Arup Chakraborty Research Group

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Chemical Engineering


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.

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Last updated: 10/12/04.