Unleashing Natural IL18 Activity Using an Anti-IL18BP Blocker Induces Potent Immune Stimulation and Antitumor Effects.

Recombinant cytokines have limited anticancer efficacy mostly due to a narrow therapeutic window and systemic adverse effects. IL18 is an inflammasome-induced proinflammatory cytokine, which enhances T- and NK-cell activity and stimulates IFNγ production. The activity of IL18 is naturally blocked by a high-affinity endogenous binding protein (IL18BP). IL18BP is induced in the tumor microenvironment (TME) in response to IFNγ upregulation in a negative feedback mechanism. In this study, we found that IL18 is upregulated in the TME compared with the periphery across multiple human tumors and most of it is bound to IL18BP. Bound IL18 levels were largely above the amount required for T-cell activation in vitro, implying that releasing IL18 in the TME could lead to potent T-cell activation. To restore the activity of endogenous IL18, we generated COM503, a high-affinity anti-IL18BP that blocks the IL18BP:IL18 interaction and displaces precomplexed IL18, thereby enhancing T- and NK-cell activation. In vivo, administration of a surrogate anti-IL18BP, either alone or in combination with anti-PD-L1, resulted in significant tumor growth inhibition and increased survival across multiple mouse tumor models. Moreover, the anti-IL18BP induced pronounced TME-localized immune modulation including an increase in polyfunctional nonexhausted T- and NK-cell numbers and activation. In contrast, no increase in inflammatory cytokines and lymphocyte numbers or activation state was observed in serum and spleen. Taken together, blocking IL18BP using an Ab is a promising approach to harness cytokine biology for the treatment of cancer.

Computational Design of Epitope-Specific Functional Antibodies.

The ultimate goal of protein design is to introduce new biological activity. We propose a computational approach for designing functional antibodies by focusing on functional epitopes, integrating large-scale statistical analysis with multiple structural models. Machine learning is used to analyze these models and predict specific residue-residue contacts. We use this approach to design a functional antibody to counter the proinflammatory effect of the cytokine interleukin-17A (IL-17A). X-ray crystallography confirms that the designed antibody binds the targeted epitope and the interaction is mediated by the designed contacts. Cell-based assays confirm that the antibody is functional. Importantly, this approach does not rely on a high-quality 3D model of the designed complex or even a solved structure of the target. As demonstrated here, this approach can be used to design biologically active antibodies, removing some of the main hurdles in antibody design and in drug discovery.

De-novo protein function prediction using DNA binding and RNA binding proteins as a test case.

Of the currently identified protein sequences, 99.6% have never been observed in the laboratory as proteins and their molecular function has not been established experimentally. Predicting the function of such proteins relies mostly on annotated homologs. However, this has resulted in some erroneous annotations, and many proteins have no annotated homologs. Here we propose a de-novo function prediction approach based on identifying biophysical features that underlie function. Using our approach, we discover DNA and RNA binding proteins that cannot be identified based on homology and validate these predictions experimentally. For example, FGF14, which belongs to a family of secreted growth factors was predicted to bind DNA. We verify this experimentally and also show that FGF14 is localized to the nucleus. Mutating the predicted binding site on FGF14 abrogated DNA binding. These results demonstrate the feasibility of automated de-novo function prediction based on identifying function-related biophysical features.

Computational identification of antigen-binding antibody fragments.

Determining which parts of the Ab are essential for Ag recognition and binding is crucial for understanding B cell-mediated immunity. Identification of fragments of Abs that maintain specificity to the Ag will also allow for the development of improved Ab-based therapy and diagnostics. In this article, we show that structural analysis of Ab-Ag complexes reveals which fragments of the Ab may bind the Ag on their own. In particular, it is possible to predict whether a given CDR is likely to bind the Ag as a peptide by analyzing the energetic contribution of each CDR to Ag binding and by assessing to what extent the interaction between that CDR and the Ag depends on other CDRs. To demonstrate this, we analyzed five Ab-Ag complexes and predicted for each of them which of the CDRs may bind the Ag on its own as a peptide. We then show that these predictions are in agreement with our experimental analysis and with previously published experimental results. These findings promote our understanding of the modular nature of Ab-Ag interactions and lay the foundation for the rational design of active CDR-derived peptides.

The interplay between components of the mitochondrial protein translocation motor studied using purified components.

The final step of protein translocation across the mitochondrial inner membrane is mediated by a translocation motor composed of 1) the matrix-localized, ATP-hydrolyzing, 70-kDa heat shock protein mHsp70; 2) its anchor to the import channel, Tim44; 3) the nucleotide exchange factor Mge1; and 4) a J-domain-containing complex of co-chaperones, Tim14/Pam18-Tim16/Pam16. Despite its essential role in the biogenesis of mitochondria, the mechanism by which the translocation motor functions is still largely unknown. The goal of this work was to carry out a structure-function analysis of the mitochondrial translocation motor utilizing purified components, with an emphasis on the formation of the Tim44-mHsp70 complex. To this end, we purified Tim44 and monitored its interaction with other components of the motor using cross-linking with bifunctional reagents. The effects of nucleotides, the J-domain-containing components, and the P5 peptide (CALLSAPRR, representing part of the mitochondrial targeting signal of aspartate aminotransferase) on the formation of the translocation motor were examined. Our results show that only the peptide and nucleotides, but not J-domain-containing proteins, affect the Tim44-mHsp70 interaction. Additionally, binding of Tim44 to mHsp70 prevents the formation of a complex between the latter and Tim14/Pam18-Tim16/Pam16. Thus, mutually exclusive interactions between various components of the motor with mHsp70 regulate its functional cycle. The results are discussed in light of known models for the function of the mitochondrial translocation motor.

The Pam18/Tim14-Pam16/Tim16 complex of the mitochondrial translocation motor: the formation of a stable complex from marginally stable proteins.

The vast majority of mitochondrial proteins are imported from the cytosol. For matrix-localized proteins, the final step of translocation across the inner membrane is mediated by the mitochondrial translocation motor, of which mhsp70 is a key component. The ATP-dependent function of mhsp70 is regulated by a complex, composed of a J-protein (called Pam18 or Tim14) and a J-like protein (called Pam16 or Tim16), and the nucleotide exchange factor Mge1. In this study, we investigated the structural properties of a recombinant purified Pam18/Tim14-Pam16/Tim16 complex using cross-linking with the bifunctional reagent DSS and CD-spectroscopy. The results of the study show that both Pam18/Tim14 and Pam16/Tim16 are thermally unstable proteins that unfold at very low temperatures (T(m) values of 16.5 degrees C and 29 degrees C, respectively). Upon mixing the proteins in vitro, or when both proteins are co-overexpressed in bacteria, Pam18/Tim14 and Pam16/Tim16 form a heterodimer that is thermally more stable than the individual proteins (T(m) = 41 degrees C). Analysis of the properties of the complex in GdnHCl shows that dissociation of the heterodimer is the limiting step in achieving full denaturation.