Hou Qingzhen, Pucci Fabrizio, Ancien François, Kwasigroch Jean-Marc, Bourgeas Raphaël, Rooman Marianne
Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong 250002, P. R. China.
National Institute of Health Data Science of China, Shandong University, Shandong 250002, P. R. China.
Bioinformatics. 2021 Jul 15;37(14):1963–1971. doi: 10.1093/bioinformatics/btab034. Epub 2021 Jan 20.
Although structured proteins adopt their lowest free energy conformation in physiological conditions, the individual residues are generally not in their lowest free energy conformation. Residues that are stability weaknesses are often involved in functional regions, whereas stability strengths ensure local structural stability. The detection of strengths and weaknesses provides key information to guide protein engineering experiments aiming to modulate folding and various functional processes.
We developed the SWOTein predictor which identifies strong and weak residues in proteins on the basis of three types of statistical energy functions describing local interactions along the chain, hydrophobic forces and tertiary interactions. The large-scale analysis of the different types of strengths and weaknesses demonstrated their complementarity and the enhancement of the information they provide. Moreover, a good average correlation was observed between predicted and experimental strengths and weaknesses obtained from native hydrogen exchange data. SWOTein application to three test cases further showed its suitability to predict and interpret strong and weak residues in the context of folding, conformational changes and protein-protein binding. In summary, SWOTein is both fast and accurate and can be applied at small and large scale to analyze and modulate folding and molecular recognition processes.
The SWOTein webserver provides the list of predicted strengths and weaknesses and a protein structure visualization tool that facilitates the interpretation of the predictions. It is freely available for academic use at http://babylone.ulb.ac.be/SWOTein/.
尽管结构化蛋白质在生理条件下采用其最低自由能构象，但单个残基通常并不处于其最低自由能构象。作为稳定性弱点的残基通常参与功能区域，而稳定性优势则确保局部结构稳定性。检测这些优势和弱点可为旨在调控折叠及各种功能过程的蛋白质工程实验提供关键信息。
我们开发了SWOTein预测器，它基于描述沿链的局部相互作用、疏水力和三级相互作用的三种统计能量函数来识别蛋白质中的强残基和弱残基。对不同类型的优势和弱点进行的大规模分析证明了它们的互补性以及所提供信息的增强。此外，从天然氢交换数据获得的预测和实验优势与弱点之间观察到良好的平均相关性。SWOTein在三个测试案例中的应用进一步表明它适用于在折叠、构象变化和蛋白质 - 蛋白质结合的背景下预测和解释强残基和弱残基。总之，SWOTein既快速又准确，可在小规模和大规模应用中用于分析和调控折叠及分子识别过程。
SWOTein网络服务器提供预测的优势和弱点列表以及一个便于解释预测结果的蛋白质结构可视化工具。它可在http://babylone.ulb.ac.be/SWOTein/上免费用于学术用途。
