José A. Caro

Research Assistant Professor | Biochemistry & Biophysics

protein, biophysics, dynamics, structure, function, cavities

Office:NMR / 313A
Email:caro@tamu.edu
Phone:979-845-5631

Our lab is fascinated by the challenge of using physical formalisms to describe the heterogeneous systems of biology. The structures we know from crystallography and electron-microscopy give us a great view of what proteins look like. Adding motion to this picture is crucial to understand how they function. Our lab studies protein dynamics by nuclear magnetic resonance (NMR) spectroscopy to learn about transitions between the many forms proteins adopt. By looking at a large set of proteins and their ligand-bound complexes, we have established a direct connection between motions we measure by NMR and the conformational entropy of binding. Lessons from this effort have allowed us to re-engineer proteins to tune motions and the underlying conformational entropy. Because entropy is one of the components determining binding affinity, our approach has become a novel avenue for affinity modulation based around targetable entropic hotspots. We are looking to implement this strategy to tune affinity and function in systems of high biomedical relevance.

Entropy modulation to tune protein function

Life depends on proteins recognizing the correct substrate to perform crucial functions such as catalysis and signaling. The physical determinants of the affinity for their ligands have been subject to intense investigation. In contrast, structural biology has illuminated the enthalpic contributions from specific interactions, such as charge-charge interactions. Our understanding of entropic contributions has lagged, such as the role of protein motions and how they change upon binding. The main reason is the experimental difficulties in quantitating the many, but minorly, populated conformations of a protein. Using NMR, we were able to establish how protein dynamics can be used to extract the conformational entropy of a protein as it binds a ligand. The experimental data guides our effort to re-engineer the conformational landscape of proteins to modulate ligands’ affinity. Some of the systems we are studying include the interleukin receptors involved in the inflammatory response, antibodies, and other protein-based pharmaceuticals.

J. A. Caro, K. W. Harpole, V. Kasinath, J. Lim, J. Granja, K. G. Valentine, K. A. Sharp, A. J. Wand, Entropy in molecular recognition by proteins. Proc. Natl. Acad. Sci. USA 114, 6563–6568 (2017).

Structural determinants of protein dynamics

Protein motions under pressure.
Proteins are tightly packed but retain small amounts of empty space in their core. By increasing pressure, proteins compress and eliminate some of these cavities, but not all. Side chains appear to notice and change their dynamics depending on whether they have space to move in or not.

Our lab’s main interest is the structure-function relationship, meaning how the structure (or lack thereof) determines its function. It is useful to know how the coordinates of a 3D structure in a PDB deposition translate to how the protein behaves and what reactions it will catalyze to what partners it will bind. An enormous challenge for this process is imparting the motions proteins experience accurately. The protein dynamics we measure daily using NMR are highly informative but are still hard to rationalize using typical structural metrics such as amino acid type or secondary structure. It remains unclear what determines whether a side chain will be highly mobile or not. We have built the largest dataset to date of protein side-chain dynamics and are using the wealth of structural information in the PDB to ask a very intuitive question: do side chains need space to move? By carefully evaluating the volume of cavities in the interior of proteins, we are beginning to understand the structural determinants of protein dynamics and conformational plasticity. We combine this survey with high-pressure NMR to explore the volumetric properties of side-chain dynamics. Lessons from this effort will help extract valuable information buried in all systems in the PDB, including those of high biomedical relevance.