SUMMARY OF ARUP K. CHAKRABORTY’S RESEARCH DIRECTIONS AND RECENT
ACCOMPLISHMENTS
Central Theme:
Research
in my group focuses on the development and use of quantum and
statistical mechanical approaches to elucidate complex phenomena
pertinent to systems that are of pragmatic importance. Within this
central theme, work in my group encompasses four broad areas:
[1]
Cell-Cell Recognition in the Immune System, [2] Polymer Science
and Engineering, [3] Sensor Technology for Pathogen Detection, and
[4] Heterogeneous Catalysis. Sophisticated theoretical and
computational methods are developed in my group to study problems in
each of these areas. Our work is closely synergistic (often
collaborative) with the world’s leading experimental researchers in
these fields. My research represents a crossroads of various
disciplines, and the twelve doctoral students and postdoctoral
fellows in my group are drawn from disciplines that include chemical
engineering, chemistry, physics, and biophysics. Below, I briefly
outline recent advances made in my group in each of the four areas
noted above.

Cell-Cell
Recognition in the Immune System:
T
lymphocytes (T cells) are the orchestrators of the adaptive immune
response in complex systems. There are two key stages in the life
cycle of T cells. One is the process of maturation and selection of
immature T cells (thymocytes) in the thymus leading to the T cell
repertoire available in the peripheral lymphoid organs. The other
is activation of mature T cells in response to pathogens which
results in an immune response. Thymocyte selection and mature T
cell activation requires the binding of T cell receptors (TCR)
expressed on the surface of these cells to peptide/major
histocompatibility complex (pMHC) molecules displayed on the surface
of antigen presenting cells (APC). During thymocyte selection,
strong TCR binding to self pMHC results in apoptosis (cell death).
During mature T cell activation, strong TCR binding to
pathogen-derived pMHC results in proliferation. How are such vastly
different biological outcomes mediated by the same signaling
molecules triggered by TCR-pMHC binding?
A
little over three years ago, immunologists discovered that during
mature T cell activation and recognition of antigen presenting cells
a highly organized pattern of different types of receptors and
ligands forms in the intercellular junction between the T cell and
the APC. Since this recognition motif appeared to be implicated in
information transfer between T cells and the APC it was named the
immunological synapse. A number of prominent immunology
laboratories are working on answering important questions that
emerged from the discovery of the synapse. The two broad questions
are: 1] How does the synapse form? and 2] What is the biological
function of the synapse?
My research group
pioneered the use of statistical mechanical methods to address these
questions of great biological importance (#s 72, 76-79, 83, 86-89 in
pub. list). In particular, we have developed and used field
theoretic methods and computer simulations. Our early papers (#s
72, 76, 77, 83 in pub. list) provided the first quantitative
insights into mechanisms that underlie synapse formation in mature T
cells. Our work highlighted the importance of cell membrane
mechanics and shape fluctuations in the process of synapse
formation. This has led immunologists to think about phenomena not
considered heretofore, and has also suggested that the cell membrane
is a viable drug target for controlling immune responses. In two
recent papers (#s 86, 89 in pub. list), we have clarified that low
TCR expression underlies the recent observations from Dr. Paul
Allen’s and Dr. Mark Davis’ laboratories that thymocytes undergoing
selection (apoptosis) form dynamic synaptic patterns that are very
different from the synapse formed by mature T cells during
activation.
Perhaps most significantly, we have shown (# 87 in pub. list) that
the differences in spatial patterns of cell surface receptors during
mature T cell activation and thymocyte selection lead to
differential signaling using the same set of signaling molecules.
This result integrates diverse experimental observations and
suggests a single model for T cell signaling in mature T cells and
thymocytes. Along with parallel genetic experiments in Dr. Andrey
Shaw’s and Dr. Mike Dustin’s laboratories, our results provide the
first clear picture of the functional role of the immunological
synapse. Receptor clustering in the synapse enhances receptor
triggering, and concomitantly increases the rate of receptor
degradation.
Our work in immunology demonstrates how sophisticated theoretical
methods developed in the physical sciences can complement
cutting-edge experimental work in developing an understanding of
important biological problems of medical interest. I believe that
the students and postdoctoral scholars working with me in this area
will be part of a generation of scientists who will contribute to
the exciting crossroads of medicine and the physical sciences. In
close synergy with experimental immunologists, our continuing
efforts aim to address the many issues concerning T cell activation
and synapse formation that are poorly understood. Although very
fundamental in nature, the ultimate goal that this research strives
to achieve is the development of modalities to control the immune
response. A spin-off from our work may be the development of design
strategies for synthetic systems that can mimic the specificity of T
cell recognition and can be used as drug delivery vehicles.
We have a very active collaboration with Prof. Michael Dustin (NYU
Medical School), who led a team of immunologists that discovered the
immunological synapse. Our work is also closely synergistic with a
number of other immunology laboratories (e.g., Prof. Andrey Shaw’s
laboratory at Washington University Medical School). We also
collaborate with an experimental biophysical chemist at Berkeley
(Prof. Groves) on this topic. There are 3 postdoctoral fellows and
2 students currently working on this project in my group. Our work
in this area is funded by the NIH and the NSF-funded Materials
Research Science and Engineering Center (MRSEC).

Polymer Science
and Engineering:
Our
recent work in polymer science and engineering aims to aid the
development of stimuli responsive polymers that can be used in
advanced applications. Specifically, we are interested in examining
how the sequence and architecture of polymers can be manipulated
such that they respond to changes in environmental conditions in
desired ways. We employ field-theoretic methods and computer
simulations to study properties of polymers in solution, in the
molten state, and at interfaces.
Polymer Melts
and Polymer Solutions: The self-assembly of nanostructures in
synthetic polymers with simple architectures and sequences such as
diblock (AB) and triblock (ABA) copolymers is well-established.
However, the rich phenomenology exhibited by these structured
materials has been hard to exploit. This is partly because
phenomena that could be exploited in applications, such as
transitions between different ordered nanostructures, occur in a
prohibitively narrow window of compositions, molecular weight, and
temperature. An alternative approach that is being pursued in
several laboratories is the use of linear multiblock copolymers
(e.g., ABC). We are attempting to exploit other features of long
chain molecules which can be manipulated to control observable
properties; viz., chain architecture and sequence distribution.
Recent developments enable the synthesis of branched copolymers with
unprecedented control over the location, chemical composition,
stiffness and length of the branches. Our program aims to develop
self-assembling branched copolymer materials for applications that
require a precise and reversible response to external stimuli. The
research involves synergistic research using theory/computation,
synthesis, and physical characterization. It is carried out in
collaboration with Profs. Balsara and Frechet at Berkeley. My group
provides the theoretical and computational expertise.
Using replica field theoretic approaches, light scattering, and
neutron scattering we have demonstrated that randomly branched
copolymers (RBCs) exhibit unusual properties in solution and in the
molten state (#s 73-75 in pub. list). We found that polystyrene
(branch) –polybutadiene (backbone) RBCs in the molten state exhibit
a dramatic change in the size of the ordered nanostructures
immediately below the order-disorder transition temperature (#s 56,
73 in pub. list). This behavior is very different from that of
linear block copolymers with ordered sequences, and is due to the
unusual entropy contributions arising from the branched architecture
and the random distribution of branch points. The finding that the
size of the microstructure responds dramatically to changes in
external conditions motivates our work on manipulating architecture
to create responsive materials. We have also carried out
theoretical calculations at the mean – field level which predict the
phase diagram of molten RBCs (# 74 in pub. list). An example of
interesting features in the phase diagram is that the disorder to
order phase transition always goes through the lamellar
microstructure. This is also different from linear block copolymers
with ordered sequences, and is a direct result of the quenched
disorder represented by the disordered distribution of branch
points.
Our studies with RBC solutions demonstrate that there exists an
optimal branching ratio that leads to micelle formation in very
slightly selective solvents (# 75 in pub. list). The prediction and
observation of this non-monotonic dependence of the critical micelle
concentration on sequence is unprecedented. It is also remarkable
that a diblock copolymer with the same monomers (styrene and
butadiene) and in the same solvent (Toluene) does not form micelles
at 10 times the concentration at which the corresponding RBC with
the optimal branching ratio does. This result demonstrates how
macromolecular architecture can be manipulated to tune self-assembly
characteristics of polymers in solution.
Polymer
interfaces: We pioneered studies which demonstrated that
disordered heteropolymers (DHPs) can recognize statistical patterns
on disordered multifunctional surfaces when the statistics
characterizing the DHP sequence distribution and the distribution of
surface sites are related in a special way (for reviews see #s 69,
71 in pub. list). This phenomenon is called statistical pattern
matching. We have now developed a new computational algorithm to
design sequences of synthetic polymers that can recognize patterns
of binding sites on a surface (# 84 in pub. list). This algorithm
uses principles of directed molecular evolution to design polymer
sequences. Recently, we have extended this approach to study how
variations in chain flexibility can be tuned to optimize the speed
with which a polymer chain can recognize and bind to a patterned
substrate with a specific shape. This work is beginning to provide
insights for designing synthetic systems that mimic enzyme ligand
interactions in biological motors.
Two PhD
students and one postdoctoral fellow work with me in this area. My
work in this field is funded by the U.S. D.O.E. (via the Materials
Science Division at LBNL) and the National Science Foundation.

Sensors
Technology for Pathogen Detection:
The
need for the development of devices that can rapidly, accurately,
and reliably screen for pathogens and biohazards cannot be
overstated. In collaboration with Prof. Majumdar (mechanical
engineering, Berkeley), we are working toward the development of
such a microdevice. The heart of this device is a microcantilever
that deflects due to nanomechanical forces resulting from
biomolecular binding. One side of the microcantilever has probe
molecules adsorbed on it. When target molecules in the adjacent
solution bind to these adsorbed probe molecules, the cantilever
deflects. We published the first reports showing that this
deflection results from a balance between forces due to the free
energetics of interactions between adsorbed molecules and that due
to the mechanical energy associated with bending the cantilever (#s
70, 81 in pub. list). Thousands of microcantilvers are being
integrated on a microchip in Prof. Majumdar’s (Mech. Engineering,
UCB) laboratory; each cantilever is functionalized with a different
probe molecule. Design and operation of such a microdevice that
performs in a reproducible fashion can be accomplished with the aid
of computational design tools. We are developing such a
hierarchical computational tool in our laboratory.
We are focusing on DNA detection to prototype this computational
tool. In this context, we have carried out the first atomistically
detailed Molecular Dynamics (MD) study of the kinetics and mechanism
of DNA hybridization and melting. This study demonstrates the vital
role of water molecules in determining the dynamics of DNA melting
and hybridization. This study was enabled by combining
sophisticated methods for sampling rare events with atomistically
detailed MD simulations. For example, new capabilities have been
added to the CHARM molecular dynamics program as a result of this
work. There is 1 PhD student and 1 postdoctoral fellow working in
this area with me, and part of this effort benefits from a
collaboration with Prof. David Chandler at Berkeley. The research
is funded by DARPA.

Heterogeneous
Catalysis:
My work
in heterogeneous catalysis is focused on zeolites. These are
microporous aluminosilicates that contain cationic species for
charge compensation. The regions surrounding the cations serve as
catalytic centers for many industrially important reactions. Over
ten years ago, we were among the first groups to use quantum
chemical calculations to study catalysis in zeolites. In the
preceding three years, we have continued such studies (#s 63-66, 80,
90, 91 in pub. list). A special feature of our current efforts in
this area is the focus on catalytic activation of C-H bonds. This
is motivated by a desire to discover catalysts that can convert
natural gas to useful products. Our work in this area is carried
out in collaboration with leading experimentalists at Berkeley
(Profs. Bell and Iglesia).
As part
of this effort, we have developed a new computational tool to assist
catalyst design. Many materials could potentially catalyze a
desired reaction. Computational tools that can rapidly screen the
thermodynamic and kinetic feasibility of reaction paths leading to
desired products in different zeolites could greatly alleviate the
costs associated with catalyst development. Standard electronic
structure calculations that aim to do this are hampered by the fact
that a priori assumptions need to be made about possible
reaction paths in a given material. Thus, reaction paths that are
not intuitively obvious cannot be studied. More sophisticated
methods (e.g., Car-Parinello MD) where no such assumptions are made
cannot sample the time scales characteristic of catalytic processes
of engineering interest. We have integrated sophisticated
statistical mechanical approaches with state-of-the-art quantum
chemical methods (with Prof. Head-Gordon) to alleviate these
difficulties. A computer algorithm that combines biased transition
state searches, reaction path Hamiltonian methods, and dynamic
corrections to transition state theory with electronic structure
calculations “on the fly” has been developed in my group (# 90 in
pub. list). We are now using this method to study a variety of
different homogeneous and heterogeneous catalytic processes. Two
PhD students and 1 postdoctoral fellow work with me in this area.
Financial support for this work is provided by BP.