:nechols@lbl.gov" target="_blank">nechols@lbl.gov</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div class="im">On Thu, Feb 14, 2013 at 7:50 AM, Pavel Afonine <<a href="mailto:pafonine@lbl.gov">pafonine@lbl.gov</a>> wrote:<br>
> The algorithm implemented in Phenix is fast: it should take from a few<br>
> seconds for small structures to a few minutes for large ones. I do not<br>
> understand why it should take long time to run (as pointed out in that Acta<br>
> D paper).<br>
<br>
</div>I suspect that's because they're running a much different algorithm.<br>
The Phenix implementation doesn't reproduce the difference densities<br>
they display, for what it's worth, but since neither the code or even<br>
the binaries for the ENIGMA program are available (!), it's hard to<br>
know exactly what they're doing differently.<br>
<div class="im"><br>
>> I see that phenix.maximum_entropy_map is now a command in Phenix.<br>
>> Some quick questions: Where is this likely to be must useful and does it<br>
>> take ridiculously long to run? From the Nishibori 2008 paper in Acta D it<br>
>> seems like this would mainly be useful for very high resolution structures<br>
>> that you would normally call complete - and that it would take a very long<br>
>> time to compute.<br>
<br>
</div>I must say, I find that paper very misleading - the conventional maps<br>
from Phenix are sufficient to identify the alternate conformation of<br>
Tyr33 in Figure 2, for instance. �The published structure doesn't have<br>
*any* alternate conformations, which at 1.3� resolution is absurd, so<br>
it's very easy to produce an improved model without doing anything<br>
fancy. �In Figure 5 they compare a conventional omit map with the MEM<br>
version, but they're using much different grid spacings, so of course<br>
they look different!<br>
<br>
Maximum entropy tends to be used most frequently by small-molecule<br>
crystallographers looking at charge densities, which is partly what<br>
the Nishibori paper is doing. �For proteins, this is what Nicholas<br>
Glykos (author of GraphEnt) told me about its use:<br>
<br>
"For well behaved and complete data the maps look very similar. But in<br>
other cases the ability of the maxent map to alleviate the problems<br>
arising from series termination errors made a difference. We had one case<br>
of [redacted] that diffracted to ~0.8A. Four passes were made to measure<br>
both high and low resolution data. Unfortunately, for one of the passes the<br>
time-per-frame was completely wrong and we ended-up with a data set missing<br>
all terms between ~4 and ~3 Angstrom. The conventional FFT had numerous<br>
peaks arising from the series termination errors, the maxent map was<br>
significantly better. In other cases, we use maxent to artificially sharpen<br>
maps (by reducing the esd's) while avoiding the noise introduced by normal<br>
(E-value-based) sharpening."<br>
<br>
-Nat<br>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br>Morten K Gr�ftehauge, PhD�<div>Pohl Group</div><div>Durham University</div>
</div>