Motivation: 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. Results: 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. Availability: 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/

中文翻译：

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SWOTein：一种基于结构的方法来预测稳定性蛋白的优点和缺点

动机：尽管结构化蛋白质在生理条件下采用最低的自由能构象，但单个残基通常不处于其最低的自由能构象。作为稳定性弱点的残基通常涉及功能区域，而稳定性强则确保局部结构稳定性。优势和劣势的检测提供了关键信息，可指导旨在调节折叠和各种功能过程的蛋白质工程实验。结果：我们开发了SWOTein预测因子，该预测因子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，可以识别蛋白质中的强残基和弱残基。对不同类型优点和缺点的大规模分析表明了它们的互补性和提供的信息的增强。此外，在从天然氢交换数据获得的预测和实验优势与劣势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了其在折叠，构象变化和蛋白质-蛋白质结合的情况下预测和解释强和弱残基的适用性。总而言之，SWOTein既快速又准确，并且可以应用于小规模和大规模分析和调节折叠和分子识别过程。可用性：SWOTein Web服务器提供了预测的优势和劣势的列表，以及有助于解释预测的蛋白质结构可视化工具。可从http://babylone.ulb.ac.be/SWOTein/免费将其用于学术用途。