Multiscale Modeling Group


The broad interest of our research group lies in modelling of self-assembly processes in soft-condensed matter systems. A particular focus of the group has been on developing and applying molecular simulation methods to provide mechanistic understanding of picoscale to microscale dynamics of such systems.

We work on investigation of static and dynamic self-assembly processes in soft-condensed matter systems using statistical thermodynamic theory and molecular simulations. Core expertise of the group lies in developing multiscale simulation models to enable in-silico determination of stability, morphology, and dynamical properties of soft matter systems. Our work on development of multiscale models is motivated by carrying out an end-to-end (from molecular scale to mesoscale and larger) investigation to understand synergistic interactions in multi-component and/or multiphase systems with applications in design of novel product formulations with target properties such as therapeutic formulations with acceptable high temperature stability, polymer blends with high solid state adhesion, and conducting polymer-based materials with high energy density. To this end, our group has developed and implemented tools for accelerated all-atom molecular dynamics simulations to obtain up to millisecond-scale atomic resolution on processes related to protein folding, protein association, and polymer nanocomposite morphology.

Research Interests

Protein folding landscape and in-silico design of peptide excipients

Structural reconfigurations of proteins occurring on a timescale of microseconds to milliseconds are known to be extremely important for their folding, activity, and stability. For several proteins, the solution structure ensemble has have important differences from the native crystal structure. Knowledge of structure of various metastable states comprising this ensemble can help in developing strategies to improve stability of liquid protein formulations and increase refolding yields of proteins. However, time averaging in experimental techniques like Nuclear Magnetic Resonance (NMR) spectroscopy makes this characterization difficult. In our group we have used metadynamics simulations to determine the solution ensemble and associated thermodynamics and kinetics of few important therapeutic proteins.

We have further developed a structural bioinformatics approach to elucidate molecular level origins of aggregation nucleation and to design peptides that inhibit dysfunctional protein association. We account for the important role of modular architecture of protein-protein binding interfaces and tertiary structure heterogeneity of protein intermediates in design of peptide inhibitors.

Coarsegrained forcefield for long timescale dynamics of polymer-clay nanocomposites

Polymer nanocomposites consisting of highly anisotropic layered-silicate (clay) nanoparticles are an important class of materials with tunable properties. These anisotrpoic nanoparticles provide a large polymer-particle interfacial area, and therefore, show significant impact on mechanical, structural, and barrier properties of polymer-clay nanocomposites (PCNC) even at low loadings. A large number of material and process parameters, and non-monotonic dependence of target properties on these parameters makes the development of PCNCs for specific applications a challenging task. Molecular simulations provide a means to quickly sample a large parameter space to probe the changes in nanoscale structure of the composite material. However, two key issues that limit the application of atomistic simulation to this system are long relaxation times associated with polymer dynamics and the requirement of large system size for anisotropic particles. To this end, our group has developed an accurate, self-consistent coarsegrained model of various polymer-clay system consisting of organically modified montmorillonite nanoclay as the nanoparticle.


Polyaniline (PAni) based materials with high energy density

Composite materials consisting of a graphene/ graphene oxide substrate and an electroactive component (e.g., polyaniline) provide an attractive route for development of electrode materials with high energy density. The surface morphology of PAni on the substrate and its dependence on surface functionalization of substrate is an extremely important factor governing electrochemical performance of these composite materials. We are specifically interested in an electrode material consisting of ionic liquid (IL) functionalized graphene as a scaffold with immobilized PAni. At present no good all-atomic force fields (FF) are available that can accurately reproduce the electrostatic potential (ESP) profile around PAni. We are using a combination of density functional theory, ab-initio molecular dynamics, and classical all-atomic molecular dynamics to develop a set of consistent parameters for this proposed system on lines of OPLS3 forcefield. An accurate all-atomic FF will enable rapid investigation of dependence of PAni morphology on IL and substrate nanostructure (graphene carbon nanotube, etc.).



·       Julie Borah (Ph.D. student) awarded 4-year fellowship under TCS Research Scholar Program to work on Design and Characterization of Conductive Polymer Nanocomposite Systems for Supercapacitor, July 2018 – July 2022.

·       Technology profile on Designed Peptides to Inhibit Insulin Aggregation published in FIIT forum, January 2018.