Protein folding and conformational change

Proteins are nature’s original “nanotechnology”–molecular machines built from chains of amino acids that have the amazing ability to self-assemble into unique three-dimensional structures and perform a vast array of biochemical functions. Of broad impact to human biology and disease is understanding the physical principles that drive folding and other kinds of conformational change. We use state-of-the-art molecular simulation methods to model these processes.

Voelz, Bowman, Beauchamp and Pande. JACS (2010)

Markov State Models of conformational dynamics

Markov State Model (MSM) approaches are a new paradigm in molecular simulation, in which conformational dynamics can be described as a kinetic network of conformational transitions. Constructing MSMs involves using simulations to identify relevant metastable states, and sampling the transitions between the states. From the inferred transition rates we can obtain information about thermodynamics and kinetics.

MSMs have several advantages over more traditional simulation methods: (1) long timescale dynamics can be inferred from ensembles of much shorter trajectories, (2) flux analysis can provide information about probable pathways, and (3) adaptive sampling methods can be used for efficient sampling. One way we are using MSMs is to make better connections between simulation studies and the kind of spectroscopic observables measured in fast folding experiments. We are also working on new ways to use MSMs as a platform for molecular design.
Razavi AM and Voelz VA. JCTC (2015)

Designing peptidomimetics

Computational design of foldamers with pre-organized structure remains a challenge. We are working on several simulation-based strategies to screen and select designs with favorable conformational and binding properties, including the use of MSMs as a platform for efficient sampling of sequence space. The application of this technology would enable whole new kinds of therapeutics and biotechnology.

Razavi AM, Wuest WM and Voelz VA. JCIM (2014)

Prediction and design of peptoid foldamers

Peptoids are oligomers of N-substituted glycines that have chemical properties similar to peptides. There has been widespread interest in peptoids as biomimetic polymers—they are relatively easy to synthesize, they are resistant to proteolysis, and their biological applications include pharmaceuticals, drug delivery technology, antimicrobials, and nanomaterials. Despite the lack of backbone hydrogen-bonding, polypeptoid sequences have been shown to exhibit foldamer properties. We are currently trying to improve existing simulation models for peptoids, so we can predict and design foldameric properties in silico.

Voelz, Dill and Chorny. Biopolymers (2010)