High-affinity human antibodies from phage-displayed synthetic Fab libraries with a single framework scaffold

Phage-displayed synthetic antibody libraries were built on a single human framework by introducing synthetic diversity at solvent-exposed positions within the heavy chain complementarity-determining regions (CDRs). The design strategy of mimicking natural diversity using tailored codons had been validated previously with scFv libraries, which produced antibodies that bound to antigen, murine vascular endothelial growth factor (mVEGF), with affinities in the 100nM range. To improve library performance, we constructed monovalent and bivalent antigen-binding fragment (Fab) libraries, and explored different CDR-H3 diversities by varying the amino acid composition and CDR length. A Fab with sub-nanomolar affinity for mVEGF was obtained from a library with CDR-H3 diversity designed to contain all 20 naturally occurring amino acids. We then expanded the library by increasing the variability of CDR-H3 length and using tailored codons that mimicked the amino acid composition of natural CDR-H3 sequences. The library was tested against a panel of 13 protein antigens and high-affinity Fabs were obtained for most antigens. Furthermore, the heavy chain of an anti-mVEGF clone was recombined with a library of light chain CDRs, and the affinity was improved from low nanomolar to low picomolar. The results demonstrated that high-affinity human antibodies can be generated from libraries with completely synthetic CDRs displayed on a single scaffold.     

Systematic classification of CDR-L3 in antibodies: implications of the light chain subtypes and the VL-VH interface

Antibody modeling is widely used for the analysis of antibody-antigen interactions and for the design of potent antibody drugs. The antibody combining site is composed of six complementarity determining regions (CDRs). The CDRs, except for CDR-H3, which is the most diverse CDR, form limited numbers of canonical structures, which can be identified from the amino acid sequences. A method to classify the CDR-H3 structure from its amino acid sequence was previously proposed. However, since those CDR structures were classified, many more antibody crystal structures have been determined. We performed systematic analyses of the CDR-L3 structures and found novel canonical structures, and we also classified a previously identified canonical structure into two subtypes. In addition, two differently defined canonical structures in the kappa and lambda subtypes were classified into the same canonical structure. We also identified a key residue in CDR-L3, which determines the conformation of CDR-H3. Several analyses of CDR-L3 loops longer than nine residues were performed. These new findings should be useful for structural modeling and are eventually expected to accelerate the design of antibody drugs.     

The diversity of H3 loops determines the antigen‐binding tendencies of antibody CDR loops

Of the complementarity‐determining regions (CDRs) of antibodies, H3 loops, with varying amino acid sequences and loop lengths, adopt particularly diverse loop conformations. The diversity of H3 conformations produces an array of antigen recognition patterns involving all the CDRs, in which the residue positions actually in contact with the antigen vary considerably. Therefore, for a deeper understanding of antigen recognition, it is necessary to relate the sequence and structural properties of each residue position in each CDR loop to its ability to bind antigens. In this study, we proposed a new method for characterizing the structural features of the CDR loops and obtained the antigen‐binding ability of each residue position in each CDR loop. This analysis led to a simple set of rules for identifying probable antigen‐binding residues. We also found that the diversity of H3 loop lengths and conformations affects the antigen‐binding tendencies of all the CDR loops.     

CDR-H3 loop ensemble in solution – conformational selection upon antibody binding

ABSTRACT

We analyzed pairs of protein-binding, peptide-binding and hapten-binding antibodies crystallized as complex and in the absence of the antigen with and without conformational differences upon binding in the complementarity-determining region (CDR)-H3 loop. Here, we introduce a molecular dynamics-based approach to capture a diverse conformational ensemble of the CDR-H3 loop in solution. The results clearly indicate that the inherently flexible CDR-H3 loop indeed needs to be characterized as a conformational ensemble. The conformational changes of the CDR-H3 loop in all antibodies investigated follow the paradigm of conformation selection, because we observe the experimentally determined binding competent conformation without the presence of the antigen within the ensemble of pre-existing conformational states in solution before binding. We also demonstrate for several examples that the conformation observed in the antibody crystal structure without antigen present is actually selected to bind the carboxyterminal tail region of the antigen-binding fragment (Fab). Thus, special care must be taken when characterizing antibody CDR-H3 loops by Fab X-ray structures, and the possibility that pre-existing conformations are present should always be considered.     

Crystal Structure and Computational Modeling of the Fab Fragment from a Protective Anti-Ricin Monoclonal Antibody

Background

Many antibody crystal structures have been solved. Structural modeling programs have been developed that utilize this information to predict 3-D structures of an antibody based upon its sequence. Because of the problem of self-reference, the accuracy and utility of these predictions can only be tested when a new structure has not yet been deposited in the Protein Data Bank.

Methods

We have solved the crystal structure of the Fab fragment of RAC18, a protective anti-ricin mAb, to 1.9 Å resolution. We have also modeled the Fv structure of RAC18 using publicly available Ab modeling tools Prediction of Immunoglobulin Structures (PIGS), RosettaAntibody, and Web Antibody Modeling (WAM). The model structures underwent energy minimization. We compared results to the crystal structure on the basis of root-mean-square deviation (RMSD), template modeling score (TM-score), Z-score, and MolProbity analysis.

Findings

The crystal structure showed a pocket formed mainly by AA residues in each of the heavy chain complementarity determining regions (CDRs). There were differences between the crystal structure and structures predicted by the modeling tools, particularly in the CDRs. There were also differences among the predicted models, although the differences were small and within experimental error. No one modeling program was clearly superior to the others. In some cases, choosing structures based only on sequence homology to the crystallized Ab yielded RMSDs comparable to the models.

Conclusions

Molecular modeling programs accurately predict the structure of most regions of antibody variable domains of RAC18. The hypervariable CDRs proved most difficult to model, particularly H chain CDR3. Because CDR3 is most often involved in contact with antigen, this defect must be considered when using models to identify potential contacts between antibody and antigen. Because this study represents only a single case, the results cannot be generalized. Rather they highlight the utility and limitations of modeling programs.     

Structural classification of CDR-H3 revisited: a lesson in antibody modeling

Among the six complementarity-determining regions (CDRs) in the variable domains of an antibody, the third CDR of the heavy chain (CDR-H3), which lies in the center of the antigen-binding site, plays a particularly important role in antigen recognition. CDR-H3 shows significant variability in its length, sequence, and structure. Although difficult, model building of this segment is the most critical step in antibody modeling. Since our first proposal of the "H3-rules," which classify CDR-H3 structure based on amino acid sequence, the number of experimentally determined antibody structures has increased. Here, we revise these H3-rules and propose an improved classification scheme for CDR-H3 structure modeling. In addition, we determine the common features of CDR-H3 in antibody drugs as well as discuss the concept of "antibody druggability," which can be applied as an indicator of antibody evaluation during drug discovery.     

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.     

Comparison of an antibody model with an X-ray structure: The variable fragment of BR96

A model of the BR96 antibody variable regions is compared to two X-ray structures of a BR96–carbohydrate complex, independently determined after the model was built and analyzed. The comparison illustrates the opportunities and limitations of antibody modeling. Encouraging results were obtained for the prediction of single CDR loop conformations and for the outline of the BR96 antigen binding site. The comparison of CDR loop conformations in the two X-ray structures provides a realistic reference frame for the CDR loop predictions. CDR loop prediction accuracy is lower when not only conformational, but also positional criteria are taken into account.     

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.     

FREAD revisited: Accurate loop structure prediction using a database search algorithm

Loops are the most variable regions of protein structure and are, in general, the least accurately predicted. Their prediction has been approached in two ways, ab initio and database search. In recent years, it has been thought that ab initio methods are more powerful. In light of the continued rapid expansion in the number of known protein structures, we have re‐evaluated FREAD, a database search method and demonstrate that the power of database search methods may have been underestimated. We found that sequence similarity as quantified by environment specific substitution scores can be used to significantly improve prediction. In fact, FREAD performs appreciably better for an identifiable subset of loops (two thirds of shorter loops and half of the longer loops tested) than the ab initio methods of MODELLER, PLOP, and RAPPER. Within this subset, FREAD's predictive ability is length independent, in general, producing results within 2Å RMSD, compared to an average of over 10Å for loop length 20 for any of the other tested methods. We also benchmarked the prediction protocols on a set of 212 loops from the model structures in CASP 7 and 8. An extended version of FREAD is able to make predictions for 127 of these, it gives the best prediction of the methods tested in 61 of these cases. In examining FREAD's ability to predict in the model environment, we found that whole structure quality did not affect the quality of loop predictions. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

CODA: a combined algorithm for predicting the structurally variable regions of protein models

CODA, an algorithm for predicting the variable regions in proteins, combines FREAD a knowledge based approach, and PETRA, which constructs the region ab initio. FREAD selects from a database of protein structure fragments with environmentally constrained substitution tables and other rule-based filters. FREAD was parameterized and tested on over 3000 loops. The average root mean square deviation ranged from 0.78 A for three residue loops to 3.5 A for eight residue loops on a nonhomologous test set. CODA clusters the predictions from the two independent programs and makes a consensus prediction that must pass a set of rule-based filters. CODA was parameterized and tested on two unrelated separate sets of structures that were nonhomologous to one another and those found in the FREAD database. The average root mean square deviation in the test set ranged from 0.76 A for three residue loops to 3.09 A for eight residue loops. CODA shows a general improvement in loop prediction over PETRA and FREAD individually. The improvement is far more marked for lengths six and upward, probably as the predictive power of PETRA becomes more important. CODA was further tested on several model structures to determine its applicability to the modeling situation. A web server of CODA is available at http://www-cryst.bioc.cam.ac.uk/~charlotte/Coda/search_coda.html.     

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.     

HuCAL PLATINUM, a synthetic Fab library optimized for sequence diversity and superior performance in mammalian expression systems

This article describes the design of HuCAL (human combinatorial antibody library) PLATINUM, an optimized, second-generation, synthetic human Fab antibody library with six trinucleotide-randomized complementarity-determining regions (CDRs). Major improvements regarding the optimized antibody library sequence space were implemented. Sequence space optimization is considered a multistep process that includes the analysis of unproductive antibody sequences in order to, for example, avoid motifs such as potential N-glycosylation sites, which are undesirable in antibody production. Gene optimization has been used to improve expression of the antibody master genes in the library context. As a result, full-length IgGs derived from the library show both significant improvements in expression levels and less undesirable glycosylation sites when compared to the previous HuCAL GOLD library. Additionally, in-depth analysis of sequences from public databases revealed that diversity of CDR-H3 is a function of loop length. Based upon this analysis, the relatively uniform diversification strategy used in the CDR-H3s of the previous HuCAL libraries was changed to a length-dependent design, which replicates the natural amino acid distribution of CDR-H3 in the human repertoire. In a side-by-side comparison of HuCAL GOLD and HuCAL PLATINUM, the new library concept led to isolation of about fourfold more unique sequences and to a higher number of high-affinity antibodies. In the majority of HuCAL PLATINUM projects, 100-300 antibodies each having different CDR-H3s are obtained against each antigen. This increased diversity pool has been shown to significantly benefit functional antibody profiling and screening for superior biophysical properties.     

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.     

Investigating the properties of Bacillus thuringiensis Cry proteins with novel loop replacements created using combinatorial molecular biology

Cry proteins are a large family of crystalline toxins produced by Bacillus thuringiensis. Individually, the family members are highly specific, but collectively, they target a diverse range of insects and nematodes. Domain II of the toxins is important for target specificity, and three loops at its apex have been studied extensively. There is considerable interest in determining whether modifications in this region may lead to toxins with novel specificity or potency. In this work, we studied the effect of loop substitution on toxin stability and specificity. For this purpose, sequences derived from antibody complementarity-determining regions (CDR) were used to replace native domain II apical loops to create "Crybodies." Each apical loop was substituted either individually or in combination with a library of third heavy-chain CDR (CDR-H3) sequences to create seven distinct Crybody types. An analysis of variants from each library indicated that the Cry1Aa framework can tolerate considerable sequence diversity at all loop positions but that some sequence combinations negatively affect structural stability and protease sensitivity. CDR-H3 substitution showed that loop position was an important determinant of insect toxicity: loop 2 was essential for activity, whereas the effects of substitutions at loop 1 and loop 3 were sequence dependent. Unexpectedly, differences in toxicity did not correlate with binding to cadherins--a major class of toxin receptors--since all Crybodies retained binding specificity. Collectively, these results serve to better define the role of the domain II apical loops as determinants of specificity and establish guidelines for their modification.     

从抗TNF抗体的CDR肽库中获得拮抗TNF的短肽

为设计来自抗体的短肽 ,以抗肿瘤坏死因子 (TNF)嵌合抗体 (cA2 )CDRs为模板 ,在其两侧各加 3个随机氨基酸残基 ( X3 CDR X3 ) ,构建了 6个以CDR为基础的肽库 .经过 3轮亲和选择 ,挑取单克隆 ,进一步经ELISA检测TNF阳性噬菌体克隆 ,分离得到 7个ELISA阳性较好的噬菌体肽克隆 ,分别命名为CDR2L1、CDR2L2、CDR2L3、CDR1L1、CDR2H1、CDR3H1、CDR3H 2 .应用MTT方法 ,检测 7个克隆对TNF生物学活性的拮抗作用 .结果显示 :来自CDR2L ,CDR3H肽库中的CDR2L2、CDR2L3,CDR3H2噬菌体肽具有明显的拮抗TNF诱导L92 9细胞的细胞毒作用 ,其中以CDR2L2噬菌体肽的拮抗活性最强 .而来源于CDR1L ,CDR2H肽库的CDR1L1和CDR2H1噬菌体肽和来自CDR2L ,CDR3H肽库中的CDR2L1和CDR3H1噬菌体肽没有明显的拮抗TNF作用 .研究结果初步表明 :从cA2抗体CDR肽库中筛选得到的噬菌体CDR模拟肽具有亲本抗体相似的结合活性和生物学效应 ,从而为开发已知抗体 (特别是治疗用抗体 )CDR为基础的肽药物创建一个技术平台奠定基础     

The X-ray crystal structure of a Valpha2.6Jalpha38 mouse T cell receptor domain at 2.5 A resolution: alternate modes of dimerization and crystal packing.

We describe here the structure of a murine T cell receptor (TCR) Valpha2.6Jalpha38 (TCRAV2S6J38) domain, derived from a T cell hybridoma with specificity for the H-2Ddmajor histocompatibility complex class I molecule bound to a decamer peptide, P18-I10, from the HIV envelope glycoprotein gp120, determined by X-ray crystallography at 2.5 A resolution. Unlike other TCR Valpha domains that have been studied in isolation, this one does not dimerize in solution at concentrations below 1 mM, and the crystal fails to show dimer contacts that are likely to be physiological. In comparison to other Valpha domains, this Valpha2.6 shows great similarity in the packing of its core residues, and exhibits the same immunoglobulin-like fold characteristic of other TCR Valpha domains. There is good electron density in all three complementarity-determining regions (CDRs), where the differences between this Valpha domain and others are most pronounced, in particular in CDR3. Examination of crystal contacts reveals an association of Valpha domains distinct from those previously seen. Comparison with other Valpha domain structures reveals variability in all loop regions, as well as in the first beta strand where placement and configuration of a proline residue at position 6, 7, 8, or 9 affects the backbone structure. The great variation in CDR3 conformations among TCR structures is consistent with an evolving view that CDR3 of TCR plays a plastic role in the interaction of the TCR with the MHC/peptide complex as well as with CDR3 of the paired TCR chain.     

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.     

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.