Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

BACKGROUND: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information. METHODOLOGY/PRINCIPAL FINDINGS: Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with K(d) = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive. CONCLUSIONS/SIGNIFICANCE: By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner

High Affinity Antigen Recognition of the Dual Specific Variants of Herceptin Is Entropy-Driven in Spite of Structural Plasticity

The antigen-binding site of Herceptin, an anti-human Epidermal Growth Factor Receptor 2 (HER2) antibody, was engineered to add a second specificity toward Vascular Endothelial Growth Factor (VEGF) to create a high affinity two-in-one antibody bH1. Crystal structures of bH1 in complex with either antigen showed that, in comparison to Herceptin, this antibody exhibited greater conformational variability, also called “structural plasticity”. Here, we analyzed the biophysical and thermodynamic properties of the dual specific variants of Herceptin to understand how a single antibody binds two unrelated protein antigens. We showed that while bH1 and the affinity-improved bH1-44, in particular, maintained many properties of Herceptin including binding affinity, kinetics and the use of residues for antigen recognition, they differed in the binding thermodynamics. The interactions of bH1 and its variants with both antigens were characterized by large favorable entropy changes whereas the Herceptin/HER2 interaction involved a large favorable enthalpy change. By dissecting the total entropy change and the energy barrier for dual interaction, we determined that the significant structural plasticity of the bH1 antibodies demanded by the dual specificity did not translate into the expected increase of entropic penalty relative to Herceptin. Clearly, dual antigen recognition of the Herceptin variants involves divergent antibody conformations of nearly equivalent energetic states. Hence, increasing the structural plasticity of an antigen-binding site without increasing the entropic cost may play a role for antibodies to evolve multi-specificity. Our report represents the first comprehensive biophysical analysis of a high affinity dual specific antibody binding two unrelated protein antigens, furthering our understanding of the thermodynamics that drive the vast antigen recognition capacity of the antibody repertoire

Synthetic antibodies for specific recognition and crystallization of structured RNA

Antibodies that bind protein antigens are indispensable in biochemical research and modern medicine. However, knowledge of RNA-binding antibodies and their application in the ever-growing RNA field is lacking. Here we have developed a robust approach using a synthetic phage-display library to select specific antigen-binding fragments (Fabs) targeting a large functional RNA. We have solved the crystal structure of the first Fab–RNA complex at 1.95 Å. Capability in phasing and crystal contact formation suggests that the Fab provides a potentially valuable crystal chaperone for RNA. The crystal structure reveals that the Fab achieves specific RNA binding on a shallow surface with complementarity-determining region (CDR) sequence diversity, length variability, and main-chain conformational plasticity. The Fab–RNA interface also differs significantly from Fab–protein interfaces in amino acid composition and light-chain participation. These findings yield valuable insights for engineering of Fabs as RNA-binding modules and facilitate further development of Fabs as possible therapeutic drugs and biochemical tools to explore RNA biology

Crystal structure of full-length KcsA in its closed conformation

KcsA is a proton-activated, voltage-modulated K+ channel that has served as the archetype pore domain in the Kv channel superfamily. Here, we have used synthetic antigen-binding fragments (Fabs) as crystallographic chaperones to determine the structure of full-length KcsA at 3.8 Å, as well as that of its isolated C-terminal domain at 2.6 Å. The structure of the full-length KcsA–Fab complex reveals a well-defined, 4-helix bundle that projects ≈70 Å toward the cytoplasm. This bundle promotes a ≈15° bending in the inner bundle gate, tightening its diameter and shifting the narrowest point 2 turns of helix below. Functional analysis of the full-length KcsA–Fab complex suggests that the C-terminal bundle remains whole during gating. We suggest that this structure likely represents the physiologically relevant closed conformation of KcsA