MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins. Issue 11 (28th May 2021)

• Record Type: Journal Article
• Authors: Kulandaisamy, A.; Zaucha, Jan; Frishman, Dmitrij; Gromiha, M. Michael
• Is Part Of: Journal of molecular biology. Volume 433:Issue 11(2021)
• Publication Date: 2021-05-28
• Subjects: membrane proteins -- thermal stability -- missense mutations -- stabilizing and destabilizing -- disease-causing mutations; PSSM position-specific scoring matrix -- MAE mean absolute error; Molecular biology -- Periodicals; Biology -- Periodicals; Biochemistry -- Periodicals; Bacteriology -- Periodicals; Molecular Biology -- Periodicals; Biochemistry -- Periodicals; Biologie moléculaire -- Périodiques; Biologie -- Périodiques; Biochimie -- Périodiques; Moleculaire biologie; Biochemistry; Biology; Molecular biology; Periodicals; 572.805
• DOI: 10.1016/j.jmb.2020.09.005
• Languages: English
• ISSNs: 0022-2836

Abstract

Abstract: The stability of membrane proteins differs from globular proteins due to the presence of nonpolar membrane-spanning regions. Using a dataset of 929 membrane protein mutations whose effects on thermal stability (Δ Tm ) were experimentally determined, we found that the average Δ Tm due to 190 stabilizing and 232 destabilizing mutations occurring in membrane-spanning regions are 2.43(3.1) °C and − 5.48(5.5) °C, respectively. The Δ Tm values for mutations occurring in solvent-exposed regions are 2.56(2.82) and − 6.8(7.2) °C. We have systematically analyzed the factors influencing the stability of mutants and observed that changes in hydrophobicity, number of contacts between Cα atoms and frequency of aliphatic residues are important determinants of the stability change induced by mutations occurring in membrane-spanning regions. We have developed structure- and sequence-based machine learning predictors of Δ Tm due to mutations specifically for membrane proteins. They showed a correlation and mean absolute error (MAE) of 0.72 and 2.85 °C, respectively, between experimental and predicted Δ Tm for mutations in membrane-spanning regions on 10-fold group-wise cross-validation. The average correlation and MAE for mutations in aqueous regions are 0.73 and 3.7 °C, respectively. These MAE values are about 50% lower than standard deviations from the mean Δ Tm values. The reliability of the method was affirmed on a test set of mutations occurring in evolutionary independent protein sequences. The developed MPTherm-pred server for predicting thermal stability changes upon mutations in membrane proteins is available at https://web.iitm.ac.in/bioinfo2/mpthermpred/ . Our results provide insights into factors influencing the stability of membrane proteins and can aid in designing mutants that are more resistant to thermal stress. Graphical abstract: Unlabelled Image Highlights: Prediction of protein stability change upon mutation (Δ Tm ) is important in protein engineering. Protein sequence and structure-based features are related with Δ Tm using multiple regression technique. Developed a novel method to predict the effect of mutations to membrane protein stability MPTherm-pred is useful to design stable mutants and to understand the factors influencing the stability of membrane proteins.