=Paper=
{{Paper
|id=Vol-2844/ainst6
|storemode=property
|title=Injecting Carbon Nanostructures in Living Cells (short paper)
|pdfUrl=https://ceur-ws.org/Vol-2844/ainst6.pdf
|volume=Vol-2844
|authors=Anastasios Gotzias
|dblpUrl=https://dblp.org/rec/conf/setn/Gotzias20
}}
==Injecting Carbon Nanostructures in Living Cells (short paper)==
https://ceur-ws.org/Vol-2844/ainst6.pdf
Injecting Carbon Nanostructures in Living Cells
Anastasios Gotzias∗
a.gotzias@inn.demokritos.gr
Institute of Nanoscience and Nanotechnology
Athens, Greece
ABSTRACT most well studied approach to delve into such processes is to use
Carbon nanoparticles are currently proposed as reinforcing agents molecular dynamics. However, lengthy simulation runs of “brute-
in synthetic biological membranes, able to be embedded in liv- force” molecular dynamics, typically on the nanosecond time scale,
ing cells and membrane bilayers. Within a biological environment, would be inefficient to capture the long-time scales of typical bio-
porous carbons are anticipated to carry out specific actions, similar logical events, which are frequently on the microsecond or millisec-
to the functionality of known assemblies of biological channels like ond time scale. More important, the dissociation of nanoparticles
cyclic peptides and aquaporins. An attainable approach to delve through interfaces of cosolvents and bilayers obtains high free en-
into the mechanism of how carbon pass through the lipid matrices ergy barriers that cannot be explored using conventional sampling
is to use molecular dynamics (MD) simulations. The mechanism methods.[18] This is because, the probability that a spontaneous
consists of different stages, the relative free energies of which may fluctuation will bring the system on top of the barrier would be
lie far apart in phase space. This induces high energy barriers be- vanishingly small.[7, 16]
tween the stages, that cannot be crossed in a single simulation. Such These challenges can be addressed through application of spe-
observations are addressed through the application of multi-stage cialized sampling techniques such as umbrella sampling and adap-
workflows, where we utilize explicit sampling schemes in every tive force biasing. Such techniques usually require a predefined
stage, ranging form grand canonical partitions, for the loading number of executions of single computational tasks. A series of
and release of drug substances, to pulling and umbrella sampling advanced sampling techniques can be algorithmically combined in
simulations, for the dissociation of nanoparticles. The successful de- multi - stage workflows, to handle complex and highly demand-
velopment of workflows relies on the encoding of the dependencies ing computational processes, like those enrolled in bio molecular
between the stages and the tasks and the assurance that data and simulations.[5, 19] Arguably, nowhere is the importance of work-
parameter variables move between the multi - stage components, flows greater than in biomolecular sciences where the scientific
appropriately. The scope is to use the workflow as a descriptor to outcome is intricately intertwined with the ability to execute work-
train machine learning models for parameter verification and free flows and computational campaigns successfully.[1]
energy calulation methods for carbon - lipid interfaces.
2 METHODOLOGY
CCS CONCEPTS We formulate a multi-stage workflow application to encode the
• Computing methodologies → Simulation support systems; entire process in which carbon nanoparticles land on, bind to and
Molecular simulation. translocate through a lipid environment and release a cargo. This
can be accomplished in four sequential computing stages. The first
KEYWORDS stage describes the adsorption simulations of the drug substance
molecular dynamics, lipid bilayer, porous carbons into the pores of the nanoparticle. The second stage performs the
pulling of the nanoparticle into the bilayer (figure 1). The third stage
1 INTRODUCTION is where the nanoparticle is embedded into the membrane and the
solvation free energies are computed by decoupling the interfacial
If porous carbons are to be exploited as drug delivery systems, it interactions. The forth stage prescribes a model for the diffusivity,
is of both fundamental and practical interest to understand how where the cargo substance exits the space of confinement and dis-
the carbon interface links to the cholesterol supporters of living sociates to an arbitrary far distance from the nanoparticle. Herefter,
cells.[3] Carbons may have nanopores of a size comparable to that we name the different stages of the workflow as 𝑖) adsorption stage,
of endogenous protein channels but mimicking their affinity and 𝑖𝑖) pulling, 𝑖𝑖𝑖) decoupling and 𝑖𝑣) drug release stage, respectively.
transport properties remains challenging.[6] For instance, surface The four stages of the workflow are partitioned in several sub-
functional groups may have adverse effects on the integrity of the tasks (jobs), the development of which, takes place in separate
lipid bilayer as they can be toxic.[4, 12, 17] actions. The four stages are then merged in the workflow, i.e., a uni-
The entire mechanism of carbon nanoparticles entering into fied module capable to be executed in a single submission. We use
and exiting from the lipid environment awaits consensus.[15] The the term "workflow", to express a front-end application handling a
∗ Corresponding author four-stage simulation problem robustly, branching decisions during
the stages without the need of user interaction. This development
entails the encoding of dependencies of the tasks and stages and
AINST2020, September 02–04, 2020, Athens, Greece the assurance that the data and parameter variables move between
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons
License Attribution 4.0 International (CC BY 4.0). the components and tasks, appropriately. This is important because
most of the tasks in a workflow use dependencies from a different
Figure 2: Indicative pathways for nanoparticle injection into
a membrane bilayer. We create a single pathway (𝛾, 𝛿) us-
ing pulling simulation and we perform umbrella sampling
along the pathway to explore numerous possible trajectories
(Γ𝑖 , Δ𝑖 ) for the injection. The trajectory inside the bilayer (𝛿)
is sampled repeatedly, in stage 𝑖𝑖 using umbrella simulations
Figure 1: Injecting a single graphene sheet (red hexagonal
and in stage 𝑖𝑖𝑖 by decoupling the carbon - lipid interactions,
lattice) into a lipid bilayer. The lipids are shown with gray
until the estimates for the relative free energy between the
lines, the hydrophilic head groups of the lipids are shown
two stages statistically converge.
with red and blue nodes. Water molecules are shown with
cyan points, ions in water are shown with blue spheres.
on the drug, that the simulation should definitely take into account.
stage and they can be only executed once all of their dependencies Within the development of stage 𝑖𝑣 in the workflow (i.e., drug re-
have been completed. Although there have been significant advan- lease stage), we employ a revised caging verification algorithm
tages in the state-of-the-theory and practice in workflows, the state that is able to chemically evaluate and predict the hypothetical
of workflow development, execution and extension leaves much formation of lipid - substance (host - guest) molecular complexes.
scope for improvement.
4 EMBEDDED NANOPARTICLES
3 POROUS CARBONS Many studies that use molecular simulation to describe the pene-
From both chemical and technical perspectives, porous carbons tration of membrane cells by carbon sorbents, report contradictory
have an important feature; internal cavities. Like in other types of results. Some of these studies depict the lipids attached on the
framework materials possessing cavities, substances under confin- carbon surface forming monolayer around the nanoparticle and
ment are involved in supramolecular interactions, in particular of blocking the pore channels. Different studies report that the lipids
the host-guest type. To discover, whether one substance can access are selective to a particular size of nanoparticles, provided that
a specific cavity is a challenging task, because the size and shape their body is hydrophobic.[13] One side of the nanoparticle has
of the substance can be very complex. With the nanocarbon model to be shorter than the thickness of the membrane, otherwise the
in hand, the only missing component of the theoretical caging pre- nanoparticle leans in a sideways orientation, in order to maximize
diction is an algorithm that takes the two geometries as input and its interface contact with the lipids. On the other hand, oxygen
determines whether the cavity can encapsulate a substance of an containing functional groups at the rim of the pore channels inter-
arbitrary shape. Algorithms of such type are extensivelly used in act with the hydrophilic head groups of the lipid bilayer forming
the pore size analysis of crystaline porous solids (metal organic and energetically favorable adsoption sites. The functional moieties
zeolitic imidazolate frameworks), where these solids are evaluated on the carbon surface, especially the highly polar ones are great
as selective gas filters.[8–10] However, compared to zeolite - type contributors of the insertion process. The polar groups affect the
solids, membrane bilayer simulations can depict different, more potential mean force of the membrane penetration so radically that
intricate caging complexes. The time the cargo substance escapes a they may render the membrane impermeable to the nanoparticle.
pore channel, it can be encapsulated by the lipid macromolecules. However, in most simulation studies, carbons are initilally embed-
The lipids configure a cage-like cavity around the drug, that appears ded in the lipid bilayer without any description of how they have
like a molecular trap. The trap imposes strong position restraints reached that place. Most studies also employ a unified force field,
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