Cell-penetrating Alphabody protein scaffolds for intracellular drug targeting.

The therapeutic scope of antibody and nonantibody protein scaffolds is still prohibitively limited against intracellular drug targets. Here, we demonstrate that the Alphabody scaffold can be engineered into a cell-penetrating protein antagonist against induced myeloid leukemia cell differentiation protein MCL-1, an intracellular target in cancer, by grafting the critical B-cell lymphoma 2 homology 3 helix of MCL-1 onto the Alphabody and tagging the scaffold's termini with designed cell-penetration polypeptides. Introduction of an albumin-binding moiety extended the serum half-life of the engineered Alphabody to therapeutically relevant levels, and administration thereof in mouse tumor xenografts based on myeloma cell lines reduced tumor burden.

Structural basis of IL-23 antagonism by an Alphabody protein scaffold.

Protein scaffolds can provide a promising alternative to antibodies for various biomedical and biotechnological applications, including therapeutics. Here we describe the design and development of the Alphabody, a protein scaffold featuring a single-chain antiparallel triple-helix coiled-coil fold. We report affinity-matured Alphabodies with favourable physicochemical properties that can specifically neutralize human interleukin (IL)-23, a pivotal therapeutic target in autoimmune inflammatory diseases such as psoriasis and multiple sclerosis.

Affinity maturation by semi-rational approaches.

Rational engineering methods can be applied with success to optimize physicochemical characteristics of antibodies. Application of in silico analysis and prediction methods to antibody Fv regions can help to find residues affecting antibody-antigen affinity when high-resolution antibody structures or antibody-antigen complex structures are known. In these cases, the identification of residues affecting affinity can facilitate the selection of candidates for guided maturation by PCR using degenerate oligonucleotides.

Binding of CDR-derived peptides is mechanistically different from that of high-affinity parental antibodies.

We present data that reveal crucial differences between the binding mode of anti-gastrin17 (G17, pyroEGPWLEEEEEAYGWMDF-NH(2)) monoclonal antibodies (mAbs) and their CDR-derived synthetic binders (SBs) with G17. The mAbs recognize the N-terminal sequence of G17 (pyroEGPWL) with nanomolar affinity and high sequence selectivity. Molecular simulations suggest that G17 recognition is based primarily on a multitude of weak antibody-ligand interactions (H-bonding, van der Waals, etc.

A combinatorial approach for the design of complementarity-determining region-derived peptidomimetics with in vitro anti-tumoral activity.

The great success of therapeutic monoclonal antibodies has fueled research toward mimicry of their binding sites and the development of new strategies for peptide-based mimetics production. Here, we describe a new combinatorial approach for the production of peptidomimetics using the complementarity-determining regions (CDRs) from gastrin17 (pyroEGPWLEEEEEAYGWMDF-NH(2)) antibodies as starting material for cyclic peptide synthesis in a microarray format. Gastrin17 is a trophic factor in gastrointestinal tumors, including pancreatic cancer, which makes it an interesting target for development of therapeutic antibodies.

Affinity maturation of antibodies assisted by in silico modeling.

Rational engineering methods can be applied with reasonable success to optimize physicochemical characteristics of proteins, in particular, antibodies. Here, we describe a combined CDR3 walking randomization and rational design-based approach to enhance the affinity of the human anti-gastrin TA4 scFv. The application of this methodology to TA4 scFv, displaying only a weak overall affinity for gastrin17 (K(D) = 6 microM), resulted in a set of nine affinity-matured scFv variants with near-nanomolar affinity (K(D) = 13.

Rational humanization of the powerful antithrombotic anti-GPIbalpha antibody: 6B4.

Fab-fragments of the monoclonal antibody 6B4, raised against human glycoprotein Ibalpha (GPIbalpha), have a powerful antithrombotic effect in baboons by blocking the GPIbalpha binding site for von Willebrand factor (VWF), without significant prolongation of the skin bleeding time. In order to bring this antibody to the clinic,we here humanized for the first time an anti-human GPIbalpha by variable-domain resurfacing guided by computer modeling. First, the genes coding for the variable regions of the heavy and light chains of 6B4 were cloned and sequenced.

Humanization by variable domain resurfacing and grafting on a human IgG4, using a new approach for determination of non-human like surface accessible framework residues based on homology modelling of variable domains.

Many antithrombotic agents have only a small therapeutic window, frequently leading to bleeding problems. However, interfering with platelet adhesion through the collagen-VWF-GPIbalpha axis is expected to cause less bleeding problems. Our group developed a monoclonal antibody, 82D6A3, directed against the von Willebrand factor (VWF) A3-domain, which inhibits the VWF-interaction to fibrillar collagen.

Anchor profiles of HLA-specific peptides: analysis by a novel affinity scoring method and experimental validation.

The study of intermolecular interactions is a fundamental research subject in biology. Here we report on the development of a quantitative structure-based affinity scoring method for peptide-protein complexes, named PepScope. The method operates on the basis of a highly specific force field function (CHARMM) that is applied to all-atom structural representations of peptide-receptor complexes.

Fast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimization.

We have developed an original method for global optimization of protein side-chain conformations, called the Fast and Accurate Side-Chain Topology and Energy Refinement (FASTER) method. The method operates by systematically overcoming local minima of increasing order. Comparison of the FASTER results with those of the dead-end elimination (DEE) algorithm showed that both methods produce nearly identical results, but the FASTER algorithm is 100-1000 times faster than the DEE method and scales in a stable and favorable way as a function of protein size.