Spontaneous Unfolding and Refolding of FNIII Domains Assayed by Thiol Exchange

Fibronectin (FN) is a large extracellular matrix (ECM) protein that is made up of

type I (FNI), type II (FNII), & type III (FNIII) domains. It assembles into an insoluble

supra-­‐‑molecular structure: the fibrillar FN matrix. FN fibrillogenesis is a cell‐‑mediated process, which is initiated when FN binds to integrins on the cell surface. The FN matrix plays an important role in cell migration, proliferation, signaling & adhesion. Despite decades of research, the FN matrix is one of the least understood supra-­‐‑molecular protein assemblies. There have been several attempts to elucidate the exact mechanism of matrix assembly resulting in significant progress in the field but it is still unclear as to what are FN-­‐‑FN interactions, the nature of these interactions and the domains of FN that

are in contact with each other. FN matrix fibrils are elastic in nature. Two models have been proposed to explain the elasticity of the fibrils. The first model: the ‘domain unfolding’ model postulates that the unraveling of FNIII domains under tension explains fibril elasticity.

The second model relies on the conformational change of FN from compact to extended to explain fibril elasticity. FN contain 15 FNIII domains, each a 7-­‐‑strand beta sandwich. Earlier work from our lab used the technique of labeling a buried Cys to study the ‘domain unfolding’ model. They used mutant FNs containing a buried Cys in a single FNIII domain and found that 6 of the 15 FNIII domains label in matrix fibrils. Domain unfolding due to tension, matrix associated conformational changes or spontaneous folding and unfolding are all possible explanation for labeling of the buried Cys. The present study also uses the technique of labeling a buried Cys to address whether it is spontaneous folding and unfolding that labels FNIII domains in cell culture. We used thiol reactive DTNB to measure the kinetics of labeling of buried Cys in eleven FN III domains over a wide range of urea concentrations (0-­‐‑9M). The kinetics data were globally fit using Mathematica. The results are equivalent to those of H-­‐‑D exchange, and

provide a comprehensive analysis of stability and unfolding/folding kinetics of each

domain. For two of the six domains spontaneous folding and unfolding is possibly the reason for labeling in cell culture. For the rest of the four domains it is probably matrix associated conformational changes or tension induced unfolding.

A long-­‐‑standing debate in the protein-­‐‑folding field is whether unfolding rate

constants or folding rate constants correlate to the stability of a protein. FNIII domains all have the same ß sandwich structure but very different stabilities and amino acid sequences. Our study analyzed the kinetics of unfolding and folding and stabilities of eleven FNIII domains and our results show that folding rate constants for FNIII domains are relatively similar and the unfolding rates vary widely and correlate to stability. FN forms a fibrillar matrix and the FN-­‐‑FN interactions during matrix fibril formation are not known. FNI 1-­‐‑9 or the N-­‐‑ terminal region is indispensible for matrix formation and its major binding partner has been shown to be FNIII 2. Earlier work from our lab, using FRET analysis showed that the interaction of FNI 1-­‐‑9 with a destabilized FNIII 2 (missing the G strand, FNIII 2ΔG) reduces the FRET efficiency. This efficiency is restored in the presence of FUD (bacterial adhesion from S. pyogenes) that has been known to interact with FNI 1-­‐‑9 via a tandem ß zipper. In the present study we

use FRET analysis and a series of deletion mutants of FNIII 2ΔG to study the shortest fragment of FNIII 2ΔG that is required to bind FNI 1-­‐‑9. Our results presented here are qualitative and show that FNIII 2ΔC’EFG is the shortest fragment required to bind FNI 1-­‐‑9. Deletion of one more strand abolishes the interaction with FNI 1-­‐‑9.

Determination of Biomolecular Interdomain Motions using Nuclear Magnetic Resonance

Biological macromolecules can rearrange interdomain orientations when binding to various partners. Interdomain dynamics serve as a molecular mechanism to guide the transitions between orientations. However, our understanding of interdomain dynamics is limited because a useful description of interdomain motions requires an estimate of the probabilities of interdomain conformations, increasing complexity of the problem.

Staphylococcal protein A (SpA) has five tandem protein-binding domains and four interdomain linkers. The domains enable Staphylococcus aureus to evade the host immune system by binding to multiple host proteins including antibodies. Here, I present a study of the interdomain motions of two adjacent domains in SpA. NMR spin relaxation experiments identified a 6-residue flexible interdomain linker and interdomain motions. To quantify the anisotropy of the distribution of interdomain orientations, we measured residual dipolar couplings (RDCs) from the two domains with multiple alignments. The N-terminal domain was directly aligned by a lanthanide ion and not influenced by interdomain motions, so it acted as a reference frame to achieve motional decoupling. We also applied {\it de novo} methods to extract spatial dynamic information from RDCs and represent interdomain motions as a continuous distribution on the 3D rotational space. Significant anisotropy was observed in the distribution, indicating the motion populates some interdomain orientations more than others. Statistical thermodynamic analysis of the observed orientational distribution suggests that it is among the energetically most favorable orientational distributions for binding to antibodies. Thus, the affinity is enhanced by a pre-posed distribution of interdomain orientations while maintaining the flexibility required for function.

The protocol described above can be applied to other biological systems in general. Protein molecule calmodulin and RNA molecule trans-activation response element (TAR) also have intensive interdomain motions with relative small intradomain dynamics. Their interdomain motions were studied using our method based on published RDC data. Our results were consistent with literature results in general. The differences could be due to previous studies' use of physical models, which contain assumptions about potential energy and thus introduced non-experimental information into the interpretations.

Structural and Functional Analysis of the Caspase –dependent and –independent Domains of the X-linked Inhibitor of Apoptosis Protein in Inflammatory Breast Cancer Tumor Biology

Inflammatory breast cancer (IBC) is an extremely rare but highly aggressive form of breast cancer characterized by the rapid development of therapeutic resistance leading to particularly poor survival. Our previous work focused on the elucidation of factors that mediate therapeutic resistance in IBC and identified increased expression of the anti-apoptotic protein, X-linked inhibitor of apoptosis protein (XIAP), to correlate with the development of resistance to chemotherapeutics. Although XIAP is classically thought of as an inhibitor of caspase activation, multiple studies have revealed that XIAP can also function as a signaling intermediate in numerous pathways. Based on preliminary evidence revealing high expression of XIAP in pre-treatment IBC cells rather than only subsequent to the development of resistance, we hypothesized that XIAP could play an important signaling role in IBC pathobiology outside of its heavily published apoptotic inhibition function. Further, based on our discovery of inhibition of chemotherapeutic efficacy, we postulated that XIAP overexpression might also play a role in resistance to other forms of therapy, such as immunotherapy. Finally, we posited that targeting of specific redox adaptive mechanisms, which are observed to be a significant barrier to successful treatment of IBC, could overcome therapeutic resistance and enhance the efficacy of chemo-, radio-, and immuno- therapies. To address these hypotheses our objectives were: 1. to determine a role for XIAP in IBC pathobiology and to elucidate the upstream regulators and downstream effectors of XIAP; 2. to evaluate and describe a role for XIAP in the inhibition of immunotherapy; and 3. to develop and characterize novel redox modulatory strategies that target identified mechanisms to prevent or reverse therapeutic resistance.

Using various genomic and proteomic approaches, combined with analysis of cellular viability, proliferation, and growth parameters both in vitro and in vivo, we demonstrate that XIAP plays a central role in both IBC pathobiology in a manner mostly independent of its role as a caspase-binding protein. Modulation of XIAP expression in cells derived from patients prior to any therapeutic intervention significantly altered key aspects IBC biology including, but not limited to: IBC-specific gene signatures; the tumorigenic capacity of tumor cells; and the metastatic phenotype of IBC, all of which are revealed to functionally hinge on XIAP-mediated NFκB activation, a robust molecular determinant of IBC. Identification of the mechanism of XIAP-mediated NFκB activation led to the characterization of novel peptide-based antagonist which was further used to identify that increased NFκB activation was responsible for redox adaptation previously observed in therapy-resistant IBC cells. Lastly, we describe the targeting of this XIAP-NFκB-ROS axis using a novel redox modulatory strategy both in vitro and in vivo. Together, the data presented here characterize a novel and crucial role for XIAP both in therapeutic resistance and the pathobiology of IBC; these results confirm our previous work in acquired therapeutic resistance and establish the feasibility of targeting XIAP-NFκB and the redox adaptive phenotype of IBC as a means to enhance survival of patients.

Using Helix-coil Models to Study Protein Unfolded States

An abstract of a thesis devoted to using helix-coil models to study unfolded states.\\

Research on polypeptide unfolded states has received much more attention in the last decade or so than it has in the past. Unfolded states are thought to be implicated in various

misfolding diseases and likely play crucial roles in protein folding equilibria and folding rates. Structural characterization of unfolded states has proven to be

much more difficult than the now well established practice of determining the structures of folded proteins. This is largely because many core assumptions underlying

folded structure determination methods are invalid for unfolded states. This has led to a dearth of knowledge concerning the nature of unfolded state conformational

distributions. While many aspects of unfolded state structure are not well known, there does exist a significant body of work stretching back half a century that

has been focused on structural characterization of marginally stable polypeptide systems. This body of work represents an extensive collection of experimental

data and biophysical models associated with describing helix-coil equilibria in polypeptide systems. Much of the work on unfolded states in the last decade has not been devoted

specifically to the improvement of our understanding of helix-coil equilibria, which arguably is the most well characterized of the various conformational equilibria

that likely contribute to unfolded state conformational distributions. This thesis seeks to provide a deeper investigation of helix-coil equilibria using modern

statistical data analysis and biophysical modeling techniques. The studies contained within seek to provide deeper insights and new perspectives on what we presumably

know very well about protein unfolded states. \\

Chapter 1 gives an overview of recent and historical work on studying protein unfolded states. The study of helix-coil equilibria is placed in the context

of the general field of unfolded state research and the basics of helix-coil models are introduced.\\

Chapter 2 introduces the newest incarnation of a sophisticated helix-coil model. State of the art modern statistical techniques are employed to estimate the energies

of various physical interactions that serve to influence helix-coil equilibria. A new Bayesian model selection approach is utilized to test many long-standing

hypotheses concerning the physical nature of the helix-coil transition. Some assumptions made in previous models are shown to be invalid and the new model

exhibits greatly improved predictive performance relative to its predecessor. \\

Chapter 3 introduces a new statistical model that can be used to interpret amide exchange measurements. As amide exchange can serve as a probe for residue-specific

properties of helix-coil ensembles, the new model provides a novel and robust method to use these types of measurements to characterize helix-coil ensembles experimentally

and test the position-specific predictions of helix-coil models. The statistical model is shown to perform exceedingly better than the most commonly used

method for interpreting amide exchange data. The estimates of the model obtained from amide exchange measurements on an example helical peptide

also show a remarkable consistency with the predictions of the helix-coil model. \\

Chapter 4 involves a study of helix-coil ensembles through the enumeration of helix-coil configurations. Aside from providing new insights into helix-coil ensembles,

this chapter also introduces a new method by which helix-coil models can be extended to calculate new types of observables. Future work on this approach could potentially

allow helix-coil models to move into use domains that were previously inaccessible and reserved for other types of unfolded state models that were introduced in chapter 1.

On Provable Algorithms for Determination of Continuous Protein Interdomain Motions from Residual Dipolar Couplings

Dynamics of biomolecules over various spatial and time scales are essential for biological functions such as molecular recognition, catalysis and signaling. However, reconstruction of biomolecular dynamics from experimental observables requires the determination of a conformational probability distribution. Unfortunately, these distributions cannot be fully constrained by the limited information from experiments, making the problem an ill-posed one in the terminology of Hadamard. The ill-posed nature of the problem comes from the fact that it has no unique solution. Multiple or even an infinite number of solutions may exist. To avoid the ill-posed nature, the problem needs to be regularized by making assumptions, which inevitably introduce biases into the result.

Here, I present two continuous probability density function approaches to solve an important inverse problem called the RDC trigonometric moment problem. By focusing on interdomain orientations we reduced the problem to determination of a distribution on the 3D rotational space from residual dipolar couplings (RDCs). We derived an analytical equation that relates alignment tensors of adjacent domains, which serves as the foundation of the two methods. In the first approach, the ill-posed nature of the problem was avoided by introducing a continuous distribution model, which enjoys a smoothness assumption. To find the optimal solution for the distribution, we also designed an efficient branch-and-bound algorithm that exploits the mathematical structure of the analytical solutions. The algorithm is guaranteed to find the distribution that best satisfies the analytical relationship. We observed good performance of the method when tested under various levels of experimental noise and when applied to two protein systems. The second approach avoids the use of any model by employing maximum entropy principles. This 'model-free' approach delivers the least biased result which presents our state of knowledge. In this approach, the solution is an exponential function of Lagrange multipliers. To determine the multipliers, a convex objective function is constructed. Consequently, the maximum entropy solution can be found easily by gradient descent methods. Both algorithms can be applied to biomolecular RDC data in general, including data from RNA and DNA molecules.