We use theoretical and atomistic simulation methods to understand how fundamental molecular interactions modulate the thermodynamic and kinetic behavior of nanoscale systems, and how these interactions might be manipulated through design of new processes and molecular architectures. Systems we study include proteins, peptides, network-forming liquids, aqueous solutions, and supercooled liquids and glasses.
Folding and design principles in proteins
Unlike synthetic macromolecules, most proteins spontaneously fold to a unique native three-dimensional structure in solution. How do proteins achieve this tremendous conformational specificity, and what general principles do they suggest for the design of synthetic systems with similar precise functionality? We use atomistic simulation to investigate in natural proteins how structure is stabilized at different levels of organization, and what factors influence folding pathways and kinetics. We also use coarse-grained and simplified models to understand what makes proteins and other complex systems designable, able to encode specific structures and functions. In particular, we are interested in quantifying designability, and elucidating the the nature of and differences between the molecular-thermodynamic and evolutionary constraints placed upon it.
Peptide structure, self-assembly, and aggregation
Peptides have emerged as versatile self-assembling systems that hold extraordinary promise for new, environmentally benign nanoscale materials and scaffolds. Rational peptide engineering strategies demand a deep understanding of the molecular driving forces underlying self-assembly. We use physics-based computational approaches to investigate the structural fluctuations, driving forces, and kinetics in these systems. By using all-atom physical force fields and thermal sampling, in conjunction with an efficient folding strategies and algorithms, we are able to make predictions that other, bioinformatics-based approachs cannot: predicting full conformational ensembles, accounting for solution and temperature effects, and accommodating nonnatural amino acids, for example. We are interested in using the detailed molecular picture gained from these computations to assess the mechanisms behind and ways to modify self-assembly and aggregation behavior.
Water and aqueous solutions
The unique properties of liquid water facilitate self-organization in living systems and many synthetic processes, driven by the hydrophobic effect. We use theory and simulation to understand the basic physics underlying this fundamental interaction, with a particular focus on simple models and perspectives that recapitulate its behavior in highly heterogeneous biomolecular environments. In addition, we use our novel multiscale simulation methods to develop and quantify the accuracy of coarse-grained water models important to large biomolecular simulations.
Multiscale modeling and advanced simulation techniques
We are developing fundamental new approaches for extracting so-called “coarse-grained” models from all atom simulations, and more generally, for linking simulations and theories across multiple length and time scales in a rigorous way. Our approach is based upon a novel information-theoretic concept called the relative entropy. We also develop algorithms for efficiently computing free energies, a challenge in modern simulations; our work is based on a class of self-optimizing “flat-histogram” algorithms. Finally, our group develops and characterizes powerful sampling strategies for complex systems. In particular for proteins, we accelerate the replica exchange molecular dynamics technique by intelligently constraining the size of the conformational space that needs to be explored.