Justin A. Caravella

Design of next-generation protein therapeutics

Since the first protein therapeutics were approved two decades ago, the field has seen a transition from the development of naturally occurring proteins to design of molecules engineered for optimal target recognition, pharmacokinetics, biodistribution, and therapeutic function. Many modified antibodies and monovalent or multispecific antibody-like molecules with custom profiles are in different stages of drug development. In addition, several non-antibody protein scaffolds that interrogate a broad range of targets are being pursued. As protein engineering efforts have expanded and diversified, it has become increasingly important to understand the biophysical and biochemical properties of proteins and to translate this knowledge into design of optimized pharmaceutical agents.

Structure-Guided Design of Antibodies

Monoclonal antibodies capable of recognizing antigens with high affinity and specificity represent a well established class of biological agents. Since the development of hybridoma technology in 1975, advances in recombinant DNA technologies and computational and biophysical methods have allowed us to develop a better understanding of the relationships between antibody sequence, structure, and function. These advances enable us to manipulate antibody sequences with the goal of improving upon, or creating new biological or biophysical properties. In this review we will focus on recent successes in using structure-guided computational methods to design antibodies and antibody-like molecules with optimized affinity and specificity to antigen and for enhancing protein stability.

Dynamic Structural Changes Are Observed upon Collagen and Metal Ion Binding to the Integrin α1 I Domain

Background: Integrin α1 I domain undergoes conformational changes upon collagen binding. Results: Deuterium exchange was used to measure the effects of cations, collagen, or an antibody on the α1I solution structure. Conclusion: Full-length collagen and metal ions induce changes that differ in key aspects from previously proposed models for α1I activation. Significance: These studies support a new model for integrin I domain activation. We have applied hydrogen-deuterium exchange mass spectrometry, in conjunction with differential scanning calorimetry and protein stability analysis, to examine solution dynamics of the integrin α1 I domain induced by the binding of divalent cations, full-length type IV collagen, or a function-blocking monoclonal antibody. These studies revealed features of integrin activation and α1I-ligand complexes that were not detected by static crystallographic data. Mg2+ and Mn2+ stabilized α1I but differed in their effects on exchange rates in the αC helix. Ca2+ impacted α1I conformational dynamics without altering its gross thermal stability. Interaction with collagen affected the exchange rates in just one of three metal ion-dependent adhesion site (MIDAS) loops, suggesting that MIDAS loop 2 plays a primary role in mediating ligand binding. Collagen also induced changes consistent with increased unfolding in both the αC and allosteric C-terminal helices of α1I. The antibody AQC2, which binds to α1I in a ligand-mimetic manner, also reduced exchange in MIDAS loop 2 and increased exchange in αC, but it did not impact the C-terminal region. This is the first study to directly demonstrate the conformational changes induced upon binding of an integrin I domain to a full-length collagen ligand, and it demonstrates the utility of the deuterium exchange mass spectrometry method to study the solution dynamics of integrin/ligand and integrin/metal ion interactions. Based on the ligand and metal ion binding data, we propose a model for collagen-binding integrin activation that explains the differing abilities of Mg2+, Mn2+, and Ca2+ to activate I domain-containing integrins.

Discovery of biaryls as RORγ inverse agonists by using structure-based design.

RORγ plays a critical role in controlling a pro-inflammatory gene expression program in several lymphocyte lineages including T cells, γδ T cells, and innate lymphoid cells. RORγ-mediated inflammation has been linked to susceptibility to Crohns disease, arthritis, and psoriasis. Thus inverse agonists of RORγ have the potential of modulating inflammation. Our goal was to optimize two RORγ inverse agonists: T0901317 from literature and 1 that we obtained from internal screening. We used information from internal X-ray structures to design two libraries that led to a new biaryl series.

Highly covarying residues have a functional role in antibody constant domains

The ability to generate and design antibodies recognizing specific targets has revolutionized the pharmaceutical industry and medical imaging. Engineering antibody therapeutics in some cases requires modifying their constant domains to enable new and altered interactions. Engineering novel specificities into antibody constant domains has proved challenging due to the complexity of inter‐domain interactions. Covarying networks of residues that tend to cluster on the protein surface and near binding sites have been identified in some proteins. However, the underlying role these networks play in the protein resulting in their conservation remains unclear in most cases. Resolving their role is crucial, because residues in these networks are not viable design targets if their role is to maintain the fold of the protein. Conversely, these networks of residues are ideal candidates for manipulating specificity if they are primarily involved in binding, such as the myriad interdomain interactions maintained within antibodies. Here, we identify networks of evolutionarily‐related residues in C‐class antibody domains by evaluating covariation, a measure of propensity with which residue pairs vary dependently during evolution. We computationally test whether mutation of residues in these networks affects stability of the folded antibody domain, determining their viability as design candidates. We find that members of covarying networks cluster at domain‐domain interfaces, and that mutations to these residues are diverse and frequent during evolution, precluding their importance to domain stability. These results indicate that networks of covarying residues exist in antibody domains for functional reasons unrelated to thermodynamic stability, making them ideal targets for antibody design. Proteins 2013.

Metric to distinguish closely related domain families using sequence information.

Engineered antibodies are emerging as a promising class of therapeutic biomolecules, as well as having applications in medical research. Knowledge on conserved functional and structural regions within antibody domains is imperative in order to rationally design stable and specific antibodies. Of particular interest for the design of therapeutics are antibody variable and constant domains, which are responsible for antigen binding and immune response. These antibody domains are part of the larger immunoglobulin (Ig) V-class and C-class families, respectively. We find that, although both classes belong to the Ig-fold superfamily, the sets of conserved residue positions and identities differ between these classes. We exploit these evolutionary differences to derive a metric based on sequence positional entropy that distinguishes C-class from V-class sequences utilizing only sequence information. By distinguishing different domain families using sequence information alone, we enable the application of domain-specific design strategies without the need for secondary or tertiary structural information.