Statistical design of experiments for protein crystal growth and the use of a precrystallization assay

Published on Jul 1, 1988in Journal of Crystal Growth1.57
· DOI :10.1016/0022-0248(88)90299-0
Charles W. Carter7
Estimated H-index: 7
(UNC: University of North Carolina at Chapel Hill),
Eric T. Baldwin1
Estimated H-index: 1
(UNC: University of North Carolina at Chapel Hill),
Lloyd Frick7
Estimated H-index: 7
(UNC: University of North Carolina at Chapel Hill)
Abstract Statistical design of crystallization experiments greatly reduces the amount of protein necessary to find conditions for crystal growth and leads naturally to a useful data base for improving crystallization conditions in cases where the initial trials do not produce adequate results. Although it is counterintuitive to vary simultaneously all the factors to be screened, this apparent loss of control over experimental parameters actually costs very little in terms of the statistical strength of inferences to be drawn from the resulting data. We have used incomplete factorial designs to crystallize all of the proteins we are now studying (tryptophanyl-tRNA synthetase, cytidine deaminase, and a manganese catalase). In each case we used a rudimentary microscopic examination to determine the experimental outcomes. From these data we have generated for each protein a “factor profile” showing the relative importance of the factors studied. In at least one case, the specific information in this profile lead to a substantial improvement in the crystals we were able to grow. Considerable potential power lies in the ability to feed information obtained from all experiments in an initial trial back into the design of subsequent improvements in crystal growth conditions. Exploitation of this feedback is limited by the accuracy of the experimental assay procedure. Microscopic examination has many limitations, including subjectivity and low precision. More importantly, it can be seriously misleading if kinetic factors force suitable nuclei to shower as a microcrystalline array which is mistakenly taken to be a precipitate. The dilution curve assay based on dynamic light scattering was developed (Kam et al., J. Mol. Biol. 123 (1978) 539-555) from the concept that hydrodynamic measurements at different protein concentrations could reflect thermodynamic interactions in aggregates without forcing the system to produce macroscopic manifestations. Hence, it should discriminate between cases involving a kinetic barrier to large crystal growth and those where thermodynamic interactions between molecules are poor. Preliminary measurements of the dilution curves of phosphoglucomutase in ammonium sulfate solutions with and without PEG-400 suggest that the dilution curve can identify microcrystalline samples.
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#2H.B. Shore (SDSU: San Diego State University)H-Index: 1
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#1Michael Zeppezauer (Royal Agricultural University)H-Index: 25
#2Hans Eklund (Royal Agricultural University)H-Index: 4
Last.E. Zeppezauer (Royal Agricultural University)H-Index: 11
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#1Marc L. PuseyH-Index: 7
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#2Morten Otto Alexander Sommer (California Institute of Technology)H-Index: 23
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#1Jörg Peters (Bayer USA: Bayer Corporation)H-Index: 3
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View next paperSparse matrix sampling: a screening method for crystallization of proteins