Targeted purification development enabled by computational biophysical modeling.

Chromatographic and non-chromatographic purification of biopharmaceuticals depend on the interactions between protein molecules and a solid-liquid interface. These interactions are dominated by the protein-surface properties, which are a function of protein sequence, structure, and dynamics. In addition, protein-surface properties are critical for in vivo recognition and activation, thus, purification strategies should strive to preserve structural integrity and retain desired pharmacological efficacy. Other factors such as surface diffusion, pore diffusion, and film mass transfer can impact chromatographic separation and resin design. The key factors that impact non-chromatographic separations (e.g., solubility, ligand affinity, charges and hydrophobic clusters, and molecular dynamics) are readily amenable to computational modeling and can enhance the understanding of protein chromatographic. Previously published studies have used computational methods such as quantitative structure-activity relationship (QSAR) or quantitative structure-property relationship (QSPR) to identify and rank order affinity ligands based on their potential to effectively bind and separate a desired biopharmaceutical from host cell protein (HCP) and other impurities. The challenge in the application of such an approach is to discern key yet subtle differences in ligands and proteins that influence biologics purification. Using a relatively small molecular weight protein (insulin), this research overcame limitations of previous modeling efforts by utilizing atomic level detail for the modeling of protein-ligand interactions, effectively leveraging and extending previous research on drug target discovery. These principles were applied to the purification of different commercially available insulin variants. The ability of these computational models to correlate directionally with empirical observation is demonstrated for several insulin systems over a range of purification challenges including resolution of subtle product variants (amino acid misincorporations). Broader application of this methodology in bioprocess development may enhance and speed the development of a robust purification platform.

Loss of T cell antigen recognition arising from changes in peptide and major histocompatibility complex protein flexibility: implications for vaccine design.

Modification of the primary anchor positions of antigenic peptides to improve binding to major histocompatibility complex (MHC) proteins is a commonly used strategy for engineering peptide-based vaccine candidates. However, such peptide modifications do not always improve antigenicity, complicating efforts to design effective vaccines for cancer and infectious disease. Here we investigated the MART-1(27-35) tumor antigen, for which anchor modification (replacement of the position two alanine with leucine) dramatically reduces or ablates antigenicity with a wide range of T cell clones despite significantly improving peptide binding to MHC. We found that anchor modification in the MART-1(27-35) antigen enhances the flexibility of both the peptide and the HLA-A*0201 molecule. Although the resulting entropic effects contribute to the improved binding of the peptide to MHC, they also negatively impact T cell receptor binding to the peptide·MHC complex. These results help explain how the "anchor-fixing" strategy fails to improve antigenicity in this case, and more generally, may be relevant for understanding the high specificity characteristic of the T cell repertoire. In addition to impacting vaccine design, modulation of peptide and MHC flexibility through changes to antigenic peptides may present an evolutionary strategy for the escape of pathogens from immune destruction.

Identification and engineering of human variable regions that allow expression of stable single-chain T cell receptors.

Single-chain antibody fragments (scFv), consisting of two linked variable regions (V(H) and V(L)), are a versatile format for engineering and as potential antigen-specific therapeutics. Although the analogous format for T cell receptors (TCRs), consisting of two linked V regions (Vα and Vß; referred to here as scTv), could provide similar opportunities, all wild-type scTv proteins examined to date are unstable. This obstacle has prevented scTv fragments from being widely used for engineering or therapeutics. To further explore whether some stable human scTv fragments could be expressed, we used a yeast system in which display of properly folded domains correlates with ability to express the folded scTv in soluble form. We discovered that, unexpectedly, scTv fragments that contained the human Vα2 region (IMGT: TRAV12 family) were displayed and properly associated with different Vß regions. Furthermore, a single polymorphic residue (Ser(α49)) in the framework region conferred additional thermal stability. These stabilized Vα2-containing scTv fragments could be expressed at high levels in Escherichia coli, and used to stain target cells that expressed the specific pep-HLA-A2 complexes. Thus, the scTv fragments can serve as a platform for engineering TCRs with diverse specificities, and possibly for therapeutic or diagnostic applications.

A general and efficient approach for NMR studies of peptide dynamics in class I MHC peptide binding grooves.

T-Cell receptor recognition of peptides bound by major histocompatibility complex (MHC) proteins initiates a cellular immune response. Dynamics of peptides within MHC binding grooves can influence TCR recognition, yet NMR studies which could address this rigorously have been hindered by the expense of isotopically labeled peptides and the large size of peptide-MHC complexes. Here we describe a methodology for characterizing peptide dynamics within MHC binding grooves via NMR, using a biosynthetic approach for producing labeled peptide. With the Tax(11-19) peptide bound to the human class I MHC HLA-A*0201, we demonstrate that peptide generated in this manner can be well characterized in MHC binding grooves by NMR, providing opportunities to more precisely study the role of peptide dynamics in TCR recognition. Demonstrating the utility of such studies, the data with the Tax(11-19) peptide indicate the presence of slow conformational exchange in the peptide, supporting an "induced-fit" style TCR binding mechanism.

Thermodynamics of T-cell receptor-peptide/MHC interactions: progress and opportunities.

alphabeta T-cell receptors (TCRs) recognize peptide antigens presented by class I or class II major histocompatibility complex molecules (pMHC). Here we review the use of thermodynamic measurements in the study of TCR-pMHC interactions, with attention to the diversity in binding thermodynamics and how this is related to the variation in TCR-pMHC interfaces. We show that there is no enthalpic or entropic signature for TCR binding; rather, enthalpy and entropy changes vary in a compensatory manner that reflects a narrow free energy window for the interactions that have been characterized. Binding enthalpy and entropy changes do not correlate with structural features such as buried surface area or the number of hydrogen bonds within TCR-pMHC interfaces, possibly reflecting the myriad of contributors to binding thermodynamics, but likely also reflecting a reliance on van't Hoff over calorimetric measurements and the unaccounted influence of equilibria linked to binding. TCR-pMHC binding heat capacity changes likewise vary considerably. In some cases, the heat capacity changes are consistent with conformational differences between bound and free receptors, but there is little data indicating these conformational differences represent the need to organize disordered CDR loops. In this regard, we discuss how thermodynamics may provide additional insight into conformational changes occurring upon TCR binding. Finally, we highlight opportunities for the further use of thermodynamic measurements in the study of TCR-pMHC interactions, not only for understanding TCR binding in general, but also for understanding specifics of individual interactions and the engineering of TCRs with desired molecular recognition properties.

Structures of MART-126/27-35 Peptide/HLA-A2 complexes reveal a remarkable disconnect between antigen structural homology and T cell recognition.

Small structural changes in peptides presented by major histocompatibility complex (MHC) molecules often result in large changes in immunogenicity, supporting the notion that T cell receptors are exquisitely sensitive to antigen structure. Yet there are striking examples of TCR recognition of structurally dissimilar ligands. The resulting unpredictability of how T cells will respond to different or modified antigens impacts both our understanding of the physical bases for TCR specificity as well as efforts to engineer peptides for immunomodulation. In cancer immunotherapy, epitopes and variants derived from the MART-1/Melan-A protein are widely used as clinical vaccines. Two overlapping epitopes spanning amino acid residues 26 through 35 are of particular interest: numerous clinical studies have been performed using variants of the MART-1 26-35 decamer, although only the 27-35 nonamer has been found on the surface of targeted melanoma cells. Here, we show that the 26-35 and 27-35 peptides adopt strikingly different conformations when bound to HLA-A2. Nevertheless, clonally distinct MART-1(26/27-35)-reactive T cells show broad cross-reactivity towards these ligands. Simultaneously, however, many of the cross-reactive T cells remain unable to recognize anchor-modified variants with very subtle structural differences. These dichotomous observations challenge our thinking about how structural information on unligated peptide/MHC complexes should be best used when addressing questions of TCR specificity. Our findings also indicate that caution is warranted in the design of immunotherapeutics based on the MART-1 26/27-35 epitopes, as neither cross-reactivity nor selectivity is predictable based on the analysis of the structures alone.

T cell receptor binding transition states and recognition of peptide/MHC.

T cell receptor recognition of peptide/MHC has been described as proceeding through a "two-step" process in which the TCR first contacts the MHC molecule prior to formation of the binding transition state using the germline-encoded CDR1 and CDR2 loops. The receptor then contacts the peptide using the hypervariable CDR3 loops as the transition state decays to the bound state. The model subdivides TCR binding into peptide-independent and peptide-dependent steps, demarcated at the binding transition state. Investigating the two-step model, here we show that two TCRs that recognize the same peptide/MHC bury very similar amounts of solvent-accessible surface area in their transition states. However, 1300-1500 A2 of surface area is buried in each, a significant amount suggestive of participation of peptide and associated CDR3 surface. Consistent with this interpretation, analysis of peptide and TCR variants indicates that stabilizing contacts to the peptide are formed within both transition states. These data are incompatible with the original two-step model, as are transition state models built using the principle of minimal frustration commonly employed in the investigation of protein folding and binding transition states. These findings will be useful in further explorations of the nature of TCR binding transition states, as well as ongoing efforts to understand the mechanisms by which T cell receptors recognize the composite peptide/MHC surface.