蛋白质缔合速率常数的自动预测。
Automated prediction of protein association rate constants.
机构信息
Department of Physics and Institute of Molecular Biophysics, Tallahassee, FL 32306, USA.
出版信息
Structure. 2011 Dec 7;19(12):1744-51. doi: 10.1016/j.str.2011.10.015.
Abstract
The association rate constants (k(a)) of proteins with other proteins or other macromolecular targets are a fundamental biophysical property. Observed rate constants span over ten orders of magnitude, from 1 to 10(10) M(-1)s(-1). Protein association can be rate limited either by the diffusional approach of the subunits to form a transient complex, with near-native separation and orientation but without short-range native interactions, or by the subsequent conformational rearrangement to form the native complex. Our transient-complex theory showed promise in predicting k(a) in the diffusion-limited regime. Here, we develop it into a web server called TransComp (http://pipe.sc.fsu.edu/transcomp/) and report on the server's accuracy and robustness based on applications to over 100 protein complexes. We expect this server to be a valuable tool for systems biology applications and for kinetic characterization of protein-protein and protein-nucleic acid association in general.
摘要
蛋白质与其他蛋白质或其他生物大分子靶标的缔合速率常数 (k(a)) 是基本的生物物理性质。观察到的速率常数跨越了十个数量级，从 1 到 10(10) M(-1)s(-1)。蛋白质的缔合可以通过亚基形成瞬态复合物的扩散方式来限速，该复合物具有近乎天然的分离和取向，但没有短程的天然相互作用，或者通过随后的构象重排形成天然复合物。我们的瞬态复合物理论在预测扩散限制区域的 k(a) 方面显示出了前景。在这里，我们将其发展成一个名为 TransComp（http://pipe.sc.fsu.edu/transcomp/）的网络服务器，并根据对 100 多个蛋白质复合物的应用报告了服务器的准确性和稳健性。我们期望该服务器成为系统生物学应用以及一般蛋白质-蛋白质和蛋白质-核酸结合的动力学特征的有价值的工具。
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