Dissipative Particle Dynamics Simulations of a Protein-Directed Self-Assembly of Nanoparticles

A Structure Independent Molecular Fragment Interfuse Model for Mesoscale Dissipative Particle Dynamics Simulation of Peptides

There is a need to develop robust computational models for mesoscale simulation of the structure of peptides over large length scales toward the discovery of novel peptides for medical applications to address the issues of peptide aggregation, enzymatic degradation, and short half-life. The primary objective was to predict the structure and conformation of peptides whose native structures are not known. This work presents a new model for computation of interaction parameters between the beads in coarse-grained dissipative particle dynamics (DPD) simulation that is properly calibrated for amino acids, supports compressibility requirement of water molecules, and accounts for subtle differences in the structure of amino acids and the charge in the side chain of charged amino acids. This new model is referred to as Structure Independent Molecular Fragment Interfuse Model, abbreviated as SIMFIM, because it accounts for specific interactions between different beads, which represent molecular fragments of the amino acids, in calculating nonbonded interaction parameters in the absence of knowing the actual peptide structure. The electrostatic interactions are incorporated in this model by using a normal distribution of charges around the center of the beads to prevent the collapse of oppositely charged soft beads. The uniquely parameterized DPD force field in the SIMFIM model is optimized for a given peptide with respect to the degree of coarse-grained graining for simulating the peptide over long times and length scales. The SIMFIM model was tested in this work using four peptides, namely, TrpZip2, Rubrivinodin, Lihuanodin, and IC3-CB1/Gai peptides, whose structures were sourced from the Protein Data Bank. The SIMFIM model predicted radius of gyration (Rg) values for the peptides closer to the actual structures as compared to the conventional model, and there was less deviation between the predicted and actual structures of the peptides.

Diversified applications of self-assembled nanocluster delivery systems- A state-of-the- art review

BACKGROUND

Self-assembled nanoclusters arrange the components into an organized structure for the nanoparticulate system and also in the transportation of cellular elements for the fabrication of microelectronic devices. Nanoclusters reduce transcytosis and increase endocytosis in intestinal mucin to strengthen the retrograde pathway that helped in the delivery of actives to the Golgi apparatus.

OBJECTIVES

This review article focuses on the self-assembled nanoclusters for cellular transportation, applications of self-assembled structures in the delivery of essential elements like the use of a peptide in targeted and stimuli-responsive drug delivery systems, self-assembly of tocopherol nanoclusters that promotes vitamin E delivery across the endothelial barrier. Methods Current innovation in the self-assembly of peptides includes the formation of nanostructures like vesicles, fibers, and rod-coil in the applications of wound healing, tissue engineering, treatment of atherosclerosis, in sensing heavy metals from biological and environmental samples and advanced drug delivery.

RESULTS

Self-assembled biodegradable nanoclusters are used as biomimetic structures for synergistic effect. Improvement in the methods of preparation like the addition of a copolymer is used for temperature-triggered drug release nanoclusters.

CONCLUSION

Green synthesis of nanoclusters, nanocluster-based biosensor and artificial intelligence are the future concept in the manufacturing and the prevention of toxicity in humans.

Multiscale simulations of polyzwitterions in aqueous bulk solutions and brush array configurations

Zwitterionic polymers are very promising candidates for antifouling materials that exhibit high chemical stability as compared to polyethylene glycol-based systems. A number of simulation and experimental studies have emerged over recent years for the investigation of sulfobetaine-based zwitterionic polymers. Investigating the structural and thermodynamic properties of such polymers requires access to broad time and length regimes, thus necessitating the development of multiscale simulation strategies. The present article advocates a mesoscopic dissipative particle dynamics (DPD) model capable of addressing a wide range of time and length scales. The mesoscopic force field was developed hand-in-hand with atomistic simulations based on the OPLS force field through a bottom-up parameterization procedure that matches the atomistically calculated strand-length, strand-angle and pair distribution functions. The DPD model is validated against atomistic simulations conducted in this work, and against relevant atomistic simulation studies, theoretical predictions and experimental correlations from the literature. Properties examined include the conformations of SPE polymers in dilute bulk aqueous solution, the density profile and thickness of brush arrays as functions of the grafting density and chain length. In addition, we compute the potential of mean force of an approaching hydrophilic or hydrophobic foulant via umbrella sampling as a function of its position relative to the poly-zwitterion-covered surface. The aforementioned observables lead to important insights regarding the conformational tendencies of grafted polyzwitterions and their antifouling properties.

Dissipative particle dynamics simulations in colloid and Interface science: a review

Dissipative particle dynamics (DPD) is one of the most efficient mesoscale coarse-grained methodologies for modeling soft matter systems. Here, we comprehensively review the progress in theoretical formulations, parametrization strategies, and applications of DPD over the last two decades. DPD bridges the gap between the microscopic atomistic and macroscopic continuum length and time scales. Numerous efforts have been performed to improve the computational efficiency and to develop advanced versions and modifications of the original DPD framework. The progress in the parametrization techniques that can reproduce the engineering properties of experimental systems attracted a lot of interest from the industrial community longing to use DPD to characterize, help design and optimize the practical products. While there are still areas for improvements, DPD has been efficiently applied to numerous colloidal and interfacial phenomena involving phase separations, self-assembly, and transport in polymeric, surfactant, nanoparticle, and biomolecules systems.

Carbon nanotube transmembrane channel formation and single-stranded DNA spontaneous internalization: a dissipative particle dynamics study

Single-walled carbon nanotube (SWCNT) transmembrane channel formation in a pure 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) bilayer, and the spontaneous internalization of single-stranded DNA (ssDNA) into the formed pore were simulated. A combination of computational techniques, Dissipative Particle Dynamics-Monte Carlo hybrid simulations and quantum mechanical calculations at the hybrid-DFT level, was used as a new proposal to perform DPD simulations granting specific chemical identity to the model particles. The simulated transmembrane channels showed that, in the case of pristine SWCNTs and upon increasing the nanotube length, a higher tilt angle with respect to the bilayer normal is observed and more time is needed for the nanotube to stabilize. On the other hand, for SWCNTs with polar rims an almost perpendicular orientation is preferred with less than 15° of tilt with respect to the bilayer normal once the nanotubes have pierced both monolayers. These findings are supported by experimental observations where CNTs of average inner diameters of 1.51 ± 0.21 nm and lengths in the 5-15 nm range were inserted in DOPC membranes [J. Geng, et al., Nature, 2014, 514(7524), 612-615]. Moreover, the narrower the SWCNTs, the slower the spontaneous internalization of ssDNA becomes, and ssDNA ends hydrophobically trapped inside the artificial pore. A dependence on the nucleotide content is found indicating that the higher the presence of adenine and thymine in the ssDNA chains the slower the internalization becomes, in agreement with the experimental [A. M. Ababneh, et al., Biophys. J., 2003, 85(2), 1111-1127] and predicted solvation tendency in water for nucleic acid bases.

Coarse-grained simulation of the translational and rotational diffusion of globular proteins by dissipative particle dynamics

With simplified interactions and degrees of freedom, coarse-grained (CG) simulations have been successfully applied to study the translational and rotational diffusion of proteins in solution. However, in order to reach larger lengths and longer timescales, many CG simulations employ an oversimplified model for proteins or an implicit-solvent model in which the hydrodynamic interactions are ignored, and thus, the real kinetics are more or less unfaithful. In this work, we develop a CG model based on the dissipative particle dynamics (DPD) that can be universally applied to different types of proteins. The proteins are modeled as a group of rigid DPD beads without conformational changes. The fluids (including solvent and ions) are also modeled as DPD beads. The electrostatic interactions between charged species are explicitly considered by including charge distributions on DPD particles. Moreover, a surface friction between the protein and fluid beads is applied to control the slip boundary condition. With this model, we investigate the self-diffusion of a single globular protein in bulk solution. The translational and rotational diffusion coefficients of the protein can be tuned by the surface frictional constant to fit the predictions of the Stokes-Einstein (SE) relation. We find that both translational and rotational diffusion coefficients that meet with the prediction of the SE relation based on experimental results of the hydrodynamic radius are reached at almost the same frictional constant for different types of proteins. Such scaling behavior indicates that the model can be applied to simulate the translational and rotational diffusion together for various types of proteins.