Feed

Titolo: Self-Assembly of Nanoparticle Mixtures in Lamellar Diblock Copolymers: multiscale molecular modeling

Titolo: Molecular modeling of Nylon 6/organoclay nanocomposite: prediction of binding energy

Titolo: Rationalizing the FS interaction discovered within a tetrafluorophenylazido-containing bola-phospholipid

Titolo: Size and shape matter! A multiscale molecular simulation approach to polymer nanocomposites
Abstract: Multiscale molecular modeling (MsM) techniques are applied in many fields of material science, but it is particularly important in the polymer field, due to the wide range of phenomena occurring at different scales which influence the ultimate properties of the materials. In this context, MsM plays a crucial role in the design of new materials whose properties are influenced by the structure at nanoscale. In this work we present the application of a multiscale molecular modeling procedure to characterize a different set of polymer-based nanocomposites (PNCs) obtained with full/partial dispersion of different nanofillers in different polymeric matrices. This approach relies on a step-by step message-passing technique from atomistic to mesoscale to finite element level, and the calculated results are compared to available experimental evidences. In details, 13 PNC systems have been studied by different molecular modeling methods, such as atomistic Molecular Mechanics and Molecular Dynamics, mesoscale Dissipative Particles Dynamics, and macroscale Finite Element Method, and their mechanical, thermal and barrier properties have been predicted in agreement with the available experimental data.

Titolo: Nanozapped! DNA and its dendritic nanovectors: a combined in silico/in vitro approach

Titolo: The Factory of the Future: Integrating Multiscale Modeling and Experiments to Produce New, Better Nanocomposite Materials

Titolo: A new frontier for modeFRONTIER: an orchestrator for molecular simulation symphony
Abstract: The successful application of high throughput molecular simulations to determine biochemical properties would be of great importance to the biomedical community if such simulations could be turned around in a clinically relevant timescale. An important example is the determination of inhibitor efficacy against varying tyrosine kinase proteins in cancer target therapy through calculation of drug-protein binding affinities.
Here, we describe the Binding Affinity Calculator (BAC), i.e., a modeFRONTIER-integrated molecular simulation tool for the automated calculation of protein-ligand binding affinities (Figure 1). The tool employs fully atomistic molecular simulations alongside the well-established Molecular Mechanics Poisson-Boltzmann Solvent Accessible Surface Area (MMPBSA) free energy methodology to enable the calculation of the binding free energy of several ligand-protein complexes, including several mutant kinase proteins known to be both the etiological agents of different cancer types and the eventual cause of ultimate drug resistance and pathological resurgence.
This enables the efficacy of these inhibitors to be ranked towards the original aberrant protein as well as across several mutant clinical isolates.
BAC is a tool that utilizes the power provided by modeFRONTIER to automate all of the stages required to compute free energies of binding: model preparation, equilibration, simulation, post-processing, and data-marshaling, fully exploiting all compute resources utilized. Such automation enables the molecular dynamics methodology to be used in a high throughput manner not achievable by manual methods. This paper describes the architecture and workflow management of BAC and the function of each of its components. Given adequate compute resources, BAC can yield quantitative information regarding drug activity and resistance at the molecular level in a timescale of direct clinical relevance, and can assist in decision support for the assessment of patient-specific optimal drug treatment and the subsequent response to therapy for any given genotype.

Titolo: Nanofutures: the impact of nanotechnology on industry in 2020
Abstract: Vedi sito

Titolo: Computational alanine scanning to probe DNA - Wild type and mutant p53 interactions.

Titolo: Multiscale modelling techniques in Life Cycle Assessment: application to product design
Abstract: This paper aims at broadening the perspective in life cycle assessment methodology, exploiting multiscale modelling towards the generation of life cycle inventory data during an early-stage product design. Our approach involves the usage of molecular modelling techniques, such as electronic, atomistic or mesoscale models, in combination with continuum models, such as process simulation or finite element methods, to provide data for the generation of life cycle inventories of complex materials and production processes. In particular, each simulation is performed at a specific length and time scale through dedicated software, passing information from the lower to the upper scale.

A practical application of the proposed approach will be illustrated for property predictions of nanostructured polymer systems used for manufacturing a marine engine cover. The material formulations capable of fulfilling the marine thermomechanical constraints were defined using in-silico techniques, allowing for the generation of materials life cycle inventories, which have been compared to identify the most environmentally friendly option.