Automated Parametrization of the Coarse-Grained Martini Force Field for Small Organic Molecules

2015 ◽  
Vol 11 (6) ◽  
pp. 2783-2791 ◽  
Author(s):  
Tristan Bereau ◽  
Kurt Kremer
Keyword(s):  
Force Field ◽  
Organic Molecules ◽  
Coarse Grained ◽  
Small Organic Molecules ◽  
Martini Force Field

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Organic Molecules ◽  
Force Fields ◽  
Liquid Density ◽  
Small Organic Molecules ◽  
Automated Generation ◽  
Energy Of Hydration ◽  
Novel Method ◽  
Force Field Parameters

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Organic Molecules ◽  
Force Fields ◽  
Liquid Density ◽  
Small Organic Molecules ◽  
Automated Generation ◽  
Energy Of Hydration ◽  
Novel Method ◽  
Force Field Parameters

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

A refined polarizable water model for the coarse-grained MARTINI force field with long-range electrostatic interactions

2017 ◽  
Vol 146 (5) ◽  
pp. 054501 ◽  
Author(s):  
Julian Michalowsky ◽  
Lars V. Schäfer ◽  
Christian Holm ◽  
Jens Smiatek
Keyword(s):  
Force Field ◽  
Long Range ◽  
Electrostatic Interactions ◽  
Coarse Grained ◽  
Water Model ◽  
Martini Force Field

scholarly journals Martini Coarse-Grained Models of Imidazolium-Based Ionic Liquids: From Nanostructural Organization to Liquid-Liquid Extraction

2020 ◽  
Author(s):  
Luis Itza Vazquez-Salazar ◽  
Michele Selle ◽  
Alex H. de Vries ◽  
Siewert-Jan Marrink ◽  
Paulo C. T. Souza
Keyword(s):  
Ionic Liquids ◽  
Force Field ◽  
Rational Design ◽  
Value Added ◽  
Liquid Extraction ◽  
Coarse Grained ◽  
Great Success ◽  
Liquid Liquid Extraction ◽  
Martini Force Field ◽  
Wide Range

<div> <div> <div> <p>Ionic liquids (IL) are remarkable green solvents, which find applications in many areas of nano- and biotechnology including extraction and purification of value-added compounds or fine chemicals. These liquid salts possess versatile solvation properties that can be tuned by modifications in the cation or anion structure. So far, in contrast to the great success of theoretical and computational methodologies applied to other fields, only a few IL models have been able to bring insights towards the rational design of such solvents. In this work, we develop coarse-grained (CG) models for imidazolium-based ILs using a new version of the Martini force field. The model is able to reproduce the main structural properties of pure ILs, including spatial heterogeneity and global densities over a wide range of temperatures. More importantly, given the high intermolecular compatibility of the Martini force field, this new IL CG model opens the possibility of large-scale simulations of liquid-liquid extraction experiments. As examples, we show two applications, namely the extraction of aromatic molecules from a petroleum oil model and the extraction of omega-3 polyunsaturated fatty acids from a fish oil model. In semi-quantitative agreement with the experiments, we show how the extraction capacity and selectivity of the IL could be affected by the cation chain length or addition of co-solvents. </p> </div> </div> </div>

scholarly journals Coarse-grained Simulation of Anionic Surfactant Sodium Dodecyl Sulfate

2021 ◽  
Author(s):  
Xiang-feng Jia ◽  
Jing-fei Chen ◽  
Hui-xue Ren ◽  
Qi Wang ◽  
Wen Xu ◽  
...  
Keyword(s):  
Force Field ◽  
Sodium Dodecyl ◽  
Coarse Grained ◽  
Inversion Method ◽  
Ionic Surfactant ◽  
Coarse Grained Model ◽  
Piecewise Function ◽  
Martini Force Field ◽  
Improved Model ◽  
Vdw Interaction

Abstract Through analyzing the deficiency of the current coarse-grained (CG) model, a new CG model for the ionic surfactant was proposed based on the Martini force field and iterative Boltzmann inversion method. In this model, the electrostatic interaction can be tackled by using a self-defined piecewise function to avoid the disadvantage of using coarse-grained solvents, and the VDW interaction parameters were derived by iterative methods. Using the improved model, the radial distribution function of NaCl and SDS solution in all-atom OPLS can be completely reproduced. The successful setup of the new coarse-grained model provides a good example of the construction of a high-precision coarse-grained force field.

scholarly journals Optimized Parameters for the Drude Polarizable Force Field for Small Organic Molecules

2019 ◽  
Vol 116 (3) ◽  
pp. 142a
Author(s):  
Chetan Rupakheti ◽  
Alexander D. MacKerell ◽  
Benoit Roux
Keyword(s):  
Force Field ◽  
Organic Molecules ◽  
Small Organic Molecules ◽  
Polarizable Force Field

CHARMM-GUI Martini Maker for Coarse-Grained Simulations with the Martini Force Field

2015 ◽  
Vol 11 (9) ◽  
pp. 4486-4494 ◽  
Author(s):  
Yifei Qi ◽  
Helgi I. Ingólfsson ◽  
Xi Cheng ◽  
Jumin Lee ◽  
Siewert J. Marrink ◽  
...  
Keyword(s):  
Force Field ◽  
Coarse Grained ◽  
Martini Force Field ◽  
Coarse Grained Simulations

scholarly journals Coarse Grained Molecular Dynamic Simulations for the Study of TNF Receptor Family Members' Transmembrane Organization

2021 ◽  
Vol 8 ◽  
Author(s):  
Mauricio P. Sica ◽  
Cristian R. Smulski
Keyword(s):  
Force Field ◽  
Higher Order ◽  
Coarse Grained ◽  
Structural Basis ◽  
Tnf Receptor ◽  
Dynamic Simulations ◽  
Rich Domain ◽  
Martini Force Field ◽  
The Impact ◽  
Homotypic Interactions

The Tumor Necrosis Factor (TNF) and the TNF receptor (TNFR) superfamilies are composed of 19 ligands and 30 receptors, respectively. The oligomeric properties of ligands, both membrane bound and soluble, has been studied most. However, less is known about the oligomeric properties of TNFRs. Earlier reports identified the extracellular, membrane-distal, cysteine-rich domain as a pre-ligand assembly domain which stabilizes receptor dimers and/or trimers in the absence of ligand. Nevertheless, recent reports based on structural nuclear magnetic resonance (NMR) highlight the intrinsic role of the transmembrane domains to form dimers (p75NTR), trimers (Fas), or dimers of trimers (DR5). Thus, understanding the structural basis of transmembrane oligomerization may shed light on the mechanism for signal transduction and the impact of disease-associated mutations in this region. To this end, here we used an in silico coarse grained molecular dynamics approach with Martini force field to study TNFR transmembrane homotypic interactions. We have first validated this approach studying the three TNFR described by NMR (p75NTR, Fas, and DR5). We have simulated membrane patches composed of 36 helices of the same receptor equidistantly distributed in order to get unbiassed information on spontaneous proteins assemblies. Good agreement was found in the specific residues involved in homotypic interactions and we were able to observe dimers, trimers, and higher-order oligomers corresponding to those reported in NMR experiments. We have, applied this approach to study the assembly of disease-related mutations being able to assess their impact on oligomerization stability. In conclusion, our results showed the usefulness of coarse grained simulations with Martini force field to study in an unbiased manner higher order transmembrane oligomerization.

scholarly journals Nanocomposite of Fullerenes and Natural Rubbers: MARTINI Force Field Molecular Dynamics Simulations

Polymers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 4044
Author(s):  
Jiramate Kitjanon ◽  
Wasinee Khuntawee ◽  
Saree Phongphanphanee ◽  
Thana Sutthibutpong ◽  
Nattaporn Chattham ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Quantitative Agreement ◽  
Filler Loading ◽  
Coarse Grained ◽  
Experimental Result ◽  
High Wear Resistance ◽  
Mechanical And Thermal Properties ◽  
Interfacial Interactions ◽  
Martini Force Field

The mechanical properties of natural rubber (NR) composites depend on many factors, including the filler loading, filler size, filler dispersion, and filler-rubber interfacial interactions. Thus, NR composites with nano-sized fillers have attracted a great deal of attention for improving properties such as stiffness, chemical resistance, and high wear resistance. Here, a coarse-grained (CG) model based on the MARTINI force field version 2.1 has been developed and deployed for simulations of cis-1,4-polyisoprene (cis-PI). The model shows qualitative and quantitative agreement with the experiments and atomistic simulations. Interestingly, only a 0.5% difference with respect to the experimental result of the glass transition temperature (Tg) of the cis-PI in the melts was observed. In addition, the mechanical and thermodynamical properties of the cis-PI-fullerene(C60) composites were investigated. Coarse-grained molecular dynamics (MD) simulations of cis-PI-C60 composites with varying fullerene concentrations (0–32 parts per hundred of rubber; phr) were performed over 200 microseconds. The structural, mechanical, and thermal properties of the composites were determined. The density, bulk modulus, thermal expansion, heat capacity, and Tg of the NR composites were found to increase with increasing C60 concentration. The presence of C60 resulted in a slight increasing of the end-to-end distance and radius of the gyration of the cis-PI chains. The contribution of C60 and cis-PI interfacial interactions led to an enhancement of the bulk moduli of the composites. This model should be helpful in the investigations and design of effective fillers of NR-C60 composites for improving their properties.

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