Structural ensembles of disordered proteins from hierarchical chain growth and 
simulation

Pietrek, Lisa M.; Stelzl, Lukas S.; Hummer, Gerhard

doi:10.1016/j.sbi.2022.102501

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Structural ensembles of disordered proteins from hierarchical chain growth and simulation

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Pietrek, Lisa M.
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

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Hummer, Gerhard
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;
Institute of Biophysics, Goethe University, Frankfurt am Main, Germany;

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引用

Pietrek, L. M., Stelzl, L. S., & Hummer, G. (2023). Structural ensembles of disordered proteins from hierarchical chain growth and simulation. Current Opinion in Structural Biology, 78:. doi:10.1016/j.sbi.2022.102501.

引用: https://hdl.handle.net/21.11116/0000-000B-BA69-E

要旨

Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.