Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures

Antibodies are attractive therapeutic candidates due to their ability to bind cognate antigens with high affinity and specificity. Still, the underlying molecular rules governing the antibody-antigen interface remain poorly understood, making in silico antibody design inherently difficult and keeping the discovery and design of novel antibodies a costly and laborious process. This study investigates the characteristics of antibody-antigen binding interfaces through a computational analysis of more than 850,000 atom-atom contacts from the largest reported set of antibody-antigen complexes with 1833 nonredundant, experimentally determined structures. The analysis compares binding characteristics of conventional antibodies and single-domain antibodies (sdAbs) targeting both protein- and peptide antigens. We find clear patterns in the number antibody-antigen contacts and amino acid frequencies in the paratope. The direct comparison of sdAbs and conventional antibodies helps elucidate the mechanisms employed by sdAbs to compensate for their smaller size and the fact that they harbor only half the number of complementarity-determining regions compared to conventional antibodies. Furthermore, we pinpoint antibody interface hotspot residues that are often found at the binding interface and the amino acid frequencies at these positions. These findings have direct potential applications in antibody engineering and the design of improved antibody libraries.

Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20 + chemistry in combination with dual unique molecular identifiers (UMIs) and an optimized bioinformatic analysis pipeline to monitor the selections. We identified binders from two single-domain antibody libraries selected against a model protein. Traditional colony-picking was compared with our ONT-UMI method. ONT-UMI enabled monitoring of diversity and enrichment before and after each selection round. By combining phage antibody selections with ONT-UMIs, deep mining of output selections is possible. The approach provides an alternative to traditional screening, enabling diversity quantification after each selection round and rare binder recovery, even when the dominating binder was > 99% abundant. Moreover, it can give insights on binding motifs for further affinity maturation and specificity optimizations. Our results demonstrate a platform for future data guided selection strategies.

Eliminating OFF-frame clones in randomized gene libraries: An improved split β-lactamase enrichment system

Large, randomized libraries are a key technology for many biotechnological applications. While genetic diversity is the main parameter most libraries direct their resources on, less focus is devoted to ensuring functional IN-frame expression. This study describes a faster and more efficient system based on a split β-lactamase complementation for removal of OFF-frame clones and increase of functional diversity, suitable for construction of randomized libraries. The gene of interest is inserted between two fragments of the β-lactamase gene, conferring resistance to β-lactam drugs only upon expression of an inserted IN-frame gene without stop codons or frameshifts. The preinduction-free system was capable of eliminating OFF-frame clones in starting mixtures of as little as 1% IN-frame clones and enriching to about 70% IN-frame clones, even when their starting rate was as low as 0.001%. The curation system was verified by constructing a single-domain antibody phage display library using trinucleotide phosphoramidites for randomizing a complementary determining region, while eliminating OFF-frame clones and maximizing functional diversity.

A window into the human immune system: comprehensive characterization of the complexity of antibody complementary-determining regions in functional antibodies

The human immune system uses antibodies to neutralize foreign antigens. They are composed of heavy and light chains, both with constant and variable regions. The variable region has six hypervariable loops, also known as complementary-determining regions (CDRs) that determine antibody diversity and antigen specificity. Knowledge of their significance, and certain residues present in these areas, is vital for antibody therapeutics development. This study includes an analysis of more than 11,000 human antibody sequences from the International Immunogenetics information system (IMGT). The analysis included parameters such as length distribution, overall amino acid diversity, amino acid frequency per CDR and residue position within antibody chains. Overall, our findings confirm existing knowledge, such as CDRH3's high length diversity and amino acid variability, increased aromatic residue usage, particularly tyrosine, charged and polar residues like aspartic acid, serine, and the flexible residue glycine. Specific residue positions within each CDR influence these occurrences, implying a unique amino acid type distribution pattern. We compared amino acid type usage in CDRs and non-CDR regions, both in globular and transmembrane proteins, which revealed distinguishing features, such as increased frequency of tyrosine, serine, aspartic acid, and arginine. These findings should prove useful for future optimization, improvement of affinity, synthetic antibody library design, or the creation of antibodies de-novo in silico.

Immobilization-Free Binding and Affinity Characterization of Higher Order Bispecific Antibody Complexes Using Size-Based Microfluidics

Simultaneous targeting of different antigens by bispecific antibodies (bsAbs) is permitting synergistic binding functionalities with high therapeutic potential, but is also rendering their analysis challenging. We introduce flow-induced dispersion analysis (FIDA) for the in-depth characterization of bsAbs with diverse molecular architectures and valencies under near-native conditions without potentially obstructive surface immobilization. Individual equilibrium dissociation constants are determined in solution, even in higher-order complexes with both antigens involved, hereby allowing the analysis of binding cooperativity and elucidation of a potential interference between the interactions. We further illustrate bispecific binding functionality as incremental increases in complex sizes when the bsAbs are exposed to one or two antigens. The possibility for comprehensive binding analysis with low material consumption and high matrix tolerability irrespective of molecular format and with little optimization renders FIDA a versatile tool for format selection and characterization of complex bi/multispecific protein therapeutics throughout the drug development and biomanufacturing pipeline.