Simplex optimization of protein crystallization conditions |
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Affiliation: | 1. Master''s Student in Engineering and Environmental Management, Universidad Surcolombiana, Neiva, Huila, Colombia;2. Research Group of Science, Engineering and Innovation, Crimarpez S.A.S, Calle 12 Sur N° 6-45, Neiva, Huila, Colombia;3. Corporación Universitaria Minuto de Dios, Programa de Administración en Seguridad y Salud en el Trabajo, Grupo de Investigación en Seguridad y Salud en el Trabajo, Neiva, Huila, Colombia;4. Universidad Surcolombiana, Faculty of Engineering, Agricultural Engineering Program, Hydro Engineering and Agricultural Development Research Group (GHIDA), Avenida Pastrana Borrero - Carrera 1, Neiva, Huila, Colombia;5. Universidad Nacional de Colombia, Bogotá Campus, Faculty of Sciences, Department of Pharmacy, Pharmaceutical-Physical-Chemical Research Group, Carrera 30 No. 45-03, Bogotá D.C., Colombia;6. Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz 51664, Iran;7. Kimia Idea Pardaz Azarbayjan (KIPA) Science Based Company, Tabriz University of Medical Sciences, Tabriz 51664, Iran;8. Universidad Cooperativa de Colombia, Department of Engineering, Industrial Engineering Program, GRIAUCC Research Group, Calle 11 No. 1 - 51, Neiva, Huila, Colombia |
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Abstract: | Simplex algorithms have been used to optimize for size, number and morphology of lysozyme and apoferritin crystals. This approach requires fewer experiments than the single-factor-at-a-time method or factorial designs and will be useful in conserving materials on the International Space Station. The simplex method has the possible advantage that it conserves on materials by reducing the number of experiments required to optimize a crystallization system. The process is iterative and exploratory and should allow optimum microgravity conditions to be determined which might very well be different from the optimum conditions on Earth. Because the simplex method uses simple mathematical operations to calculate the next set of crystallization conditions it will be easier for crystal growers to implement than factorial designs. Factorial experiments are based on varying all factors simultaneously at a limited number of factor levels. This results in a model that is used to determine the influence of each factor and their interactions. Factorial design experiments are especially useful at the beginning of an experimental study and as a screening tool to investigate a large number of factors. The simplex method is an optimization method which is model-independent and requires no fitting of models to data. Also, when applied to protein crystal growth the simplex method does not rely on an absolute quality score. Instead, with each iteration a comparison is made to the last experiment and the results are assigned as being “better or worse”. In this study, commercially obtained apoferritin was purified from 65% monomeric apoferritin to 92% monomeric apoferritin by size exclusion chromatography. Simplex optimization found the best apoferritin crystals were obtained at 15 mg/ml apoferritin, 2.0% CdSO4, 25°C using the hanging drop vapor diffusion method of crystallization and at 24 mg/ml apoferritin, 1.5% CdSO4, 25°C using the containerless crystallization method. For lysozyme, the simplex method found the best crystals at 19 mg/ml lysozyme, 7.0% (w/v) NaCl, pH 4.0, 25°C using the hanging drop vapor diffusion method of crystallization. For both proteins, the optimum conditions were found with less than ten experiments using very little protein. Finally, we report that the factors to be considered in the successful application of this method to crystallization are the number of variables to be studied, the initial conditions, step size and analysis of crystal quality. |
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