scholarly journals Evaluating the Efficiency of the Martini Force Field to Study Protein Dimerization in Aqueous and Membrane Environments

2021 ◽  
Author(s):  
Christos Lamprakis ◽  
Ioannis Andreadelis ◽  
John Manchester ◽  
Camilo Velez-Vega ◽  
José S. Duca ◽  
...  
Keyword(s):  
Free Energy ◽  
Membrane Proteins ◽  
Force Field ◽  
Biological Activities ◽  
Coarse Grained ◽  
Protein Oligomerization ◽  
Free Energy Surface ◽  
Collective Variables ◽  
Protein Dimerization ◽  
Dimerization Process

<p>Protein-protein complex assembly is one of the major drivers of biological response. Understanding the mechanisms of protein oligomerization/dimerization would allow one to elucidate how these complexes participate in biological activities and could ultimately lead to new approaches in designing novel therapeutic agents. However, determining the exact association pathways and structures of such complexes remains a challenge. Here, we use parallel tempering metadynamics simulations in the well-tempered ensemble to evaluate the performance of Martini 2.2P and Martini open-beta 3 (Martini 3) force fields in reproducing the structure and energetics of the dimerization process of membrane proteins and proteins in an aqueous solution in reasonable accuracy and throughput. We find that Martini 2.2P systematically overestimates the free energy of association by estimating large barriers in distinct areas, which likely leads to overaggregation when multiple monomers are present. In comparison, the less viscous Martini 3 results in a systematic underestimation of the free energy of association for proteins in solution, while it performs well in describing the association of membrane proteins. In all cases the near-native dimer complexes are identified as minima in the free energy surface albeit not always as the lowest minima. In the case of Martini 3 we find that the spurious supramolecular protein aggregation present in Martini 2.2P multimer simulations is alleviated and thus this force field may be more suitable for the study of protein oligomerization. We propose that the use of enhanced sampling simulations with a refined coarse-grained force field and appropriately defined collective variables is a robust approach for studying the protein dimerization process, although one should be cautious of the ranking of energy minima.</p>

scholarly journals Evaluating the Efficiency of the Martini Force Field to Study Protein Dimerization in Aqueous and Membrane Environments

2021 ◽  
Author(s):  
Christos Lamprakis ◽  
Ioannis Andreadelis ◽  
John Manchester ◽  
Camilo Velez-Vega ◽  
José S. Duca ◽  
...  
Keyword(s):  
Free Energy ◽  
Membrane Proteins ◽  
Force Field ◽  
Biological Activities ◽  
Coarse Grained ◽  
Protein Oligomerization ◽  
Free Energy Surface ◽  
Collective Variables ◽  
Protein Dimerization ◽  
Dimerization Process

<p>Protein-protein complex assembly is one of the major drivers of biological response. Understanding the mechanisms of protein oligomerization/dimerization would allow one to elucidate how these complexes participate in biological activities and could ultimately lead to new approaches in designing novel therapeutic agents. However, determining the exact association pathways and structures of such complexes remains a challenge. Here, we use parallel tempering metadynamics simulations in the well-tempered ensemble to evaluate the performance of Martini 2.2P and Martini open-beta 3 (Martini 3) force fields in reproducing the structure and energetics of the dimerization process of membrane proteins and proteins in an aqueous solution in reasonable accuracy and throughput. We find that Martini 2.2P systematically overestimates the free energy of association by estimating large barriers in distinct areas, which likely leads to overaggregation when multiple monomers are present. In comparison, the less viscous Martini 3 results in a systematic underestimation of the free energy of association for proteins in solution, while it performs well in describing the association of membrane proteins. In all cases the near-native dimer complexes are identified as minima in the free energy surface albeit not always as the lowest minima. In the case of Martini 3 we find that the spurious supramolecular protein aggregation present in Martini 2.2P multimer simulations is alleviated and thus this force field may be more suitable for the study of protein oligomerization. We propose that the use of enhanced sampling simulations with a refined coarse-grained force field and appropriately defined collective variables is a robust approach for studying the protein dimerization process, although one should be cautious of the ranking of energy minima.</p>

Extension of the UNRES Coarse-Grained Force Field to Membrane Proteins in the Lipid Bilayer

2019 ◽  
Vol 123 (37) ◽  
pp. 7829-7839
Author(s):  
Karolina Ziȩba ◽  
Magdalena Ślusarz ◽  
Rafał Ślusarz ◽  
Adam Liwo ◽  
Cezary Czaplewski ◽  
...  
Keyword(s):  
Membrane Proteins ◽  
Force Field ◽  
Lipid Bilayer ◽  
Coarse Grained

scholarly journals Refining amino acid hydrophobicity for dynamics simulation of membrane proteins

2017 ◽  
Author(s):  
Ronald D Hills, Jr
Keyword(s):  
Molecular Dynamics ◽  
Membrane Proteins ◽  
Force Field ◽  
Molecular Dynamics Simulations ◽  
Dynamics Simulation ◽  
Coarse Grained ◽  
Interfacial Behavior ◽  
Potentials Of Mean Force ◽  
Arginine Residues ◽  
Dynamics Simulations

Coarse-grained simulations enable the study of membrane proteins in the context of their native environment but require reliable parameters. The CgProt force field is assessed by comparing the potentials of mean force for sidechain insertion in a DOPC bilayer to results reported for atomistic molecular dynamics simulations. The reassignment of polar sidechain sites was found to improve the attractive interfacial behavior of tyrosine, phenylalanine and asparagine as well as charged lysine and arginine residues. The solvation energy at membrane depths of 0, 1.3 and 1.7 nm correlate with experimental partition coefficients in aqueous mixtures of cyclohexane, octanol and POPC, respectively, for sidechain analogs and Wimley-White peptides. These data points can be used to further discriminate between alternate force field parameters. Available partitioning data was also used to reparameterize the representation of the polar peptide backbone for non-alanine residues. The newly developed force field, CgProt 2.4, correctly predicts the global energy minimum in the potentials of mean force for insertion of the uncharged membrane-associated peptides LS3 and WALP23. CgProt will find application in molecular dynamics simulations of a variety of membrane protein systems.

scholarly journals Discover, Sample and Refine: Exploring Chemistry with Enhanced Sampling Techniques

2021 ◽  
Author(s):  
Umberto Raucci ◽  
Valerio Rizzi ◽  
Michele Parrinello
Keyword(s):  
Free Energy ◽  
Ad Hoc ◽  
Spectral Graph Theory ◽  
Ab Initio Molecular Dynamics ◽  
Enhanced Sampling ◽  
Free Energy Surface ◽  
Collective Variables ◽  
User Input ◽  
Specific Reactions

Over the last few decades enhanced sampling methods have made great strides. Here, we exploit this progress and propose a modular workflow for blind reaction discovery and characterization of reaction paths. Central to our strategy is the use of the recently developed explore variant of the on-the-fly probability enhanced sampling method. Like metadynamics, this method is based on the identification of appropriate collective variables. Our first step is the discovery of new chemical reactions and it is performed biasing a one dimensional collective variable derived from spectral graph theory. Once new reaction pathways are detected, we construct ad-hoc tailored neural-network based collective variables to improve sampling of specific reactions and finally we refine the results using free energy perturbation theory. Our workflow has been successfully applied to both intramolecular and intermolecular reactions. Without any chemical hypothesis, we discovered several possible products, computed the free energy surface at semiempirical level, and finally refined it with a more accurate Hamiltonian. Our workflow requires minimal user input, and thanks to its modularity and flexibility, can extend the scope of ab initio molecular dynamics for the exploration and characterization of reaction space.

scholarly journals Molecular dynamics simulations of liquid silica crystallization

2018 ◽  
Vol 115 (21) ◽  
pp. 5348-5352 ◽  
Author(s):  
Haiyang Niu ◽  
Pablo M. Piaggi ◽  
Michele Invernizzi ◽  
Michele Parrinello
Keyword(s):  
Free Energy ◽  
Nucleation Theory ◽  
Classical Nucleation Theory ◽  
Free Energy Surface ◽  
X Ray Diffraction ◽  
Collective Variables ◽  
Atomic Simulations ◽  
The Difference ◽  
Dynamics Simulations ◽  
Good Agreement

Silica is one of the most abundant minerals on Earth and is widely used in many fields. Investigating the crystallization of liquid silica by atomic simulations is of great importance to understand the crystallization mechanism; however, the high crystallization barrier and the tendency of silica to form glasses make such simulations very challenging. Here we have studied liquid silica crystallization to β-cristobalite with metadynamics, using X-ray diffraction (XRD) peak intensities as collective variables. The frequent transitions between solid and liquid of the biased runs demonstrate the highly successful use of the XRD peak intensities as collective variables, which leads to the convergence of the free-energy surface. By calculating the difference in free energy, we have estimated the melting temperature of β-cristobalite, which is in good agreement with the literature. The nucleation mechanism during the crystallization of liquid silica can be described by classical nucleation theory.

scholarly journals The Automated Optimisation of a Coarse-Grained Force Field Using Free Energy Data

2021 ◽  
Author(s):  
Javier Caceres-Delpiano ◽  
Lee-Ping Wang ◽  
Jonathan Wynne Essex
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Coarse Grained ◽  
Energy Data ◽  
Molecular Systems ◽  
Atomistic Models ◽  
Large Systems ◽  
Long Timescales

Atomistic models provide a detailed representation of molecular systems, but are sometimes inadequate for simulations of large systems over long timescales. Coarse-grained models enable accelerated simulations by reducing the number...

scholarly journals Transferring the PRIMO Coarse-Grained Force Field to the Membrane Environment: Simulations of Membrane Proteins and Helix–Helix Association

2014 ◽  
Vol 10 (8) ◽  
pp. 3459-3472 ◽  
Author(s):  
Parimal Kar ◽  
Srinivasa Murthy Gopal ◽  
Yi-Ming Cheng ◽  
Afra Panahi ◽  
Michael Feig
Keyword(s):  
Membrane Proteins ◽  
Force Field ◽  
Coarse Grained

scholarly journals Thermodynamics and free energy landscape of BAR-domain dimerization from molecular simulations

2020 ◽  
Author(s):  
Adip Jhaveri ◽  
Dhruw Maisuria ◽  
Matthew Varga ◽  
Dariush Mohammadyani ◽  
Margaret E Johnson
Keyword(s):  
Free Energy ◽  
Energy Surface ◽  
Md Simulations ◽  
Coarse Grained ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Free Energy Surface ◽  
Bar Domain ◽  
Bar Domains ◽  
Protein Models

AbstractNearly all proteins interact specifically with other proteins, often forming reversible bound structures whose stability is critical to function. Proteins with BAR domains function to bind to, bend, and remodel biological membranes, where the dimerization of BAR domains is a key step in this function. Here we characterize the binding thermodynamics of homodimerization between the LSP1 BAR domain proteins in solution, using Molecular Dynamics (MD) simulations. By combining the MARTINI coarse-grained protein models with enhanced sampling through metadynamics, we construct a two-dimensional free energy surface quantifying the bound versus unbound ensembles as a function of two distance variables. Our simulations portray a heterogeneous and extraordinarily stable bound ensemble for these modeled LSP1 proteins. The proper crystal structure dimer has a large hydrophobic interface that is part of a stable minima on the free energy surface, which is enthalpically the minima of all bound structures. However, we also find several other stable nonspecific dimers with comparable free energies to the specific dimer. Through structure-based clustering of these bound structures, we find that some of these ‘nonspecific’ contacts involve extended tail regions that help stabilize the higher-order oligomers formed by BAR-domains, contacts that are separated from the homodimer interface. We find that the known membrane-binding residues of the LSP1 proteins rarely participate in any of the bound interfaces, but that both patches of residues are aligned to interact with the membrane in the specific dimer. Hence, we would expect a strong selection of the specific dimer in binding to the membrane. The effect of a 100mM NaCl buffer reduces the relative stability of nonspecific dimers compared to the specific dimer, indicating that it would help prevent aggregation of the proteins. With these results, we provide the first free energy characterization of interaction pathways in this important class of membrane sculpting domains, revealing a variety of interfacial contacts outside of the specific dimer that may help stabilize its oligomeric assemblies.

scholarly journals The Automated Optimisation of a Coarse-Grained Force Field Using Free Energy Data

2020 ◽  
Author(s):  
Javier Caceres-Delpiano ◽  
Lee-Ping Wang ◽  
Jonathan W. Essex
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Degrees Of Freedom ◽  
Coarse Grained ◽  
Free Energies ◽  
Energy Data ◽  
Molecular Systems ◽  
Atomistic Models ◽  
The Cost ◽  
Long Timescales

AbstractAtomistic models provide a detailed representation of molecular systems, but are sometimes inadequate for simulations of large systems over long timescales. Coarse-grained models enable accelerated simulations by reducing the number of degrees of freedom, at the cost of reduced accuracy. New optimisation processes to parameterise these models could improve their quality and range of applicability. We present an automated approach for the optimisation of coarse-grained force fields, by reproducing free energy data derived from atomistic molecular simulations. To illustrate the approach, we implemented hydration free energy gradients as a new target for force field optimisation in ForceBalance and applied it successfully to optimise the un-charged side-chains and the protein backbone in the SIRAH protein coarse-grain force field. The optimised parameters closely reproduced hydration free energies of atomistic models and gave improved agreement with experiment.

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