Frontiers in integrative structural biology: modeling disordered proteins and utilizing in situ data

TL;DR

This paper reviews recent advances in integrative structural biology, focusing on modeling disordered proteins and analyzing cryo-electron tomography data to understand large macromolecular assemblies.

Contribution

It highlights new methods developed for modeling disordered regions and utilizing in situ cryo-ET data within integrative modeling frameworks.

Findings

Development of new methods for modeling disordered regions.

Advances in integrating cryo-electron tomography data.

Application to large macromolecular assemblies.

Abstract

Integrative modeling enables structure determination for large macromolecular assemblies by combining data from multiple sources of experiment data with theoretical and computational predictions. Recent advancements in AI-based structure prediction and electron cryo-microscopy have sparked renewed enthusiasm for integrative modeling; structures from AI-based methods can be integrated with in situ maps to characterize large assemblies. This approach previously allowed us and others to determine the architectures of diverse macromolecular assemblies, such as nuclear pore complexes, chromatin remodelers, and cell-cell junctions. Experimental data spanning several scales was used in these studies, ranging from high-resolution data, such as X-ray crystallography and Alphafold structures, to low-resolution data, such as cryo-electron tomography maps and data from co-immunoprecipitation experiments. Two recurrent modeling challenges emerged across a range of studies. First, modeling disordered regions, which constituted a significant portion of these assemblies, necessitated the development of new methods. Second, methods needed to be developed to utilize the information from cryo-electron tomography, a timely challenge as structural biology is increasingly moving towards in situ characterization. Here, we recapitulate recent developments in the modeling of disordered proteins and the analysis of cryo-electron tomography data and highlight opportunities for method development in the context of integrative modeling.