Abstract
Antifreeze proteins are important antifreeze materials that have been widely used in industry, including in cryopreservation, de-icing, and food storage applications. However, the quantity of some commercially produced antifreeze proteins is insufficient for large-scale industrial applications. Further, many antifreeze proteins have properties such as cytotoxicity, severely hindering their applications. Understanding the mechanisms underlying the protein–ice interactions and identifying novel antifreeze proteins are, therefore, urgently needed. In this study, to uncover the mechanisms underlying protein–ice interactions and provide an efficient and accurate tool for identifying antifreeze proteins, we assessed various evolutionary features based on position-specific scoring matrices (PSSMs) and evaluated their importance for discriminating of antifreeze and non-antifreeze proteins. We then parsimoniously selected seven key features with the highest importance. We found that the selected features showed opposite tendencies (regarding the conservation of certain amino acids) between antifreeze and non-antifreeze proteins. Five out of the seven features had relatively high contributions to the discrimination of antifreeze and non-antifreeze proteins, as revealed by a principal component analysis, i.e., the conservation of the replacement of Cys, Trp, and Gly in antifreeze proteins by Ala, Met, and Ala, respectively, in the related proteins, and the conservation of the replacement of Arg in non-antifreeze proteins by Ser and Arg in the related proteins. Based on the seven parsimoniously selected key features, we established a classifier using support vector machine, which outperformed the state-of-the-art tools. These results suggest that understanding evolutionary information is crucial to designing accurate automated methods for discriminating antifreeze and non-antifreeze proteins. Our classifier, therefore, is an efficient tool for annotating new proteins with antifreeze functions based on sequence information and can facilitate their application in industry.
Highlights
IntroductionAntifreeze proteins can protect cells and body fluids from freezing by hindering the nucleation, inhibiting the growth of ice crystals, and impeding the recrystallization of ice (Kandaswamy et al, 2011) and are important natural antifreeze materials that are widely used in food preservation (Zhan et al, 2018; Provesi et al, 2019; Song et al, 2019), medicine (Lee et al, 2012; Khan et al, 2019), and biotechnological applications (Naing and Kim, 2019)
Seven features derived from position-specific scoring matrices (PSSMs) were parsimoniously selected as key features for discriminating antifreeze and non-antifreeze proteins (Figure 1A)
Along PC1, the replacements of Cys and Trp in non-antifreeze proteins by Ala and Met, respectively, in the related proteins increased in line with increasing occurrences of non-antifreeze proteins (Figures 1B,C)
Summary
Antifreeze proteins can protect cells and body fluids from freezing by hindering the nucleation, inhibiting the growth of ice crystals, and impeding the recrystallization of ice (Kandaswamy et al, 2011) and are important natural antifreeze materials that are widely used in food preservation (Zhan et al, 2018; Provesi et al, 2019; Song et al, 2019), medicine (Lee et al, 2012; Khan et al, 2019), and biotechnological applications (Naing and Kim, 2019) They were first found in the Evolutionary Information Identifies Antifreeze Proteins blood of Antarctic fishes about 50 years ago (DeVries and Wohlschlag, 1969; DeVries et al, 1970). Developing tools to identify novel proteins with antifreeze functions is urgently needed
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