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Predicting thermostability difference between cellular protein orthologs.
Fang, Jianwen.
Afiliação
  • Fang J; Computational & Systems Biology Branch, Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, United States.
Bioinformatics ; 39(8)2023 08 01.
Article em En | MEDLINE | ID: mdl-37572303
MOTIVATION: Protein thermostability is of great interest, both in theory and in practice. RESULTS: This study compared orthologous proteins with different cellular thermostability. A large number of physicochemical properties of protein were calculated and used to develop a series of machine learning models for predicting cellular thermostability differences between orthologous proteins. Most of the important features in these models are also highly correlated to relative cellular thermostability. A comparison between the present study with previous comparison of orthologous proteins from thermophilic and mesophilic organisms found that most highly correlated features are consistent in these studies, suggesting they may be important to protein thermostability. AVAILABILITY AND IMPLEMENTATION: Data freely available for download at https://github.com/fangj3/cellular-protein-thermostability-dataset.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article