Dataset Information

ProTstab2 for Prediction of Protein Thermal Stabilities.

ABSTRACT: The stability of proteins is an essential property that has several biological implications. Knowledge about protein stability is important in many ways, ranging from protein purification and structure determination to stability in cells and biotechnological applications. Experimental determination of thermal stabilities has been tedious and available data have been limited. The introduction of limited proteolysis and mass spectrometry approaches has facilitated more extensive cellular protein stability data production. We collected melting temperature information for 34,913 proteins and developed a machine learning predictor, ProTstab2, by utilizing a gradient boosting algorithm after testing seven algorithms. The method performance was assessed on a blind test data set and showed a Pearson correlation coefficient of 0.753 and root mean square error of 7.005. Comparison to previous methods indicated that ProTstab2 had superior performance. The method is fast, so it was applied to predict and compare the stabilities of all proteins in human, mouse, and zebrafish proteomes for which experimental data were not determined. The tool is freely available.

SUBMITTER: Yang Y

PROVIDER: S-EPMC9505338 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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ProTstab2 for Prediction of Protein Thermal Stabilities.

Yang Yang Y Zhao Jianjun J Zeng Lianjie L Vihinen Mauno M

International journal of molecular sciences 20220916 18

The stability of proteins is an essential property that has several biological implications. Knowledge about protein stability is important in many ways, ranging from protein purification and structure determination to stability in cells and biotechnological applications. Experimental determination of thermal stabilities has been tedious and available data have been limited. The introduction of limited proteolysis and mass spectrometry approaches has facilitated more extensive cellular protein s ...[more]

PMID: 36142711

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Project description:This study aimed to assess the efficacy of a bacterioruberin-rich carotenoid extract (HAE) derived from the halophilic archaea Halorubrum ezzemoulense DSM 19316 in protecting crude fish oil against thermal oxidation. The research used fish oil derived from anchovies, which had a peroxide value (PV) of 6.44 ± 0.81 meq O2 kg-1. To assess the impact of HAE on the thermal stability and post-oxidation characteristics of fish oil, several concentrations of HAE were added to the fish oil samples: 0 ppm (no additive) (HAE0), 50 ppm (HAE50), 100 ppm (HAE100), 500 ppm (HAE500), and 1000 ppm (HAE1000). Furthermore, a control group was established with the addition of 100 ppm butylated hydroxytoluene (BHT100) in order to evaluate the effectiveness of HAE with a synthetic antioxidant that is commercially available. Prior to the fast oxidation experiment, thermogravimetric analysis was conducted on samples from all experimental groups. At the conclusion of the examination, it was seen that the HAE500 and HAE1000 groups exhibited a delay in the degradation temperature. The experimental groups underwent oxidation at a temperature of 55.0 ± 0.5 °C for a duration of 96 h. The measurement of PV was conducted every 24 h during this time. PV in all experimental groups exhibited a time-dependent rise (p < 0.05). However, the HAE500 group had the lowest PV measurement at the conclusion of the 96 h period (p < 0.05). Significant disparities were detected in the fatty acid compositions of the experimental groups at the completion of the oxidation experiment. The HAE500 group exhibited the highest levels of EPA, DHA, and ΣPUFA at the end of oxidation, with statistical significance (p < 0.05). Through the examination of volatile component analysis, specifically an oxidation marker, it was shown that the HAE500 group exhibited the lowest level of volatile components (p < 0.05). Consequently, it was concluded that the addition of HAE to fish oil provided superior protection compared to BHT at an equivalent rate. Moreover, the group that used 500 ppm HAE demonstrated the highest level of performance in the investigation.

Dataset Information

ProTstab2 for Prediction of Protein Thermal Stabilities.

Publications

ProTstab2 for Prediction of Protein Thermal Stabilities.

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