Fisher Charles K, Ullman Orly, Stultz Collin M
Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, Massachusetts 02139-4307, United States.
Pac Symp Biocomput. 2012:82-93.
Constructing an accurate model for the thermally accessible states of an Intrinsically Disordered Protein (IDP) is a fundamental problem in structural biology. This problem requires one to consider a large number of conformations in order to ensure that the model adequately represents the range of structures that the protein can adopt. Typically, one samples a wide range of structures in an attempt to obtain an ensemble that agrees with some pre-specified set of experimental data. However, models that contain more structures than the available experimental restraints are problematic as the large number of degrees of freedom in the ensemble leads to considerable uncertainty in the final model. We introduce a computationally efficient algorithm called Variational Bayesian Weighting with Structure Selection (VBWSS) for constructing a model for the ensemble of an IDP that contains a minimal number of conformations and, simultaneously, provides estimates for the uncertainty in properties calculated from the model. The algorithm is validated using reference ensembles and applied to construct an ensemble for the 140-residue IDP, monomeric α- synuclein.
构建内在无序蛋白质（IDP）热可及状态的精确模型是结构生物学中的一个基本问题。这个问题要求人们考虑大量的构象，以确保模型能充分代表蛋白质可以采用的结构范围。通常，人们会对广泛的结构进行采样，试图获得一个与某些预先指定的实验数据集相符的集合。然而，包含比可用实验约束更多结构的模型存在问题，因为集合中的大量自由度会导致最终模型存在相当大的不确定性。我们引入了一种计算效率高的算法，称为带结构选择的变分贝叶斯加权（VBWSS），用于构建IDP集合的模型，该模型包含最少数量的构象，同时还能为根据模型计算的属性不确定性提供估计。该算法使用参考集合进行了验证，并应用于构建140个残基的IDP单体α-突触核蛋白的集合。
