Proteins function as specialized machines inside living organisms. Many physiological processes rely on proteins interacting with specific small molecule ligands. Such interactions can lead to changes in protein structure which switch the protein to a metastable, functional state. These functional states are key to many cellular processes that include: removal of toxins, response to temperature changes, and transport of nutrients. In many proteins, the dominant native structure can be measured by traditional experimental techniques such as NMR or crystallography. However, it is often difficult to capture the structure of the metastable, functional state. In addition, an unmet need in biophysics is to elucidate the entire conformational transition pathway for a given protein switch. This transition pathway includes all intermediate states from the initial to final state and includes metastable, functional state of interest.

One promising pathway is to combine EPR based distance measurements with MD simulations. For this purpose, we have worked with Junmei Wang (Pitt) to develop force fields for the Cu(II) labels that are used for proteins and DNA.  However, while conventional MD can access some transient states of a protein along a conformational change pathway, standard MD methods are still unable to feasibly access all active conformations and transition pathways of a given protein due to the expensive cost of running such simulations and the long (s-ms) timescales of conformational change processes.

We are working with Lillian Chong’s group (Pitt) to develop a strategy to integrate EPR point-to-point distances with enhanced sampling MD strategies to generate high-resolution images of transient functional protein states at atomistic detail, and more importantly, to elucidate pathways of interconversion between these functional states. Such a strategy has recently provided a pathway for “watching” a ca. 1 sec induced conformational change in an enzyme (see movie) that is important for cellular defense. Weighted ensemble simulations generated unbiased pathways for the seconds-timescale transition between alternate states of the enzyme, leading to the generation of atomically detailed structures of the ligand-free state. Notably, this work provide a mechanistic understanding of protein function.  We observe negative cooperativity between the monomers of the dimeric protein, which involve the mutually exclusive docking of helix 9 in each monomer as a lid over the active site. We identify key interactions between residues that lead to this negative cooperativity.  

Collaborators: Junmei Wang, Lillian Chong