scholarly journals Constant pH simulations with the coarse-grained MARTINI model — Application to oleic acid aggregates

2013 ◽  
Vol 91 (9) ◽  
pp. 839-846 ◽  
Author(s):  
W.F. Drew Bennett ◽  
Alexander W. Chen ◽  
Serena Donnini ◽  
Gerrit Groenhof ◽  
D. Peter Tieleman
Keyword(s):  
Fatty Acids ◽  
Oleic Acid ◽  
Phase Behavior ◽  
Large Scale ◽  
Md Simulations ◽  
Industrial Applications ◽  
Coarse Grained ◽  
Head Group ◽  
Constant Ph ◽  
Surfactant Phase

Long chain fatty acids are biologically important molecules with complex and pH sensitive aggregation behavior. The carboxylic head group of oleic acid is ionizable, with the pKa shifting to larger values, even above a value of 7, in certain aggregate states. While experiments have determined the macroscopic phase behavior, we have yet to understand the molecular level details for this complex behavior. This level of detail is likely required to fully appreciate the role of fatty acids in biology and for nanoscale biotechnological and industrial applications. Here, we introduce the use of constant pH molecular dynamics (MD) simulations with the coarse-grained MARTINI model and apply the method to oleic acid aggregates and a model lipid bilayer. By running simulations at different constant pH values, we determined titration curves and the resulting pKa for oleic acid in different environments. The coarse-grained model predicts positive pKa shifts, with a shift from 4.8 in water to 6.5 in a small micelle, and 6.6 in a dioleoylphosphatidylcholine (DOPC) bilayer, similar to experimental estimates. The size of the micelles increased as the pH increased, and correlated with the fraction of deprotonated oleic acid. We show this combination of constant pH MD and the coarse-grained MARTINI model can be used to model pH-dependent surfactant phase behavior. This suggests a large number of potential new applications of large-scale MARTINI simulations in other biological systems with ionizable molecules.

scholarly journals Antimicrobial action of the cationic peptide, chrysophsin-3: a coarse-grained molecular dynamics study

Soft Matter ◽  
2018 ◽  
Vol 14 (15) ◽  
pp. 2796-2807 ◽  
Author(s):  
Andrea Catte ◽  
Mark R. Wilson ◽  
Martin Walker ◽  
Vasily S. Oganesyan
Keyword(s):  
Molecular Dynamics ◽  
Large Scale ◽  
Md Simulations ◽  
Antimicrobial Action ◽  
Coarse Grained ◽  
Cationic Peptide ◽  
Coarse Grained Molecular Dynamics

Antimicrobial action of a cationic peptide is modelled by large scale MD simulations.

Constant-pH MD Simulations of an Oleic Acid Bilayer

2015 ◽  
Vol 11 (5) ◽  
pp. 2367-2376 ◽  
Author(s):  
Diogo Vila-Viçosa ◽  
Vitor H. Teixeira ◽  
António M. Baptista ◽  
Miguel Machuqueiro
Keyword(s):  
Oleic Acid ◽  
Md Simulations ◽  
Constant Ph

scholarly journals Explicit and implicit modeling of nanobubbles in hydrophobic confinement

2010 ◽  
Vol 82 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Joachim Dzubiella
Keyword(s):  
Large Scale ◽  
Md Simulations ◽  
Energy Functional ◽  
Coarse Grained ◽  
Implicit Solvent ◽  
Implicit Solvent Model ◽  
Solvent Model ◽  
Nanofluidic Devices ◽  
Capillary Evaporation ◽  
Hydrophobic Solutes

Water at normal conditions is a fluid thermodynamically close to the liquid-vapor phase coexistence and features a large surface tension. This combination can lead to interesting capillary phenomena on microscopic scales. Explicit water molecular dynamics (MD) computer simulations of hydrophobic solutes, for instance, give evidence of capillary evaporation on nanometer scales, i.e., the formation of nanometer-sized vapor bubbles (nanobubbles) between confining hydrophobic surfaces. This phenomenon has been exemplified for solutes with varying complexity, e.g., paraffin plates, coarse-grained homopolymers, biological and solid-state channels, and atomistically resolved proteins. It has been argued that nanobubbles strongly impact interactions in nanofluidic devices, translocation processes, and even in protein stability, function, and folding. As large-scale MD simulations are computationally expensive, the efficient multiscale modeling of nanobubbles and the prediction of their stability poses a formidable task to the'nanophysical' community. Recently, we have presented a conceptually novel and versatile implicit solvent model, namely, the variational implicit solvent model (VISM), which is based on a geometric energy functional. As reviewed here, first solvation studies of simple hydrophobic solutes using VISM coupled with the numerical level-set scheme show promising results, and, in particular, capture nanobubble formation and its subtle competition to local energetic potentials in hydrophobic confinement.

scholarly journals Increasing Monounsaturated Fatty Acid Contents in Hexaploid Camelina sativa Seed Oil by FAD2 Gene Knockout Using CRISPR-Cas9

2021 ◽  
Vol 12 ◽  
Author(s):  
Kyeong-Ryeol Lee ◽  
Inhwa Jeon ◽  
Hami Yu ◽  
Sang-Gyu Kim ◽  
Hyun-Sung Kim ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Oleic Acid ◽  
Fatty Acid ◽  
Seed Oil ◽  
Edible Oils ◽  
Gene Knockout ◽  
Industrial Applications ◽  
Selection Marker ◽  
Egg Cell ◽  
Oilseed Crop

Seed oils are used as edible oils and increasingly also for industrial applications. Although high-oleic seed oil is preferred for industrial use, most seed oil is high in polyunsaturated fatty acids (PUFAs) and low in monounsaturated fatty acids (MUFAs) such as oleic acid. Oil from Camelina, an emerging oilseed crop with a high seed oil content and resistance to environmental stress, contains 60% PUFAs and 30% MUFAs. Hexaploid Camelina carries three homoeologs of FAD2, encoding fatty acid desaturase 2 (FAD2), which is responsible for the synthesis of linoleic acid from oleic acid. In this study, to increase the MUFA contents of Camelina seed oil, we generated CsFAD2 knockout plants via CRISPR-Cas9-mediated gene editing using the pRedU6fad2EcCas9 vector containing DsRed as a selection marker, the U6 promoter to drive a single guide RNA (sgRNA) covering the common region of the three CsFAD2 homoeologs, and an egg-cell-specific promoter to drive Cas9 expression. We analyzed CsFAD2 homoeolog-specific sequences by PCR using genomic DNA from transformed Camelina leaves. Knockout of all three pairs of FAD2 homoeologs led to a stunted bushy phenotype, but greatly enhanced MUFA levels (by 80%) in seeds. However, transformants with two pairs of CsFAD2 homoeologs knocked out but the other pair wild-type heterozygous showed normal growth and a seed MUFAs production increased up to 60%. These results provide a basis for the metabolic engineering of genes that affect growth in polyploid crops through genome editing.

scholarly journals Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation

2020 ◽  
Author(s):  
Erik W. Martin ◽  
F. Emil Thomasen ◽  
Nicole M. Milkovic ◽  
Matthew J. Cuneo ◽  
Christy R. Grace ◽  
...  
Keyword(s):  
Phase Separation ◽  
Phase Behavior ◽  
Rna Binding ◽  
Mechanistic Explanation ◽  
Md Simulations ◽  
Low Complexity ◽  
Coarse Grained ◽  
Intrinsically Disordered ◽  
X Ray Scattering

AbstractLiquid-liquid phase separation underlies the membrane-less compartmentalization of cells. Intrinsically disordered low-complexity domains (LCDs) often mediate phase separation, but how their phase behavior is modulated by folded domains is incompletely understood. Here, we interrogate the interplay between folded and disordered domains of the RNA-binding protein hnRNPA1. The LCD of hnRNPA1 is sufficient for mediating phase separation in vitro. However, we show that the folded RRM domains and a folded solubility-tag modify the phase behavior, even in the absence of RNA. Notably, the presence of the folded domains reverses the salt dependence of the driving force for phase separation relative to the LCD alone. Small-angle X-ray scattering experiments and coarse-grained MD simulations show that the LCD interacts transiently with the RRMs and/or the solubility-tag in a salt-sensitive manner, providing a mechanistic explanation for the observed salt-dependent phase separation. These data point to two effects from the folded domains: (1) electrostatically mediated interactions that compact hnRNPA1 and contribute to phase separation, and (2) increased solubility at higher ionic strengths mediated by the folded domains. The interplay between disordered and folded domains can modify the dependence of phase behavior on solution conditions and can obscure signatures of physicochemical interactions underlying phase separation.Graphical abstracthnRNPA1 phase separation is highly salt sensitive.Phase separation of the low-complexity domain (LCD) of hnRNPA1 increases with NaCl. In contrast, phase separation of full-length hnRNPA1 is saltsensitive. At low NaCl concentrations, electrostatic RRM-LCD interactions occur and can contribute positively to phase separation, but they are screened at high NaCl concentrations. The folded domains solubilize hnRNPA1 under these conditions and prevent phase separation.

scholarly journals Mesoscale computational protocols for the design of highly cooperative bivalent macromolecules

2019 ◽  
Author(s):  
S. Saurabh ◽  
F. Piazza
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Computational Design ◽  
Md Simulations ◽  
Coarse Grained ◽  
Immune Synapse ◽  
Multi Scale ◽  
Therapeutic Molecules ◽  
Potentials Of Mean Force ◽  
Design Protocol

ABSTRACTThe last decade has witnessed a swiftly increasing interest in the design and production of novel multivalent molecules as powerful alternatives for conventional antibodies in the fight against cancer and infectious diseases. However, while it is widely accepted that large-scale flexibility (10 − 100 nm) and free/constrained dynamics (100 ns −µs) control the activity of such novel molecules, computational strategies at the mesoscale still lag behind experiments in optimizing the design of crucial features, such as the binding cooperativity (a.k.a. avidity).In this study, we introduced different coarse-grained models of a polymer-linked, two-nanobody composite molecule, with the aim of laying down the physical bases of a thorough computational drug design protocol at the mesoscale. We show that the calculation of suitable potentials of mean force allows one to apprehend the nature, range and strength of the thermodynamic forces that govern the motion of free and wall-tethered molecules. Furthermore, we develop a simple computational strategy to quantify the encounter/dissociation dynamics between the free end of a wall-tethered molecule and the surface, at the roots of binding cooperativity. This procedure allows one to pinpoint the role of internal flexibility and weak non-specific interactions on the kinetic constants of the NB-wall encounter and dissociation. Finally, we quantify the role and weight of rare events, which are expected to play a major role in real-life situations, such as in the immune synapse, where the binding kinetics is likely dominated by fluctuations.SIGNIFICANCEMultivalent and multispecific molecules composed of polymer-linked nanobodies have gained interest as engineered alternatives to conventional antibodies. These therapeutic molecules have a larger reach due to their smaller size and promise substantial and tunable gains in avidity. This paper studies a model diabody to lay the bases of a multi-scale computational design of the structural and dynamical determinants of binding cooperativity, rooted in a blend of atomistic and coarse-grained MD simulations and concepts from statistical mechanics.

Expansion and Additional Validation of PKA17: A Fast Real-Time and Web-Based pKa Predictor

2020 ◽  
pp. 1-12
Author(s):  
John P. Cvitkovic ◽  
Connor D. Pauplis ◽  
Phoebe C. Carney ◽  
George A. Kaminski
Keyword(s):  
Metal Ions ◽  
Large Scale ◽  
Transition Metal Ions ◽  
Coarse Grained ◽  
Acidity Constants ◽  
Protein Residues ◽  
Constant Ph ◽  
Computational Speed ◽  
Order Of Magnitude ◽  
Dynamics Simulations

We have further improved and validated PKA17, our fast software for predicting p[Formula: see text] values of protein residues. The methodology employs coarse-grained lattice-based model of proteins. It was previously demonstrated to perform ca. an order of magnitude faster than such successful and widely used frameworks as PROPKA without losing accuracy of the calculations. In this paper, we report the following improvements: (i) We have expanded our training and testing sets of protein residues by 128%, from 442 to 1009 cases; (ii) we have added and parameterized PKA17’s capability to predict acidity constants of cysteine residues that are important in many biomedical applications, including but not limited to binding of such transition metal ions as copper(I) and platinum(II); (iii) we have carried out the comparison of accuracy of predicted Asp and Glu p[Formula: see text] values not only between PKA17 and PROPKA, but also with DelPhiPKa and H[Formula: see text]. The computational speed of PKA17 remains the highest of all the methods used in our studies, and the accuracy of PKA17 is somewhat inferior only to those of such more sophisticated methods as Multi-Conformation Continuum Electrostatic (MCCE) ones. For instance, the average unsigned deviations of predicted p[Formula: see text] values from the experiment for 416 Glu residues were found to be 0.706, 0.766, 0.867, and 0.520[Formula: see text]pH units when obtained with PROPKA, DelPhiPKa, H[Formula: see text], and PKA17, respectively (0.487[Formula: see text]pH units with PKA17 after refitting). The average unsigned errors for cysteine p[Formula: see text] values calculated with PROPKA, DelPhiPKa, H[Formula: see text], and PKA17 were 3.50, 2.06, 3.17, and 1.26[Formula: see text]pH units. PKA17 has also performed well in assessing the cysteine acidity constants of the CXXC motif of CopZ protein involved in binding of copper(I) metal ions. Our results demonstrate that the PKA17 methodology and current parameters are accurate and robust, and its computational speed makes it possible to be employed in large-scale p[Formula: see text] screening calculations and in constant-pH protein dynamics simulations. The resulting PKA17 software has been deployed online at http://kaminski.wpi.edu/PKA17/pka_calc.html.

scholarly journals Capturing Protein-Ligand Recognition Pathways in Coarse-grained Simulation

2019 ◽  
Author(s):  
Bhupendra R. Dandekar ◽  
Jagannath Mondal
Keyword(s):  
Large Scale ◽  
Computational Cost ◽  
Md Simulations ◽  
Coarse Grained ◽  
Attractive Alternative ◽  
Complex Process ◽  
Potential Binding ◽  
Allosteric Sites ◽  
Potential Binding Site ◽  
Complete Process

AbstractProtein-substrate recognition is highly dynamic and complex process in nature. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of substrate in its act of binding to its designated protein cavity. Towards this end, microsecond long atomistic molecular dynamics (MD) simulation has recently emerged as a popular method of choice, due its ability to record these events at high spatial and temporal resolution. However, success in this approach comes at an exorbitant computational cost. Here we demonstrate that coarse grained models of protein, when systematically optimised to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to cavity, within orders of magnitude shorter wall clock time compared to that of all-atom MD simulations. The simulated and crystallographic binding pose are in excellent agreement. We find that the exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation at a frugal computational cost, in combination with Markov state modelling, leads to clearer mechanistic insights and discovery of novel recognition pathways. The result is successfully validated against three popular protein-ligand systems. Overall, the approach provides an affordable and attractive alternative of all-atom simulation and promises a way-forward for replacing traditional docking based small molecule discovery by high-throughput coarse-grained simulation for searching potential binding site and allosteric sites. This also provides practical avenues for first-hand exploration of bio-molecular recognition processes in large-scale biological systems, otherwise inaccessible in all-atom simulations.

scholarly journals Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation

2021 ◽  
Author(s):  
Erik W Martin ◽  
F Emil Thomasen ◽  
Nicole M Milkovic ◽  
Matthew J Cuneo ◽  
Christy R Grace ◽  
...  
Keyword(s):  
Phase Separation ◽  
Phase Behavior ◽  
Rna Binding ◽  
Mechanistic Explanation ◽  
Md Simulations ◽  
Low Complexity ◽  
Coarse Grained ◽  
Intrinsically Disordered ◽  
X Ray Scattering

Abstract Liquid–liquid phase separation underlies the membrane-less compartmentalization of cells. Intrinsically disordered low-complexity domains (LCDs) often mediate phase separation, but how their phase behavior is modulated by folded domains is incompletely understood. Here, we interrogate the interplay between folded and disordered domains of the RNA-binding protein hnRNPA1. The LCD of hnRNPA1 is sufficient for mediating phase separation in vitro. However, we show that the folded RRM domains and a folded solubility-tag modify the phase behavior, even in the absence of RNA. Notably, the presence of the folded domains reverses the salt dependence of the driving force for phase separation relative to the LCD alone. Small-angle X-ray scattering experiments and coarse-grained MD simulations show that the LCD interacts transiently with the RRMs and/or the solubility-tag in a salt-sensitive manner, providing a mechanistic explanation for the observed salt-dependent phase separation. These data point to two effects from the folded domains: (i) electrostatically-mediated interactions that compact hnRNPA1 and contribute to phase separation and (ii) increased solubility at higher ionic strengths mediated by the folded domains. The interplay between disordered and folded domains can modify the dependence of phase behavior on solution conditions and can obscure signatures of physicochemical interactions underlying phase separation.

scholarly journals The kinetics of the solidification of highly supersaturated solutions of palmitic acid in oleic acid: A comparison between two models

1999 ◽  
Vol 64 (7-8) ◽  
pp. 471-481 ◽  
Author(s):  
Alberto Gallegos-Infante ◽  
Ramiro Rico-Martinez
Keyword(s):  
Fatty Acids ◽  
Oleic Acid ◽  
Palmitic Acid ◽  
Theoretical Models ◽  
Industrial Applications ◽  
Thermodynamic Force ◽  
Avrami Model ◽  
High Concentrations ◽  
D Model ◽  
Supersaturated Solutions

The crystallization of fatty acids is very important in industrial applications and biological systems. A comparison between theoretical models and experimental data helps in clarifying mechanistic aspects of these systems. In this contribution, we compare the performance of two models in fitting data from the crystallization of supersaturated solutions of palmitic acid in oleic acid. One of themodels was developed by Avrami and the other is based on considering diffusion as limiting (the D-model). The D-model fitted the data better than the Avrami model in all cases. The D-model has a low value of the regression coefficient (r2, lower than 0.9) in only three cases. For these points, the thermodynamic force was smaller. Differences in the parameter n (an index of dimensionality) were observed; these differences indicate that clusters were present previous to the crystallization process. Furthermore, there appears to be a difference in the mechanism of crystallization of pure solutions of palmitic acid and solutions with a small fraction of oleic acid. Thus, one is lead to the conclusion that the rate of crystallization of fatty acids at high concentrations is limited by diffusion.

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