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SD3 Projects Report Narrative (H. Ashbaugh and D. Moldovan)
The goal of SD3 is to develop new biomolecular material systems for the encapsulation, delivery,
and release of therapeutics to targeted tissues. The barriers to achieving these goals are modeling length
scales on the order of 10-9 to 10-7 m and the lack of sufficiently efficient force fields to enable simulations
to reach time scales of 10-6 to 10-3 s required for meaningful predictions. We have put together multidisciplinary teams of scientists at four institutions (Tulane, LSU, UNO, and LATech) that combine
theoretical/computational scientists with experimentalists to investigate aspects necessary for building
predictive models of uni-molecular and multi-molecular vehicles for targeted drug delivery. Participating
researchers are investigating: The accurate modeling of the driving forces for assembly; the synthesis of
amphiphilic homopolymers; the assembly of micelles for delivery; the preparation of lipid and
nanoparticle systems for delivery; the development of advanced techniques for fast and accurate free
energy determination; efficient coupled continuum/molecular flow simulations; new methods for DNA
separations; high throughput techniques for submitting large numbers of molecular simulations across
distributed networks; and diffusion with tumors and self-healing materials. Progress in each of these
projects over the 2010 to 2011 funding year is described below.
Accurate simulation of water-mediated interactions driving self-assembly (H. Ashbaugh, S. Grayson
and L. Liu): The insolubility of non-polar oils in water (the hydrophobic effect) provides one of the
primary driving forces for the assembly of biomacromolecules and surfactant assemblies. Current state of
the art potential models for the alkanes typically under-predict their solubility in aqueous solution (e.g.,
Fig. 1), thereby over estimating hydrophobic driving forces for self-assembly. The application of higher
order ab initio vacuum calculations for overcoming this deficiency do not account for this discrepancy,
however, since it results from unaccounted for condensed phase polarization interactions between water
and the alkane. To address this problem, we have undertaken a simulation study to empirically tune
alkane-water interactions for an existing alkane and
water model to reproduce the experimentally observed
solubilities of the linear and branched alkanes.
Beginning with the Transferable Potentials for
Phase Equilibria (TraPPE) United-Atom model for the
linear and branched alkanes and the TIP4P/2005 model
for water, both of which have been optimized to
reproduce the pure component liquid/vapor phase
diagrams, we evaluated free energies using the
GROMACS MD simulation package to determine
predicted linear and branched alkane solubilities in
water. The cross alkane-water Lennard-Jones interaction
parameters were subsequently optimized to minimize
the root mean square difference between the predicted
and experimental alkane solubilities. The parameter set
so derived, refereed to as the Hydrophobic Hydration
Alkane (HH-Alkane) model, provides a near Figure 1. Ostwald solubility of neopentane in
quantitative description of alkane solubility in water water as a function of temperature. Results for the
over a broad temperature range (e.g., Fig. 1). The results TraPPE and HH-Alkane model in TIP4P/2005
of this study will translate into an improved description water are compared to experiment.
of hydrophobic assembly, and have been submitted for
publication to the Journal of Chemical Physics.
In ongoing studies, we are performing simulations of the temperature-induced collapse of poly-Nisopropylacrylamide in water, which is used as a potential trigger for polymer based drug delivery
vehicles. This collapse is driven by the diminished solubility of the isopropyl group in water with
increasing temperature, as captured by the HH-Alkane model. Secondly, we are initiating coarse-grained
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study of click polymerization to examine the topologies of uni-molecular drug delivery vehicles
synthesized in the Grayson lab.
Synthesis of new uni-molecular drug delivery vehicles (S. Grayson and Y. Wang): Extensive work has
been carried out with linear amphiphilic block copolymers in order to optimize control of their selfassembly into polymer micelles. Tuning the
block lengths and the relative block ratios
(polar/non-polar monomers) results in control
over the size and stability of the resulting
assemblies. However, a wide variety of other
amphiphilic polymers remain to be explored.
One particularly interesting class of
amphiphilic polymers is the amphiphilic
homopolymer, in which each repeat unit bears
a polar side chain (in blue) as well as a
nonpolar side chain (in orange) (Scheme 1). A
synthetic methodology has been determined
for the preparation of amphiphilic monomers,
and polymerization investigated using both
traditional free radical polymerization and
atom transfer radical polymerization, to yield
Scheme 1: Synthesis of amphiliphilic monomer
amphiphilic homopolymers with molecular
weights as large as 50,000.
Initial investigation of the encapsulation
properties suggest these polymers do aggregate to yield micellar structures capable of encapsulating Rose
Bengal (a polar dye) in hexane. The 50,000 MW polymers exhibit a critical micelle concentration around
0.04mg/ml. Further synthetic efforts are targeting a similar monomer which also exhibits aqueous
solubility, and perhaps can rearrange from a micelle to a reverse micelle, with changes in solvent polarity.
Molecular dynamics simulation studies of self-assembly of Span-80 into micelles (D. Moldovan, C.
Sabliov, D. Nikitopoulos, H. Ashbaugh, B. Thakur, B. Novak, R. Kumuditha, J. Lin, and K. Xia): The goal
of this project is to study drug encapsulation in surfactant assemblies, and their subsequent delivery across
a cell membrane. In our MD simulations a lipid bilayer is
used to model the cell membrane. We have begun
simulations of the self-assembly of Span-80 in water above
the critical micelle concentration. Specifically, we
investigated the aggregation kinetics starting from
disordered mixtures of Span-80 and letting the systems
naturally aggregate into a single micelle (Fig. 2). Selfassembly was found to place in three stages: A fast initial
stage (~1ns) in which the surfactants form small sub- Figure 2. Snapshots of the time
micellar clusters; this is followed by a ripening stage in evolution of Span-80 assembly into a
which the larger clusters grow at the expense of the smaller single micelle.
ones; finally the larger substantial aggregates more slowly
diffuse and coalesce into equilibrium micelles.
To carry out these simulations, we have had to develop a new force field model for Span-80 to
overcome problems with the original force field generated using PRODRG2, the automated topology
builder that only allows up to HF/STO-3G level of theory. The structure of Span-80 was created using
GaussView and subsequently relaxed by a MD minimization step followed by Gaussian minimization to
obtain a relaxed starting geometry. Analyzing the structure of Span-80, it is evident that the torsions near
the ring structure plays a crucial role. The torsional energy, characterizing rotation around the C-C bond
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(D1 in Fig. 3) connecting the ring to the rest of the molecule, is dominant. Moreover, the D1 torsion is
coupled to the ring confirmation and hence to the orientations of the two hydroxyl groups of the ring
(angles D2 and D3 in Fig. 3). We therefore did simultaneous scans of all three torsions. The D1 torsion
was re-parameterized for the Amber force field using ab initio calculations (performed with Gaussian and
the HF/6-311g(d) basis set). Torsions D1, D2 and
D3 were scanned in concert through 360 degrees
at increments of 60 degrees. This multi-dihedral
scan ensures all important configurations are
sampled. D1 was scanned in increments of 5
degrees. Our methodology can be used to obtain
reliable force field parameters for other complex
molecules for which there are no existing force
fields. Generalized scripts and Fortran modules
Figure 3. Representation of the Span80 and the three
will be distributed on the LA-SiGMA webpage.
relevant dihedral angles.
Experimental assessment of the effect of nanoparticles on vesicle transport properties (R. Devireddy,
C. Sabliov, D. Moldovan, D. Nikitopoulos, and D. Chanda): Liposomes (lipid vesicles) are formed when
thin lipid films or lipid cakes are hydrated and stacks of liquid crystalline bilayers become fluid and swell.
The hydrated lipid sheets detach during agitation and self-close to form large, multilamellar vesicles
(LMVs) which prevents interaction of water with the hydrocarbon core of the bilayer at the edges.
Specifically, lipid solutions were prepared at 10-20mg lipid/ml organic solvent. Once the lipids were
thoroughly mixed in the organic solvent, the solvent was removed to yield a lipid film. The lipid film was
thoroughly dried to remove residual organic solvent and transferred to containers. The containers were
frozen by placing them in a dry ice-ethanol bath. After freezing completely, the frozen lipid cake was
lyophilized until dry (1-3 days depending on volume). Hydration of the dry lipid film/cake was
accomplished by adding an aqueous medium to the container of dried lipid and agitating. Once a stable,
hydrated LMV suspension has been produced, it was forced through a polycarbonate filter with a defined
pore size to yield particles having a diameter near the pore size of the filter used. Extrusion through filters
with 100nm pores typically yielded large, unilamellar vesicles (LUV) with a mean diameter of 120-140
nm. Mean particle size was reproducible from batch to batch.
Polymeric nanoparticle-cell interactions (C. Sabliov and M. Whaley): Polymeric nanoparticles of
controlled physical properties were synthesized by the emulsion evaporation method. The empty and
loaded poly(lactic-co-glycolic) acid nanoparticles were characterized by transmission electron
microscopy and dynamic light scattering to confirm spherical morphology, tight size distribution
(polydispersity index < 0.15) and small size (diameter < 200 nm). Cellular cytoxicity studies for these
nanoparticles were carried out in the HepG2 (human liver carcinoma) cell line to determine the cytoxic
concentration when compared to a control. Cellular uptake of fluorescent conjugated (TRITC) PLGA
naoparticles were evaluated qualitatively and quantitatively through microscopy. Cells readily
internalized EC-PLGA-TRITC nanoparticles as confirmed by an increase in cytoplasmic fluorescence
over time, and confirmed quantitatively.
Transport of DNA nucleotides through nanochannels (D. Moldovan, D. Nikitopoulos, B. Novak, and
K. Xia): The goal of this project is to study the interaction of the DNA nucleotides with the walls of a
nano-channel, which is critical for the development of sequencing devices based on nanometer scale
geometries. Equilibrium and non-equilibrium MD simulations with gravity and electric field driven flows
have been performed. The equilibrium simulations were used to calculate the free energy of nucleotides in
the proximity of the walls to provide an indication of the nucleotide affinity for the wall. Our nonequilibrium simulations found that the nucleotide behavior depends on the driving force for flow. In
gravity-like driven flow, the trend of increasing time of flight of the nucleotides through the channel (C <
G < A < T) was correlated with the increasing hydrophobicity of the bases (G < C < A < T) and the
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increasing free energy differences (C < A < G < T), although the position of G relative to A and C was
not the same. In the case of electric field driven flow and atomically smooth walls, however, the
nucleotides slide faster on the walls since the force on the nucleotides due to the electric field is constant
across the slit instead of decreasing near the walls as in the case of gravity-like forces. This faster sliding
caused the flight times of the nucleotides to be almost the same. We are presently constructing more
realistic channel walls to determine the effects of surface group chemistry on nucleotide/wall interactions.
Hybrid MD-continuum simulation methodology for biomolecular systems: LAMMPSANSYS/Fluent coupling implementation and transition to CPU/GPU high performance computing
(D. Nikitopoulos, D. Moldovan, S. Jha, N. Kim, J. Ko, B. Novak, and K. Hessary): Work has been
conducted towards further development of a tool for generically coupling continuum CFD and MD
simulation codes for the study of non-equilibrium flow in mixed-scale domains (mm to atomistic)
involving biological materials. A graduate student, Kasra Hesary, has successfully used the tool to couple
the MD package LAMMPS to a commercial CFD code
(ANSYS/Fluent) and verified the results for simple test
problems (Fig. 4). He is now working with computer
science colleagues under LA-SiGMA to leverage use of
CPU and GPU computing to dramatically accelerate the
coupled CFD/MD simulations.
This work will enable exploration of non-equilibrium
phenomena in both purely biological and hybrid nonbio/bio systems, which are inherently multi-scale, through
efficient high-performance simulations, which would
otherwise not be possible. Furthermore, it will revolutionize
the design capabilities of such systems and processes. The
group has initiated collaboration with the developer of
LAMMPS, Dr. Steve Plimpton of Sandia, to develop a Figure 4. Velocity profiles at various
“fix” and related documentation for LAMMPS that will times for the coupled CFD/MD transient
make this tool available to the broader scientific Couette test problem with strong
fluid/moving-wall molecular interaction.
community.
Advanced techniques for hydration and binding free energy evaluation (D. Mobley, S. Rick, J.
Shraberg, S. Liu): Previous work in my group highlighted that substantial obstacles hamper efforts to
obtain accurate thermodynamic properties for even rather small molecules in solution from molecular
simulations (e.g., those resulting from the torsional barriers to hydroxyl reorientation in solution).
Calculations of properties such as hydration and transfer free energies are now becoming routine and are,
in many cases, quite accurate, providing for potential new applications in the area of solubility prediction
and control. In collaboration with Prof. Ed Maginn’s group at the University of Notre Dame, we have
benchmarked an advanced expanded ensemble approach for computing hydration free energies of small
molecules, compared it to more traditional approaches, and demonstrated substantial speedups. A key
insight is that torsional barriers can be deliberately reduced at intermediate state and restored at the end,
yielding enhanced accuracy and efficiency. This work has been submitted for publication.
In a second project, we are developing techniques for the automated calculation of binding affinities
of large groups of candidate drugs to protein targets. A major goal in this area is to be able to apply
accurate calculations to estimate binding affinities of hundreds of compounds, which could be tested, to
narrow synthetic searches to smaller groups of highly promising drug candidates. Our previous work has
largely focused on accurate binding free energy calculations. We are now developing tools to automate
the planning of relative free energy calculations to compare binding affinities of ~570 different molecules
to a target receptor. Known compounds are included in the library, so that absolute binding free energies
of all of the potential ligands may be computed using relative free energies connecting unknown
molecules to those with known affinities. To begin, similarly structured molecules are clustered into
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groups, thereby adding computational efficiency. Subsequently, connections between clusters are added
to ensure that each molecule can be reached via multiple paths from any other molecule. Then,
calculations are added between structural clusters to connect the most similar members and ensure
absolute binding free energies can be computed between all molecules.
Distributed molecular simulations of solvated nucleosomes (T. Bishop, S. Jha, and R. Mukherjee):
Nucleosomes are a protein DNA complex in which 147 base pair of DNA are wrapped into nearly two
turns of a superhelix. In humans, and other
eukaryotes such folding of the DNA is necessary to
pack it into the cell nucleus because the length of a
genome as a molecular fiber far exceeds the width
of the cell nucleus. In the case of humans the ratio is
on the order of 1,000,000 to 1. The material
properties of DNA, (e.g., stiffness or flexibility and
conformation) have a significant impact on the
details of the packing, yet we do not sufficiently
understand the relationships. Simple physical
models and sequence-based rules have proven
insufficient to capture the biologic reality.
Moreover, it is not possible to investigate all ~(4)146
possible sequence variants either by experiment or
computation thus we seek to develop computational
workflows that allow us to efficiently and rapidly
investigate any sequence “on-demand”. All-atom
MD simulations capture these complexities but
require a large number of simulations to extract and
verify the generalities. In our case, each simulation
Figure 5. Top: Coarse-grained models of the folding
demands high performance computing resources.
of DNA (small yellow spheres) into nucleosomes
We use between 32 and 192 processors, depending
(larger colored spheres) and chromatin (entire
on availability, running for 12 to 24 hours at a time
complex) have proven insufficient to explain biologic
just to represent 1 ns in the life of the 150,000
mechanisms. Bottom: All atom models contain
atoms of a solvated nucleosome.
sufficient detail to capture heterogeneity in the
To date we have utilized nearly 2,000,000 hours
properties of proteins and DNA at the atomic level.
of computer time at four different supercomputing
sites (NCSA, TACC, NICS, LONI) and our departmental resources to accumulate over 3 µs of simulated
dynamics for ~500 different models of the nucleosome. To manage the ~6,000 simulation tasks associated
with this project we have developed a set of tools in Python called “ManyJobs” which tracks the status of
the individual tasks and automatically distributes them to various supercomputing resources as the
resources become available. The tool ManyJobs is available at dna.ccs.tulane.edu.
Diffusion of molecules and nanoparicles from blood vessels into tumors (P. Derosa and V.
Podduturi): In this project a model is being developed to study the diffusion of nanoparticles from the
blood stream into cancer tumors. The main assumption of the model is that particles are dragged along
the blood vessel. Tumor blood vessels are known to be leakier that blood vessels in healthy tissue, a
property that can be exploded to selectively deliver drugs to tumors if nanoparticles of appropriate size
are chosen. A model that combines random walk with diffusion principles to study the diffusion process
of particles in the blood stream into tumors was proposed. Particles pass from the blood vessel through
the pore due to a pressure difference between the pore and the tumor. Particle delivery as a function of
the concentration of particles in blood, blood pressure, and blood vessel diameter and pore size are being
studied. Preliminary studies show good agreement with experiments.
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Diffusion of particles in nanotubes, storage and release (Y. Lvov, P. Derosa, E. Abdullayev, D.
Elumalai, K. Arapov): The hollow tubular structure of halloysite makes it attractive for use as
nanocontainers for encapsulating corrosion inhibitors and other active agents for corrosion protection.
Experimental efforts in Prof. Lvov’s lab were demostrated for self-healing coatings. First, halloysite
nanotubes loaded with desired healing substances are added to liquid paint and applied to a metal surface.
Halloysite loaded with substances that stay sealed in dry paint as long as no cracks occur in the paint.
Once the paint is damaged, tubes are exposed to the environment and loaded agents leak into the
corrosive aqeous media and to form a protective layer on the exposed metal surface. In Prof. Derosa’s lab
a MC model is being develop to study this process, all relevant physical interactions between the particles
and nanotubes are being included. The main objective of modelling is to aid the design of nanocontainers
with on-demand delivery properties, not only for self-healing coatings but also for drug delivery amongst
other applications.
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