Multi‐constraint computational design suggests that native sequences of germline antibody H3 loops are nearly optimal for conformational flexibility

The limited size of the germline antibody repertoire has to recognize a far larger number of potential antigens. The ability of a single antibody to bind multiple ligands due to conformational flexibility in the antigen‐binding site can significantly enlarge the repertoire. Among the six complementarity determining regions (CDRs) that generally comprise the binding site, the CDR H3 loop is particularly variable. Computational protein design studies showed that predicted low energy sequences compatible with a given backbone structure often have considerable similarity to the corresponding native sequences of naturally occurring proteins, indicating that native protein sequences are close to optimal for their structures. Here, we take a step forward to determine whether conformational flexibility, believed to play a key functional role in germline antibodies, is also central in shaping their native sequence. In particular, we use a multi‐constraint computational design strategy, along with the Rosetta scoring function, to propose that the native sequences of CDR H3 loops from germline antibodies are nearly optimal for conformational flexibility. Moreover, we find that antibody maturation may lead to sequences with a higher degree of optimization for a single conformation, while disfavoring sequences that are intrinsically flexible. In addition, this computational strategy allows us to predict mutations in the CDR H3 loop to stabilize the antigen‐bound conformation, a computational mimic of affinity maturation, that may increase antigen binding affinity by preorganizing the antigen binding loop. In vivo affinity maturation data are consistent with our predictions. The method described here can be useful to design antibodies with higher selectivity and affinity by reducing conformational diversity. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

Antibodies as a model system for comparative model refinement

Predicting the conformations of loops is a critical aspect of protein comparative (homology) modeling. Despite considerable advances in developing loop prediction algorithms, refining loops in homology models remains challenging. In this work, we use antibodies as a model system to investigate strategies for more robustly predicting loop conformations when the protein model contains errors in the conformations of side chains and protein backbone surrounding the loop in question. Specifically, our test system consists of partial models of antibodies in which the “scaffold” (i.e., the portion other than the complementarity determining region, CDR, loops) retains native backbone conformation, whereas the CDR loops are predicted using a combination of knowledge‐based modeling (H1, H2, L1, L2, and L3) and ab initio loop prediction (H3). H3 is the most variable of the CDRs. Using a previously published method, a test set of 10 shorter H3 loops (5–7 residues) are predicted to an average backbone (N? Cα? C? O) RMSD of 2.7 Å while 11 longer loops (8–9 residues) are predicted to 5.1 Å, thus recapitulating the difficulties in refining loops in models. By contrast, in control calculations predicting the same loops in crystal structures, the same method reconstructs the loops to an average of 0.5 and 1.4 Å for the shorter and longer loops, respectively. We modify the loop prediction method to improve the ability to sample near‐native loop conformations in the models, primarily by reducing the sensitivity of the sampling to the loop surroundings, and allowing the other CDR loops to optimize with the H3 loop. The new method improves the average accuracy significantly to 1.3 Å RMSD and 3.1 Å RMSD for the shorter and longer loops, respectively. Finally, we present results predicting 8–10 residue loops within complete comparative models of five nonantibody proteins. While anecdotal, these mixed, full‐model results suggest our approach is a promising step toward more accurately predicting loops in homology models. Furthermore, while significant challenges remain, our method is a potentially useful tool for predicting antibody structures based on a known Fv scaffold. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Analysis of the binding loops configuration and surface adaptation of different crystallized single‐domain antibodies in response to various antigens

Monoclonal antibodies have revolutionized the biomedical field through their ubiquitous utilization in different diagnostics and therapeutic applications. Despite this widespread use, their large size and structural complexity have limited their versatility in specific applications. The antibody variable region that is responsible for binding antigen is embodied within domains that can be rescued individually as single‐domain antibody (sdAb) fragments. Because of the unique characteristics of sdAbs, such as low molecular weight, high physicochemical stability, and the ability to bind antigens inaccessible to conventional antibodies, they represent a viable alternative to full‐length antibodies. Consequently, 149 crystal structures of sdAbs, originating from human (VH), camelids (VHH), or sharks (VNAR), were retrieved from the Protein Data Bank, and their structures were compared. The 3 types of sdAbs displayed complementarity determining regions (CDRs) with different lengths and configurations. CDR3 of the VHH and VNAR domains were dominated by pleated and extended orientations, respectively. Although VNAR showed the smallest average molecular weight and molecular surface area compared with VHH and VH antibodies. However, the solvent accessible surface area measurements of the 3 tested sdAbs types were very similar. All the antihapten VHH antibodies showed pleated CDR3, which were sufficient to create a binding pocket to accommodate haptens (methotrexate and azo dyes) in terms of shape and electrostatic potential. The sdAbs that recognized lysozyme showed more diversity in their CDR3 orientation to enable them to recognize various topographies of lysozyme. Subsequently, the three sdAb classes were different in size and surface area and have shown distinguishable ability to optimize their CDR length and orientation to recognize different antigen classes.     

Toward high‐resolution homology modeling of antibody Fv regions and application to antibody–antigen docking

High‐resolution homology models are useful in structure‐based protein engineering applications, especially when a crystallographic structure is unavailable. Here, we report the development and implementation of RosettaAntibody, a protocol for homology modeling of antibody variable regions. The protocol combines comparative modeling of canonical complementarity determining region (CDR) loop conformations and de novo loop modeling of CDR H3 conformation with simultaneous optimization of V_L‐V_H rigid‐body orientation and CDR backbone and side‐chain conformations. The protocol was tested on a benchmark of 54 antibody crystal structures. The median root mean square deviation (rmsd) of the antigen binding pocket comprised of all the CDR residues was 1.5 Å with 80% of the targets having an rmsd lower than 2.0 Å. The median backbone heavy atom global rmsd of the CDR H3 loop prediction was 1.6, 1.9, 2.4, 3.1, and 6.0 Å for very short (4–6 residues), short (7–9), medium (10–11), long (12–14) and very long (17–22) loops, respectively. When the set of ten top‐scoring antibody homology models are used in local ensemble docking to antigen, a moderate‐to‐high accuracy docking prediction was achieved in seven of fifteen targets. This success in computational docking with high‐resolution homology models is encouraging, but challenges still remain in modeling antibody structures for sequences with long H3 loops. This first large‐scale antibody–antigen docking study using homology models reveals the level of “functional accuracy” of these structural models toward protein engineering applications. Proteins 2009; 74:497–514. © 2008 Wiley‐Liss, Inc.     

Structural diversity in a human antibody germline library

To support antibody therapeutic development, the crystal structures of a set of 16 germline variants composed of 4 different kappa light chains paired with 4 different heavy chains have been determined. All four heavy chains of the antigen-binding fragments (Fabs) have the same complementarity-determining region (CDR) H3 that was reported in an earlier Fab structure. The structure analyses include comparisons of the overall structures, canonical structures of the CDRs and the VH:VL packing interactions. The CDR conformations for the most part are tightly clustered, especially for the ones with shorter lengths. The longer CDRs with tandem glycines or serines have more conformational diversity than the others. CDR H3, despite having the same amino acid sequence, exhibits the largest conformational diversity. About half of the structures have CDR H3 conformations similar to that of the parent; the others diverge significantly. One conclusion is that the CDR H3 conformations are influenced by both their amino acid sequence and their structural environment determined by the heavy and light chain pairing. The stem regions of 14 of the variant pairs are in the ‘kinked’ conformation, and only 2 are in the extended conformation. The packing of the VH and VL domains is consistent with our knowledge of antibody structure, and the tilt angles between these domains cover a range of 11 degrees. Two of 16 structures showed particularly large variations in the tilt angles when compared with the other pairings. The structures and their analyses provide a rich foundation for future antibody modeling and engineering efforts.     

The H3 loop of antibodies shows unique structural characteristics

The H3 loop in the Complementarity Determining Region of antibodies plays a key role in their ability to bind the diverse space of potential antigens. It is also exceptionally difficult to model computationally causing a significant hurdle for in silico development of antibody biotherapeutics. In this article, we show that most H3s have unique structural characteristics which may explain why they are so challenging to model. We found that over 75% of H3 loops do not have a sub‐Angstrom structural neighbor in the non‐antibody world. Also, in a comparison with a nonredundant set of all protein fragments over 30% of H3 loops have a unique structure, with the average for all of other loops being less than 3%. We further observed that this structural difference can be seen at the level of four residue fragments where H3 loops present numerous novel conformations, and also at the level of individual residues with Tyrosine and Glycine often found in energetically unfavorable conformations. Proteins 2017; 85:1311–1318. © 2017 Wiley Periodicals, Inc.     

Predicting antibody complementarity determining region structures without classification

Antibodies are used extensively in medical and biological research. Their complementarity determining regions (CDRs) define the majority of their antigen binding functionality. CDR structures have been intensively studied and classified (canonical structures). Here we show that CDR structure prediction is no different from the standard loop structure prediction problem and predict them without classification. FREAD, a successful database loop prediction technique, is able to produce accurate predictions for all CDR loops (0.81, 0.42, 0.96, 0.98, 0.88 and 2.25 ? RMSD for CDR-L1 to CDR-H3). In order to overcome the relatively poor predictions of CDR-H3, we developed two variants of FREAD, one focused on sequence similarity (FREAD-S) and another which includes contact information (ConFREAD). Both of the methods improve accuracy for CDR-H3 to 1.34 ? and 1.23 ? respectively. The FREAD variants are also tested on homology models and compared to RosettaAntibody (CDR-H3 prediction on models: 1.98 and 2.62 ? for ConFREAD and RosettaAntibody respectively). CDRs are known to change their structural conformations upon binding the antigen. Traditional CDR classifications are based on sequence similarity and do not account for such environment changes. Using a set of antigen-free and antigen-bound structures, we compared our FREAD variants. ConFREAD which includes contact information successfully discriminates the bound and unbound CDR structures and achieves an accuracy of 1.35 ? for bound structures of CDR-H3.     

Analysis and modeling of the variable region of camelid single-domain antibodies

Camelids have a special type of Ab, known as heavy chain Abs, which are devoid of classical Ab light chains. Relative to classical Abs, camelid heavy chain Abs (cAbs) have comparable immunogenicity, Ag recognition diversity and binding affinities, higher stability and solubility, and better manufacturability, making them promising candidates for alternate therapeutic scaffolds. Rational engineering of cAbs to improve therapeutic function requires knowledge of the differences of sequence and structural features between cAbs and classical Abs. In this study, amino acid sequences of 27 cAb variable regions (V(H)H) were aligned with the respective regions of 54 classical Abs to detect amino acid differences, enabling automatic identification of cAb V(H)H CDRs. CDR analysis revealed that the H1 often (and sometimes the H2) adopts diverse conformations not classifiable by established canonical rules. Also, although the cAb H3 is much longer than classical H3 loops, it often contains common structural motifs and sometimes a disulfide bond to the H1. Leveraging these observations, we created a Monte Carlo-based cAb V(H)H structural modeling tool, where the CDR H1 and H2 loops exhibited a median root-mean-square deviation to natives of 3.1 and 1.5 ?, respectively. The protocol generated 8-12, 14-16, and 16-24 residue H3 loops with a median root-mean-square deviation to natives of 5.7, 4.5, and 6.8 ?, respectively. The large deviation of the predicted loops underscores the challenge in modeling such long loops. cAb V(H)H homology models can provide structural insights into interaction mechanisms to enable development of novel Abs for therapeutic and biotechnological use.     

Predicting antibody hypervariable loop conformations. II: Minimization and molecular dynamics studies of MCPC603 from many randomly generated loop conformations

We describe a method for predicting the conformations of loops in proteins and its application to four of the complementarity determining regions [CDRs] in the crystallographically determined structure of MCPC603. The method is based on the generation of a large number of randomly generated conformations for the backbone of the loop being studied, followed by either minimization or molecular dynamics followed by minimization starting from these random structures. The details of the algorithm for the generation of the loops are presented in the first paper in this series (Shenkin et al. [submitted]). The results of minimization and molecular dynamics applied to these loops is presented here. For the two shortest CDRs studied (H1 and L2, which are five and seven amino acids long), minimizations and dynamics simulations which ignore interactions of the loop amino acids beyond the carbon beta replicate the conformation of the crystal structure closely. This suggests that these loops fold independently of sequence variation. For the third CDR (L3, which is nine amino acids), those portions of the CDR near its base which are hydrogen bonded to framework are well replicated by our procedures, but the top of the loop shows significant conformational variability. This variability persists when side chain interactions for the MCPC603 sequence are included. For a fourth CDR (H3, which is 11 amino acids long), new low-energy backbone conformations are found; however, only those which are close to the crystal are compatible with the sequence when side chain interactions are taken into account. Results from minimization and dynamics on single CDRs with all other CDRs removed are presented. These allow us to explore the extent to which individual CDR conformations are determined by interactions with framework only.     

A single-domain antibody fragment in complex with RNase A: non-canonical loop structures and nanomolar affinity using two CDR loops

BACKGROUND: Camelid serum contains a large fraction of functional heavy-chain antibodies - homodimers of heavy chains without light chains. The variable domains of these heavy-chain antibodies (VHH) have a long complementarity determining region 3 (CDR3) loop that compensates for the absence of the antigen-binding loops of the variable light chains (VL). In the case of the VHH fragment cAb-Lys3, part of the 24 amino acid long CDR3 loop protrudes from the antigen-binding surface and inserts into the active-site cleft of its antigen, rendering cAb-Lys3 a competitive enzyme inhibitor. RESULTS: A dromedary VHH with specificity for bovine RNase A, cAb-RN05, has a short CDR3 loop of 12 amino acids and is not a competitive enzyme inhibitor. The structure of the cAb-RN05-RNase A complex has been solved at 2.8 A. The VHH scaffold architecture is close to that of a human VH (variable heavy chain). The structure of the antigen-binding hypervariable 1 loop (H1) of both cAb-RN05 and cAb-Lys3 differ from the known canonical structures; in addition these H1 loops resemble each other. The CDR3 provides an antigen-binding surface and shields the face of the domain that interacts with VL in conventional antibodies. CONCLUSIONS: VHHs adopt the common immunoglobulin fold of variable domains, but the antigen-binding loops deviate from the predicted canonical structure. We define a new canonical structure for the H1 loop of immunoglobulins, with cAb-RN05 and cAb-Lys3 as reference structures. This new loop structure might also occur in human or mouse VH domains. Surprisingly, only two loops are involved in antigen recognition; the CDR2 does not participate. Nevertheless, the antigen binding occurs with nanomolar affinities because of a preferential usage of mainchain atoms for antigen interaction.     

High-affinity, peptide-specific T cell receptors can be generated by mutations in CDR1, CDR2 or CDR3

The third complementarity-determining regions (CDR3s) of antibodies and T cell receptors (TCRs) have been shown to play a major role in antigen binding and specificity. Consistent with this notion, we demonstrated previously that high-affinity, peptide-specific TCRs could be generated in vitro by mutations in the CDR3alpha region of the 2C TCR. In contrast, it has been argued that CDR1 and CDR2 are involved to a greater extent than CDR3s in the process of MHC restriction, due to their engagement of MHC helices. Based on this premise, we initiated the present study to explore whether higher affinity TCRs generated through mutations in these CDRs or other regions would lead to significant reductions in peptide specificity (i.e. the result of greater binding energy gained through interactions with major histocompatibility complex (MHC) helices). Yeast-display technology and flow sorting were used to select high-affinity TCRs from libraries of CDR mutants or random mutants. High-affinity TCRs with mutations in the first residue of the Valpha, CDR1, CDR2, or CDR3 were isolated. Unexpectedly, every TCR mutant, including those in CDR1 and CDR2, retained remarkable peptide specificity. Molecular modeling of various mutants suggested that such exquisite specificity may be due to: (1) enhanced electrostatic interactions with key peptide or MHC residues; or (2) stabilization of CDRs in specific conformations. The results indicate that the TCR is positioned so that virtually every CDR can contribute to the antigen-specificity of a T cell. The conserved diagonal docking of TCRs could thus orient each CDR loop to sense the peptide directly or indirectly through peptide-induced effects on the MHC.     

Length of the antibody heavy chain complementarity determining region 3 as a specificity-determining factor

The antigen binding site of an antibody is made up of residues residing in six hypervariable loops of the heavy and light chains. In most cases several or all of these loops are required for the establishment of the antigen-binding surface. Five of these loops display a limited diversity in length and sequence while the third complementarity determining region (CDR) of the heavy chain is highly different between antibodies not only with respect to sequence but also with respect to length. Its extensive diversity is a key component in the establishment of binding sites allowing for the recognition of essentially any antigen by humoral immunity. The relative importance of its sequence vs its length diversity in this context is however, not very well established. To investigate this matter further we have used an approach employing combinatorial antibody libraries and antigen-specific selection in the search for CDRH3 length and sequence diversity compatible with a given antigen specificity, the major antigenic determinant on the tumour-associated antigen mucin-1. In this way we have now defined heavy chain CDR3 length as a critical parameter in the creation of an antigen-specific binding site. We also propose that this may reflect a dependence of a particular structure of this hypervariable loop, the major carrier of diversity in the binding site, for establishment of a given specificity.     

Development of a Functional Antibody by Using a Green Fluorescent Protein Frame as the Template

Single-chain variable fragment (scFv) antibodies are widely used as diagnostic and therapeutic agents or biosensors for a majority of human disease. However, the limitations of the present scFv antibody in terms of stability, solubility, and affinity are challenging to produce by traditional antibody screening and expression formats. We describe here a feasible strategy for creating the green fluorescent protein (GFP)-based antibody. Complementarity-determining region 3 (CDR3), which retains the antigen binding activity, was introduced into the structural loops of superfolder GFP, and the result showed that CDR3-inserted GFP displayed almost the same fluorescence intensity as wild-type GFP, and the purified proteins of CDR3 insertion showed the similar binding activity to antigen as the corresponding scFv. Among of all of the CDRs, CDR3s are responsible for antigen recognition, and only the CDR3a insertion is the best format for producing GFP-based antibody binding to specific antigen. The wide versatility of this system was further verified by introducing CDR3 from other scFvs into loop 9 of GFP. We developed a feasible method for rapidly and effectively producing a high-affinity GFP-based antibody by inserting CDR3s into GFP loops. Further, the affinity can be enhanced by specific amino acids scanning and site-directed mutagenesis. Notably, this method had better versatility for creating antibodies to various antigens using GFP as the scaffold, suggesting that a GFP-based antibody with high affinity and specificity may be useful for disease diagnosis and therapy.     

Effects of somatic mutations on CDR loop flexibility during affinity maturation

Prior studies suggest that antibody affinity maturation is achieved, in part, via prearranging the CDRs for binding. The implication is that the entropy cost of binding is reduced and that this rigidification occurs as a consequence of somatic mutations during maturation. However, how these mutations modulate CDR flexibility is unclear. Here, molecular dynamics simulations captured CDR flexibility differences between four mature antibodies (7G12, AZ28, 28B4, and 48G7) and their germline predecessors. Analysis of their trajectories: (1) rationalized how mutations during affinity maturation restrict CDR motility, (2) captured the equilibrium between bound and unbound conformations for the H3 loop of unliganded 7G12, and (3) predicted a set of new mutations that, according to our simulations, should diminish binding by increasing flexibility.     

Crystal structure of a T cell receptor Valpha11 (AV11S5) domain: new canonical forms for the first and second complementarity determining regions.

We describe the X-ray crystallographic structure of a murine T cell receptor (TCR) Valpha domain ("Valpha85.33"; AV11S5-AJ17) to 1.85 A resolution. The Valpha85.33 domain is derived from a TCR that recognizes a type II collagen peptide associated with the murine major histocompatibility complex (MHC) class II molecule, I-A(q). Valpha85.33 packs as a Valpha-Valpha homodimer with a highly symmetric monomer-monomer interface. The first and second complementarity determining regions (CDR1 and CDR2) of this Valpha are shorter than the CDRs corresponding to the majority of other Valpha gene families, and three-dimensional structures of CDRs of these lengths have not been described previously. The CDR1 and CDR2 therefore represent new canonical forms that could serve as templates for AV11 family members. CDR3 of the Valpha85.33 domain is highly flexible and this is consistent with plasticity of this region of the TCR. The fourth hypervariable loop (HV4alpha) of AV11 and AV10 family members is one residue longer than that of other HV4alpha regions and shows a high degree of flexibility. The increase in length results in a distinct disposition of the conserved residue Lys68, which has been shown in other studies to play a role in antigen recognition. The X-ray structure of Valpha85.33 extends the database of canonical forms for CDR1 and CDR2, and has implications for antigen recognition by TCRs that contain related Valpha domains.     

Fine mapping of the antigen–antibody interaction of scFv215, a recombinant antibody inhibiting RNA polymerase II from Drosophila melanogaster

A bacterially expressed single chain antibody (scFv215) directed against the largest subunit of drosophila RNA polymerase II was analysed. Structure and function of the antigen binding site in scFv215 were probed by chain shuffling and by site‐specific mutagenesis. The entire variable region of either the heavy or light chain was replaced by an unrelated heavy or light chain. Both replacements resulted in a total loss of binding activity suggesting that the antigen binding site is contributed by both chains. The functional contributions of each complementarity determining region (CDR) were investigated by site specific mutagenesis of each CDR separately. Mutations in two of the CDRs, CDR1 of light chain and CDR2 of heavy chain, reduced the binding activity significantly. Each of the amino acids in these two CDRs was replaced individually by alanine (alanine walking). Seven amino acid substitutions in the two CDRs were found to reduce the binding activity by more than 50%. The data support a computer model of scFv215 which fits an epitope model based on a mutational analysis of the epitope suggesting an alpha‐helical structure for the main contact area. Copyright © 1999 John Wiley & Sons, Ltd.     

Ab initio structure prediction of the antibody hypervariable H3 loop

Antibodies have the capability of binding a wide range of antigens due to the diversity of the six loops constituting the complementarity determining region (CDR). Among the six loops, the H3 loop is the most diverse in structure, length, and sequence identity. Prediction of the three‐dimensional structures of antibodies, especially the CDR loops, is an important step in the computational design and engineering of novel antibodies for improved affinity and specificity. Although it has been demonstrated that the conformation of the five non‐H3 loops can be accurately predicted by comparing their sequences against databases of canonical loop conformations, no such connection has been established for H3 loops. In this work, we present the results for ab initio structure prediction of the H3 loop using conformational sampling and energy calculations with the program Prime on a dataset of 53 loops ranging in length from 4 to 22 residues. When the prediction is performed in the crystal environment and including symmetry mates, the median backbone root mean square deviation (RMSD) is 0.5 Å to the crystal structure, with 91% of cases having an RMSD of less than 2.0 Å. When the prediction is performed in a noncrystallographic environment, where the scaffold is constructed by swapping the H3 loops between homologous antibodies, 70% of cases have an RMSD below 2.0 Å. These results show promise for ab initio loop predictions applied to modeling of antibodies. © 2012 Wiley Periodicals, Inc.     

The versatility of the αβ T‐cell antigen receptor

The T‐cell antigen receptor is a heterodimeric αβ protein (TCR) expressed on the surface of T‐lymphocytes, with each chain of the TCR comprising three complementarity‐determining regions (CDRs) that collectively form the antigen‐binding site. Unlike antibodies, which are closely related proteins that recognize intact protein antigens, TCRs classically bind, via their CDR loops, to peptides (p) that are presented by molecules of the major histocompatibility complex (MHC). This TCR‐pMHC interaction is crucially important in cell‐mediated immunity, with the specificity in the cellular immune response being attributable to MHC polymorphism, an extensive TCR repertoire and a variable peptide cargo. The ensuing structural and biophysical studies within the TCR‐pMHC axis have been highly informative in understanding the fundamental events that underpin protective immunity and dysfunctional T‐cell responses that occur during autoimmunity. In addition, TCRs can recognize the CD1 family, a family of MHC‐related molecules that instead of presenting peptides are ideally suited to bind lipid‐based antigens. Structural studies within the CD1‐lipid antigen system are beginning to inform us how lipid antigens are specifically presented by CD1, and how such CD1‐lipid antigen complexes are recognized by the TCR. Moreover, it has recently been shown that certain TCRs can bind to vitamin B based metabolites that are bound to an MHC‐like molecule termed MR1. Thus, TCRs can recognize peptides, lipids, and small molecule metabolites, and here we review the basic principles underpinning this versatile and fascinating receptor recognition system that is vital to a host's survival.     

Length-independent structural similarities enrich the antibody CDR canonical class model

Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach.

To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ～20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing.