Our studies try to establish a long-hypothesized link between the sequence of proteins and their internal motions, which underly many mechanisms and functions of proteins (for example, allostery). With a combination of physical models and AI methods, we predict regions in the protein that facilitate these functional large-scale motions. These studies propose a physical picture of protein as sequence-encoded viscoelastic machines.
quantum mechanics in classical systems
We adopt the formalisms of quantum mechanics to explain collective phenomena in the classical world. We predicted and observed quantum phenomena in a classical dissipative system: A flowing crystal of particles exhibited quasiparticles and flat-band modes, as seen in graphene. Other examples include exotic topology (fractional charges, execptional points etc.) in soft matter systems and the mapping the dynamics of spins to the motion of rolling bodies (see also), leading to a general mathematical theorem in rotation groups.
multiscale organization of living matter
Hierarchical organization,
rich in loops and cycles, is a hallmark of living systems, and we explore how such a multiscale organization may emerge.
In particular, we examine evolving information networks and developmental programs. Some of the basic questions we ask are: How does information flow in the presence of complex interactions? What are the thermodynamic limits to information flow? Can we reverse-engineer complex non-equilibrium steady states? Examples range from the emergence of chirality to de-novo genes.