Abstract
Crystallization of proteins is a very delicate process, which is influenced by many known and unknown factors. Of tested factors, many factors are exclusively related to individual amino-acid characters such as molecular weight or protein characters such as protein length. It is considered necessary to test factors that combine both individual amino-acid characters and protein characters with respect to success rate of crystallization. In this study, two combined characters characterizing individual amino-acid character and protein character, amino acid distribution probability and future composition, were used to correlate the success rate of crystallization of proteins from Lactobacillus via modeling. The results obtained from logistic regression and neural network were compared against the results obtained from each of 533 individual amino-acid characters. This study demonstrated that the combined characters are involved in crystallization process and should be taken into account for predicting the success rate of crystallization process.
Highlights
Crystallization of proteins is a very delicate process and costs time, because many known and unknown factors influence the process of crystallization
Many factors are exclusively related to individual amino-acid characters, for example, molecular weight of amino acid, whereas a small number of tested factors are related to the whole protein characters, for example, the length of a protein
The molecular weight of an amino acid is a character of an individual amino acid and is unchangeable no matter where the given amino acid is located at any position in a protein
Summary
Crystallization of proteins is a very delicate process and costs time, because many known and unknown factors influence the process of crystallization. Intensive efforts are made to search various factors, and correlate these factors with the success rate of crystallization of proteins [1,2,3,4,5,6,7,8]. It is necessary to correlate the factors that combine both individual amino-acid characters and whole protein characters with the rate of protein crystallization. The relationship between various factors and success rate of crystallization of proteins was established via modeling, because it is impossible to run a control experiment without individual amino-acid characters and protein characters. An attempt was made to test the role of combined characters in crystallization of Lactobacillus proteins via logistic regression and neural network model, whose results were compared with the results obtained from each of 531 individual amino-acid characters. The sample of data is relatively larger than proteins from other species of interests [16]
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