TargetFreeze: Identifying Antifreeze Proteins via a Combination of Weights using Sequence Evolutionary Information and Pseudo Amino Acid Composition

He, Xue; Han, Koeun; Hu, Jun; Yan, Hui; Yang, Jingyu; Shen, Hong‐Bin; Yu, Dong‐Jun

doi:10.1007/s00232-015-9811-z

Cited by 41 publications

(28 citation statements)

References 51 publications

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“…Amino acid sequences of the four wheat proteins were analyzed using TargetFreeze, a recently‐developed bioinformatics tool that predicts the likelihood of a protein to possess antifreeze activity . This would be suggested if the score obtained is higher than the threshold of 0.66.…”

Section: Discussionmentioning

confidence: 99%

“…Amino acid sequences of the four wheat proteins were analyzed using TargetFreeze, a recentlydeveloped bioinformatics tool that predicts the likelihood of a protein to possess antifreeze activity. 24 This would be suggested if the score obtained is higher than the threshold of 0.66. Values of 0.115 and 0.017 were obtained for TaBAS1 (BAA19099.1) and TaENO (AGH20061.1), respectively, indicating that these two proteins are not predicted to affect ice formation.…”

Section: Discussionmentioning

confidence: 99%

“…The microscopy images clearly show that TaENO causes a notable decrease in the size of ice crystals, despite the fact that no antifreeze activity was predicted from analysis of the amino acid sequence using the AFP predictor TargetFreeze. 24 Even though TargetFreeze analyses multiple protein features, it appears that nontypical antifreeze domains remain to be identified and included in the algorithms used for AFP prediction.…”

Section: Discussionmentioning

confidence: 99%

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Inhibition of ice recrystallization and cryoprotective activity of wheat proteins in liver and pancreatic cells

et al. 2016

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Efficient cryopreservation of cells at ultralow temperatures requires the use of substances that help maintain viability and metabolic functions post-thaw. We are developing new technology where plant proteins are used to substitute the commonly-used, but relatively toxic chemical dimethyl sulfoxide. Recombinant forms of four structurally diverse wheat proteins, TaIRI-2 (ice recrystallization inhibition), TaBAS1 (2-Cys peroxiredoxin), WCS120 (dehydrin), and TaENO (enolase) can efficiently cryopreserve hepatocytes and insulin-secreting INS832/13 cells. This study shows that TaIRI-2 and TaENO are internalized during the freeze-thaw process, while TaBAS1 and WCS120 remain at the extracellular level. Possible antifreeze activity of the four proteins was assessed. The "splat cooling" method for quantifying ice recrystallization inhibition activity (a property that characterizes antifreeze proteins) revealed that TaIRI-2 and TaENO are more potent than TaBAS1 and WCS120. Because of their ability to inhibit ice recrystallization, the wheat recombinant proteins TaIRI-2 and TaENO are promising candidates and could prove useful to improve cryopreservation protocols for hepatocytes and insulin-secreting cells, and possibly other cell types. TaENO does not have typical ice-binding domains, and the TargetFreeze tool did not predict an antifreeze capacity, suggesting the existence of nontypical antifreeze domains. The fact that TaBAS1 is an efficient cryoprotectant but does not show antifreeze activity indicates a different mechanism of action. The cryoprotective properties conferred by WCS120 depend on biochemical properties that remain to be determined. Overall, our results show that the proteins' efficiencies vary between cell types, and confirm that a combination of different protection mechanisms is needed to successfully cryopreserve mammalian cells.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Inhibition of ice recrystallization and cryoprotective activity of wheat proteins in liver and pancreatic cells

et al. 2016

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“…With the advancements of genome sequencing, a large number of sequenced proteins have been accumulated and need to be functionally annotated. Many auto-annotation tools exist to identify antifreeze proteins, such as TargetFreeze (He et al, 2015), AFP_PSSM (Zhao et al, 2012), CryoProtect (Pratiwi et al, 2017), and afpCOOL (Eslami et al, 2018). However, these tools use too many features ( Table 2), which may often be redundant and lead to overfitting.…”

Section: Comparison Of Our Seven Key Featuresmentioning

confidence: 99%

“…In contrast, despite the presumed convergent evolution of antifreeze proteins, Zhao et al (2012) built a classifier with high performance solely based on evolutionary features derived from position-specific scoring matrices (PSSMs), suggesting that evolutionary information is also important for identifying antifreeze proteins. He et al (2015) further compared the performances of evolutionary features with two amino acid composition metrics (i.e., amino acid composition and pseudo amino acid composition), and showed that features derived from PSSMs achieved higher performance. Similarly, Yang et al (2015) reported that among various features pertinent to identifying antifreeze proteins, features derived from PSSMs accounted for the largest proportion, though another study showed that physicochemical properties were more important (Eslami et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Identifying Antifreeze Proteins Based on Key Evolutionary Information

Sun

Ding

Wang

et al. 2020

Front. Bioeng. Biotechnol.

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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.

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Transcriptome analyses and weighted gene coexpression network analysis reveal key pathways and genes involved in the rapid cold resistance of the Chinese white wax scale insect

Zhang

Liu

et al. 2021

Arch Insect Biochem Physiol

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The Chinese white wax scale insect, Ericerus pela, is an important resource insect in China. The rapid response of E. pela to decreasing temperatures plays key roles in the population distribution. In this study, we analyzed the gene expression of E. pela treated with low temperature using transcriptome analyses and weighted gene coexpression network analysis (WGCNA). The results showed that the cold resistance of E. pela involved changes in the expression of many genes. The genes were mainly involved in alcohol formation activity, lipid metabolism, membrane and structure, and oxidoreductase activity. According to the WGCNA results, some pathways related to cold resistance were found in the genes in the modules, such as cytoskeleton proteins, cytoskeleton protein pathway, biosynthesis of unsaturated fatty acids, glycerophospholipid metabolism, ether lipid metabolism, and thermogenesis. Some of the hub genes were nonspecific lipid‐transfer proteins, DnaJ homolog subfamily C member 13, paramyosin, tropomodulin, and tubulin beta chain. In particular, the hub genes of the tan module included the heat shock protein (hsp) 10, hsp 60, hsp 70, and hsp 90 genes. Thirty‐five antifreeze protein (afp) genes were identified according to the annotation results. Three afp genes were further identified among the hub genes. Six of these genes were selected for heterogeneous protein expression. One of them was expressed successfully. The thermal hysteresis activity (THA) analyses showed that the THA was 1.73°C. These results showed that the cytoskeleton, lipid metabolism, thermogenesis, HSPs and AFPs may play important roles in the cold resistance of E. pela.

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TargetFreeze: Identifying Antifreeze Proteins via a Combination of Weights using Sequence Evolutionary Information and Pseudo Amino Acid Composition

Cited by 41 publications

References 51 publications

Inhibition of ice recrystallization and cryoprotective activity of wheat proteins in liver and pancreatic cells

Inhibition of ice recrystallization and cryoprotective activity of wheat proteins in liver and pancreatic cells

Identifying Antifreeze Proteins Based on Key Evolutionary Information

Transcriptome analyses and weighted gene coexpression network analysis reveal key pathways and genes involved in the rapid cold resistance of the Chinese white wax scale insect

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