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An Y, Gao T, Wang T, Zhang D, Bharti B. Effects of charge asymmetry on the liquid-liquid phase separation of polyampholytes and their condensate properties. SOFT MATTER 2024; 20:6150-6159. [PMID: 39044475 DOI: 10.1039/d4sm00532e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2024]
Abstract
Liquid-liquid phase separation (LLPS) is the mechanism underlying the formation of bio-molecular condensates which are important compartments regulating intra- and extra-cellular functions. Electrostatic interactions are some of the important driving forces of the LLPS behaviors of biomolecules. However, the understanding of the electrostatic interactions is still limited, especially in the mixtures of biomolecules with different charge patterns. Here, we focus on the electrostatic interactions in mixtures of charge-asymmetric and charge-symmetric polyampholytes and their roles in the phase separation behaviors. We build charge-asymmetric and charge-symmetric model proteins consisting of both glutamic acid (E, negatively charged) and lysine (K, positively charged), i.e. polyampholytes of E35K15 (charge asymmetric) and E25K25 (charge symmetric). Pure E25K25 can undergo LLPS. To investigate the effects of charge-asymmetric polyampholytes on the mixtures of E25K25/E35K15, we perform coarse-grained simulations to determine their phase separation. The charge-asymmetric polyampholyte E35K15 is resistant to the LLPS of the mixtures of E25K25/E35K15. The condensate density decreases with the molar fraction of E35K15 increasing to 0.4, and no LLPS occurs at the molar fraction of 0.5 and above. This can be attributed to the electrostatic repulsion between the negatively charged E35K15 polymers. We further investigate the effects of charge asymmetry on the conformations and properties of the condensates. The E35K15 polymers in the condensates exhibit a more collapsed state as the molar fraction of E35K15 increases. However, the conformation of E25K25 polymers changes slightly across different condensates. The surface tensions of condensates decline with the increase of the molar fraction of E35K15 polymers, while the diffusivity of polymers in the condensed phases is enhanced. This work elucidates the role of charge-asymmetric polyampholytes in determining the LLPS behaviours of binary mixtures of charge-symmetric and charge-asymmetric proteins as well as the properties of condensed phases.
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Affiliation(s)
- Yaxin An
- Department of Chemical Engineering, Louisiana State University, USA.
| | - Tong Gao
- Department of Chemical Engineering, Louisiana State University, USA.
| | - Tianyi Wang
- Department of Chemical Engineering, Louisiana State University, USA.
| | - Donghui Zhang
- Department of Chemistry, Louisiana State University, USA
| | - Bhuvnesh Bharti
- Department of Chemical Engineering, Louisiana State University, USA.
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2
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Nicy, Morgan JWR, Wales DJ. Energy landscapes for clusters of hexapeptides. J Chem Phys 2024; 161:054112. [PMID: 39092941 DOI: 10.1063/5.0220652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 07/17/2024] [Indexed: 08/04/2024] Open
Abstract
We present the results for energy landscapes of hexapeptides obtained using interfaces to the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. We have used basin-hopping global optimization and discrete path sampling to explore the landscapes of hexapeptide monomers, dimers, and oligomers containing 10, 100, and 200 monomers modeled using a residue-level coarse-grained potential, Mpipi, implemented in LAMMPS. We find that the dimers of peptides containing amino acid residues that are better at promoting phase separation, such as tyrosine and arginine, have melting peaks at higher temperature in their heat capacity compared to phenylalanine and lysine, respectively. This observation correlates with previous work on the same uncapped hexapeptide monomers modeled using atomistic potential. For oligomers, we compare the variation in monomer conformations with radial distance and observe trends for selected angles calculated for each monomer. The LAMMPS interfaces to the GMIN and OPTIM programs for landscape exploration offer new opportunities to investigate larger systems and provide access to the coarse-grained potentials implemented within LAMMPS.
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Affiliation(s)
- Nicy
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - John W R Morgan
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - David J Wales
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
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3
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Rana U, Xu K, Narayanan A, Walls MT, Panagiotopoulos AZ, Avalos JL, Brangwynne CP. Asymmetric oligomerization state and sequence patterning can tune multiphase condensate miscibility. Nat Chem 2024; 16:1073-1082. [PMID: 38383656 PMCID: PMC11230906 DOI: 10.1038/s41557-024-01456-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 01/19/2024] [Indexed: 02/23/2024]
Abstract
Endogenous biomolecular condensates, composed of a multitude of proteins and RNAs, can organize into multiphasic structures with compositionally distinct phases. This multiphasic organization is generally understood to be critical for facilitating their proper biological function. However, the biophysical principles driving multiphase formation are not completely understood. Here we use in vivo condensate reconstitution experiments and coarse-grained molecular simulations to investigate how oligomerization and sequence interactions modulate multiphase organization in biomolecular condensates. We demonstrate that increasing the oligomerization state of an intrinsically disordered protein results in enhanced immiscibility and multiphase formation. Interestingly, we find that oligomerization tunes the miscibility of intrinsically disordered proteins in an asymmetric manner, with the effect being more pronounced when the intrinsically disordered protein, exhibiting stronger homotypic interactions, is oligomerized. Our findings suggest that oligomerization is a flexible biophysical mechanism that cells can exploit to tune the internal organization of biomolecular condensates and their associated biological functions.
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Affiliation(s)
- Ushnish Rana
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
| | - Ke Xu
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
| | - Amal Narayanan
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, USA
| | - Mackenzie T Walls
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
| | | | - José L Avalos
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA.
- Andlinger Center for Energy and the Environment, Princeton University, Princeton, NJ, USA.
- Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ, USA.
| | - Clifford P Brangwynne
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA.
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, USA.
- Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ, USA.
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4
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Panagiotopoulos AZ. Sequence dependence of critical properties for two-letter chains. J Chem Phys 2024; 160:234902. [PMID: 38884406 DOI: 10.1063/5.0215700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 05/31/2024] [Indexed: 06/18/2024] Open
Abstract
Histogram-reweighting grand canonical Monte Carlo simulations are used to obtain the critical properties of lattice chains composed of solvophilic and solvophobic monomers. The model is a modification of one proposed by Larson et al. [J. Chem. Phys. 83, 2411 (1985)], lowering the "contrast" between beads of different types to prevent aggregation into finite-size micelles that would mask true phase separation between bulk high- and low-density phases. Oligomeric chains of lengths between 5 and 24 beads are studied. Mixed-field finite-size scaling methods are used to obtain the critical properties with typical relative accuracies of better than 10-4 for the critical temperature and 10-3 for the critical volume fraction. Diblock chains are found to have lower critical temperatures and volume fractions relative to the corresponding homopolymers. The addition of solvophilic blocks of increasing length to a fixed-length solvophobic segment results in a decrease of both the critical temperature and the critical volume fraction, with an eventual slow asymptotic approach to the long-chain limiting behavior. Moving a single solvophobic or solvophilic bead along a chain leads to a minimum or maximum in the critical temperature, with no change in the critical volume fraction. Chains of identical length and composition have a significant spread in their critical properties, depending on their precise sequence. The present study has implications for understanding biomolecular phase separation and for developing design rules for synthetic polymers with specific phase separation properties. It also provides data potentially useful for the further development of theoretical models for polymer and surfactant phase behavior.
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5
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Zhu X, Chu X, Wang H, Liao Z, Xiang H, Zhao W, Yang L, Wu P, Liu X, Chen D, Xie J, Dai W, Li L, Wang J, Zhao H. Investigating neuropathological changes and underlying neurobiological mechanisms in the early stages of primary blast-induced traumatic brain injury: Insights from a rat model. Exp Neurol 2024; 375:114731. [PMID: 38373483 DOI: 10.1016/j.expneurol.2024.114731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 02/06/2024] [Accepted: 02/14/2024] [Indexed: 02/21/2024]
Abstract
The utilization of explosives and chemicals has resulted in a rise in blast-induced traumatic brain injury (bTBI) in recent times. However, there is a dearth of diagnostic biomarkers and therapeutic targets for bTBI due to a limited understanding of biological mechanisms, particularly in the early stages. The objective of this study was to examine the early neuropathological characteristics and underlying biological mechanisms of primary bTBI. A total of 83 Sprague Dawley rats were employed, with their heads subjected to a blast shockwave of peak overpressure ranging from 172 to 421 kPa in the GI, GII, and GIII groups within a closed shock tube, while the body was shielded. Neuromotor dysfunctions, morphological changes, and neuropathological alterations were detected through modified neurologic severity scores, brain water content analysis, MRI scans, histological, TUNEL, and caspase-3 immunohistochemical staining. In addition, label-free quantitative (LFQ)-proteomics was utilized to investigate the biological mechanisms associated with the observed neuropathology. Notably, no evident damage was discernible in the GII and GI groups, whereas mild brain injury was observed in the GIII group. Neuropathological features of bTBI were characterized by morphologic changes, including neuronal injury and apoptosis, cerebral edema, and cerebrovascular injury in the shockwave's path. Subsequently, 3153 proteins were identified and quantified in the GIII group, with subsequent enriched neurological responses consistent with pathological findings. Further analysis revealed that signaling pathways such as relaxin signaling, hippo signaling, gap junction, chemokine signaling, and sphingolipid signaling, as well as hub proteins including Prkacb, Adcy5, and various G-protein subunits (Gnai2, Gnai3, Gnao1, Gnb1, Gnb2, Gnb4, and Gnb5), were closely associated with the observed neuropathology. The expression of hub proteins was confirmed via Western blotting. Accordingly, this study proposes signaling pathways and key proteins that exhibit sensitivity to brain injury and are correlated with the early pathologies of bTBI. Furthermore, it highlights the significance of G-protein subunits in bTBI pathophysiology, thereby establishing a theoretical foundation for early diagnosis and treatment strategies for primary bTBI.
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Affiliation(s)
- Xiyan Zhu
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Xiang Chu
- Cognitive Development and Learning and Memory Disorders Translational Medicine Laboratory, Children's Hospital, Chongqing Medical University, Chongqing, China; Emergency department, Daping Hospital, Army Medical University, Chongqing, China
| | - Hao Wang
- Neurosurgery department, Daping Hospital, Army Medical University, Chongqing, China
| | - Zhikang Liao
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Hongyi Xiang
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Wenbing Zhao
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Li Yang
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Pengfei Wu
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Xing Liu
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Diyou Chen
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Jingru Xie
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Wei Dai
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China
| | - Lei Li
- Trauma Medical Center, Daping Hospital, Army Medical University, Chongqing, China
| | - Jianmin Wang
- Department of Weapon Bioeffect Assessment, Daping Hospital, Army Medical University, Chongqing, China.
| | - Hui Zhao
- Department of Military Traffic Injury Prevention and Control, Daping Hospital, Army Medical University, Chongqing, China.
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6
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Rana U, Wingreen NS, Brangwynne CP, Panagiotopoulos AZ. Interfacial exchange dynamics of biomolecular condensates are highly sensitive to client interactions. J Chem Phys 2024; 160:145102. [PMID: 38591689 PMCID: PMC11006425 DOI: 10.1063/5.0188461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/22/2024] [Indexed: 04/10/2024] Open
Abstract
Phase separation of biomolecules can facilitate their spatiotemporally regulated self-assembly within living cells. Due to the selective yet dynamic exchange of biomolecules across condensate interfaces, condensates can function as reactive hubs by concentrating enzymatic components for faster kinetics. The principles governing this dynamic exchange between condensate phases, however, are poorly understood. In this work, we systematically investigate the influence of client-sticker interactions on the exchange dynamics of protein molecules across condensate interfaces. We show that increasing affinity between a model protein scaffold and its client molecules causes the exchange of protein chains between the dilute and dense phases to slow down and that beyond a threshold interaction strength, this slowdown in exchange becomes substantial. Investigating the impact of interaction symmetry, we found that chain exchange dynamics are also considerably slower when client molecules interact equally with different sticky residues in the protein. The slowdown of exchange is due to a sequestration effect, by which there are fewer unbound stickers available at the interface to which dilute phase chains may attach. These findings highlight the fundamental connection between client-scaffold interaction networks and condensate exchange dynamics.
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Affiliation(s)
- Ushnish Rana
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA
| | - Ned S. Wingreen
- Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
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7
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Quoika PK, Zacharias M. Liquid-Vapor Coexistence and Spontaneous Evaporation at Atmospheric Pressure of Common Rigid Three-Point Water Models in Molecular Simulations. J Phys Chem B 2024; 128:2457-2468. [PMID: 38427971 PMCID: PMC10945489 DOI: 10.1021/acs.jpcb.3c08183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/03/2024]
Abstract
Molecular dynamics (MD) simulations are widely used to investigate molecular systems at atomic resolution including biomolecular structures, drug-receptor interactions, and novel materials. Frequently, MD simulations are performed in an aqueous solution with explicit models of water molecules. Commonly, such models are parameterized to reproduce the liquid phase of water under ambient conditions. However, often, simulations at significantly higher temperatures are also of interest. Hence, it is important to investigate the equilibrium of the liquid and vapor phases of molecular models of water at elevated temperatures. Here, we evaluate the behavior of 11 common rigid three-point water models over a wide range of temperatures. From liquid-vapor coexistence simulations, we estimated the critical points and studied the spontaneous evaporation of these water models. Moreover, we investigated the influence of the system size, choice of the pressure-coupling algorithm, and rate of heating on the process and compared them with the experimental data. We found that modern rigid three-point water models reproduce the critical point surprisingly well. Furthermore, we discovered that the critical temperature correlates with the quadrupole moment of the respective water model. This indicates that the spatial arrangement of the partial charges is important for reproducing the liquid-vapor phase transition. Our findings may guide the selection of water models for simulations conducted at high temperatures.
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Affiliation(s)
- Patrick K. Quoika
- Center for Functional Protein
Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
| | - Martin Zacharias
- Center for Functional Protein
Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany
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8
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Rajpersaud T, Tabandeh S, Leon L, Loverde SM. Molecular Dynamics Simulations of Polyelectrolyte Complexes. Biomacromolecules 2024; 25:1468-1480. [PMID: 38366971 DOI: 10.1021/acs.biomac.3c01032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Polyelectrolyte complexes (PECs) are currently of great interest due to their applications toward developing new adaptive materials and their relevance in membraneless organelles. These complexes emerge during phase separation when oppositely charged polymers are mixed in aqueous media. Peptide-based PECs are particularly useful toward developing new drug delivery methods due to their inherent biocompatibility. The underlying peptide sequence can be tuned to optimize specific material properties of the complex, such as interfacial tension and viscosity. Given their applicability, it would be advantageous to understand the underlying sequence-dependent phase behavior of oppositely charged peptides. Here, we report microsecond molecular dynamic simulations to characterize the effect of hydrophobicity on the sequence-dependent peptide conformation for model polypeptide sequences that were previously reported by Tabandeh et al. These sequences are designed with alternating chirality of the peptide backbone. We present microsecond simulations of six oppositely charged peptide pairs, characterizing the sequence-dependent effect on peptide size, degree of hydrogen bonding, secondary structure, and conformation. This analysis recapitulates sensible trends in peptide conformation and degree of hydrogen bonding, consistent with experimentally reported results. Ramachandran plots reveal that backbone conformation at the single amino acid level is highly influenced by the neighboring sequence in the chain. These results give insight into how subtle changes in hydrophobic side chain size and chirality influence the strength of hydrogen bonding between the chains and, ultimately, the secondary structure. Furthermore, principal component analysis reveals that the minimum energy structures may be subtly modulated by the underlying sequence.
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Affiliation(s)
- Tania Rajpersaud
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
| | - Sara Tabandeh
- Department of Materials Science and Engineering, University of Central Florida, 4000 Central Florida Boulevard, Orlando, FL 32816, United States
| | - Lorraine Leon
- Department of Materials Science and Engineering, University of Central Florida, 4000 Central Florida Boulevard, Orlando, FL 32816, United States
| | - Sharon M Loverde
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States
- Department of Chemistry, College of Staten Island, The City University of New York, 2800 Victory Boulevard, Staten Island, NY 10314, United States
- Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, NY 10016, United States
- Ph.D. Program in Physics, The Graduate Center of the City University of New York, New York, NY 10016, United States
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9
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Yan X, Zhang M, Wang D. Interplay between posttranslational modifications and liquid‒liquid phase separation in tumors. Cancer Lett 2024; 584:216614. [PMID: 38246226 DOI: 10.1016/j.canlet.2024.216614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 12/22/2023] [Accepted: 12/30/2023] [Indexed: 01/23/2024]
Abstract
Liquid‒liquid phase separation (LLPS) is a general phenomenon recently recognized to be critically involved in the regulation of a variety of cellular biological processes, such as transcriptional regulation, heterochromatin formation and signal transduction, through the compartmentalization of proteins or nucleic acids into droplet-like condensates. These processes are directly or indirectly related to tumor initiation and treatment. Posttranslational modifications (PTMs), which represent a rapid and reversible mechanism involved in the functional regulation of proteins, have emerged as key events in modulating LLPS under physiological or pathophysiological conditions, including tumorigenesis and antitumor therapy. In this review, we introduce the biological functions participated in cancer-associated LLPS, discuss the potential roles of LLPS during tumor onset or therapy, and emphasize the mechanistic characteristics of LLPS regulated by PTMs and its effects on tumor progression. We then provide a perspective on further studies on LLPS and its regulation by PTMs in cancer research. This review aims to broaden the understanding of the functions of LLPS and its regulation by PTMs under normal or aberrant cellular conditions.
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Affiliation(s)
- Xiaojun Yan
- State Key Laboratory of Common Mechanism Research for Major Diseases & Department of Medical Genetics, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
| | - Meng Zhang
- State Key Laboratory of Common Mechanism Research for Major Diseases & Department of Medical Genetics, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
| | - Donglai Wang
- State Key Laboratory of Common Mechanism Research for Major Diseases & Department of Medical Genetics, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China.
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10
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Zerze GH. Optimizing the Martini 3 Force Field Reveals the Effects of the Intricate Balance between Protein-Water Interaction Strength and Salt Concentration on Biomolecular Condensate Formation. J Chem Theory Comput 2024; 20:1646-1655. [PMID: 37043540 DOI: 10.1021/acs.jctc.2c01273] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Condensation/dissolution has become a widely acknowledged biological macromolecular assembly phenomenon in subcellular compartmentalization. The MARTINI force field offers a coarse-grained protein model with a resolution that preserves molecular details with an explicit (CG) solvent. Despite its relatively higher resolution, it can still achieve condensate formation in a reasonable computing time with explicit solvent and ionic species. Therefore, it is highly desirable to tune this force field to be able to reproduce the experimentally observed properties of the condensate formation. In this work, we studied the condensate formation of the low-sequence complexity domain of fused in sarcoma protein using a MARTINI 3 force field by systematically modifying (increasing) the protein-water interaction strength and varying the salt concentration. We found that the condensate formation is sensitive both to the protein-water interaction strength and the presence of salt. While the unmodified MARTINI force field yields a complete collapse of proteins into one dense phase (i.e., no dilute phase), we reported a range of modified protein-water interaction strength that is capable of capturing the experimentally found transfer free energy between dense and dilute phases. We also found that the condensates lose their spherical shape upon the addition of salt, especially when the protein-water interactions are weak. Interchain amino acid contact map analysis showed one explanation for this observation: the protein-protein contact fraction reduces as salt is added to systems (when the protein-water interactions are weak), consistent with electrostatic screening effects. This reduction might be responsible for the condensates becoming nonspherical upon the addition of salt by reducing the need for minimizing the interfacial area. However, as the protein-water interactions become stronger to the extent that makes the transfer free energy agree well with experimentally observed transfer free energy, we found an increase in the protein-protein contact fraction upon the addition of salt, consistent with the salting-out effects. Therefore, we concluded that there is an intricate balance between screening effects and salting-out effects upon the addition of salt and this balance is highly sensitive to the strength of protein-water interactions.
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Affiliation(s)
- Gül H Zerze
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, Texas 77204, United States
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11
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An Y, Webb MA, Jacobs WM. Active learning of the thermodynamics-dynamics trade-off in protein condensates. SCIENCE ADVANCES 2024; 10:eadj2448. [PMID: 38181073 PMCID: PMC10775998 DOI: 10.1126/sciadv.adj2448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 12/04/2023] [Indexed: 01/07/2024]
Abstract
Phase-separated biomolecular condensates exhibit a wide range of dynamic properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino acid compositions and nonuniform sequence patterning map to a range of independently tunable dynamic and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.
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Affiliation(s)
- Yaxin An
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Michael A. Webb
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA
| | - William M. Jacobs
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
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12
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Cai L, Wang GG. Through the lens of phase separation: intrinsically unstructured protein and chromatin looping. Nucleus 2023; 14:2179766. [PMID: 36821650 PMCID: PMC9980480 DOI: 10.1080/19491034.2023.2179766] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
The establishment, maintenance and dynamic regulation of three-dimensional (3D) chromatin structures provide an important means for partitioning of genome into functionally distinctive domains, which helps to define specialized gene expression programs associated with developmental stages and cell types. Increasing evidence supports critical roles for intrinsically disordered regions (IDRs) harbored within transcription factors (TFs) and chromatin-modulatory proteins in inducing phase separation, a phenomenon of forming membrane-less condensates through partitioning of biomolecules. Such a process is also critically involved in the establishment of high-order chromatin structures and looping. IDR- and phase separation-driven 3D genome (re)organization often goes wrong in disease such as cancer. This review discusses about recent advances in understanding how phase separation of intrinsically disordered proteins (IDPs) modulates chromatin looping and gene expression.
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Affiliation(s)
- Ling Cai
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA,Department of Genetics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA,Ling Cai Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC27599, USA
| | - Gang Greg Wang
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA,Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA,CONTACT Gang Greg Wang Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC27599, USA
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13
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Osmanović D, Franco E. Chemical reaction motifs driving non-equilibrium behaviours in phase separating materials. J R Soc Interface 2023; 20:20230117. [PMID: 37907095 PMCID: PMC10618056 DOI: 10.1098/rsif.2023.0117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 10/11/2023] [Indexed: 11/02/2023] Open
Abstract
Chemical reactions that couple to systems that phase separate have been implicated in diverse contexts from biology to materials science. However, how a particular set of chemical reactions (chemical reaction network, CRN) would affect the behaviours of a phase separating system is difficult to fully predict theoretically. In this paper, we analyse a mean field theory coupling CRNs to a combined system of phase separating and non-phase separating materials and analyse how the properties of the CRNs affect different classes of non-equilibrium behaviour: microphase separation or temporally oscillating patterns. We examine the problem of achieving microphase separated condensates by statistical analysis of the Jacobians, of which the most important motifs are negative feedback of the phase separating component and combined inhibition/activation by the non-phase separating components. We then identify CRN motifs that are likely to yield microphase by examining randomly generated networks and parameters. Molecular sequestration of the phase separating motif is shown to be the most robust towards yielding microphase separation. Subsequently, we find that dynamics of the phase separating species is promoted most easily by inducing oscillations in the diffusive components coupled to the phase separating species. Our results provide guidance towards the design of CRNs that manage the formation, dissolution and organization of compartments.
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Affiliation(s)
- Dino Osmanović
- Department of Mechanical and Aerospace Engineering, University of California, Los Angeles 90095, CA, USA
| | - Elisa Franco
- Department of Mechanical and Aerospace Engineering, University of California, Los Angeles 90095, CA, USA
- Department of Bioengineering, University of California, Los Angeles 90095, CA, USA
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14
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Kang WB, Bao L, Zhang K, Guo J, Zhu BC, Tang QY, Ren WT, Zhu G. Multi-scale molecular simulation of random peptide phase separation and its extended-to-compact structure transition driven by hydrophobic interactions. SOFT MATTER 2023; 19:7944-7954. [PMID: 37815389 DOI: 10.1039/d3sm00633f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
Intrinsically disordered proteins (IDPs) often undergo liquid-liquid phase separation (LLPS) and form membraneless organelles or protein condensates. One of the core problems is how do electrostatic repulsion and hydrophobic interactions in peptides regulate the phase separation process? To answer this question, this study uses random peptides composed of positively charged arginine (Arg, R) and hydrophobic isoleucine (Ile, I) as the model systems, and conduct large-scale simulations using all atom and coarse-grained model multi-scale simulation methods. In this article, we investigate the phase separation of different sequences using a coarse-grained model. It is found that the stronger the electrostatic repulsion in the system, the more extended the single-chain structure, and the more likely the system forms a low-density homogeneous phase. In contrast, the stronger the hydrophobic effect of the system, the more compact the single-chain structure, the easier phase separation, and the higher the critical temperature of phase separation. Overall, by taking the random polypeptides composed of two types of amino acid residues as model systems, this study discusses the relationship between the protein sequence and phase behaviour, and provides theoretical insights into the interactions within or between proteins. It is expected to provide essential physical information for the sequence design of functional IDPs, as well as data to support the diagnosis and treatment of the LLPS-associated diseases.
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Affiliation(s)
- Wen Bin Kang
- School of Public Health, Hubei University of Medicine, Shiyan 442000, China.
| | - Lei Bao
- School of Public Health, Hubei University of Medicine, Shiyan 442000, China.
| | - Kai Zhang
- School of Physics, Nanjing University, Nanjing 210093, China
| | - Jia Guo
- School of Public Health, Hubei University of Medicine, Shiyan 442000, China.
| | - Ben Chao Zhu
- School of Public Health, Hubei University of Medicine, Shiyan 442000, China.
| | - Qian-Yuan Tang
- Department of Physics, Hong Kong Baptist University, Kowloon, Hong Kong SAR, China
| | - Wei Tong Ren
- Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, China
| | - Gen Zhu
- School of Public Health, Hubei University of Medicine, Shiyan 442000, China.
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15
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Himanshu, Chakraborty K, Patra TK. Developing efficient deep learning model for predicting copolymer properties. Phys Chem Chem Phys 2023; 25:25166-25176. [PMID: 37712405 DOI: 10.1039/d3cp03100d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/16/2023]
Abstract
Deep learning models are gaining popularity and potency in predicting polymer properties. These models can be built using pre-existing data and are useful for the rapid prediction of polymer properties. However, the performance of a deep learning model is intricately connected to its topology and the volume of training data. There is no facile protocol available to select a deep learning architecture, and there is a lack of a large volume of homogeneous sequence-property data of polymers. These two factors are the primary bottleneck for the efficient development of deep learning models for polymers. Here we assess the severity of these factors and propose strategies to address them. We show that a linear layer-by-layer expansion of a neural network can help in identifying the best neural network topology for a given problem. Moreover, we map the discrete sequence space of a polymer to a continuous one-dimensional latent space using a feature extraction technique to identify minimal data points for training a deep learning model. We implement these approaches for two representative cases of building sequence-property surrogate models, viz., the single-molecule radius of gyration of a copolymer and copolymer compatibilizer. This work demonstrates efficient methods for building deep learning models with minimal data and hyperparameters for predicting sequence-defined properties of polymers.
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Affiliation(s)
- Himanshu
- Department of Chemical Engineering and Center for Atomistic Modeling and Materials Design, Indian Institute of Technology Madras, Chennai, TN 600036, India.
| | - Kaushik Chakraborty
- Department of Chemical Engineering and Center for Atomistic Modeling and Materials Design, Indian Institute of Technology Madras, Chennai, TN 600036, India.
| | - Tarak K Patra
- Department of Chemical Engineering and Center for Atomistic Modeling and Materials Design, Indian Institute of Technology Madras, Chennai, TN 600036, India.
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16
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Mukherjee S, Schäfer LV. Thermodynamic forces from protein and water govern condensate formation of an intrinsically disordered protein domain. Nat Commun 2023; 14:5892. [PMID: 37735186 PMCID: PMC10514047 DOI: 10.1038/s41467-023-41586-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/08/2023] [Indexed: 09/23/2023] Open
Abstract
Liquid-liquid phase separation (LLPS) can drive a multitude of cellular processes by compartmentalizing biological cells via the formation of dense liquid biomolecular condensates, which can function as membraneless organelles. Despite its importance, the molecular-level understanding of the underlying thermodynamics of this process remains incomplete. In this study, we use atomistic molecular dynamics simulations of the low complexity domain (LCD) of human fused in sarcoma (FUS) protein to investigate the contributions of water and protein molecules to the free energy changes that govern LLPS. Both protein and water components are found to have comparably sizeable thermodynamic contributions to the formation of FUS condensates. Moreover, we quantify the counteracting effects of water molecules that are released into the bulk upon condensate formation and the waters retained within the protein droplets. Among the various factors considered, solvation entropy and protein interaction enthalpy are identified as the most important contributions, while solvation enthalpy and protein entropy changes are smaller. These results provide detailed molecular insights on the intricate thermodynamic interplay between protein- and solvation-related forces underlying the formation of biomolecular condensates.
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Affiliation(s)
- Saumyak Mukherjee
- Center for Theoretical Chemistry, Ruhr University Bochum, D-44780, Bochum, Germany
| | - Lars V Schäfer
- Center for Theoretical Chemistry, Ruhr University Bochum, D-44780, Bochum, Germany.
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17
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Saar KL, Qian D, Good LL, Morgunov AS, Collepardo-Guevara R, Best RB, Knowles TPJ. Theoretical and Data-Driven Approaches for Biomolecular Condensates. Chem Rev 2023; 123:8988-9009. [PMID: 37171907 PMCID: PMC10375482 DOI: 10.1021/acs.chemrev.2c00586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Indexed: 05/14/2023]
Abstract
Biomolecular condensation processes are increasingly recognized as a fundamental mechanism that living cells use to organize biomolecules in time and space. These processes can lead to the formation of membraneless organelles that enable cells to perform distinct biochemical processes in controlled local environments, thereby supplying them with an additional degree of spatial control relative to that achieved by membrane-bound organelles. This fundamental importance of biomolecular condensation has motivated a quest to discover and understand the molecular mechanisms and determinants that drive and control this process. Within this molecular viewpoint, computational methods can provide a unique angle to studying biomolecular condensation processes by contributing the resolution and scale that are challenging to reach with experimental techniques alone. In this Review, we focus on three types of dry-lab approaches: theoretical methods, physics-driven simulations and data-driven machine learning methods. We review recent progress in using these tools for probing biomolecular condensation across all three fields and outline the key advantages and limitations of each of the approaches. We further discuss some of the key outstanding challenges that we foresee the community addressing next in order to develop a more complete picture of the molecular driving forces behind biomolecular condensation processes and their biological roles in health and disease.
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Affiliation(s)
- Kadi L. Saar
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Cambridge CB2 1EW, United Kingdom
- Transition
Bio Ltd., Cambridge, United Kingdom
| | - Daoyuan Qian
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Lydia L. Good
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Cambridge CB2 1EW, United Kingdom
- Laboratory
of Chemical Physics, National Institute of Diabetes and Digestive
and Kidney Diseases, National Institutes
of Health, Bethesda, Maryland 20892, United States
| | - Alexey S. Morgunov
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Rosana Collepardo-Guevara
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Cambridge CB2 1EW, United Kingdom
- Department
of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Robert B. Best
- Laboratory
of Chemical Physics, National Institute of Diabetes and Digestive
and Kidney Diseases, National Institutes
of Health, Bethesda, Maryland 20892, United States
| | - Tuomas P. J. Knowles
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Cambridge CB2 1EW, United Kingdom
- Cavendish
Laboratory, Department of Physics, University
of Cambridge, Cambridge CB3 0HE, United Kingdom
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18
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Shi J, Albreiki F, Yamil J Colón, Srivastava S, Whitmer JK. Transfer Learning Facilitates the Prediction of Polymer-Surface Adhesion Strength. J Chem Theory Comput 2023; 19:4631-4640. [PMID: 37068204 DOI: 10.1021/acs.jctc.2c01314] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Abstract
Machine learning (ML) accelerates the exploration of material properties and their links to the structure of the underlying molecules. In previous work [Shi et al. ACS Applied Materials & Interfaces 2022, 14, 37161-37169.], ML models were applied to predict the adhesive free energy of polymer-surface interactions with high accuracy from the knowledge of the sequence data, demonstrating successes in inverse-design of polymer sequence for known surface compositions. While the method was shown to be successful in designing polymers for a known surface, extensive data sets were needed for each specific surface in order to train the surrogate models. Ideally, one should be able to infer information about similar surfaces without having to regenerate a full complement of adhesion data for each new case. In the current work, we demonstrate a transfer learning (TL) technique using a deep neural network to improve the accuracy of ML models trained on small data sets by pretraining on a larger database from a related system and fine-tuning the weights of all layers with a small amount of additional data. The shared knowledge from the pretrained model facilitates the prediction accuracy significantly on small data sets. We also explore the limits of database size on accuracy and the optimal tuning of network architecture and parameters for our learning tasks. While applied to a relatively simple coarse-grained (CG) polymer model, the general lessons of this study apply to detailed modeling studies and the broader problems of inverse materials design.
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Affiliation(s)
- Jiale Shi
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Fahed Albreiki
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Yamil J Colón
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Samanvaya Srivastava
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
- California NanoSystems Institute, Center for Biological Physics, University of California, Los Angeles, Los Angeles, California 90095, United States
- Institute for Carbon Management, University of California, Los Angeles, Los Angeles, California 90095, United States
- Center for Biological Physics, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Jonathan K Whitmer
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States
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19
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Sanchez-Burgos I, Herriott L, Collepardo-Guevara R, Espinosa JR. Surfactants or scaffolds? RNAs of varying lengths control the thermodynamic stability of condensates differently. Biophys J 2023; 122:2973-2987. [PMID: 36883003 PMCID: PMC10398262 DOI: 10.1016/j.bpj.2023.03.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/23/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Biomolecular condensates, thought to form via liquid-liquid phase separation of intracellular mixtures, are multicomponent systems that can include diverse types of proteins and RNAs. RNA is a critical modulator of RNA-protein condensate stability, as it induces an RNA concentration-dependent reentrant phase transition-increasing stability at low RNA concentrations and decreasing it at high concentrations. Beyond concentration, RNAs inside condensates can be heterogeneous in length, sequence, and structure. Here, we use multiscale simulations to understand how different RNA parameters interact with one another to modulate the properties of RNA-protein condensates. To do so, we perform residue/nucleotide resolution coarse-grained molecular dynamics simulations of multicomponent RNA-protein condensates containing RNAs of different lengths and concentrations, and either FUS or PR25 proteins. Our simulations reveal that RNA length regulates the reentrant phase behavior of RNA-protein condensates: increasing RNA length sensitively rises the maximum value that the critical temperature of the mixture reaches, and the maximum concentration of RNA that the condensate can incorporate before beginning to become unstable. Strikingly, RNAs of different lengths are organized heterogeneously inside condensates, which allows them to enhance condensate stability via two distinct mechanisms: shorter RNA chains accumulate at the condensate's surface acting as natural biomolecular surfactants, while longer RNA chains concentrate inside the core to saturate their bonds and enhance the density of molecular connections in the condensate. Using a patchy particle model, we additionally demonstrate that the combined impact of RNA length and concentration on condensate properties is dictated by the valency, binding affinity, and polymer length of the various biomolecules involved. Our results postulate that diversity on RNA parameters within condensates allows RNAs to increase condensate stability by fulfilling two different criteria: maximizing enthalpic gain and minimizing interfacial free energy; hence, RNA diversity should be considered when assessing the impact of RNA on biomolecular condensates regulation.
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Affiliation(s)
- Ignacio Sanchez-Burgos
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, United Kingdom
| | - Lara Herriott
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, United Kingdom
| | - Rosana Collepardo-Guevara
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom; Department of Genetics, University of Cambridge, Cambridge, United Kingdom.
| | - Jorge R Espinosa
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, United Kingdom; Departament of Chemical Physics, Faculty of Chemical Sciences, Universidad Complutense de Madrid, Madrid, Spain.
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20
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Hutin S, Kumita JR, Strotmann VI, Dolata A, Ling WL, Louafi N, Popov A, Milhiet PE, Blackledge M, Nanao MH, Wigge PA, Stahl Y, Costa L, Tully MD, Zubieta C. Phase separation and molecular ordering of the prion-like domain of the Arabidopsis thermosensory protein EARLY FLOWERING 3. Proc Natl Acad Sci U S A 2023; 120:e2304714120. [PMID: 37399408 PMCID: PMC10334799 DOI: 10.1073/pnas.2304714120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 06/06/2023] [Indexed: 07/05/2023] Open
Abstract
Liquid-liquid phase separation (LLPS) is an important mechanism enabling the dynamic compartmentalization of macromolecules, including complex polymers such as proteins and nucleic acids, and occurs as a function of the physicochemical environment. In the model plant, Arabidopsis thaliana, LLPS by the protein EARLY FLOWERING3 (ELF3) occurs in a temperature-sensitive manner and controls thermoresponsive growth. ELF3 contains a largely unstructured prion-like domain (PrLD) that acts as a driver of LLPS in vivo and in vitro. The PrLD contains a poly-glutamine (polyQ) tract, whose length varies across natural Arabidopsis accessions. Here, we use a combination of biochemical, biophysical, and structural techniques to investigate the dilute and condensed phases of the ELF3 PrLD with varying polyQ lengths. We demonstrate that the dilute phase of the ELF3 PrLD forms a monodisperse higher-order oligomer that does not depend on the presence of the polyQ sequence. This species undergoes LLPS in a pH- and temperature-sensitive manner and the polyQ region of the protein tunes the initial stages of phase separation. The liquid phase rapidly undergoes aging and forms a hydrogel as shown by fluorescence and atomic force microscopies. Furthermore, we demonstrate that the hydrogel assumes a semiordered structure as determined by small-angle X-ray scattering, electron microscopy, and X-ray diffraction. These experiments demonstrate a rich structural landscape for a PrLD protein and provide a framework to describe the structural and biophysical properties of biomolecular condensates.
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Affiliation(s)
- Stephanie Hutin
- Laboratoire de Physiologie Cellulaire et Végétale, University Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l'énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Institut de recherche interdisciplinaire de Grenoble, Grenoble38054, France
| | - Janet R. Kumita
- Department of Pharmacology, University of Cambridge, CambridgeCB2 1PD, United Kingdom
| | - Vivien I. Strotmann
- Institute for Developmental Genetics, Heinrich-Heine University, DüsseldorfD-40225, Germany
| | - Anika Dolata
- Institute for Developmental Genetics, Heinrich-Heine University, DüsseldorfD-40225, Germany
| | - Wai Li Ling
- University Grenoble Alpes, Commissariat à l'énergie atomique et aux énergies alternatives, Centre national de la recherche scientifique, Institut de Biologie Structurale, Institut de recherche interdisciplinaire de Grenoble, Grenoble38000, France
| | - Nessim Louafi
- Centre de Biologie Structurale, University Montpellier, Centre national de la recherche scientifique, Institut national de la santé et de la recherche médicale, Montpellier34090, France
| | - Anton Popov
- European Synchrotron Radiation Facility, Structural Biology Group, Grenoble38000, France
| | - Pierre-Emmanuel Milhiet
- Centre de Biologie Structurale, University Montpellier, Centre national de la recherche scientifique, Institut national de la santé et de la recherche médicale, Montpellier34090, France
| | - Martin Blackledge
- University Grenoble Alpes, Commissariat à l'énergie atomique et aux énergies alternatives, Centre national de la recherche scientifique, Institut de Biologie Structurale, Institut de recherche interdisciplinaire de Grenoble, Grenoble38000, France
| | - Max H. Nanao
- European Synchrotron Radiation Facility, Structural Biology Group, Grenoble38000, France
| | - Philip A. Wigge
- Leibniz-Institut für Gemüse- und Zierpflanzenbau, 14979Grossbeeren, Germany
- Institute of Biochemistry and Biology, University of Potsdam, 14476Potsdam, Germany
| | - Yvonne Stahl
- Institute for Developmental Genetics, Heinrich-Heine University, DüsseldorfD-40225, Germany
- Cluster of Excellence on Plant Sciences, Heinrich-Heine University, DüsseldorfD-40225, Germany
| | - Luca Costa
- Centre de Biologie Structurale, University Montpellier, Centre national de la recherche scientifique, Institut national de la santé et de la recherche médicale, Montpellier34090, France
| | - Mark D. Tully
- European Synchrotron Radiation Facility, Structural Biology Group, Grenoble38000, France
| | - Chloe Zubieta
- Laboratoire de Physiologie Cellulaire et Végétale, University Grenoble Alpes, Centre national de la recherche scientifique, Commissariat à l'énergie atomique et aux énergies alternatives, Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Institut de recherche interdisciplinaire de Grenoble, Grenoble38054, France
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21
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Abstract
Biomolecular condensates constitute a newly recognized form of spatial organization in living cells. Although many condensates are believed to form as a result of phase separation, the physicochemical properties that determine the phase behavior of heterogeneous biomolecular mixtures are only beginning to be explored. Theory and simulation provide invaluable tools for probing the relationship between molecular determinants, such as protein and RNA sequences, and the emergence of phase-separated condensates in such complex environments. This review covers recent advances in the prediction and computational design of biomolecular mixtures that phase-separate into many coexisting phases. First, we review efforts to understand the phase behavior of mixtures with hundreds or thousands of species using theoretical models and statistical approaches. We then describe progress in developing analytical theories and coarse-grained simulation models to predict multiphase condensates with the molecular detail required to make contact with biophysical experiments. We conclude by summarizing the challenges ahead for modeling the inhomogeneous spatial organization of biomolecular mixtures in living cells.
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Affiliation(s)
- William M Jacobs
- Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
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22
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Rekhi S, Sundaravadivelu Devarajan D, Howard MP, Kim YC, Nikoubashman A, Mittal J. Role of Strong Localized vs Weak Distributed Interactions in Disordered Protein Phase Separation. J Phys Chem B 2023; 127:3829-3838. [PMID: 37079924 PMCID: PMC10187732 DOI: 10.1021/acs.jpcb.3c00830] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 04/03/2023] [Indexed: 04/22/2023]
Abstract
Interaction strength and localization are critical parameters controlling the single-chain and condensed-state properties of intrinsically disordered proteins (IDPs). Here, we decipher these relationships using coarse-grained heteropolymers comprised of hydrophobic (H) and polar (P) monomers as model IDPs. We systematically vary the fraction of P monomers XP and employ two distinct particle-based models that include either strong localized attractions between only H-H pairs (HP model) or weak distributed attractions between both H-H and H-P pairs (HP+ model). To compare different sequences and models, we first carefully tune the attraction strength for all sequences to match the single-chain radius of gyration. Interestingly, we find that this procedure produces similar conformational ensembles, nonbonded potential energies, and chain-level dynamics for single chains of almost all sequences in both models, with some deviations for the HP model at large XP. However, we observe a surprisingly rich phase behavior for the sequences in both models that deviates from the expectation that similarity at the single-chain level will translate to a similar phase-separation propensity. Coexistence between dilute and dense phases is only observed up to a model-dependent XP, despite the presence of favorable interchain interactions, which we quantify using the second virial coefficient. Instead, the limited number of attractive sites (H monomers) leads to the self-assembly of finite-sized clusters of different sizes depending on XP. Our findings strongly suggest that models with distributed interactions favor the formation of liquid-like condensates over a much larger range of sequence compositions compared to models with localized interactions.
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Affiliation(s)
- Shiv Rekhi
- Artie
McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | | | - Michael P. Howard
- Department
of Chemical Engineering, Auburn University, Auburn, Alabama 36849, United States
| | - Young C. Kim
- Center
for Materials Physics and Technology, Naval
Research Laboratory, Washington, D.C. 20375, United States
| | - Arash Nikoubashman
- Institute
of Physics, Johannes Gutenberg University
Mainz, Staudingerweg 7, 55128 Mainz, Germany
| | - Jeetain Mittal
- Artie
McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
- Department
of Chemistry, Texas A&M University, College Station, Texas 77843, United States
- Interdisciplinary
Graduate Program in Genetics and Genomics, Texas A&M University, College
Station, Texas 77843, United States
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23
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Panagiotopoulos AZ. Phase separation and aggregation in multiblock chains. J Chem Phys 2023; 158:2882254. [PMID: 37094002 DOI: 10.1063/5.0146673] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 03/30/2023] [Indexed: 04/26/2023] Open
Abstract
This paper focuses on phase and aggregation behavior for linear chains composed of blocks of hydrophilic and hydrophobic segments. Phase and conformational transitions of patterned chains are relevant for understanding liquid-liquid separation of biomolecular condensates, which play a prominent role in cellular biophysics and for surfactant and polymer applications. Previous studies of simple models for multiblock chains have shown that, depending on the sequence pattern and chain length, such systems can fall into one of two categories: displaying either phase separation or aggregation into finite-size clusters. The key new result of this paper is that both formation of finite-size aggregates and phase separation can be observed for certain chain architectures at appropriate conditions of temperature and concentration. For such systems, a bulk dense liquid condenses from a dilute phase that already contains multi-chain finite-size aggregates. The computational approach used in this study involves several distinct steps using histogram-reweighting grand canonical Monte Carlo simulations, which are described in some level of detail.
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24
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Gavrilov AA, Potemkin II. Copolymers with Nonblocky Sequences as Novel Materials with Finely Tuned Properties. J Phys Chem B 2023; 127:1479-1489. [PMID: 36790352 DOI: 10.1021/acs.jpcb.2c07689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
The copolymer sequence can be considered as a new tool to shape the resulting system properties on demand. This perspective is devoted to copolymers with "partially segregated" (or nonblocky) sequences. Such copolymers include gradient copolymers and copolymers with random sequences as well as copolymers with precisely controlled sequences. We overview recent developments in the synthesis of these systems as well as new findings regarding their properties, in particular, self-assembly in solutions and in melts. An emphasis is put on how the microscopic behavior of polymer chains is influenced by the chain sequences. In addition to that, a novel class of approaches allowing one to efficiently tackle the problem of copolymer chain sequence design─data driven methods (artificial intelligence and machine learning)─is discussed.
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Affiliation(s)
- Alexey A Gavrilov
- Physics Department, Lomonosov Moscow State University, Moscow 119991, Russian Federation.,Semenov Federal Research Center for Chemical Physics, Moscow 119991, Russian Federation
| | - Igor I Potemkin
- Physics Department, Lomonosov Moscow State University, Moscow 119991, Russian Federation
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25
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Chew PY, Reinhardt A. Phase diagrams-Why they matter and how to predict them. J Chem Phys 2023; 158:030902. [PMID: 36681642 DOI: 10.1063/5.0131028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Understanding the thermodynamic stability and metastability of materials can help us to, for example, gauge whether crystalline polymorphs in pharmaceutical formulations are likely to be durable. It can also help us to design experimental routes to novel phases with potentially interesting properties. In this Perspective, we provide an overview of how thermodynamic phase behavior can be quantified both in computer simulations and machine-learning approaches to determine phase diagrams, as well as combinations of the two. We review the basic workflow of free-energy computations for condensed phases, including some practical implementation advice, ranging from the Frenkel-Ladd approach to thermodynamic integration and to direct-coexistence simulations. We illustrate the applications of such methods on a range of systems from materials chemistry to biological phase separation. Finally, we outline some challenges, questions, and practical applications of phase-diagram determination which we believe are likely to be possible to address in the near future using such state-of-the-art free-energy calculations, which may provide fundamental insight into separation processes using multicomponent solvents.
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Affiliation(s)
- Pin Yu Chew
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Aleks Reinhardt
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
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26
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Millar SR, Huang JQ, Schreiber KJ, Tsai YC, Won J, Zhang J, Moses AM, Youn JY. A New Phase of Networking: The Molecular Composition and Regulatory Dynamics of Mammalian Stress Granules. Chem Rev 2023. [PMID: 36662637 PMCID: PMC10375481 DOI: 10.1021/acs.chemrev.2c00608] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Stress granules (SGs) are cytosolic biomolecular condensates that form in response to cellular stress. Weak, multivalent interactions between their protein and RNA constituents drive their rapid, dynamic assembly through phase separation coupled to percolation. Though a consensus model of SG function has yet to be determined, their perceived implication in cytoprotective processes (e.g., antiviral responses and inhibition of apoptosis) and possible role in the pathogenesis of various neurodegenerative diseases (e.g., amyotrophic lateral sclerosis and frontotemporal dementia) have drawn great interest. Consequently, new studies using numerous cell biological, genetic, and proteomic methods have been performed to unravel the mechanisms underlying SG formation, organization, and function and, with them, a more clearly defined SG proteome. Here, we provide a consensus SG proteome through literature curation and an update of the user-friendly database RNAgranuleDB to version 2.0 (http://rnagranuledb.lunenfeld.ca/). With this updated SG proteome, we use next-generation phase separation prediction tools to assess the predisposition of SG proteins for phase separation and aggregation. Next, we analyze the primary sequence features of intrinsically disordered regions (IDRs) within SG-resident proteins. Finally, we review the protein- and RNA-level determinants, including post-translational modifications (PTMs), that regulate SG composition and assembly/disassembly dynamics.
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Affiliation(s)
- Sean R Millar
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Jie Qi Huang
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Karl J Schreiber
- Program in Molecular Medicine, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Yi-Cheng Tsai
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Jiyun Won
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario M5S 3B2, Canada
| | - Jianping Zhang
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario M5G 1X5, Canada
| | - Alan M Moses
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario M5S 3B2, Canada.,Department of Computer Science, University of Toronto, Toronto, Ontario M5T 3A1, Canada.,The Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario M5S 3B2, Canada
| | - Ji-Young Youn
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.,Program in Molecular Medicine, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
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27
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Ramesh PS, Patra TK. Polymer sequence design via molecular simulation-based active learning. SOFT MATTER 2023; 19:282-294. [PMID: 36519427 DOI: 10.1039/d2sm01193j] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Molecular-scale interactions and chemical structures offer an enormous opportunity to tune material properties. However, designing materials from their molecular scale is a grand challenge owing to the practical limitations in exploring astronomically large design spaces using traditional experimental or computational methods. Advancements in data science and machine learning have produced a host of tools and techniques that can address this problem and facilitate the efficient exploration of large search spaces. In this work, a blended approach integrating physics-based methods, machine learning techniques and uncertainty quantification is implemented to effectively screen a macromolecular sequence space and design target structures. Here, we survey and assess the efficacy of data-driven methods within the framework of active learning for a challenging design problem, viz., sequence optimization of a copolymer. We report the impact of surrogate models, kernels, and initial conditions on the convergence of the active learning method for the sequence design problem. This work establishes optimal strategies and hyperparameters for efficient inverse design of polymer sequences via active learning.
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Affiliation(s)
- Praneeth S Ramesh
- Department of Chemical Engineering, Center for Atomistic Modeling and Materials Design and Center for Carbon Capture Utilization and Storage, Indian Institute of Technology Madras, Chennai, TN 600036, India.
| | - Tarak K Patra
- Department of Chemical Engineering, Center for Atomistic Modeling and Materials Design and Center for Carbon Capture Utilization and Storage, Indian Institute of Technology Madras, Chennai, TN 600036, India.
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28
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Najafi S, McCarty J, Delaney KT, Fredrickson GH, Shea JE. Field-Theoretic Simulation Method to Study the Liquid-Liquid Phase Separation of Polymers. Methods Mol Biol 2023; 2563:37-49. [PMID: 36227467 DOI: 10.1007/978-1-0716-2663-4_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Liquid-liquid phase separation (LLPS) is a process that results in the formation of a polymer-rich liquid phase coexisting with a polymer-depleted liquid phase. LLPS plays a critical role in the cell through the formation of membrane-less organelles, but it also has a number of biotechnical and biomedical applications such as drug confinement and its targeted delivery. In this chapter, we present a computational efficient methodology that uses field-theoretic simulations (FTS) with complex Langevin (CL) sampling to characterize polymer phase behavior and delineate the LLPS phase boundaries. This approach is a powerful complement to analytical and explicit-particle simulations, and it can serve to inform experimental LLPS studies. The strength of the method lies in its ability to properly sample a large ensemble of polymers in a saturated solution while including the effect of composition fluctuations on LLPS. We describe the approaches that can be used to accurately construct phase diagrams of a variety of molecularly designed polymers and illustrate the method by generating an approximation-free phase diagram for a classical symmetric diblock polyampholyte.
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Affiliation(s)
- Saeed Najafi
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, CA, USA
- Materials Research Laboratory, University of California, Santa Barbara, CA, USA
| | - James McCarty
- Department of Chemistry, Western Washington University, Bellingham, WA, USA
| | - Kris T Delaney
- Materials Research Laboratory, University of California, Santa Barbara, CA, USA
| | - Glenn H Fredrickson
- Materials Research Laboratory, University of California, Santa Barbara, CA, USA
- Department of Chemical Engineering, University of California, Santa Barbara, CA, USA
| | - Joan-Emma Shea
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, CA, USA.
- Department of Physics, University of California Santa Barbara, Santa Barbara, CA, USA.
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29
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Workman RJ, Gorle S, Pettitt BM. Effects of Conformational Constraint on Peptide Solubility Limits. J Phys Chem B 2022; 126:10510-10518. [PMID: 36450134 DOI: 10.1021/acs.jpcb.2c06458] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
Liquid-liquid phase separation of proteins preferentially involves intrinsically disordered proteins or disordered regions. Understanding the solution chemistry of these phase separations is key to learning how to quantify and manipulate systems that involve such processes. Here, we investigate the effect of cyclization on the liquid-liquid phase separation of short polyglycine peptides. We simulated separate aqueous systems of supersaturated cyclic and linear GGGGG and observed spontaneous liquid-liquid phase separation in each of the solutions. The cyclic GGGGG phase separates less robustly than linear GGGGG and has a higher aqueous solubility, even though linear GGGGG has a more favorable single molecule solvation free energy. The versatile and abundant interpeptide contacts formed by the linear GGGGG stabilize the condensed droplet phase, driving the phase separation in this system. In particular, we find that van der Waals close contact interactions are enriched in the droplet phase as opposed to electrostatic interactions. An analysis of the change in backbone conformational entropy that accompanies the phase transition revealed that cyclic peptides lose significantly less entropy in this process as expected. However, we find that the enhanced interaction enthalpy of linear GGGGG in the droplet phase is enough to compensate for a larger decrease in conformational entropy.
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Affiliation(s)
- Riley J Workman
- Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0304, United States
| | - Suresh Gorle
- Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0304, United States
| | - B Montgomery Pettitt
- Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0304, United States
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30
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Huo Z, Skala SJ, Falck LR, Laaser JE, Statt A. Computational Study of Mechanochemical Activation in Nanostructured Triblock Copolymers. ACS POLYMERS AU 2022; 2:467-477. [PMID: 36536889 PMCID: PMC9756960 DOI: 10.1021/acspolymersau.2c00031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 06/17/2023]
Abstract
Force-driven chemical reactions have emerged as an attractive platform for diverse applications in polymeric materials. However, the microscopic chain conformations and topologies necessary for efficiently transducing macroscopic forces to the molecular scale are not well-understood. In this work, we use a coarse-grained model to investigate the impact of network-like topologies on mechanochemical activation in self-assembled triblock copolymers. We find that mechanochemical activation during tensile deformation depends strongly on both the polymer composition and chain conformation in these materials. Activation primarily occurs in the tie chains connecting different glassy domains and in loop chains that are hooked onto each other by physical entanglements. Activation also requires a higher stress in materials having a higher glassy block content. Overall, the lamellar samples show the highest percent activation at high stress. In contrast, at low stress, the spherical morphology, which has the lowest glassy fraction, shows the highest activation. Additionally, we observe a spatial pattern of activation, which appears to be tied to distortion of the self-assembled morphology. Higher activation is observed in the tips of the chevrons formed during deformation of lamellar samples as well as in the centers between the cylinders in the cylindrical morphology. Our work shows that changes in the network-like topology in different morphologies significantly impact mechanochemical activation efficiencies in these materials, suggesting that this area will be a fruitful avenue for further experimental research.
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Affiliation(s)
- Zijian Huo
- Department
of Chemistry, University of Pittsburgh, 219 Parkman Ave., Pittsburgh, Pennsylvania 15260, United States
| | - Stephen J Skala
- Materials
Science and Engineering, Grainger College of Engineering, University of Illinois, Urbana−Champaign, Illinois 61801, United States
| | - Lavinia R Falck
- Department
of Chemistry, University of Pittsburgh, 219 Parkman Ave., Pittsburgh, Pennsylvania 15260, United States
| | - Jennifer E Laaser
- Department
of Chemistry, University of Pittsburgh, 219 Parkman Ave., Pittsburgh, Pennsylvania 15260, United States
| | - Antonia Statt
- Materials
Science and Engineering, Grainger College of Engineering, University of Illinois, Urbana−Champaign, Illinois 61801, United States
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31
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Wessén J, Das S, Pal T, Chan HS. Analytical Formulation and Field-Theoretic Simulation of Sequence-Specific Phase Separation of Protein-Like Heteropolymers with Short- and Long-Spatial-Range Interactions. J Phys Chem B 2022; 126:9222-9245. [PMID: 36343363 DOI: 10.1021/acs.jpcb.2c06181] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
A theory for sequence-dependent liquid-liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs) in the study of biomolecular condensates is formulated by extending the random phase approximation (RPA) and field-theoretic simulation (FTS) of heteropolymers with spatially long-range Coulomb interactions to include the fundamental effects of short-range, hydrophobic-like interactions between amino acid residues. To this end, short-range effects are modeled by Yukawa interactions between multiple nonelectrostatic charges derived from an eigenvalue decomposition of pairwise residue-residue contact energies. Chain excluded volume is afforded by incompressibility constraints. A mean-field approximation leads to an effective Flory-Huggins χ parameter, which, in conjunction with RPA, accounts for the contact-interaction effects of amino acid composition and the sequence-pattern effects of long-range electrostatics in IDP LLPS, whereas FTS based on the formulation provides full sequence dependence for both short- and long-range interactions. This general approach is illustrated here by applications to variants of a natural IDP in the context of several different amino-acid interaction schemes as well as a set of different model hydrophobic-polar sequences sharing the same composition. Effectiveness of the methodology is verified by coarse-grained explicit-chain molecular dynamics simulations.
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Affiliation(s)
- Jonas Wessén
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Suman Das
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Tanmoy Pal
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Hue Sun Chan
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
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32
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Mazarakos K, Prasad R, Zhou HX. SpiDec: Computing binodals and interfacial tension of biomolecular condensates from simulations of spinodal decomposition. Front Mol Biosci 2022; 9:1021939. [PMID: 36353733 PMCID: PMC9637972 DOI: 10.3389/fmolb.2022.1021939] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/12/2022] [Indexed: 08/31/2023] Open
Abstract
Phase separation of intrinsically disordered proteins (IDPs) is a phenomenon associated with many essential cellular processes, but a robust method to compute the binodal from molecular dynamics simulations of IDPs modeled at the all-atom level in explicit solvent is still elusive, due to the difficulty in preparing a suitable initial dense configuration and in achieving phase equilibration. Here we present SpiDec as such a method, based on spontaneous phase separation via spinodal decomposition that produces a dense slab when the system is initiated at a homogeneous, low density. After illustrating the method on four model systems, we apply SpiDec to a tetrapeptide modeled at the all-atom level and solvated in TIP3P water. The concentrations in the dense and dilute phases agree qualitatively with experimental results and point to binodals as a sensitive property for force-field parameterization. SpiDec may prove useful for the accurate determination of the phase equilibrium of IDPs.
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Affiliation(s)
| | - Ramesh Prasad
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL, United States
| | - Huan-Xiang Zhou
- Department of Physics, University of Illinois at Chicago, Chicago, IL, United States
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL, United States
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33
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Tejedor AR, Sanchez-Burgos I, Estevez-Espinosa M, Garaizar A, Collepardo-Guevara R, Ramirez J, Espinosa JR. Protein structural transitions critically transform the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it. Nat Commun 2022; 13:5717. [PMID: 36175408 PMCID: PMC9522849 DOI: 10.1038/s41467-022-32874-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 08/18/2022] [Indexed: 12/03/2022] Open
Abstract
Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. One potential source of loss of liquid-like properties during ageing of RNA-binding protein condensates is the progressive formation of inter-protein β-sheets. To bridge microscopic understanding between accumulation of inter-protein β-sheets over time and the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that exhibit accumulation of inter-protein β-sheets over time. We reveal that inter-protein β-sheets notably increase condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered, culminating in gelation when the network of strong β-sheets fully percolates. However, high concentrations of RNA decelerate the emergence of inter-protein β-sheets. Our study uncovers molecular and kinetic factors explaining how the accumulation of inter-protein β-sheets can trigger liquid-to-solid transitions in condensates, and suggests a potential mechanism to slow such transitions down. In this work the authors propose a multiscale computational approach, integrating atomistic and coarse-grained models simulations, to study the thermodynamic and kinetic factors playing a major role in the liquid-to-solid transition of biomolecular condensates. It is revealed how the gradual accumulation of inter-protein β-sheets increases the viscosity of functional liquid-like condensates, transforming them into gel-like pathological aggregates, and it is also shown how high concentrations of RNA can decelerate such transition.
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Affiliation(s)
- Andres R Tejedor
- Department of Chemical Engineering, Universidad Politécnica de Madrid, José Gutiérrez Abascal 2, 28006, Madrid, Spain.,Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK
| | - Ignacio Sanchez-Burgos
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK
| | - Maria Estevez-Espinosa
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK.,Department of Biochemistry, University College London, Gower Street, London, WC1E 6BT, UK
| | - Adiran Garaizar
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK
| | - Rosana Collepardo-Guevara
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK.,Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK.,Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK
| | - Jorge Ramirez
- Department of Chemical Engineering, Universidad Politécnica de Madrid, José Gutiérrez Abascal 2, 28006, Madrid, Spain.
| | - Jorge R Espinosa
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK.
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34
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Shillcock JC, Lagisquet C, Alexandre J, Vuillon L, Ipsen JH. Model biomolecular condensates have heterogeneous structure quantitatively dependent on the interaction profile of their constituent macromolecules. SOFT MATTER 2022; 18:6674-6693. [PMID: 36004748 DOI: 10.1039/d2sm00387b] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Biomolecular condensates play numerous roles in cells by selectively concentrating client proteins while excluding others. These functions are likely to be sensitive to the spatial organization of the scaffold proteins forming the condensate. We use coarse-grained molecular simulations to show that model intrinsically-disordered proteins phase separate into a heterogeneous, structured fluid characterized by a well-defined length scale. The proteins are modelled as semi-flexible polymers with punctate, multifunctional binding sites in good solvent conditions. Their dense phase is highly solvated with a spatial structure that is more sensitive to the separation of the binding sites than their affinity. We introduce graph theoretic measures to quantify their heterogeneity, and find that it increases with increasing binding site number, and exhibits multi-timescale dynamics. The model proteins also swell on passing from the dilute solution to the dense phase. The simulations predict that the structure of the dense phase is modulated by the location and affinity of binding sites distant from the termini of the proteins, while sites near the termini more strongly affect its phase behaviour. The relations uncovered between the arrangement of weak interaction sites on disordered proteins and the material properties of their dense phase can be experimentally tested to give insight into the biophysical properties, pathological effects, and rational design of biomolecular condensates.
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Affiliation(s)
- Julian C Shillcock
- Blue Brain Project and Laboratory of Molecular and Chemical Biology of Neurodegeneration, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
| | - Clément Lagisquet
- LAMA, Univ. Savoie Mont Blanc, CNRS, LAMA, 73376 Le Bourget du Lac, France.
| | - Jérémy Alexandre
- Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Laurent Vuillon
- LAMA, Univ. Savoie Mont Blanc, CNRS, LAMA, 73376 Le Bourget du Lac, France.
| | - John H Ipsen
- Dept. of Physics, Chemistry and Pharmacy, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark
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35
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Shi J, Quevillon MJ, Amorim Valença PH, Whitmer JK. Predicting Adhesive Free Energies of Polymer-Surface Interactions with Machine Learning. ACS APPLIED MATERIALS & INTERFACES 2022; 14:37161-37169. [PMID: 35917495 DOI: 10.1021/acsami.2c08891] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Polymer-surface interactions are crucial to many biological processes and industrial applications. Here we propose a machine learning method to connect a model polymer's sequence with its adhesion to decorated surfaces. We simulate the adhesive free energies of 20000 unique coarse-grained one-dimensional polymer sequences interacting with functionalized surfaces and build support vector regression models that demonstrate inexpensive and reliable prediction of the adhesive free energy as a function of sequence. Our work highlights the promising integration of coarse-grained simulation with data-driven machine learning methods for the design of functional polymers and represents an important step toward linking polymer compositions with polymer-surface interactions.
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Affiliation(s)
- Jiale Shi
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Michael J Quevillon
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Pedro H Amorim Valença
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Jonathan K Whitmer
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States
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36
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Wang Y, Stillinger FH, Debenedetti PG. Fluid-fluid phase transitions in a chiral molecular model. J Chem Phys 2022; 157:084501. [DOI: 10.1063/5.0105851] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Molecular chirality is a fundamental phenomenon, underlying both life as we know it and industrial pharmaceutical syntheses. Understanding the symmetry-breaking phase transitions exhibited by many chiral molecular substances provides basic insights for topics ranging from the origin of life to the rational design of drug manufacturing processes. In this work, we have performed molecular dynamics simulations to investigate the fluid-fluid phase transitions of a flexible 3-dimensional four-site chiral molecular model developed by Latinwo et al. [J. Chem. Phys. 145, 154503 (2016)] and Petsev et al. [J. Chem. Phys. 155, 084105 (2021)]. By introducing a bias favoring local homochiral versus heterochiral interactions, the system exhibits a phase transition from a single achiral phase to a single chiral phase which undergoes infrequent interconversion between the two thermodynamically identical chiral states, the L-rich and D-rich phases. According to the phase rule, this reactive binary system has two independent degrees of freedom and exhibits a density-dependent critical locus. Below the liquid-liquid critical locus, there exists a first-order vapor-liquid coexistence region with a single independent degree of freedom. Our results provide basic thermodynamic and kinetic insights for understanding many-body chiral symmetry breaking phenomena.
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Affiliation(s)
- Yiming Wang
- Princeton University, United States of America
| | - Frank H. Stillinger
- Chemistry Dept., Room 158, Princeton University Department of Chemistry, United States of America
| | - Pablo G. Debenedetti
- Chemical and Biological Engineering, Princeton University, United States of America
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37
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Graf IR, Machta BB. Thermodynamic stability and critical points in multicomponent mixtures with structured interactions. PHYSICAL REVIEW RESEARCH 2022; 4:033144. [PMID: 38343561 PMCID: PMC10857862 DOI: 10.1103/physrevresearch.4.033144] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Theoretical work has shed light on the phase behavior of idealized mixtures of many components with random interactions. However, typical mixtures interact through particular physical features, leading to a structured, nonrandom interaction matrix of lower rank. Here, we develop a theoretical framework for such mixtures and derive mean-field conditions for thermodynamic stability and critical behavior. Irrespective of the number of components and features, this framework allows for a generally lower-dimensional representation in the space of features and proposes a principled way to coarse-grain multicomponent mixtures as binary mixtures. Moreover, it suggests a way to systematically characterize different series of critical points and their codimensions in mean-field. Since every pairwise interaction matrix can be expressed in terms of features, our work is applicable to a broad class of mean-field models.
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Affiliation(s)
- Isabella R. Graf
- Department of Physics, Yale University, New Haven, Connecticut 06511, USA
| | - Benjamin B. Machta
- Department of Physics and Quantitative Biology Institute, Yale University, New Haven, Connecticut 06511, USA
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38
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Rovigatti L, Sciortino F. Designing Enhanced Entropy Binding in Single-Chain Nanoparticles. PHYSICAL REVIEW LETTERS 2022; 129:047801. [PMID: 35939033 DOI: 10.1103/physrevlett.129.047801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 06/24/2022] [Accepted: 07/01/2022] [Indexed: 06/15/2023]
Abstract
Single-chain nanoparticles (SCNPs) are a new class of bio- and soft-matter polymeric objects in which a fraction of the monomers are able to form equivalently intra- or interpolymer bonds. Here we numerically show that a fully entropic gas-liquid phase separation can take place in SCNP systems. Control over the discontinuous (first-order) change-from a phase of independent diluted (fully-bonded) polymers to a phase in which polymers entropically bind to each other to form a (fully-bonded) polymer network-can be achieved by a judicious design of the patterns of reactive monomers along the polymer chain. Such a sensitivity arises from a delicate balance between the distinct entropic contributions controlling the binding.
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Affiliation(s)
- Lorenzo Rovigatti
- Department of Physics, Sapienza Università di Roma, Piazzale A. Moro 2, IT-00185 Roma, Italy and CNR-ISC Uos Sapienza, Piazzale A. Moro 2, IT-00185 Roma, Italy
| | - Francesco Sciortino
- Department of Physics, Sapienza Università di Roma, Piazzale A. Moro 2, IT-00185 Roma, Italy
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39
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Bhattacharya D, Kleeblatt DC, Statt A, Reinhart WF. Predicting aggregate morphology of sequence-defined macromolecules with recurrent neural networks. SOFT MATTER 2022; 18:5037-5051. [PMID: 35748651 DOI: 10.1039/d2sm00452f] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Self-assembly of dilute sequence-defined macromolecules is a complex phenomenon in which the local arrangement of chemical moieties can lead to the formation of long-range structure. The dependence of this structure on the sequence necessarily implies that a mapping between the two exists, yet it has been difficult to model so far. Predicting the aggregation behavior of these macromolecules is challenging due to the lack of effective order parameters, a vast design space, inherent variability, and high computational costs associated with currently available simulation techniques. Here, we accurately predict the morphology of aggregates self-assembled from sequence-defined macromolecules using supervised machine learning. We find that regression models with implicit representation learning perform significantly better than those based on engineered features such as k-mer counting, and a recurrent-neural-network-based regressor performs the best out of nine model architectures we tested. Furthermore, we demonstrate the high-throughput screening of monomer sequences using the regression model to identify candidates for self-assembly into selected morphologies. Our strategy is shown to successfully identify multiple suitable sequences in every test we performed, so we hope the insights gained here can be extended to other increasingly complex design scenarios in the future, such as the design of sequences under polydispersity and at varying environmental conditions.
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Affiliation(s)
- Debjyoti Bhattacharya
- Materials Science and Engineering, Pennsylvania State University, University Park, PA 16802, USA.
| | - Devon C Kleeblatt
- Materials Science and Engineering, Pennsylvania State University, University Park, PA 16802, USA.
| | - Antonia Statt
- Materials Science and Engineering, Grainger College of Engineering, University of Illinois, Urbana-Champaign, IL 61801, USA
| | - Wesley F Reinhart
- Materials Science and Engineering, Pennsylvania State University, University Park, PA 16802, USA.
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA 16802, USA
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40
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Lemetti L, Scacchi A, Yin Y, Shen M, Linder MB, Sammalkorpi M, Aranko AS. Liquid-Liquid Phase Separation and Assembly of Silk-like Proteins is Dependent on the Polymer Length. Biomacromolecules 2022; 23:3142-3153. [PMID: 35796676 PMCID: PMC9364312 DOI: 10.1021/acs.biomac.2c00179] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
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Phase transitions
have an essential role in the assembly of nature’s
protein-based materials into hierarchically organized structures,
yet many of the underlying mechanisms and interactions remain to be
resolved. A central question for designing proteins for materials
is how the protein architecture and sequence affects the nature of
the phase transitions and resulting assembly. In this work, we produced
82 kDa (1×), 143 kDa (2×), and 204 kDa (3×) silk-mimicking
proteins by taking advantage of protein ligation by SpyCatcher/Tag
protein-peptide pair. We show that the three silk proteins all undergo
a phase transition from homogeneous solution to assembly formation.
In the assembly phase, a length- and concentration-dependent transition
between two distinct assembly morphologies, one forming aggregates
and another coacervates, exists. The coacervates showed properties
that were dependent on the protein size. Computational modeling of
the proteins by a bead-spring model supports the experimental results
and provides us a possible mechanistic origin for the assembly transitions
based on architectures and interactions.
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Affiliation(s)
- Laura Lemetti
- Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Kemistintie 1, Espoo 02150, Finland.,Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), Aalto University, Kemistintie 1, Espoo 02150, Finland
| | - Alberto Scacchi
- Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), Aalto University, Kemistintie 1, Espoo 02150, Finland.,Department of Chemistry and Materials Science, School of Chemical Engineering, Aalto University, Kemistintie 1, Espoo 02150, Finland.,Department of Applied Physics, School of Science, Aalto University, Otakaari 1, Espoo 02150, Finland
| | - Yin Yin
- Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Kemistintie 1, Espoo 02150, Finland.,Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), Aalto University, Kemistintie 1, Espoo 02150, Finland
| | - Mengjie Shen
- Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Kemistintie 1, Espoo 02150, Finland.,Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), Aalto University, Kemistintie 1, Espoo 02150, Finland
| | - Markus B Linder
- Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Kemistintie 1, Espoo 02150, Finland.,Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), Aalto University, Kemistintie 1, Espoo 02150, Finland
| | - Maria Sammalkorpi
- Department of Bioproducts and Biosystems, Department of Chemistry and Materials Science, and Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), School of Chemical Engineering, Aalto University, Espoo, 02150, Finland
| | - A Sesilja Aranko
- Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Kemistintie 1, Espoo 02150, Finland.,Academy of Finland Center of Excellence in Life-Inspired Hybrid Materials (LIBER), Aalto University, Kemistintie 1, Espoo 02150, Finland
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41
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Affinity of disordered protein complexes is modulated by entropy-energy reinforcement. Proc Natl Acad Sci U S A 2022; 119:e2120456119. [PMID: 35727975 PMCID: PMC9245678 DOI: 10.1073/pnas.2120456119] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Intrinsically disordered proteins (IDPs), which are very common and essential to many biological activities, sometimes function via interaction with another IDP and form a fuzzy complex, which can be highly stable. It is unclear what the biophysical forces are that govern their thermodynamics and specificity, which are essential for de novo fuzzy complex design. Here, we explored the fuzzy complex formed between ProTα and H1, which are oppositely charged IDPs, by swapping the charges between them, generating variants that have either greater polyampholytic or polyelectrolytic nature as well as different charge patterns. Charge swapping and shuffling dramatically change the affinity of the fuzzy complex, which is contributed to by both enthalpy and entropy, where the latter is dominated by counterion release. The association between two intrinsically disordered proteins (IDPs) may produce a fuzzy complex characterized by a high binding affinity, similar to that found in the ultrastable complexes formed between two well-structured proteins. Here, using coarse-grained simulations, we quantified the biophysical forces driving the formation of such fuzzy complexes. We found that the high-affinity complex formed between the highly and oppositely charged H1 and ProTα proteins is sensitive to electrostatic interactions. We investigated 52 variants of the complex by swapping charges between the two oppositely charged proteins to produce sequences whose negatively or positively charged residue content was more homogeneous or heterogenous (i.e., polyelectrolytic or polyampholytic, having higher or lower absolute net charges, respectively) than the wild type. We also changed the distributions of oppositely charged residues within each participating sequence to produce variants in which the charges were segregated or well mixed. Both types of changes significantly affect binding affinity in fuzzy complexes, which is governed by both enthalpy and entropy. The formation of H1–ProTa is supported by an increase in configurational entropy and by entropy due to counterion release. The latter can be twice as large as the former, illustrating the dominance of counterion entropy in modulating the binding thermodynamics. Complexes formed between proteins with greater absolute net charges are more stable, both enthalpically and entropically, indicating that enthalpy and entropy have a mutually reinforcing effect. The sensitivity of the thermodynamics of the complex to net charge and the charge pattern within each of the binding constituents may provide a means to achieve binding specificity between IDPs.
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42
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King M, Gottlieb D, Boucher D. Impact of regioregularity on the solubility parameters of poly(3‐hexylthiophene). JOURNAL OF POLYMER SCIENCE 2022. [DOI: 10.1002/pol.20220235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- McKenna King
- Department of Chemistry and Biochemistry College of Charleston Charleston South Carolina USA
| | - Danielle Gottlieb
- Department of Chemistry and Biochemistry College of Charleston Charleston South Carolina USA
| | - David Boucher
- Department of Chemistry and Biochemistry College of Charleston Charleston South Carolina USA
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43
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Ghosh K, Huihui J, Phillips M, Haider A. Rules of Physical Mathematics Govern Intrinsically Disordered Proteins. Annu Rev Biophys 2022; 51:355-376. [PMID: 35119946 PMCID: PMC9190209 DOI: 10.1146/annurev-biophys-120221-095357] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
In stark contrast to foldable proteins with a unique folded state, intrinsically disordered proteins and regions (IDPs) persist in perpetually disordered ensembles. Yet an IDP ensemble has conformational features-even when averaged-that are specific to its sequence. In fact, subtle changes in an IDP sequence can modulate its conformational features and its function. Recent advances in theoretical physics reveal a set of elegant mathematical expressions that describe the intricate relationships among IDP sequences, their ensemble conformations, and the regulation of their biological functions. These equations also describe the molecular properties of IDP sequences that predict similarities and dissimilarities in their functions and facilitate classification of sequences by function, an unmet challenge to traditional bioinformatics. These physical sequence-patterning metrics offer a promising new avenue for advancing synthetic biology at a time when multiple novel functional modes mediated by IDPs are emerging.
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Affiliation(s)
- Kingshuk Ghosh
- Department of Physics and Astronomy, University of Denver, Denver, Colorado, USA,Molecular and Cellular Biophysics Program, University of Denver, Denver, Colorado, USA
| | - Jonathan Huihui
- Department of Physics and Astronomy, University of Denver, Denver, Colorado, USA
| | - Michael Phillips
- Department of Physics and Astronomy, University of Denver, Denver, Colorado, USA
| | - Austin Haider
- Molecular and Cellular Biophysics Program, University of Denver, Denver, Colorado, USA
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44
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Bale AA, Gautham SMB, Patra TK. Sequence‐defined Pareto frontier of a copolymer structure. JOURNAL OF POLYMER SCIENCE 2022. [DOI: 10.1002/pol.20220088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Ashwin A. Bale
- Department of Chemical Engineering Birla Institute of Technology and Science Pilani‐Hyderabad Hyderabad India
| | - Sachin M. B. Gautham
- Department of Chemical Engineering, Center for Atomistic Modeling and Materials Design and Center for Carbon Capture Utilization and Storage Indian Institute of Technology Madras Chennai India
| | - Tarak K. Patra
- Department of Chemical Engineering, Center for Atomistic Modeling and Materials Design and Center for Carbon Capture Utilization and Storage Indian Institute of Technology Madras Chennai India
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45
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Lebold KM, Best RB. Tuning Formation of Protein-DNA Coacervates by Sequence and Environment. J Phys Chem B 2022; 126:2407-2419. [PMID: 35317553 DOI: 10.1021/acs.jpcb.2c00424] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The high concentration of nucleic acids and positively charged proteins in the cell nucleus provides many possibilities for complex coacervation. We consider a prototypical mixture of nucleic acids together with the polycationic C-terminus of histone H1 (CH1). Using a minimal coarse-grained model that captures the shape, flexibility, and charge distributions of the molecules, we find that coacervates are readily formed at physiological ionic strengths, in agreement with experiment, with a progressive increase in local ordering at low ionic strength. Variation of the positions of charged residues in the protein tunes phase separation: for well-mixed or only moderately blocky distributions of charge, there is a modest increase of local ordering with increasing blockiness that is also associated with an increased propensity to phase separate. This ordering is also associated with a slowdown of rotational and translational diffusion in the dense phase. However, for more extreme blockiness (and consequently higher local charge density), we see a qualitative change in the condensed phase to become a segregated structure with a dramatically increased ordering of the DNA. Naturally occurring proteins with these sequence properties, such as protamines in sperm cells, are found to be associated with very dense packing of nucleic acids.
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Affiliation(s)
- Kathryn M Lebold
- Laboratory of Chemical Physics, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Robert B Best
- Laboratory of Chemical Physics, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
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46
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Garaizar A, Espinosa JR, Joseph JA, Collepardo-Guevara R. Kinetic interplay between droplet maturation and coalescence modulates shape of aged protein condensates. Sci Rep 2022; 12:4390. [PMID: 35293386 PMCID: PMC8924231 DOI: 10.1038/s41598-022-08130-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 02/07/2022] [Indexed: 12/29/2022] Open
Abstract
Biomolecular condensates formed by the process of liquid-liquid phase separation (LLPS) play diverse roles inside cells, from spatiotemporal compartmentalisation to speeding up chemical reactions. Upon maturation, the liquid-like properties of condensates, which underpin their functions, are gradually lost, eventually giving rise to solid-like states with potential pathological implications. Enhancement of inter-protein interactions is one of the main mechanisms suggested to trigger the formation of solid-like condensates. To gain a molecular-level understanding of how the accumulation of stronger interactions among proteins inside condensates affect the kinetic and thermodynamic properties of biomolecular condensates, and their shapes over time, we develop a tailored coarse-grained model of proteins that transition from establishing weak to stronger inter-protein interactions inside condensates. Our simulations reveal that the fast accumulation of strongly binding proteins during the nucleation and growth stages of condensate formation results in aspherical solid-like condensates. In contrast, when strong inter-protein interactions appear only after the equilibrium condensate has been formed, or when they accumulate slowly over time with respect to the time needed for droplets to fuse and grow, spherical solid-like droplets emerge. By conducting atomistic potential-of-mean-force simulations of NUP-98 peptides-prone to forming inter-protein [Formula: see text]-sheets-we observe that formation of inter-peptide [Formula: see text]-sheets increases the strength of the interactions consistently with the loss of liquid-like condensate properties we observe at the coarse-grained level. Overall, our work aids in elucidating fundamental molecular, kinetic, and thermodynamic mechanisms linking the rate of change in protein interaction strength to condensate shape and maturation during ageing.
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Affiliation(s)
- Adiran Garaizar
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
| | - Jorge R Espinosa
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
| | - Jerelle A Joseph
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
- Department of Genetics, University of Cambridge, Downing Site, Cambridge, CB2 3EH, UK
| | - Rosana Collepardo-Guevara
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, CB3 0HE, UK.
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK.
- Department of Genetics, University of Cambridge, Downing Site, Cambridge, CB2 3EH, UK.
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47
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Tulsi DK, Simmons DS. Hierarchical Shape-Specified Model Polymer Nanoparticles via Copolymer Sequence Control. Macromolecules 2022. [DOI: 10.1021/acs.macromol.1c02215] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Davindra K. Tulsi
- The University of South Florida, 4202 East Fowler Avenue, ENB 118, Tampa, Florida 33620, United States
| | - David S. Simmons
- The University of South Florida, 4202 East Fowler Avenue, ENB 118, Tampa, Florida 33620, United States
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48
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Sanchez-Burgos I, Espinosa JR, Joseph JA, Collepardo-Guevara R. RNA length has a non-trivial effect in the stability of biomolecular condensates formed by RNA-binding proteins. PLoS Comput Biol 2022; 18:e1009810. [PMID: 35108264 PMCID: PMC8896709 DOI: 10.1371/journal.pcbi.1009810] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 03/04/2022] [Accepted: 01/06/2022] [Indexed: 12/29/2022] Open
Abstract
Biomolecular condensates formed via liquid-liquid phase separation (LLPS) play a crucial role in the spatiotemporal organization of the cell material. Nucleic acids can act as critical modulators in the stability of these protein condensates. To unveil the role of RNA length in regulating the stability of RNA binding protein (RBP) condensates, we present a multiscale computational strategy that exploits the advantages of a sequence-dependent coarse-grained representation of proteins and a minimal coarse-grained model wherein proteins are described as patchy colloids. We find that for a constant nucleotide/protein ratio, the protein fused in sarcoma (FUS), which can phase separate on its own-i.e., via homotypic interactions-only exhibits a mild dependency on the RNA strand length. In contrast, the 25-repeat proline-arginine peptide (PR25), which does not undergo LLPS on its own at physiological conditions but instead exhibits complex coacervation with RNA-i.e., via heterotypic interactions-shows a strong dependence on the length of the RNA strands. Our minimal patchy particle simulations suggest that the strikingly different effect of RNA length on homotypic LLPS versus RBP-RNA complex coacervation is general. Phase separation is RNA-length dependent whenever the relative contribution of heterotypic interactions sustaining LLPS is comparable or higher than those stemming from protein homotypic interactions. Taken together, our results contribute to illuminate the intricate physicochemical mechanisms that influence the stability of RBP condensates through RNA inclusion.
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Affiliation(s)
- Ignacio Sanchez-Burgos
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, United Kingdom
| | - Jorge R. Espinosa
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, United Kingdom
| | - Jerelle A. Joseph
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, United Kingdom
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, United Kingdom
- Department of Genetics, University of Cambridge, Downing Site, Cambridge, United Kingdom
| | - Rosana Collepardo-Guevara
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge, United Kingdom
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, United Kingdom
- Department of Genetics, University of Cambridge, Downing Site, Cambridge, United Kingdom
- * E-mail:
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49
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Surface tension and super-stoichiometric surface enrichment in two-component biomolecular condensates. iScience 2022; 25:103852. [PMID: 35198903 PMCID: PMC8851291 DOI: 10.1016/j.isci.2022.103852] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 12/28/2021] [Accepted: 01/26/2022] [Indexed: 11/24/2022] Open
Abstract
Cells can achieve internal organization by exploiting liquid-liquid phase separation to form biomolecular condensates. Here we focus on the surface properties of condensates composed of two multivalent associative polymers held together by one-to-one “sticker” bonds. Using coarse-grained molecular-dynamics simulations, we study the influence of component stoichiometry on condensate surface properties. We find that unequal stoichiometry results in enrichment of the majority species at the interface and a sharp reduction of surface tension. To relate these two effects, we show that the reduction in surface tension scales linearly with the excess concentration of free binding sites at the interface. Our results imply that each excess free site contributes an approximately fixed additional energy and entropy to the interface, with the latter dominating such that enrichment of free majority sites lowers the surface tension. Our work provides insight into novel physical mechanisms by which cells can regulate condensate surface properties. Stoichiometry controls the surface tension of two-component biomolecular condensates Unequal stoichiometry leads to enrichment of the majority species at the interface Enrichment of the free majority binding sites increases the interfacial entropy Surface tension is drastically reduced at unequal stoichiometry
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50
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Nilsson D, Bozorg B, Mohanty S, Söderberg B, Irbäck A. Limitations of field-theory simulation for exploring phase separation: The role of repulsion in a lattice protein model. J Chem Phys 2022; 156:015101. [PMID: 34998327 DOI: 10.1063/5.0070412] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Field-theory simulation by the complex Langevin method offers an alternative to conventional sampling techniques for exploring the forces driving biomolecular liquid-liquid phase separation. Such simulations have recently been used to study several polyampholyte systems. Here, we formulate a field theory corresponding to the hydrophobic/polar (HP) lattice protein model, with finite same-site repulsion and nearest-neighbor attraction between HH bead pairs. By direct comparison with particle-based Monte Carlo simulations, we show that complex Langevin sampling of the field theory reproduces the thermodynamic properties of the HP model only if the same-site repulsion is not too strong. Unfortunately, the repulsion has to be taken weaker than what is needed to prevent condensed droplets from assuming an artificially compact shape. Analysis of a minimal and analytically solvable toy model hints that the sampling problems caused by repulsive interaction may stem from loss of ergodicity.
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Affiliation(s)
- Daniel Nilsson
- Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Sölvegatan 14A, SE-22362 Lund, Sweden
| | - Behruz Bozorg
- Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Sölvegatan 14A, SE-22362 Lund, Sweden
| | - Sandipan Mohanty
- Institute for Advanced Simulation, Jülich Supercomputing Centre, Forschungszentrum Jülich, D-52425 Jülich, Germany
| | - Bo Söderberg
- Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Sölvegatan 14A, SE-22362 Lund, Sweden
| | - Anders Irbäck
- Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Sölvegatan 14A, SE-22362 Lund, Sweden
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