Research in the MacCallum lab explores problems in protein biophysics and structural biology using both experimental and computational approaches. Our focus is on problems where the right combination of experiment and computation can lead to progress.

Integrative Structural Biology

How can we determine the structures of biomolecules and their complexes when the traditional approaches of X-ray crystallography and solution NMR have not worked? Integrative structural biology combines powerful computational models with often sparse, ambiguous, and unreliable data to infer the structures of biomolecules.

This line of research develops and applies new combinations of experiment and computation for structure determination. Specific projects include:

• Automated structure determination from sparsely-labeled NMR experiments

• NMR structure determination using the paramagnetic relaxation enhancement effect in both solution and solid-states

• Using chemical cross-linking and solvent exposure mass spec experiments to infer the structure of proteins and complexes

• Predicting protein structures from sequence data

Biomolecular Recognition and Design

How does one molecule (e.g. a protein) recognize and bind tightly to another (e.g. protein or DNA)? These biomolecular recognition events are underly how information is relayed within the cell, but we lack quantitative physical models that can accurately predict affinity and specificity.

We approach this problem both by examining natural complexes and by designing new complexes that do not exist in nature.

By examining natural complexes, we aim to develop physical models that can explain how the sequence and structure affect binding affinity and specificity.

But the true test is to use what we've learned to design new non-natural interactions, which have a wide range of applications as new therapeutic molecules, biosensors and molecular diagnostics, and bio-nano materials.

Designing a Protein to Fit a Drug: Recognizing THC from Cannabis

Fatty acid binding proteins (FABP) function as fatty acid transporters and have been dubbed the “lipid chaperones” of the cell. This family of proteins have a conserved tertiary structure of beta barrel pocket for fatty acid incorporation with a flexible lid domain. The role of FABPs in eukaryotic cells is to traffic lipids between cellular compartments. This class of proteins have flexible binding pockets that can host a variety of nonpolar compounds.

Brain Fatty Acid Binding Protein (FABP7) regulates brain lipid homeostasis, hosting a variety of hydrophobic molecules including fatty acids like DHA, endocannabinoids and plant cannabinoids, such as Δ9-tetrahydrocannabinol (THC).

The protein binds these ligands with different affinities. We want to understand the mechanisms of these interactions so that we can tune the protein’s selectivity to bind cannabis drugs. Modified FABP7 will then be incorporated into a point-of-contact sensor.

Characterization of FABP7 with Fatty Acids

A challenge with this protein family is that several different binding affinities have been reported for FABP7 and the fatty acid ligands of docosahexaenoic acid (DHA), oleic acid (OA), and stearic acid (SA). Our long-term goal is to test FABP7 interaction with cannabinoids.

To resolve these differences with the literature, we compared binding affinities measured using several different methods including fluorescence displacement, fluorescence polarization, and microscale thermophoresis (MST).

The molecular details of these binding interactions are also being characterized with molecular dynamic simulation experiments and NMR.

With this understanding of what controls FABP7 interactions, we can then use these model interactions as controls to compare with binding studies that we will do of uncharacterized molecules.

In parallel to performing protein interaction studies, we have characterized the electro-oxidation reactions of THC and THC metabolites on carbon paper (Electrochimica Acta, 307, 351-359).