Latham Andrew P, Rožič Miha, Webb Benjamin M, Sali Andrej
Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, USA.
Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.
Protein Sci. 2025 Apr;34(4):e70107. doi: 10.1002/pro.70107.
Cells function through dynamic interactions between macromolecules. Detailed characterization of the dynamics of large biomolecular systems is often not feasible by individual biophysical methods. In such cases, it may be possible to compute useful models by integrating multiple sources of information. We have previously developed an integrative method to model dynamic processes by computing biomolecular heterogeneity at fixed time points, then generating static integrative structural modes for each of these heterogeneity models, and finally connecting these static models to produce a scored trajectory model that depicts the process. Here, we demonstrate how to compute, score, and assess these integrative spatiotemporal models using our open-source Integrative Modeling Platform (IMP) program (https://integrativemodeling.org/).
细胞通过大分子之间的动态相互作用发挥功能。对于大型生物分子系统的动力学进行详细表征,仅靠单一的生物物理方法往往是不可行的。在这种情况下,通过整合多种信息源来计算有用的模型可能是可行的。我们之前已经开发了一种整合方法,通过在固定时间点计算生物分子异质性来对动态过程进行建模,然后为每个异质性模型生成静态整合结构模式,最后将这些静态模型连接起来,以生成一个描绘该过程的评分轨迹模型。在这里,我们展示了如何使用我们的开源整合建模平台(IMP)程序(https://integrativemodeling.org/)来计算、评分和评估这些整合的时空模型。