Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India.
Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; Basic and Translational Research Division, Department of Cardiology, Boston Children's Hospital, Boston, MA 02115, USA.
Methods. 2023 Oct;218:118-124. doi: 10.1016/j.ymeth.2023.08.005. Epub 2023 Aug 11.
The folding and stability of transmembrane proteins (TMPs) are governed by the insertion of secondary structural elements into the cell membrane followed by their assembly. Understanding the important features that dictate the stability of TMPs is important for elucidating their functions. In this work, we related sequence and structure-based parameters with free energy (ΔG) of α-helical membrane proteins. Our results showed that the free energy transfer of hydrophobic peptides, relative contact order, total interaction energy, number of hydrogen bonds and lipid accessibility of transmembrane regions are important for stability. Further, we have developed multiple-regression models to predict the stability of α-helical membrane proteins using these features and our method can predict the stability with a correlation and mean absolute error (MAE) of 0.89 and 1.21 kcal/mol, respectively, on jack-knife test. The method was validated with a blind test set of three recently reported experimental ΔG, which could predict the stability within an average MAE of 0.51 kcal/mol. Further, we developed a webserver for predicting the stability and it is freely available at (https://web.iitm.ac.in/bioinfo2/TMHS/). The importance of selected parameters and limitations are discussed.
跨膜蛋白(TMP)的折叠和稳定性由二级结构元件插入细胞膜并随后组装决定。了解决定 TMP 稳定性的重要特征对于阐明其功能很重要。在这项工作中,我们将序列和结构参数与α-螺旋膜蛋白的自由能(ΔG)相关联。我们的结果表明,疏水性肽的自由能转移、相对接触顺序、总相互作用能、氢键数量和跨膜区域的脂质可及性对稳定性很重要。此外,我们还开发了多元回归模型,使用这些特征来预测α-螺旋膜蛋白的稳定性,我们的方法可以在 Jackknife 测试中分别以 0.89 和 1.21 kcal/mol 的相关性和平均绝对误差(MAE)进行预测。该方法通过对三个最近报道的实验ΔG 的盲测试集进行了验证,可以在平均 MAE 为 0.51 kcal/mol 的范围内预测稳定性。此外,我们还开发了一个用于预测稳定性的网络服务器,可在(https://web.iitm.ac.in/bioinfo2/TMHS/)上免费获得。讨论了选定参数的重要性和局限性。