bioRxivBiophysicsPreprint
INTEGRATOR: Structural Elucidation of the INO80 Chromatin Remodeler via Experimentally Guided Molecular Simulations
Jules NdeiD, Gihan PanapitiyaiD, Margaret S. CheungiD, C. Mark MaupiniD, Mihaela E. SardiuiD
Abstract
The INO80 chromatin remodeling complex plays a central role in DNA repair, transcription, and replication. Yet, a comprehensive understanding of its structural organization remains incomplete due to the dynamic nature of several of its subunits and the sharing of several subunits with related remodeling complexes. Here, we report a computational model of the three-dimensional structure of the S. cerevisiae INO80 complex using an integrative approach that combines experimental crosslinking mass spectrometry, molecular docking, and molecular dynamics simulations. Our results reveal the spatial and dynamical organization of key modules--ARP8, ARP5, NHP10, and RVB1/2--within the intact complex. The resulting structural model agrees with crosslinking constraints, highlighting the architecture of the previously uncharacterized NHP10 module. This module, including the C-terminal region of the Ino80 scaffolding protein, has remained elusive due to its intrinsic flexibility and lack of high-resolution structural data. To facilitate this integrative modeling workflow and make it broadly accessible, we presented INTEGRATOR: (INTEGRAtive TempOral and stRuctural Analysis of protein modules), a versatile workflow package designed as a tool to elucidate the structure and dynamics of large, flexible macromolecular assemblies using well-established softwares. Our findings demonstrate the power of integrative modeling in resolving the role of the highly disordered NPH10 module in recruiting other dynamic modules into INO80 large protein assemblies and offer a generalizable framework for determining the architecture of similarly complex and heterogeneous molecular machines. This work carries broad implications for understanding the structural basis of chromatin regulation in microbial organisms and the implications for the dysregulation in diseases such as cancer.
- organism: yeast
- assay: structural biology
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
- approach: simulation
- Citations
- 0
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