Jaafar N. Haidar

Structure-Based Design of a T Cell Receptor Leads to Nearly 100-Fold Improvement in Binding Affinity for pepMHC

T‐cell receptors (TCRs) are proteins that recognize peptides from foreign proteins bound to the major histocompatibility complex (MHC) on the surface of an antigen‐presenting cell. This interaction enables the T cells to initiate a cell‐mediated immune response to terminate cells displaying the foreign peptide on their MHC. Naturally occurring TCRs have high specificity but low affinity toward the peptide‐MHC (pepMHC) complex. This prevents the usage of solubilized TCRs for diagnosis and treatment of viral infections or cancers. Efforts to enhance the binding affinity of several TCRs have been reported in recent years, through randomized libraries and in vitro selection. However, there have been no reported efforts to enhance the affinity via structure‐based design, which allows more control and understanding of the mechanism of improvement. Here, we have applied structure‐based design to a human TCR to improve its pepMHC binding. Our design method evolved based on iterative steps of prediction, testing, and generating more predictions based on the new data. The final design function, named ZAFFI, has a correlation of 0.77 and average error of 0.35 kcal/mol with the binding free energies of 26 point mutations for this system that we measured by surface plasmon resonance (SPR). Applying the filter that we developed to remove nonbinding predictions, this correlation increases to 0.85, and the average error decreases to 0.3 kcal/mol. Using this algorithm, we predicted and tested several point mutations that improved binding, with one giving over sixfold binding improvement. Four of the point mutations that improved binding were then combined to give a mutant TCR that binds the pepMHC 99 times more strongly than the wild‐type TCR. Proteins 2009.

A universal combinatorial design of antibody framework to graft distinct CDR sequences: A bioinformatics approach

Antibody (Ab) humanization is crucial to generate clinically relevant biologics from hybridoma‐derived monoclonal antibodies (mAbs). In this study, we integrated antibody structural information from the Protein Data Bank with known back‐to‐mouse mutational data to build a universal consensus of framework positions (10 heavy and 7 light) critical for the preservation of the functional conformation of the Complimentarity Determining Region of antibodies. On the basis of FR consensus, we describe here a universal combinatorial library suitable for humanizing exogenous antibodies by CDR‐grafting. The six CDRs of the murine anti‐human EGFR Fab M225 were grafted onto a distinct (low FR sequence similarity to M225) human FR sequence that incorporates at the 17 FR consensus positions the permutations of the naturally observed amino acid diversities. Ten clones were selected from the combinatorial library expressing phage‐displayed humanized M225 Fabs. Surprisingly, 2 of the 10 clones were found to bind EGFR with stronger affinity than M225. Cell‐based assays demonstrated that the 10 selected clones retained epitope specificity by blocking EGFR phosphorylation and thus hindering cellular proliferation. Our results suggest that there is a universal and structurally rigid near‐CDR set of FR positions that cooperatively support the binding conformation of CDRs. Proteins 2011.

Backbone flexibility of CDR3 and immune recognition of antigens

Conformational entropy is an important component of protein-protein interactions; however, there is no reliable method for computing this parameter. We have developed a statistical measure of residual backbone entropy in folded proteins by using the ϕ-ψ distributions of the 20 amino acids in common secondary structures. The backbone entropy patterns of amino acids within helix, sheet or coil form clusters that recapitulate the branching and hydrogen bonding properties of the side chains in the secondary structure type. The same types of residues in coil and sheet have identical backbone entropies, while helix residues have much smaller conformational entropies. We estimated the backbone entropy change for immunoglobulin complementarity-determining regions (CDRs) from the crystal structures of 34 low-affinity T-cell receptors and 40 high-affinity Fabs as a result of the formation of protein complexes. Surprisingly, we discovered that the computed backbone entropy loss of only the CDR3, but not all CDRs, correlated significantly with the kinetic and affinity constants of the 74 selected complexes. Consequently, we propose a simple algorithm to introduce proline mutations that restrict the conformational flexibility of CDRs and enhance the kinetics and affinity of immunoglobulin interactions. Combining the proline mutations with rationally designed mutants from a previous study led to 2400-fold increase in the affinity of the A6 T-cell receptor for Tax-HLAA2. However, this mutational scheme failed to induce significant binding changes in the already-high-affinity C225-Fab/huEGFR interface. Our results will serve as a roadmap to formulate more effective target functions to design immune complexes with improved biological functions.

Combinations of affinity-enhancing mutations in a T cell receptor reveal highly nonadditive effects within and between complementarity determining regions and chains.

Understanding the energetic and structural response to multiple mutations in a protein-protein interface is a key aspect of rational protein design. Here we investigate the cooperativity of combinations of point mutations of a T cell receptor (TCR) that binds in vivo to HLA-A2 MHC and a viral peptide. The mutations were obtained from two sources: a structure-based design study on the TCR alpha chain (nine mutations) and an in vitro selection study on the TCR beta chain (four mutations). In addition to combining the highest-affinity variants from each chain, we tested other combinations of mutations within and among the chains, for a total of 23 TCR mutants that we measured for binding kinetics to the peptide and major histocompatibility complex. A wide range of binding affinities was observed, from 2- to 1000-fold binding improvement versus that of the wild type, with significant nonadditive effects observed within and between TCR chains. This included an amino acid-dependent cooperative interaction between CDR1 and CDR3 residues that are separated by more than 9 A in the wild-type complex. When analyzing the kinetics of the mutations, we found that the association rates were primarily responsible for the cooperativity, while the dissociation rates were responsible for the anticooperativity (less-than-additive energetics). On the basis of structural modeling of anticooperative mutants, we determined that side chain clash between proximal mutants likely led to nonadditive binding energies. These results highlight the complex nature of TCR association and binding and will be informative in future design efforts that combine multiple mutant residues.

Comparison of predicted extinction coefficients of monoclonal antibodies with experimental values as measured by the Edelhoch method.

Pace et al. (1995) [1] recommended an equation used to predict extinction coefficient of a protein. However, no antibody data was included in the development of this equation. The main objective of this study was to therefore investigate how the predicted value of the extinction coefficient is comparable to the experimentally determined extinction coefficient of antibodies measured by the Edelhoch method. We have measured the extinction coefficients (ɛ) of 13 IgG1 monoclonal antibodies (mAbs) in phosphate buffer at pH 7.2. The maximum variability in the experimentally measured extinction coefficient of a given mAb molecule was found to be about 2%. Experimentally determined extinction coefficients of all mAbs were found to be lower than the predicted value, with the maximum difference found to being 4.7%. The highest and lowest values of experimental extinction coefficient among the thirteen IgG1 monoclonal antibodies obtained were 230525.9M(-1)cm(-1) (i.e. 1.55(mg/ml)(-1)cm(-1)) and 191,411.6M(-1)cm(-1) (i.e. 1.29(mg/ml)(-1)cm(-1)). A difference of <3% (with respect to mean value) was observed between the experimental and predicted values of the extinction coefficient. A comprehensive analysis and interpretation of the comparison of the predicted and experimentally determined extinction coefficient by the Edelhoch method is discussed in terms of structural characterization and accessible surface area (ASA).

Molecular Basis for Necitumumab Inhibition of EGFR Variants Associated with Acquired Cetuximab Resistance

Acquired resistance to cetuximab, an antibody that targets the EGFR, impacts clinical benefit in head and neck, and colorectal cancers. One of the mechanisms of resistance to cetuximab is the acquisition of mutations that map to the cetuximab epitope on EGFR and prevent drug binding. We find that necitumumab, another FDA-approved EGFR antibody, can bind to EGFR that harbors the most common cetuximab-resistant substitution, S468R (or S492R, depending on the amino acid numbering system). We determined an X-ray crystal structure to 2.8 Å resolution of the necitumumab Fab bound to an S468R variant of EGFR domain III. The arginine is accommodated in a large, preexisting cavity in the necitumumab paratope. We predict that this paratope shape will be permissive to other epitope substitutions, and show that necitumumab binds to most cetuximab- and panitumumab-resistant EGFR variants. We find that a simple computational approach can predict with high success which EGFR epitope substitutions abrogate antibody binding. This computational method will be valuable to determine whether necitumumab will bind to EGFR as new epitope resistance variants are identified. This method could also be useful for rapid evaluation of the effect on binding of alterations in other antibody/antigen interfaces. Together, these data suggest that necitumumab may be active in patients who are resistant to cetuximab or panitumumab through EGFR epitope mutation. Furthermore, our analysis leads us to speculate that antibodies with large paratope cavities may be less susceptible to resistance due to mutations mapping to the antigen epitope. Mol Cancer Ther; 17(2); 521–31. ©2017 AACR.

Discovery and preclinical characterization of the antagonist anti-PD-L1 monoclonal antibody LY3300054

BackgroundModulation of the PD-1/PD-L1 axis through antagonist antibodies that block either receptor or ligand has been shown to reinvigorate the function of tumor-specific T cells and unleash potent anti-tumor immunity, leading to durable objective responses in a subset of patients across multiple tumor types.ResultsHere we describe the discovery and preclinical characterization of LY3300054, a fully human IgG1λ monoclonal antibody that binds to human PD-L1 with high affinity and inhibits interactions of PD-L1 with its two cognate receptors PD-1 and CD80. The functional activity of LY3300054 on primary human T cells is evaluated using a series of in vitro T cell functional assays and in vivo models using human-immune reconstituted mice. LY3300054 is shown to induce primary T cell activation in vitro, increase T cell activation in combination with anti-CTLA4 antibody, and to potently enhance anti-tumor alloreactivity in several xenograft mouse tumor models with reconstituted human immune cells. High-content molecular analysis of tumor and peripheral tissues from animals treated with LY3300054 reveals distinct adaptive immune activation signatures, and also previously not described modulation of innate immune pathways.ConclusionsLY3300054 is currently being evaluated in phase I clinical trials for oncology indications.

Correction to: Discovery and preclinical characterization of the antagonist anti-PD-L1 monoclonal antibody LY3300054

Unfortunately, after publication of this article [1], it was noticed that corrections to the legends of Figs.xa01 and 2 were not correctly incorporated. The correct legends can be seen below.