Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, California, USA.
National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.
Protein Sci. 2021 Jan;30(1):250-261. doi: 10.1002/pro.3995. Epub 2020 Dec 3.
Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data-dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org).
生物学通过构建生物系统（如蛋白质复合物）的结构模型来取得进展。有些系统对传统的结构测定方法具有抗性。在这种情况下，通过依赖于多种类型数据的同时使用的综合结构测定，仍然有可能生成有用的模型。通过由数据依赖评分函数指导的结构抽样方法，生成与数据足够一致的模型集合。模型集合的变化量化了结构的不确定性，通常是由于输入信息的不确定性和用于产生数据的样本中的实际结构异质性造成的。在这里，我们描述了如何使用我们的开源综合建模平台程序（https://integrativemodeling.org）生成、评估和解释综合结构模型的集合。
