Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates.
Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemic...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1012737 |
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| author | Alejandro Feito Ignacio Sanchez-Burgos Ignacio Tejero Eduardo Sanz Antonio Rey Rosana Collepardo-Guevara Andrés R Tejedor Jorge R Espinosa |
| author_facet | Alejandro Feito Ignacio Sanchez-Burgos Ignacio Tejero Eduardo Sanz Antonio Rey Rosana Collepardo-Guevara Andrés R Tejedor Jorge R Espinosa |
| author_sort | Alejandro Feito |
| collection | DOAJ |
| description | Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules. Specifically, we assess the HPS, HPS-cation-π, HPS-Urry, CALVADOS2, Mpipi, and Mpipi-Recharged models in their predictions of the condensate saturation concentration, critical solution temperature, and condensate viscosity of the A1-LCD variants. Our analyses demonstrate that, among the tested models, Mpipi, Mpipi-Recharged, and CALVADOS2 provide accurate descriptions of the critical solution temperatures and saturation concentrations for the multiple A1-LCD variants tested. Regarding the prediction of material properties for condensates of A1-LCD and its variants, Mpipi-Recharged stands out as the most reliable model. Overall, this study benchmarks a range of residue-resolution coarse-grained models for the study of the thermodynamic stability and material properties of condensates and establishes a direct link between their performance and the ranking of intermolecular interactions these models consider. |
| format | Article |
| id | doaj-art-d07b856099f042a9abc668fd0ce4ecc4 |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-d07b856099f042a9abc668fd0ce4ecc42025-08-20T03:52:07ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-01-01211e101273710.1371/journal.pcbi.1012737Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates.Alejandro FeitoIgnacio Sanchez-BurgosIgnacio TejeroEduardo SanzAntonio ReyRosana Collepardo-GuevaraAndrés R TejedorJorge R EspinosaIntracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules. Specifically, we assess the HPS, HPS-cation-π, HPS-Urry, CALVADOS2, Mpipi, and Mpipi-Recharged models in their predictions of the condensate saturation concentration, critical solution temperature, and condensate viscosity of the A1-LCD variants. Our analyses demonstrate that, among the tested models, Mpipi, Mpipi-Recharged, and CALVADOS2 provide accurate descriptions of the critical solution temperatures and saturation concentrations for the multiple A1-LCD variants tested. Regarding the prediction of material properties for condensates of A1-LCD and its variants, Mpipi-Recharged stands out as the most reliable model. Overall, this study benchmarks a range of residue-resolution coarse-grained models for the study of the thermodynamic stability and material properties of condensates and establishes a direct link between their performance and the ranking of intermolecular interactions these models consider.https://doi.org/10.1371/journal.pcbi.1012737 |
| spellingShingle | Alejandro Feito Ignacio Sanchez-Burgos Ignacio Tejero Eduardo Sanz Antonio Rey Rosana Collepardo-Guevara Andrés R Tejedor Jorge R Espinosa Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates. PLoS Computational Biology |
| title | Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates. |
| title_full | Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates. |
| title_fullStr | Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates. |
| title_full_unstemmed | Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates. |
| title_short | Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates. |
| title_sort | benchmarking residue resolution protein coarse grained models for simulations of biomolecular condensates |
| url | https://doi.org/10.1371/journal.pcbi.1012737 |
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