Modelling the structure and interactions of intrinsically disordered peptides with multiple-replica, metadynamics-based sampling methods and force-field combinations

Intrinsically disordered proteins (IDPs) play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and forcefields. Nevertheless, differences in fine details emerge from varying forcefield/sampling method combinations. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which can be common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field/enhanced sampling method combinations for accurate structural and thermodynamic information in the study of general disordered proteins

FBR for Polyolefin Production in Gas Phase: Validation of a Two-phase Compartmentalized Model by Comparison with CFD

Two different modeling approaches are applied in this work to the simulation of fluidized bed reactors containing solid particles of Geldart A-B type and operated at conditions typically used for polyolefins production. On one side, a fully detailed computational fluid dynamics (CFD) model is developed, considering a 2D planar geometry and a multi-fluid description with kinetic theory of granular flows. On the other, a conventional three-phase, 1D compartmentalized model (SCM) is also developed, implementing the fluid dynamic description based on popular, semi-empirical relationships available in the literature. Given the huge difference of computational effort associated with the corresponding numerical solutions, our aim is to confirm the reliability of the simplified model by comparison with the results of the detailed CFD model. The comparison is carried out considering the fluidization of a bed of solid particles without reaction and solid injection or withdrawal, thus focusing on the steady-state fluid dynamic behavior of the expanded bed. Three different gas velocities and different monodisperse and polydisperse particle populations are analyzed. The results show that the oversimplified compartmentalized approach is capable to predict the solid mixing features established inside the reactor operated in bubbling fluidization regime with good reliability for non-reactive polyethylene particles. Average solid volume fractions are particularly close to the values predicted by the CFD model when monodisperse particles are considered inside the examined range of gas velocity values. A generally good agreement is also found when solids with broad size distribution are analyzed. Overall, these comparisons provide a meaningful validation of the simplified compartmentalized models: given their negligible computational demand and general versatility (complex kinetic schemes and single particle models are easily accounted for), they still represent an effective tool of industrial process design

Comparison between detailed (CFD) and simplified models for the prediction of solid particle size distribution in fluidized bed reactors

This work is aimed at developing a simplified model suitable to effectively describe the fluidization behavior within fluidized beds with minimal computational efforts. The simplified model was validated through detailed CFD Euler-Euler simulations showing a good agreement in the case of large particles (about 450 micron) at all the gas velocities considered (20, 40, 61 cm/s). Slightly less accurate outcomes were observed for smaller particles (about 220 micron). This was due to the underestimation of the particle size effect on the fluidization behavior by the simplified approach

The influence of substituents on gelation and stacking order of oligoaramid – based supramolecular networks

Self-assembly has proven to be a powerful tool for functional, smart materials such as hydrogels derived from low molecular weight compounds. However, the targeted design of functional gelators remains difficult. Here, we present a set of four Y-shaped aromatic amide tetramers with varying functionalities able to undergo different non- covalent interactions. These compounds were explored towards their self-assembly behavior and hydrogel formation by experimental methods such as UV-vis spectroscopy, rheology, small angle X-ray scattering (SAXS), scanning/transmission electron, and atomic force microscopy. Additionally, we investigated the main mechanisms behind oligomer aggregation and the structure of the resulting supramolecular chains through full atomistic molecular dynamics simulations

A detailed CFD analysis of flow patterns and single-phase velocity variations in spiral jet mills affected by caking phenomena

8siIn this work we present a method to investigate the fluid-dynamics of a 3D, real-scale spiral jet mill when caking is occurring. CFD simulations are employed to deeply study the pressure and the velocity fields of the gas phase when the nozzles inlet pressure and the chamber diameter are varied to mimic the condition generated by the aggregates formation during the micronizaton process. The computational model is built replicating the experimental observation consisting in the fact that most of the crusts form on the outer wall of the chamber. Simulations underline that caking causes the deterioration of the classification capabilities of the system if the gas mass flow rate is kept constant at nozzles, allowing larger particles for escaping the system. It is shown that it is possible to mitigate this phenomenon by gradually reducing the gas mass-flow rate to keep constant the nozzles absolute pressure. This keeps unchanged the fluid spin ratio and the classification characteristics when caking is advancing.openopenSabia, Carmine; Frigerio, Giovanni; Casalini, Tommaso; Cornolti, Luca; Martinoli, Luca; Buffo, Antonio; Marchisio, Daniele L.; Barbato, Maurizio C.Sabia, Carmine; Frigerio, Giovanni; Casalini, Tommaso; Cornolti, Luca; Martinoli, Luca; Buffo, Antonio; Marchisio, Daniele L.; Barbato, Maurizio C

A novel uncoupled quasi-3D Euler-Euler model to study the spiral jet mill micronization of pharmaceutical substances at process scale: model development and validation

In this work we present a novel approach to model the micronization of pharmaceutical ingredients at process scales and times. 3D single-phase fluid-dynamics simulations are used to compute the gas velocity field within a spiral jet mill which are provided as input in a 1D compartmentalized model to calculate solid velocities along the radial direction. The particles size reduction is taken into account through a breakage kernel that is function of gas energy and local solid holdup. Simulation results are validated against micronization experiments for lactose and paracetamol, comparing the model predictions with D10, D50 and D90 diameters values coming from Design of Experiments isosurfaces. The developed model allows for a fair estimation of the outlet particle size distribution in a short computational time, with very good predictions especially for D90 values

Structural Characterization of Poly-l-lactic Acid (PLLA) and Poly(glycolic acid)(PGA) Oligomers

Structural characterization of poly-l-lactic acid (PLLA) and poly(glycolic acid) (PGA) oligomers containing three units was carried out with an atomistic approach. Oligomer structures were first optimized through quantum chemical calculations, using density functional theory (DFT); rotational barriers concerning dihedral angles along the chain were then investigated. Diffusion coefficients of l-lactic acid and glycolic acid in pure water were estimated through molecular dynamic (MD) simulations. Monomer structures were obtained with quantum chemical computation in implicit water using DFT method; atomic charges were fitted with Restrained Electrostatic Potentials (RESP) formalism, starting from electrostatic potentials calculated with quantum chemistry. MD simulations were carried out in explicit water, in order to take into account solvent presence

Characterization and Degradation Behavior of Agar–Carbomer Based Hydrogels for Drug Delivery Applications: Solute Effect

In this study hydrogels synthesized from agarose and carbomer 974P macromers were selected for their potential application in spinal cord injury (SCI) repair strategies following their ability to carry cells and drugs. Indeed, in drug delivery applications, one of the most important issues to be addressed concerns hydrogel ability to provide a finely controlled delivery of loaded drugs, together with a coherent degradation kinetic. Nevertheless, solute effects on drug delivery system are often neglected in the large body of literature, focusing only on the characterization of unloaded matrices. For this reason, in this work, hydrogels were loaded with a chromophoric salt able to mimic, in terms of steric hindrance, many steroids commonly used in SCI repair, and its effects were investigated both from a structural and a rheological point of view, considering the pH-sensitivity of the material. Additionally, degradation chemistry was assessed by means of infrared bond response (FT-IR) and mass loss

Not only in silico drug discovery: Molecular modeling towards in silico drug delivery formulations

The use of methods at molecular scale for the discovery of new potential active ligands, as well as previously unknown binding sites for target proteins, is now an established reality. Literature offers many successful stories of active compounds developed starting from insights obtained in silico and approved by Food and Drug Administration (FDA). One of the most famous examples is raltegravir, a HIV integrase inhibitor, which was developed after the discovery of a previously unknown transient binding area thanks to molecular dynamics simulations. Molecular simulations have the potential to also improve the design and engineering of drug delivery devices, which are still largely based on fundamental conservation equations. Although they can highlight the dominant release mechanism and quantitatively link the release rate to design parameters (size, drug loading, et cetera), their spatial resolution does not allow to fully capture how phenomena at molecular scale influence system behavior. In this scenario, the “computational microscope” offered by simulations at atomic scale can shed light on the impact of molecular interactions on crucial parameters such as release rate and the response of the drug delivery device to external stimuli, providing insights that are difficult or impossible to obtain experimentally. Moreover, the new paradigm brought by nanomedicine further underlined the importance of such computational microscope to study the interactions between nanoparticles and biological components with an unprecedented level of detail. Such knowledge is a fundamental pillar to perform device engineering and to achieve efficient and safe formulations. After a brief theoretical background, this review aims at discussing the potential of molecular simulations for the rational design of drug delivery systems.ISSN:0168-3659ISSN:1873-499

From Microscale to Macroscale: Nine Orders of Magnitude for a Comprehensive Modeling of Hydrogels for Controlled Drug Delivery

Because of their inherent biocompatibility and tailorable network design, hydrogels meet an increasing interest as biomaterials for the fabrication of controlled drug delivery devices. In this regard, mathematical modeling can highlight release mechanisms and governing phenomena, thus gaining a key role as complementary tool for experimental activity. Starting from the seminal contribution given by Flory–Rehner equation back in 1943 for the determination of matrix structural properties, over more than 70 years, hydrogel modeling has not only taken advantage of new theories and the increasing computational power, but also of the methods offered by computational chemistry, which provide details at the fundamental molecular level. Simulation techniques such as molecular dynamics act as a “computational microscope„ and allow for obtaining a new and deeper understanding of the specific interactions between the solute and the polymer, opening new exciting possibilities for an in silico network design at the molecular scale. Moreover, system modeling constitutes an essential step within the “safety by design„ paradigm that is becoming one of the new regulatory standard requirements also in the field-controlled release devices. This review aims at providing a summary of the most frequently used modeling approaches (molecular dynamics, coarse-grained models, Brownian dynamics, dissipative particle dynamics, Monte Carlo simulations, and mass conservation equations), which are here classified according to the characteristic length scale. The outcomes and the opportunities of each approach are compared and discussed with selected examples from literature