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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