B7-H4Ig inhibits mouse and human T-cell function and treats EAE via IL-10/Treg-dependent mechanisms.

We evaluated the therapeutic efficacy and mechanisms of action of both mouse and human B7-H4 Immunoglobulin fusion proteins (mB7-H4Ig; hB7-H4Ig) in treating EAE. The present data show that mB7-H4Ig both directly and indirectly (via increasing Treg function) inhibited CD4⁺ T-cell proliferation and differentiation in both Th1- and Th17-cell promoting conditions while inducing production of IL-10. B7-H4Ig treatment effectively ameliorated progression of both relapsing (R-EAE) and chronic EAE correlating with decreased numbers of activated CD4⁺ T-cells within the CNS and spleen, and a concurrent increase in number and function of Tregs. The functional requirement for Treg activation in treating EAE was demonstrated by a loss of therapeutic efficacy of hB7-H4Ig in R-EAE following inactivation of Treg function either by anti-CD25 treatment or blockade of IL-10. Significant to the eventual translation of this treatment into clinical practice, hB7-H4Ig similarly inhibited the in vitro differentiation of naïve human CD4⁺ T-cells in both Th1- and Th17-promoting conditions, while promoting the production of IL-10. B7-H4Ig thus regulates pro-inflammatory T-cell responses by a unique dual mechanism of action and demonstrates significant promise as a therapeutic for autoimmune diseases, including MS.

Blockade of nonhormonal fibroblast growth factors by FP-1039 inhibits growth of multiple types of cancer.

The fibroblast growth factor (FGF) pathway promotes tumor growth and angiogenesis in many solid tumors. Although there has long been interest in FGF pathway inhibitors, development has been complicated: An effective FGF inhibitor must block the activity of multiple mitogenic FGF ligands but must spare the metabolic hormone FGFs (FGF-19, FGF-21, and FGF-23) to avoid unacceptable toxicity. To achieve these design requirements, we engineered a soluble FGF receptor 1 Fc fusion protein, FP-1039. FP-1039 binds tightly to all of the mitogenic FGF ligands, inhibits FGF-stimulated cell proliferation in vitro, blocks FGF- and vascular endothelial growth factor (VEGF)-induced angiogenesis in vivo, and inhibits in vivo growth of a broad range of tumor types. FP-1039 antitumor response is positively correlated with RNA levels of FGF2, FGF18, FGFR1c, FGFR3c, and ETV4; models with genetic aberrations in the FGF pathway, including FGFR1-amplified lung cancer and FGFR2-mutated endometrial cancer, are particularly sensitive to FP-1039-mediated tumor inhibition. FP-1039 does not appreciably bind the hormonal FGFs, because these ligands require a cell surface co-receptor, klotho or ß-klotho, for high-affinity binding and signaling. Serum calcium and phosphate levels, which are regulated by FGF-23, are not altered by administration of FP-1039. By selectively blocking nonhormonal FGFs, FP-1039 treatment confers antitumor efficacy without the toxicities associated with other FGF pathway inhibitors.

An improved pairwise decomposable finite-difference Poisson-Boltzmann method for computational protein design.

Our goal is to develop accurate electrostatic models that can be implemented in current computational protein design protocols. To this end, we improve upon a previously reported pairwise decomposable, finite difference Poisson-Boltzmann (FDPB) model for protein design (Marshall et al., Protein Sci 2005, 14, 1293). The improvement involves placing generic sidechains at positions with unknown amino acid identity and explicitly capturing two-body perturbations to the dielectric environment. We compare the original and improved FDPB methods to standard FDPB calculations in which the dielectric environment is completely determined by protein atoms. The generic sidechain approach yields a two to threefold increase in accuracy per residue or residue pair over the original pairwise FDPB implementation, with no additional computational cost. Distance dependent dielectric and solvent-exclusion models were also compared with standard FDPB energies. The accuracy of the new pairwise FDPB method is shown to be superior to these models, even after reparameterization of the solvent-exclusion model.

Simple electrostatic model improves designed protein sequences.

Electrostatic interactions are important for both protein stability and function, including binding and catalysis. As protein design moves into these areas, an accurate description of electrostatic energy becomes necessary. Here, we show that a simple distance-dependent Coulombic function parameterized by a comparison to Poisson-Boltzmann calculations is able to capture some of these electrostatic interactions. Specifically, all three helix N-capping interactions in the engrailed homeodomain fold are recovered using the newly parameterized model. The stability of this designed protein is similar to a protein forced by sequence restriction to have beneficial electrostatic interactions.

One- and two-body decomposable Poisson-Boltzmann methods for protein design calculations.

Successfully modeling electrostatic interactions is one of the key factors required for the computational design of proteins with desired physical, chemical, and biological properties. In this paper, we present formulations of the finite difference Poisson-Boltzmann (FDPB) model that are pairwise decomposable by side chain. These methods use reduced representations of the protein structure based on the backbone and one or two side chains in order to approximate the dielectric environment in and around the protein. For the desolvation of polar side chains, the two-body model has a 0.64 kcal/mol RMSD compared to FDPB calculations performed using the full representation of the protein structure. Screened Coulombic interaction energies between side chains are approximated with an RMSD of 0.13 kcal/mol. The methods presented here are compatible with the computational demands of protein design calculations and produce energies that are very similar to the results of traditional FDPB calculations.

Minimizing the immunogenicity of protein therapeutics.

As is cautioned in many package inserts, 'with all therapeutic proteins, there is a potential for immunogenicity'. Immunogenicity problems in humans, which currently can be detected only in clinical trials or after product launch, pose a significant barrier to the development and acceptance of protein drugs. Recent and ongoing research, presented in this review, seeks to address the challenge of protein therapeutic immunogenicity by elucidating the mechanisms underlying immune recognition of protein therapeutics, establishing preclinical methods for assessing immunogenicity and developing strategies for minimizing immune responses.

Designing proteins for therapeutic applications.

Protein design is becoming an increasingly useful tool for optimizing protein drugs and creating novel biotherapeutics. Recent progress includes the engineering of monoclonal antibodies, cytokines, enzymes and viral fusion inhibitors.

NMR and temperature-jump measurements of de novo designed proteins demonstrate rapid folding in the absence of explicit selection for kinetics.

We address the importance of natural selection in the origin and maintenance of rapid protein folding by experimentally characterizing the folding kinetics of two de novo designed proteins, NC3-NCAP and ENH-FSM1. These 51 residue proteins, which adopt the helix-turn-helix homeodomain fold, share as few as 12 residues in common with their most closely related natural analog. Despite the replacement of up to 3/4 of their residues by a computer algorithm optimizing only thermodynamic properties, the designed proteins fold as fast or faster than the 35,000 s(-1) observed for the closest natural analog. Thus these de novo designed proteins, which were produced in the complete absence of selective pressures or design constraints explicitly aimed at ensuring rapid folding, are among the most rapidly folding proteins reported to date.

Rational design and engineering of therapeutic proteins.

An increasing number of engineered protein therapeutics are currently being developed, tested in clinical trials and marketed for use. Many of these proteins arose out of hit-and-miss efforts to discover specific mutations, fusion partners or chemical modifications that confer desired properties. Through these efforts, several useful strategies have emerged for rational optimization of therapeutic candidates. The controlled manipulation of the physical, chemical and biological properties of proteins enabled by structure-based simulation is now being used to refine established rational engineering approaches and to advance new strategies. These methods provide clear, hypothesis-driven routes to solve problems that plague many proteins and to create novel mechanisms of action. We anticipate that rational protein engineering will shape the field of protein therapeutics dramatically by improving existing products and enabling the development of novel therapeutic agents.

Electrostatics significantly affect the stability of designed homeodomain variants.

The role of electrostatic interactions in determining the stability of designed proteins was studied by constructing and analyzing a set of designed variants of the Drosophila engrailed homeodomain. Computational redesign of 29 surface positions results in a 25-fold mutant with moderate stability, similar to the wild-type protein. Incorporating helix dipole and N-capping considerations into the design algorithm by restricting amino acid composition at the helix termini and N-capping positions yields a ninefold mutant of the initial design (a 23-fold mutant of wild-type) that is over 3 kcal mol(-1) more stable than the protein resulting from the unbiased design. Four additional proteins were constructed and analyzed to isolate the effects of helix dipole and N-capping interactions in each helix. Based on the results of urea-denaturation experiments and calculations using the finite difference Poisson-Boltzmann method, both classes of interaction are found to increase the stability of the designed proteins significantly. The simple electrostatic model used in the optimization of rotamers by iterative techniques (ORBIT) force-field, which is similar to the electrostatic models used in other protein design force-fields, is unable to predict the experimentally determined stabilities of the designed variants. The helix dipole and N-capping restrictions provide a simple but effective method to incorporate two types of electrostatic interactions that impact protein stability significantly.