Christian,
I happened to see your post to the CCP4 bulletin board. In answer to
your question, we continue to base all of our work on proper
experimental design. Two papers cited below document the flexibility
and power of response surface methods in biochemical experimentation,
especially in cases where the readout is quantitative, rather than
qualitative as is the case necessarily with optimizing protein
crystals. That said, I should add that there is no free lunch, and
the experiments, especially in Chester, et al., had to be replicated
numerous times to achieve satisfactory signal to noise, because the
readout (run-off transcription) was very noisy. Nonetheless, the
effort paid off handsomely, and we discovered several new and
unexpected phenomena about RNA editing by the APOBEC-1 enzyme and the
role of auxiliary factors.
Charlie
Chester, et al., 2004, Optimization of apolipoprotein B mRNA editing
by APOBEC1 apoenzyme and the role of its auxiliary factor, ACF, RNA
10:1399-1411
Yin & Carter, 1996, Incomplete Factorial and Response Surface Methods
in Experimental Design: Yield Optimization of tRNATrp from inv vitro
T7 RNA Polymerase Transcription. NAR, 24:1279-1286.
On May 15, 2009, at 10:06 AM, Benda, Christian wrote:
Dear all
I recently came across the "experimental design" method for
systematic optimization of multiparametric problems like
macromolecular crystal growth.
(The response surface concept has been introduced to protein
crystallization by Carter et al. (e.g. Meth. Mol. Biol, vol. 363)
and should theoretically enable optimization of a multiparatmetric
problem by simultaneous variation of several variables).
I am wondering if anyone is actually making use of this method on a
regular basis and what their experiences are. It would also be
interesting to now if tools (web-based) are available to help in
designing and evaluating experiments.
Any comment appreciated!
Thanks very much
Christian
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