 | Acta Crystallographica Section F Acta Crystallographica Section F STRUCTURAL BIOLOGY COMMUNICATIONS |
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![[Figure 1]](nj5280fig1mag.jpg)
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Figure 1
Decision tree representing the iterative screen optimization algorithm. (a) Drop 1 of each crystallization condition in a crystal screen is evaluated after five days and assigned a user-generated score of either `Clear' (white), `Crystal' (red), `Light Precipitation' (light blue) or `Heavy Precipitation' (dark blue). This score is then used to calculate an optimized precipitant concentration for each drop of the subsequent experiment (C2) based upon the initial precipitant concentration (C1). Once all 96 crystallization conditions have been reformulated to generate Plate 2, the optimized drops can be assigned a score after an additional five days. Further optimized precipitant concentrations (Cx) take into account the scores of both of the two prior precipitant concentrations (Cx−1 and Cx−2). This process can be repeated multiple times until conditions that foster nucleation and crystal growth are found. The equations used to recalculate precipitant concentrations are listed beneath each arrow. Drops at time = 0 d have not been assigned a score and are represented by gray circles. Once conditions that result in crystal nucleation and growth have been obtained, subsequent optimization of that condition is halted. (b) An example from each of the possible scoring categories is shown. The circle at the top left of each image represents the score that was assigned to that drop. |
![[Figure 1]](nj5280fig1.jpg)
| STRUCTURAL BIOLOGY COMMUNICATIONS |
ISSN: 2053-230X
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