Throughout our history, we, humans, have sought to better control and understand our environment. To this end, we have extended our natural senses with a host of sensors-tools that enable us to detect both the very large, such as the merging of two black holes at a distance of 1.3 billion light-years from Earth, and the very small, such as the identification of individual viral particles from a complex mixture. This dissertation is devoted to studying the physical mechanisms that govern a tiny, yet highly versatile sensor: the biological nanopore. Biological nanopores are protein molecules that form nanometer-sized apertures in lipid membranes. When an individual molecule passes through this aperture (i.e., "translocates"), the temporary disturbance of the ionic current caused by its passage reveals valuable information on its identity and properties. Despite this seemingly straightforward sensing principle, the complexity of the interactions between the nanopore and the translocating molecule implies that it is often very challenging to unambiguously link the changes in the ionic current with the precise physical phenomena that cause them. It is here that the computational methods employed in this dissertation have the potential to shine, as they are capable of modeling nearly all aspects of the sensing process with near atomistic precision.
Beyond familiarizing the reader with the concepts and state-of-the-art of the nanopore field, the primary goals of this dissertation are fourfold: (1) Develop methodologies for accurate modeling of biological nanopores; (2) Investigate the equilibrium electrostatics of biological nanopores; (3) Elucidate the trapping behavior of a protein inside a biological nanopore; and (4) Mapping the transport properties of a biological nanopore.
In the first results chapter of this thesis (Chapter 3), we used 3D equilibrium simulations [...]
Technical challenges in molecule sensing and chemical detection have created an increasing demand for transformative materials with high sensitivity and specificity. Biohybrid nanopores have attracted growing interest as they can ideally combine the durability of solid-state nanopores with the precise structure of biological nanopores. Particular care must be taken to control how biological nanopores adapt to their surroundings once in contact with the solid-state nanopore. Two major challenges are to precisely control this adaptability under dynamic conditions and provide predesigned function…
We report Molecular Dynamics (MD) simulations of a generic hydrophobic nanopore connecting two reservoirs which are initially at different Na+ concentrations, as in a biological cell. The nanopore is impermeable to water under equilibrium conditions, but the strong electric field caused by the ionic concentration gradient drives water molecules in. The density and structure of water in the pore are highly field dependent. In a typical simulation run, we observe a succession of cation passages through the pore, characterized by approximately bulk mobility. These ion passages reduce the electric…
The last decade, nanopores have emerged as a new and interesting tool for the study of biological macromolecules like proteins and DNA. While biological pores, especially alpha-hemolysin, have been promising for the detection of DNA, their poor chemical stability limits their use. For this reason, researchers are trying to mimic their behaviour using more stable, solid-state nanopores. The most successful tools to fabricate such nanopores use high energy electron or ions beams to drill or reshape holes in very thin membranes. While the resolution of these methods can be very good, they require…
In the framework of a multiscale modeling approach, we present a systematic study of a bipolar rectifying nanopore using a continuum and a particle simulation method. The common ground in the two methods is the application of the Nernst-Planck (NP) equation to compute ion transport in the framework of the implicit-water electrolyte model. The difference is that the Poisson-Boltzmann theory is used in the Poisson-Nernst-Planck (PNP) approach, while the Local Equilibrium Monte Carlo (LEMC) method is used in the particle simulation approach (NP+LEMC) to relate the concentration profile to the ele…
Nanopores -- nanosized holes that can transport ions and molecules -- are very promising devices for genomic screening, in particular DNA sequencing. Both solid-state and biological pores suffer from the drawback, however, that the channel constituting the pore is long, viz. 10-100 times the distance between two bases in a DNA molecule (0.5 nm for single-stranded DNA). Here, we demonstrate that it is possible to realize and use ultrathin nanopores fabricated in graphene monolayers for single-molecule DNA translocation. The pores are obtained by placing a graphene flake over a microsize hole in…
Using first-principles quantum transport simulations, based on the nonequilibrium Green function formalism combined with density functional theory (NEGF+DFT), we examine changes in the total and local electronic currents within the plane of graphene nanoribbon with zigzag edges (ZGNR) hosting a nanopore which are induced by inserting a DNA nucleobase into the pore. We find a sizable change of the zero-bias conductance of two-terminal ZGNR + nanopore device after the nucleobase is placed into the most probable position (according to molecular dynamics trajectories) inside the nanopore of a smal…
Longitudinal resolution and lateral sensitivity are decisive characteristics that determine the suitability of a nanopore sensor for sequencing a strand of DNA as well as other important polymers. Previous modeling of DNA induced ionic current blockades in single atom thick graphene nanopores has shown these nanopores to have sufficient longitudinal resolution to distinguish individual nucleobases along the length of a DNA molecule. Here we experimentally focus on the sensitivity to small changes in DNA diameter that can be discerned with graphene nanopores. We show that remarkably large sensi…
We employ a multiscale approach to model the translocation of biopolymers through nanometer size pores. Our computational scheme combines microscopic Langevin molecular dynamics (MD) with a mesoscopic lattice Boltzmann (LB) method for the solvent dynamics, explicitly taking into account the interactions of the molecule with the surrounding fluid. Both dynamical and statistical aspects of the translocation process were investigated, by simulating polymers of various initial configurations and lengths. For a representative molecule size, we explore the effects of important parameters that enter …
Water plays a key role in biological membrane transport. In ion channels and water-conducting pores (aquaporins), one dimensional confinement in conjunction with strong surface effects changes the physical behavior of water. In molecular dynamics simulations of water in short (0.8 nm) hydrophobic pores the water density in the pore fluctuates on a nanosecond time scale. In long simulations (460 ns in total) at pore radii ranging from 0.35 nm to 1.0 nm we quantify the kinetics of oscillations between a liquid-filled and a vapor-filled pore. This behavior can be explained as capillary evaporatio…
Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks -- obtained by aggregating or neglecting temporal or categorical description of biological data -- are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of …
The thermal modeling of biological systems has increasing importance in developing more advanced, more precise techniques such as ultrasound surgery. One of the primary barriers is the complexity of biological materials: the geometrical, structural, and material properties vary in a wide range, and they depend on many factors. Despite these difficulties, there is a tremendous effort to develop a reliable and implementable thermal model. In the present paper, we focus on the continuum modeling of heterogeneous materials with biological origin. There are numerous examples in the literature for n…
The aim of this paper is to provide a fractional generalization of the Gompertz law via a Caputo-like definition of fractional derivative of a function with respect to another function. In particular, we observe that the model presented appears to be substantially different from the other attempt of fractional modifications of this model, since the fractional nature is carried along by the general solution even in its asymptotic behavior for long times. We then validate the presented model by employing it as a reference frame to model three biological systems of peculiar interest for biophysic…
This article presents a novel computational model to study the selective filtering of biological hydrogels due to the surface charge and size of diffusing particles. It is the first model that includes the random 3D fiber orientation and connectivity of the biopolymer network and that accounts for elastic deformations of the fibers by means of beam theory. As a key component of the model, novel formulations are proposed both for the electrostatic and repulsive steric interactions between a spherical particle and a beam. In addition to providing a thorough validation of the model, the presented…
Inspired by active shape morphing in developing tissues and biomaterials, we investigate two generic mechanochemical models where the deformations of a thin elastic sheet are driven by, and in turn affect, the concentration gradients of a chemical signal. We develop numerical methods to study the coupled elastic deformations and chemical concentration kinetics, and illustrate with computations the formation of different patterns depending on shell thickness, strength of mechanochemical coupling and diffusivity. In the first model, the sheet curvature governs the production of a contractility i…
This article presents an algorithm that allows modeling of biological networks in a qualitative framework with continuous time. Mathematical modeling is used as a systems biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and to predict the effect of perturbations. We propose a modeling approach that is intrinsically continuous in time. The algorithm presented here fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to desc…
Comment on "Reproducibility study of Monte Carlo simulations for nanoparticle dose enhancement and biological modeling of cell survival curves" by Velten et al. [Biomed Phys Eng Express 2023;9:045004]
The end-Permian mass extinction is the most severe known from the fossil record. The most likely cause is massive volcanic activity associated with the formation of the Permo-Triassic Siberian flood basalts. A proposed mechanism for extinction due to this volcanic activity is depletion of stratospheric ozone, leading to increased penetration of biologically damaging Solar ultraviolet-B (UVB) radiation to Earth's surface. Previous work has modeled the atmospheric chemistry effects of volcanic emission at the end-Permian. Here we use those results as input for detailed radiative transfer simulat…
Membrane tubulation is a ubiquitous process that occurs both at the plasma membrane and on the membranes of intracellular organelles. These tubulation events are known to be mediated by forces applied on the membrane either due to motor proteins, by polymerization of the cytoskeleton, or due to the interactions between membrane proteins binding onto the membrane. The numerous experimental observations of tube formation have been amply supported by mathematical modeling of the associated membrane mechanics and have provided insights into the force-displacement relationships of membrane tubes. R…
In modern surgery, a multitude of minimally intrusive operational techniques are used which are based on the punctual heating of target zones of human tissue via laser or radio-frequency currents. Traditionally, these processes are modeled by the bioheat equation introduced by Pennes, who considers Fourier's theory of heat conduction. We present an alternative and more realistic model established by the hyperbolic equation of heat transfer. To demonstrate some features and advantages of our proposed method, we apply the obtained results to different types of tissue heating with high energy flu…
Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this regard. However, classical machine learning techniques often ignore the fundamental laws of physics and result in ill-posed pr…
We review the computation models for biofilm and bacteria cells, providing perspectives on biofilm's various properties and potential serving as engineering living materials (ELMs), considering the omnipresence of such biological matter. The minireview starts from the molecular regime, bottom-up to the mesoscale, to continuum, with an emphasis on the mesoscale algorithms such as dissipative particles dynamics (DPD) and individual-based modeling (IbM). Some representative works are highlighted considering different modeling methods on each scale. The advantages and limitations of each algorithm…
We suggest a novel approach to treating symbiotic relations between biological species or social entities. The main idea is the characterisation of symbiotic relations of coexisting species through their mutual influence on their respective carrying capacities, taking into account that this influence can be quite strong and requires a nonlinear functional framework. We distinguish three variants of mutual influence, representing the main types of relations between species: (i) passive symbiosis, when the mutual carrying capacities are influenced by other species without their direct interactio…
