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Modeling Pressure-Driven Transport of Proteins through a Nanochannel.

ABSTRACT: Reducing the size of a nanofluidic channel not only creates new opportunities for high-precision manipulation of biological macromolecules, but also makes the performance of the entire nanofluidic system more susceptible to undesirable interactions between the transported biomolecules and the walls of the channel. In this manuscript, we report molecular dynamics simulations of a pressure-driven flow through a silica nanochannel that characterized, with atomic resolution, adsorption of a model protein to its surface. Although the simulated adsorption of the proteins was found to be nonspecific, it had a dramatic effect on the rate of the protein transport. To determine the relative strength of the protein-silica interactions in different adsorbed states, we simulated flow-induced desorption of the proteins from the silica surface. Our analysis of the protein conformations in the adsorbed states did not reveal any simple dependence of the adsorption strength on the size and composition of the protein-silica contact, suggesting that the heterogeneity of the silica surface may be a important factor.

SUBMITTER: Carr R

PROVIDER: S-EPMC3353732 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Modeling Pressure-Driven Transport of Proteins through a Nanochannel.

Carr Rogan R Comer Jeffrey J Ginsberg Mark D MD Aksimentiev Aleksei A

IEEE transactions on nanotechnology 20110101 1

Reducing the size of a nanofluidic channel not only creates new opportunities for high-precision manipulation of biological macromolecules, but also makes the performance of the entire nanofluidic system more susceptible to undesirable interactions between the transported biomolecules and the walls of the channel. In this manuscript, we report molecular dynamics simulations of a pressure-driven flow through a silica nanochannel that characterized, with atomic resolution, adsorption of a model pr ...[more]

PMID: 22611338

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Project description:: Sensing proteins (receptors) are nanostructures that exhibit very complex behaviors (ions pumping, conformational change, reaction catalysis, etc). They are constituted by a specific sequence of amino acids within a codified spatial organization. The functioning of these macromolecules is intrinsically connected with their spatial structure, which modifications are normally associated with their biological function. With the advance of nanotechnology, the investigation of the electrical properties of receptors has emerged as a demanding issue. Beside the fundamental interest, the possibility to exploit the electrical properties for the development of bioelectronic devices of new generations has attracted major interest. From the experimental side, we investigate three complementary kinds of measurements: (1) current-voltage (I-V) measurements in nanometric layers sandwiched between macroscopic contacts, (2) I-V measurements within an AFM environment in nanometric monolayers deposited on a conducting substrate, and (3) electrochemical impedance spectroscopy measurements on appropriate monolayers of self-assembled samples. From the theoretical side, a microscopic interpretation of these experiments is still a challenging issue. This paper reviews recent theoretical results carried out within the European project, Bioelectronic Olfactory Neuron Device, which provides a first quantitative interpretation of charge transport experiments exploiting static and dynamic electrical properties of several receptors. To this purpose, we have developed an impedance network protein analogue (INPA) which considers the interaction between neighboring amino acids within a given radius as responsible of charge transfer throughout the protein. The conformational change, due to the sensing action produced by the capture of the ligand (photon, odour), induces a modification of the spatial structure and, thus, of the electrical properties of the receptor. By a scaling procedure, the electrical change of the receptor when passing from the native to the active state is used to interpret the macroscopic measurement obtained within different methods. The developed INPA model is found to be very promising for a better understanding of the role of receptor topology in the mechanism responsible of charge transfer. Present results point favorably to the development of a new generation of nano-biosensors within the lab-on-chip strategy.

Project description:In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer's cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

Dataset Information

Modeling Pressure-Driven Transport of Proteins through a Nanochannel.

Publications

Modeling Pressure-Driven Transport of Proteins through a Nanochannel.

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