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

[This corrects the article DOI: 10.1371/journal.pcbi.1007207.].

Design of a basigin-mimicking inhibitor targeting the malaria invasion protein RH5.

Many human pathogens use host cell-surface receptors to attach and invade cells. Often, the host-pathogen interaction affinity is low, presenting opportunities to block invasion using a soluble, high-affinity mimic of the host protein. The Plasmodium falciparum reticulocyte-binding protein homolog 5 (RH5) provides an exciting candidate for mimicry: it is highly conserved and its moderate affinity binding to the human receptor basigin (KD ≥1 µM) is an essential step in erythrocyte invasion by this malaria parasite. We used deep mutational scanning of a soluble fragment of human basigin to systematically characterize point mutations that enhance basigin affinity for RH5 and then used Rosetta to design a variant within the sequence space of affinity-enhancing mutations. The resulting seven-mutation design exhibited 1900-fold higher affinity (KD approximately 1 nM) for RH5 with a very slow binding off rate (0.23 h-1 ) and reduced the effective Plasmodium growth-inhibitory concentration by at least 10-fold compared to human basigin. The design provides a favorable starting point for engineering on-rate improvements that are likely to be essential to reach therapeutically effective growth inhibition.

Site-Specific Conjugation of Native Antibodies Using Engineered Microbial Transglutaminases.

Site-specific bioconjugation technologies are frequently employed to generate homogeneous antibody-drug conjugates (ADCs) and are generally considered superior to stochastic approaches like lysine coupling. However, most of the technologies developed so far require undesired manipulation of the antibody sequence or its glycan structures. Herein, we report the successful engineering of microbial transglutaminase enabling efficient, site-specific conjugation of drug-linker constructs to position HC-Q295 of native, fully glycosylated IgG-type antibodies. ADCs generated via this approach demonstrate excellent stability in vitro as well as strong efficacy in vitro and in vivo. As it employs different drug-linker structures and several native antibodies, our study additionally proves the broad applicability of this approach.

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.

SUMO: In Silico Sequence Assessment Using Multiple Optimization Parameters.

To select the most promising screening hits from antibody and VHH display campaigns for subsequent in-depth profiling and optimization, it is highly desirable to assess and select sequences on properties beyond only their binding signals from the sorting process. In addition, developability risk criteria, sequence diversity, and the anticipated complexity for sequence optimization are relevant attributes for hit selection and optimization. Here, we describe an approach for the in silico developability assessment of antibody and VHH sequences. This method not only allows for ranking and filtering multiple sequences with regard to their predicted developability properties and diversity, but also visualizes relevant sequence and structural features of potentially problematic regions and thereby provides rationales and starting points for multi-parameter sequence optimization.

Biomolecular Recognition of the Glycan Neoantigen CA19-9 by Distinct Antibodies.

Glycans decorate the cell surface, secreted glycoproteins and glycolipids, and altered glycans are often found in cancers. Despite their high diagnostic and therapeutic potential, however, glycans are polar and flexible molecules that are quite challenging for the development and design of high-affinity binding antibodies. To understand the mechanisms by which glycan neoantigens are specifically recognized by antibodies, we analyze the biomolecular recognition of the tumor-associated carbohydrate antigen CA19-9 by two distinct antibodies using X-ray crystallography. Despite the potential plasticity of glycans and the very different antigen-binding surfaces presented by the antibodies, both structures reveal an essentially identical extended CA19-9 conformer, suggesting that this conformer's stability selects the antibodies. Starting from the bound structure of one of the antibodies, we use the AbLIFT computational algorithm to design a variant with seven core mutations in the variable domain's light-heavy chain interface that exhibits tenfold improved affinity for CA19-9. The results reveal strategies used by antibodies to specifically recognize glycan antigens and show how automated antibody-optimization methods may be used to enhance the clinical potential of existing antibodies.

Rapid characterization of secreted recombinant proteins by native mass spectrometry.

Characterization of overexpressed proteins is essential for assessing their quality, and providing input for iterative redesign and optimization. This process is typically carried out following purification procedures that require pronounced cost of time and labor. Therefore, quality assessment of recombinant proteins with no prior purification offers a major advantage. Here, we report a native mass spectrometry method that enables characterization of overproduced proteins directly from culture media. Properties such as solubility, molecular weight, folding, assembly state, overall structure, post-translational modifications and binding to relevant biomolecules are immediately revealed. We show the applicability of the method for in-depth characterization of secreted recombinant proteins from eukaryotic systems such as yeast, insect, and human cells. This method, which can be readily extended to high-throughput analysis, considerably shortens the time gap between protein production and characterization, and is particularly suitable for characterizing engineered and mutated proteins, and optimizing yield and quality of overexpressed proteins.

A Novel Allosteric Mechanism of NF-κB Dimerization and DNA Binding Targeted by an Anti-Inflammatory Drug.

The NF-κB family plays key roles in immune and stress responses, and its deregulation contributes to several diseases. Therefore its modulation has become an important therapeutic target. Here, we used a high-throughput screen for small molecules that directly inhibit dimerization of the NF-κB protein p65. One of the identified inhibitors is withaferin A (WFA), a documented anticancer and anti-inflammatory compound. Computational modeling suggests that WFA contacts the dimerization interface on one subunit and surface residues E285 and Q287 on the other. Despite their locations far from the dimerization site, E285 and Q287 substitutions diminished both dimerization and the WFA effect. Further investigation revealed that their effects on dimerization are associated with their proximity to a conserved hydrophobic core domain (HCD) that is crucial for dimerization and DNA binding. Our findings established NF-κB dimerization as a drug target and uncovered an allosteric domain as a target of WFA action.

A "fuzzy"-logic language for encoding multiple physical traits in biomolecules.

To carry out their activities, biological macromolecules balance different physical traits, such as stability, interaction affinity, and selectivity. How such often opposing traits are encoded in a macromolecular system is critical to our understanding of evolutionary processes and ability to design new molecules with desired functions. We present a framework for constraining design simulations to balance different physical characteristics. Each trait is represented by the equilibrium fractional occupancy of the desired state relative to its alternatives, ranging from none to full occupancy, and the different traits are combined using Boolean operators to effect a "fuzzy"-logic language for encoding any combination of traits. In another paper, we presented a new combinatorial backbone design algorithm AbDesign where the fuzzy-logic framework was used to optimize protein backbones and sequences for both stability and binding affinity in antibody-design simulation. We now extend this framework and find that fuzzy-logic design simulations reproduce sequence and structure design principles seen in nature to underlie exquisite specificity on the one hand and multispecificity on the other hand. The fuzzy-logic language is broadly applicable and could help define the space of tolerated and beneficial mutations in natural biomolecular systems and design artificial molecules that encode complex characteristics.

Type I interferons induce apoptosis by balancing cFLIP and caspase-8 independent of death ligands.

Interferons induce a pleiotropy of responses through binding the same cell surface receptor. Here we investigated the molecular mechanism driving interferon-induced apoptosis. Using a nonbiased small interfering RNA (siRNA) screen, we show that silencing genes whose products are directly engaged in the initiation of interferon signaling completely abrogate the interferon antiproliferative response. Apoptosis-related genes such as the caspase-8, cFLIP, and DR5 genes specifically interfere with interferon-induced apoptosis, which we found to be independent of the activity of death ligands. The one gene for which silencing resulted in the strongest proapoptotic effect upon interferon signaling is the cFLIP gene, where silencing shortened the time of initiation of apoptosis from days to hours and increased dramatically the population of apoptotic cells. Thus, cFLIP serves as a regulator for interferon-induced apoptosis. A shift over time in the balance between cFLIP and caspase-8 results in downstream caspase activation and apoptosis. While gamma interferon (IFN-γ) also causes caspase-8 upregulation, we suggest that it follows a different path to apoptosis.