Statistical accuracy of molecular dynamics-based methods for sampling conformational ensembles of disordered proteins
Adolfo Bastida1, José Zúñiga1, Federico Fogolari2
1Departamento de Química Física, Universidad de Murcia, 30100 Murcia, Spain. bastida@um.es.
Physical Chemistry Chemical Physics : PCCP
|August 27, 2024
Summary
Characterizing intrinsically disordered regions (IDRs) is challenging. A new probabilistic molecular dynamics chain growth (PMD-CG) method quickly generates conformational ensembles comparable to replica exchange solute tempering (REST).
Area of Science:
- Computational Biology
- Biophysics
- Protein Dynamics
Background:
- Intrinsically disordered regions (IDRs) present significant challenges for conformational characterization.
- Molecular dynamics (MD) simulations are crucial for sampling the vast conformational space of IDRs.
Purpose of the Study:
- To develop and validate a novel computational protocol for efficiently characterizing IDR conformations.
- To compare the performance of the new protocol against established methods like replica exchange solute tempering (REST).
Main Methods:
- Development of the probabilistic molecular dynamics chain growth (PMD-CG) protocol, integrating flexible-meccano and hierarchical chain growth.
- Utilizing statistical data from tripeptide MD trajectories as a foundation for PMD-CG.
- Application of PMD-CG to a 20-residue region of the p53 tumor suppressor protein C-terminal domain (p53-CTD).
Main Results:
- PMD-CG rapidly generates a diverse ensemble of conformations for the target IDR.
- The conformational ensemble produced by PMD-CG is computationally efficient.
- Experimentally measurable quantities derived from the PMD-CG ensemble show strong agreement with those from the REST ensemble.
Conclusions:
- PMD-CG offers a fast and accurate method for simulating IDR conformational ensembles.
- The novel PMD-CG protocol provides a valuable alternative to existing methods for IDR characterization.
- This approach advances the computational study of intrinsically disordered proteins.
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