PROTEIN DESIGN. Inspired by nature

Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces

Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.

Physicochemical Position-Dependent Properties in the Protein Secondary Structures

BACKGROUND

Establishing theories for designing arbitrary protein structures is complicated and depends on understanding the principles for protein folding, which is affected by applied features. Computer algorithms can reach high precision and stability in computationally designed enzymes and binders by applying informative features obtained from natural structures.

METHODS

In this study, a position-specific analysis of secondary structures (α-helix, β-strand, and tight turn) was performed to reveal novel features for protein structure prediction and protein design.

RESULTS

Our results showed that the secondary structures in the N-termini region tend to be more compact than C-termini. Decoying periodicity in length and distribution of amino acids in α-helices is deciphered using the curve-fitting methods. Compared with α-helix, β-strands do not show distinct periodicities in length. Also, significant differences in position-dependent distribution of physicochemical properties are shown in secondary structures.

CONCLUSION

Position-specific propensities in our study underline valuable parameters that could be used by researchers in the field of structural biology, particularly protein design through site-directed mutagenesis.

Ultrahigh specificity in a network of computationally designed protein-interaction pairs

Protein networks in all organisms comprise homologous interacting pairs. In these networks, some proteins are specific, interacting with one or a few binding partners, whereas others are multispecific and bind a range of targets. We describe an algorithm that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences. Applied to a high-affinity bacterial pair, the algorithm results in 18 new ones, with cognate affinities from pico- to micromolar. Three pairs exhibit 3-5 orders of magnitude switch in specificity relative to the wild type, whereas others are multispecific, collectively forming a protein-interaction network. Crystallographic analysis confirms design accuracy, including in new backbones and polar interactions. Preorganized polar interaction networks are responsible for high specificity, thus defining design principles that can be applied to program synthetic cellular interaction networks of desired affinity and specificity.

The molecular basis of ultrahigh specificity in protein-protein interactions remains obscure. The authors present a computational method to design atomically accurate new pairs exhibiting >100,000-fold specificity switches, generating a large and complex interaction network.

Lymphatic vessel density is associated with CD8+ T cell infiltration and immunosuppressive factors in human melanoma

Increased density of tumor-associated lymphatic vessels correlates with poor patient survival in melanoma and other cancers, yet lymphatic drainage is essential for initiating an immune response. Here we asked whether and how lymphatic vessel density (LVD) correlates with immune cell infiltration in primary tumors and lymph nodes (LNs) from patients with cutaneous melanoma. Using immunohistochemistry and quantitative image analysis, we found significant positive correlations between LVD and CD8+ T cell infiltration as well as expression of the immunosuppressive molecules inducible nitric oxide synthase (iNOS) and 2,3-dioxygénase (IDO). Interestingly, similar associations were seen in tumor-free LNs adjacent to metastatic ones, indicating loco-regional effects of tumors. Our data suggest that lymphatic vessels play multiple roles at tumor sites and LNs, promoting both T cell infiltration and adaptive immunosuppressive mechanisms. Lymph vessel associated T cell infiltration may increase immunotherapy success rates provided that the treatment overcomes adaptive immune resistance.

Principles for computational design of binding antibodies

Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called "ideal" folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes.

Harnessing self-assembled peptide nanoparticles in epitope vaccine design

Vaccination has been one of the most successful breakthroughs in medical history. In recent years, epitope-based subunit vaccines have been introduced as a safer alternative to traditional vaccines. However, they suffer from limited immunogenicity. Nanotechnology has shown value in solving this issue. Different kinds of nanovaccines have been employed, among which virus-like nanoparticles (VLPs) and self-assembled peptide nanoparticles (SAPNs) seem very promising. Recently, SAPNs have attracted special interest due to their unique properties, including molecular specificity, biodegradability, and biocompatibility. They also resemble pathogens in terms of their size. Their multivalency allows an orderly repetitive display of antigens on their surface, which induces a stronger immune response than single immunogens. In vaccine design, SAPN self-adjuvanticity is regarded an outstanding advantage, since the use of toxic adjuvants is no longer required. SAPNs are usually composed of helical or β-sheet secondary structures and are tailored from natural peptides or de novo structures. Flexibility in subunit selection opens the door to a wide variety of molecules with different characteristics. SAPN engineering is an emerging area, and more novel structures are expected to be generated in the future, particularly with the rapid progress in related computational tools. The aim of this review is to provide a state-of-the-art overview of self-assembled peptide nanoparticles and their use in vaccine design in recent studies. Additionally, principles for their design and the application of computational approaches to vaccine design are summarized.

Distinct roles of a tyrosine-associated hydrogen-bond network in fine-tuning the structure and function of heme proteins: two cases designed for myoglobin

A hydrogen-bond (H-bond) network, specifically a Tyr-associated H-bond network, plays key roles in regulating the structure and function of proteins, as exemplified by abundant heme proteins in nature. To explore an approach for fine-tuning the structure and function of artificial heme proteins, we herein used myoglobin (Mb) as a model protein and introduced a Tyr residue in the secondary sphere of the heme active site at two different positions (107 and 138). We performed X-ray crystallography, UV-Vis spectroscopy, stopped-flow kinetics, and electron paramagnetic resonance (EPR) studies for the two single mutants, I107Y Mb and F138Y Mb, and compared to that of wild-type Mb under the same conditions. The results showed that both Tyr107 and Tyr138 form a distinct H-bond network involving water molecules and neighboring residues, which fine-tunes ligand binding to the heme iron and enhances the protein stability, respectively. Moreover, the Tyr107-associated H-bond network was shown to fine-tune both H2O2 binding and activation. With two cases demonstrated for Mb, this study suggests that the Tyr-associated H-bond network has distinct roles in regulating the protein structure, properties and functions, depending on its location in the protein scaffold. Therefore, it is possible to design a Tyr-associated H-bond network in general to create other artificial heme proteins with improved properties and functions.