Three-Dimensional Model of the BR96 Monoclonal Antibody Variable

Comparison of an antibody model with an X-ray structure: The variable fragment of BR96. Jürgen Bajorath , Steven Sheriff. Proteins: Structure, Functi...
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Bioconjugate Chem. 1994, 5, 213-219

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Three-Dimensional Model of the BR96 Monoclonal Antibody Variable Fragment Jurgen Bajorath Bristol-Myers Squibb Pharmaceutical Research Institute, 3005 First Avenue, Seattle, Washington 98121. Received December 27, 1993”

Molecular modeling was used to build a three-dimensional model of the variable regions of the tumorreactive monoclonal antibody BR96. An immunoconjugate of this antibody with the anticancer drug doxorubicin is currently in a phase I clinical trial for the treatment of solid tumors. A model structure of the BR96 variable fragment was generated to guide site-specific mutagenesis experiments and further improve the affinity of the antibody. The model displayed a distinct groove-type binding site which contained a significant number of aromatic residues. The dimensions and nature of the proposed binding site were consistent with the binding of the Ley tetrasaccharide which was found to bind to BR96. On the basis of the model, some BR96 residues are proposed to be crucial for antigen binding. BR96 and its complex with the Ley determinant have recently been crystallized, and structure determination is currently underway. Therefore, the detailed prediction of the BR96 combining site will soon be assessed, as a “blind test”, based on crystallographic data.

INTRODUCTION The murine mAb BR96 was originally raised against human breast carcinoma cells and was found to bind to a Ley-related antigen (Hellstrom et al., 1990). The Leytetrasaccharide (or determinant) is found on a variety of glycoproteins and glycolipids. The BR96 antigen is expressed at elevated levels (>200 000 molecules/cell) on >80% of human breast, colon, lung, and ovarian carcinomas and, at significantly lower levels, on some differentiated cells of the gastrointestinal epithelium and the pancreas (Hellstrom et al., 1990). Modified Ley’ antigens have been found associated with several human carcinomas (Hakamori et al., 1989). After binding to its antigen, BR96 is rapidly internalized into cells by receptormediated endocytosis and is ultimately degraded in endosomes and lysosomes (Garrigues et al., 1993). A chimeric form of BR96 was constructed by homologous recombination (Fell et al., 1989). The BR96 variable regions were cloned and sequenced, and the BR96 immunoglobulinVLwas identified as a member of the murine K class I1 family and the VH as a member of the V~7183 gene family (McAndrewet al., to be published). A chemical conjugate of chimeric BR96 with the anticancer drug doxorubicin was prepared (Willner et al., 1993; Trail et al., 1993). This immunoconjugate was found to induce complete regression of human carcinoma xenografts growing subcutaneously in athymic mouse and rat models (Trail et al., 1993) and is currently the subject of clinical trials. Here, the generation and analysis of a three-dimensional BR96 model is reported. This model was generated using comparative model building (Greer, 1990; Bajorath et al., 1993),canonical CDR loop conformations (Chothia et al., 1989),and conformational search calculations (Bruccoleri et al., 1988). The aim of this study was (a) to predict, prior to crystallographic analysis, the three-dimensional Abstract publishedin Advance ACSAbstracts, April 1,1994. Abbreviations: A, angstrom; CDR, complementaritydetermining region; Fv, variable fragment; FRD, framework determinant; Ley, Lewis-Y; mAb, monoclonalantibody; rms, root mean square; VH, variable heavy chain; VL,variable light chain. @

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structure of a novel antibody combining site and (b) to characterize the geometry and chemical nature of the antigen binding site of BR96. This latter analysis has enabled us to select BR96 binding site residues thought be important for antigen binding and has provided the basis for mutagenesis studies. A detailed prediction of an antibody combining site requires a discussion of the principal opportunities and limitations of such modeling. Different variable light and variable heavy chain structures can be combined, as structural templates, on the basis of the presence of highly conserved residues at the VL-VH domain interface (Novotny and Sharp, 1992). The conformations of canonical CDR loops can be predicted with some confidence (Chothia et al., 1989), and, in some cases, conformational search has successfully been used to reproduce CDR loop conformations, including the noncanonical H3 loop (Bruccoleri et al., 1988; Bajorath and Fine, 1992). In combination, these techniques allow an approximation of the architecture and nature of a novel antibody combining site to be made. At the same time, current modeling methods are insufficient to allow the detailed prediction of antibody-antigen interactions or the assessment of conformationalchangesin antibodies upon antigen binding (Bhat et al., 1990, Wilson and Stanfield, 1993; Stanfield et al., 1993). The BR96 model structure shows that BR96 displays a very distinctive groove-type binding site architecture with a prevalence of aromatic residues. On the basis of the dimensions of the groove, all four monosaccharideunits of the Ley tetrasaccharide are likely to be involved in the binding, and selected tyrosine residues in BR96 are thought to be crucial for the interaction with Ley. It is suggested that CDR loop L2 does not participate in antigen binding. Recently, X-ray suitable crystals were obtained for the BR96 Fab fragment and for its complex with the Ley tetrasaccharide (Chang et al., 1994), and refined crystallographic coordinates will soon become available (S. Sheriff, personal communication). This makes the prediction of the BR96 combining site particularly attractive since we expect to soon have the opportunity to directly assess this prediction by comparison with a crystallographic model. Such “blind tests” (Chothia et al., 1986; 0 1994 American Chemical Society

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Chothia et al., 1989;Eigenbrot et al., 1993) which are still rare in the field of antibody modeling make it possible to assess the quality of structural predictions and, therefore, contribute to the assessment and improvement of predictive methods. Equally important, it will be possible to answer the question whether the model-based analysis of the BR96 combining site and the conclusions regarding carbohydrate binding to BR96 were valid. METHODS

The model structure of the BR96 variable regions was constructed using a strategy which included structurebased predictions and conformational search (Bajorath and Fine, 1992). In the first step, structural templates for the Fv framework regions were selected based on sequence similarity, and necessary residue replacements were carried out. In the second step, main-chain and side-chain conformations were included for those CDR loops which could unambiguously be assigned to known canonical conformations (Chothia et al., 1989). CDR loops which could not be modeled using known structural motifs were aproximated by conformational search calculations (Bruccoleri et al., 1988). Finally, the stereochemistry and intramolecular contacts of the initial model were refined by constrained energy minimization. This modeling protocol is not automated and requires interactive model building. In the following text, the different stages of the modeling procedure are described in more details. Rees and colleagues have developed an automated method (Martin et al., 1989; 1991) which also combines structurebased predictions of CDR loops with conformational search. The details of this method will be discussed later on. Computer graphic model building was carried out using Insight11 (Insight 11, Version 2.0.0, Molecular Modeling Program, Biosym Technologies, Inc., San Diego). For energy minimization calculations, the Discover program (Discover, Version 2.7, Molecular Mechanics Program, Biosym Technologies, Inc., San Diego) was used. Conformational search calculations (Bruccoleri et al., 1988) were carried out with CONGEN (Vers. 2, R. E. Bruccoleri and Bristol-Myers Squibb Co., 1991). For modeling, the antibody combining site was divided into framework regions and the CDR loops according to Chothia and Lesk (Chothia and Lesk, 1987; Chothia et al., 1989). The confirmed sequence of the BR96 variable regions was made available by Dr. S. McAndrew, Bristol-Myers Squibb, Seattle. The Brookhaven Protein Databank (Bernstein et al., 1977), including prerelease entries, was searched for framework structures with high sequence similarity to the BR96 variable regions. The crystallographic resolution and the degree of refinement were considered as additional criteria for the selection of template structures. The VL and VH chains of different antibodies were selected and combined based on a superposition of the most conserved structural framework segments (Novotny and Sharp, 1992). The conformations of five CDR loops (Ll-L3; the first, second, and third CDR loop of the VL chain; H1 and H2, the first and second CDR loop of the VH chain) were assigned to canonical structure types (Chothia et al., 1989). On the basis of these assignments, canonical (crystallographic) CDR loop conformations were selected and included in the model using interactive computer graphics. Often, CDR loops of antibodies different from the chosen VH or VL template structures are selected. It is then required to splice the backbone of these CDR loops into

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the adjacent framework regions. This is accomplished using the SpliceLoop feature of Insight’s Biopolymer module following superposition of the five N- and Cterminal framework residues of the loop on the corresponding framework residues of the structural template. The conformation of the noncanonical H3 CDR loop was approximated by systematic conformational search using CONGEN. Due to possible canonical conformation ambiguity, alternative H2 loop conformations were generated by conformationalsearch using a previously described protocol (Bruccoleri et al., 1988). Side-chain replacements within framework regions were carried out in conformations as similar as possible. Sidechain replacements within the canonical CDR loops were modeled according to the side-chain conformations of residues a t corresponding positions in other CDR loops belonging to the same canonical structure class. The sidechain conformations in the noncanonical H3 loop were modeled using iterative conformational search. The stereochemistry of the BR96 model structure was refined with a constrained energy minimization protocol using a distance-dependent dielectric constant (4r) and a 14-A cutoff distance for nonbonded interactions. Initially, harmonic constraints of 20 kcal/mol/A2 were applied to all protein backbone atoms but were subsequently reduced to 10 kcal/mol/A2. The minimization was carried out until the rms derivative of the energy function was approximately 2 kcal/mol/A. At this stage of the minimization, the average protein backbone rms deviation from the template structures was less than 0.3 A. The H3 loop, which lacked any crystallographic template, was excluded from the rms comparison. The coordinates of the BR96 model structure were deposited, prior to crystallography of BR96, with Dr. R. Stenkamp, Department of Biological Structure, University of Washington, Seattle, WA, and Dr. S. Sheriff, Department Macromolecular Crystallography, Bristol-Myers Squibb, Princeton, NJ. The a carbon coordinates for all 230 residues of the BR96 model are given in Table 1 (supplementary material). RESULTS

The BR96 Model Structure. Structural templates for the BR96 V regions were selected based on sequence similarity searches in the Brookhaven Protein Data Bank. The VLchain of BR96 is closely related (-87 76 sequence identity) to the fluorescein binding mAb 4-4-20 (Herron et al., 1989) which is only available in complex with fluorescein. The 4-4-20 VL chain was used as template structure for VL chain modeling. Coordinates of 4-4-20 refined to 1.75 A resolution were a generous gift of Dr. J. Herron. The VH chain sequence of BR96 was found to share -77% identity with the VH chain of 17/9 (Rini et al., 1992). The structure of 17/9 is available at 2.0-A resolution in uncomplexed form and at 2.7-A resolution in antigen-bound (peptide-bound) form. The unbound form was, therefore, selected as structural template for the BR96 VH chain. All parts of the crystallographic structure which were found to undergo some conformational changes upon antigen binding (Rini et al., 1992) were deleted prior to model building. On the basis of these selections, the BR96 model should, in principle, resemble the antigen-bound form of BR96 more closely than its uncomplexed form. The selected template structures were combined to a composite Fv template after superposition of the most conserved residues in antibody variable regions (Novotny and Sharp, 1992). Included in the superposition were the backbone of residues L40-L43, L91-L93, H36-

BR96 Monoclonal Antibody Variable Fragment

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BR9 6 G L D D G A W F A Y Figure 1. CDR loop sequences in BR96. The sequences of the five canonical CDR loops (Ll-L3, Hl-H2) (Chothia et al., 1989) and of the noncanonical H3 loop in BR96 are shown and numbered according to Kabat and Wu (1987).CDR loop H3 is defined according to Kabat and Wu (1987). The canonical CDR loops L1 to L3 in BR96 are aligned with the corresponding regions in 4-4-20 (Herron et al., 1989), and CDR loops H1 and H2 in BR96 are aligned with the corresponding loops in 17/9 (Rini et al., 1992). Structural determinant residues for canonical CDR loom in the framework regions (Chothia et al., 1989) are shown in italics. The single-letter code is used for the amino acid residues.

H39, and H96-H98 in 4-4-20 and the corresponding set of residues in 17/9 (L35-L38, L86-L88, H36-H39, and H90-H92). The rms deviation for the superposition of these residues was 0.5 A. Figure 1shows the sequences of the CDR loops in BR96 according to the canonical structure model and the residues in the framework regions which are important for the conformation of single CDR loops (Chothia et al., 1989). The sequence of BR96 CDR loop L2 is identical to 4-4-20. The CDR loop L3 displays a sequence motif consistent with canonical structure class 1(Chothia et al., 1989) for both BR96 and 4-4-20. CDR loops L1 in BR96 and 4-4-20 are unusually long but have the same length. BR96 displays structural determinant residues consistent with a canonical structure class 4 (Chothia et al., 1989). The L1 loops in 4-4-20 and BR96 are, therefore, similar. It should be considered, however, that the conformation of the tip of such long L1 loops (here with a six residue insertion relative to canonical structure class 1)may not be predictable (Steipe et al., 1992) since structural stabilization of the framework-distant portion of these loops is essentially absent. The nonstabilized portions of these loops can be expected to be somewhat flexible in their conformation. The CDR loops H1 in 17/9 and BR96 belong to canonical structure class 1. The four CDR loops L1-L3 and H1 could be unambiguously assigned to known canonical structure types. On the basis of the canonical assignments, it was possible to include the backbone of the three light chain CDR loops in 4-4-20 and the backbone of the H1 loop in 17/9 as templates for the corresponding CDR loops in BR96. Therefore, loop splicing was not required for these CDR loops in BR96.

An unambiguous assignment to a known canonical conformation was not possible for CDR loop H2 in BR96 although the loop is four residues long and displays a sequence motif consistent with a canonical conformation type 3 (Chothia et al., 1989). H2 loops belonging to this canonical structure type usually have a glycine residue at position 54 in the loop (capable of adopting unusual cpl+ torsion angles) and an arginine as structural determinant a t position 71 in the framework. H2 in the crystallographic structure of 17/9appears to adopt a canonical conformation type 3, although 17/9has three glycine residues a t positions 53-55. BR96 has two glycines a t positions 53 and 54, both of which may adopt unusual p/+ torsion angles and may have a local conformation different from the canonical structure. The backbone conformations of H2 in 1719was included in the BR96 model as a first approximation, and an alternative BR96 conformation of H2, including the six VH residues 52-56, was generated using CONGEN conformational search calculations. The search produced 36 H2 conformations with acceptable conformational energies, with three of these conformations being within 2 kcal/mol of the energy minimum. The conformation with smallest solvent-accessible surface within this energy interval was selected. In contrast to the canonical conformation the selected conformation shows that the glycine at position 54 is in acceptable cpl+ regions but that the glycine at position 53 has usually unacceptable cpl+ torsional angles. This suggests the possibility of alternative H2 conformations in BR96. The backbone rms deviation between the H2 conformation found in 1719 and the CONGEN-generated H2 conformation in BR96 is relatively small, approximately 1.2 A.

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The noncanonical H3 loop in BR96 was modeled using conformational searching. The conformational search over H3 was carried out as the final step of model building in the presence of the modeled framework regions and all CDR loops. A total of 145 conformations were generated but only two of these were within 10 kcal/mol of the energy minimum. The two loop conformations were similar (backbone rms of 0.35 A). The energy minimum conformation was included in the model. The stereochemistry and the nonbonded interactions in the initial model were improved by application of a constrained energy minimization protocol. In the final model, backbone rms deviations relative to the crystallographic templates, excluding the CDR loops, were less than 0.3 A. Proposed Architecture of the BR96 Combining Site. Figure 2 (top left) shows a stereo representation of the a carbon trace of the BR96 Fv model. The conformations of the single CDR loops can be seen and the geometry of the antigen-binding site proposed. The space-filling representation inFigure 2 (top right) emphasizes the most prominent feature of this combining site, the groove-type architecture. The architecture of the groove is determined by interactions of the CDR loops L1, L3, and H3. Residues of CDR loops H2, and to a lesser extent H1, form the bottom of the groove. BR96 has an average length H3 loop (10 residues) and a long L1 loop (12 residues). Interactions between these loops significantly contribute to the gross architecture of the binding site. The other prominent feature of the BR96 binding site is the significant number of aromatic residues which participate in the formation of the groove. These residues are depicted in Figure 2 (bottom right). Implications for Antigen Binding. CDR loop L2 does not participate in the formation of the groove and is, therefore, not expected to be involved in antigen binding. We believe, as well as others (Bundle and Young, 1992), that the accuracy of current predictive methods is not sufficient to propose protein-carbohydrate complexes in detail. However, simple docking studies with model-built Ley conformers suggest that the BR96 binding site groove is sufficiently large to bind all four monosaccharide units of the Ley determinant. These studies also allow the identification of a number of residues in BR96 which may contact the carbohydrate. The following residues in BR96 are proposed to be likely carbohydrate contact residues and, therefore, thought to be important for antigen binding: L1, His31, Asn3la, Asn3lb, Tyr32; L3, Phe96; H1, Tyr33, Tyr35; H2, Tyr50, Gln52a, Asp58; H3, Ala100). The analysis suggests that H3 residues in BR96 do not contribute significant side-chain contacts to the BR96Ley interactions. Furthermore, it should be noted that four of the BR96 residues thought to be important for antigen binding (Tyr33H,Tyr35H, Trp50H, and Asp58H) are, according to the definition of Chothia and Lesk (19871, not CDR but framework residues. On the basis of the architecture of the BR96 binding site, these residues participate in the formation of the groove. The analysis of the three-dimensional model is essential for the selection of these residues. DISCUSSION

The BR96 Fv fragment was modeled with an emphasis on preference for structure-based predictions. A conformational search has been applied to approximate the conformations of CDR loops only when the assignment to known conformations was potentially ambiguous (H2) or impossible (H3). The identification of canonical conformational motifs for five of the six CDR loops in antibodies

Bajorath

by Chothia, Lesk, and colleagues (Chothiaand Lesk, 1987; Chothia et al., 1989) has much enhanced the ability to carry out knowledge-based predictions of antibody combining sites. Canonical CDR loop motifs represent defined classes of conformations which are found in antibody crystal structures and are determined by the presence of a few key residues within the loop or within the framework regions. These motifs have been shown to be largely insensitive to sequence variations a t other positions (Chothia et al., 1989). Therefore, five of six CDR loops in antibodies with unknown structure can frequently be assigned to known canonical conformations on the basis of the analysis of their sequences. In contrast, canonical conformations have not yet been identified for CDR loop H3. Approximation of H3 conformations in antibody modeling therefore remains usually dependent on the application of ab initio techniques such as conformational search. Major problems of structure-based CDR loop predictions presently include (a) the inability to identify canonical motifs for H3, (b) the remaining ambiguities in the assignment of sequences to known structural motifs, (c) the still limited database of crystallographic antibody structures refined to high resolution, and (d) the inability to take potential interactions between CDR loops into account. The major current problems of CDR loop predictions on the basis of conformational search are (a) the selection of the “right”conformation from an ensemble of generated conformations and (b) the computer time required for conformational search over longer loops. A fully automated method to model CDR loop conformations by combining structure-based predictions and conformational search has been introduced by Rees and co-workers (Martin et al., 1989; 1991). These researchers essentially use the ( a carbon distance matrix) loop search technique of Jones and Thirup (1986) to extract loop conformations from the Brookhaven Protein Data Bank. For conformational search the CONGEN program (Bruccoleri and Karplus, 1987; Bruccoleri et al., 1988) is used. CDR loops consisting of up to five residues are modeled using CONGEN. CDR loops consisting of six or seven residues are modeled using the database loop search. For CDR loops of eight or more residues, database loop search is first applied, and then the midsection of the loop is remodeled with CONGEN. Generated conformations are filtered using solvent-modified potential functions (Martin et al., 1989). The approach depends on the assumptions (a) that the conformational space available to loops consisting of six to seven residues is sufficiently represented in the currently available protein structures, (b) that correct N- and C-terminal base segments for loops of eight or more residues can be extracted, and (c) that solvent-modified energy screening of generated conformations is capable of selecting the “right” conformation. Rees and colleagues also suggest the selection of framework regions based on sequence similarity and, furthermore, the inclusion of the assignment of CDR loops to canonical conformations if possible (Martin et al., 1991). In the case of BR96, it was possible to identify structural templates for the framework regions which share significant sequence similarity. CDR loops L2, L3, and H1 were found to display well-established canonical conformations. Some uncertainty remains concerning the conformation of the distal part of CDR loop L1 (Steipe et al., 1992) and the canonical assignment of H2 for which an alternative (albeit similar) conformation was generated. This uncertainty is in spite of the fact that both CDR loops L1 and H2 are related to known structures. No H3 loop with identical length and significant sequence similarity to

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BR96 was found in the database of known antibody crystal structures, and therefore, conformational search calculations were carried out. To evaluate the conformational space available to H3 as well as its spatial position, we have simulated the conformation of H3 within the structural context provided by the BR96 model. Crystallographic structures of the carbohydrate binding antibodies 5539 (Suh et al., 1986) and Se155-4 (Cygler et al., 1991) show characteristic cavities or grooves as a prominent feature of their binding sites. The groove-type architecture proposed for the BR96 combining site is consistent with these crystallographic structures and represents a prominent feature of the BR96 model. The accuracy of current model building methodology is insufficient to explore the molecular details of antibodycarbohydrate interactions (Bundle and Young, 1992).This is primarily due to the conformational flexibility of carbohydrates and to the fact that the role of water molecules in carbohydrate-protein interactions (Vyas, 1991; Cygler et al., 1991) is difficult, if not impossible, to analyze in the absence of high-resolution crystallographic data (Bundle and Young, 1992). Analysis of the BR96 model strongly suggests a prevalence of aromatic residues involved in the formation of the binding site. Several of these residues, such as Tyr33H and Tyr50H, are very likely to represent carbohydrate contact residues. Such contacts suggest a different mode of carbohydrate binding than that frequently observed in other carbohydrate binding proteins, where charged and planar side-chains often dominate the interactions (Vyas, 1991). However, aromatic residue-carbohydrate interactions have been observed in the crystal structure of the Se155-4 antibody complexed with its carbohydrate epitope (Cygler et al., 1991). Tyrosine residues are frequently found in CDR loops of antibodies (Padlan, 1991), possibly due to their versatility in forming hydrogen bonds, van der Waals contacts, and aromatic interactions, in addition to their moderate loss of conformational entropy upon antigen binding. The proposed importance of aromatic residues in the formation of the BR96 antigen binding site is another prominent feature of the BR96 model structure. The analysis of a proposed binding site can lead to the identification of residues crucial for antigen binding and may also allow conclusions regarding the nature of the antigen, if unknown, to be made. This was shown for the anticancer antibody L6 (Fell et al., 1992). The presence of a rather flat and irregular combining site was predicted for L6 (Fell et al., 1992). This led to the conclusion that L6 should recognize a protein surface rather than a carbohydrate epitope-a prediction that was subsequently experimentally confirmed (Fell et al., 1992). In contrast, BR96 is proposed to display a very distinct groove-type binding site architecture, consistent with the notion that it binds a carbohydrate antigen. Comparison of crystallographic structures of uncomplexed and antigen-bound antibody fragments has shown that conformational changes occur in antibodies upon antigen binding (Bhat et al., 1990) which can be of significant magnitude (Wilsonand Stanfield, 1993). These changes include segmental motions (Stanfield et al., 1990) and conformational changes of single (Rini et al., 1992)or several (Herron et al., 1991)CDR loops as well as changes in the relative VL-VH domain orientation (Herron et al., 1991; Stanfield et al., 1993). The assessment of these possible conformational changes represents a major problem for antibody modeling attempts. The possibility and magnitude of such effects remains unpredictable and can only be determined by direct comparison of uncomplexed

and complexed structures. In the case of BR96, we may soon have the opportunity to evaluate the detailed prediction of the antibody-combining site with the crystallographic structures of the complexedand uncomplexed antibody and to assess the magnitude of potential conformational changes upon Ley binding. ACKNOWLEDGMENT

The author thanks Dr. Steven McAndrew for providing the sequence of the BR96 variable regions prior to publication. Furthermore, the author thanks Dr. Steven Sheriff and Dr. Jiri Novotny for many discussions and for support and Dr. Peter Senter for his critical review of the manuscript. The author is grateful to Dr. James Herron for providing high-resolution coordinates of 4-4-20 and to Debby Baxter for her help in the preparation of the manuscript. Supplementary Material Available: CY carbon coordinates, sequence, and CDR loops for the BR96 Fv model structure (6 pages). Ordering information is given on any current masthead page. LITERATURE CITED Bajorath, J., and Fine, R. M. (1992) On the use of minimization from many randomly generated loop structures in modeling antibody combining sites. ImmunoMethods I , 137-146. Bajorath, J., Stenkamp, R., and Aruffo, A. (1993) Knowledgebased model building of proteins: Concepts and examples. Protein Sci. 2, 1798-1810. Bernstein, F. C., Koetzle, T. F., Williams, G. J. B., Meyer, E. F., Brice, M. D., Rodgers, J. R., Kennard, O., Shimanouchi, T., and Tasumi, M. (1977) The protein data bank: a computerbased archival file for macromolecular structures. J.Mol. Biol. 112,535-542. Bhat, T. N., Bentley, G. A., Fischmann, T. O., Boulot, G., and Poljak, R. J. (1990). Small Rearrangements in Structures of Fv and Fab Fragments of Antibody D1.3 on Antigen Binding. Nature 347, 483-485. Bruccoleri, R. E., and Karplus, M. (1987). Prediction of folding of short polypeptide segments by uniform conformational sampling. Biopolymers 26, 137-168. Bruccoleri, R. E., Haber, E., and Novotny, J. (1988) Structure of antibody hypervariable loops reproduced by a conformational search algorithm. Nature 335, 564-568. Bundle, D. R., and Young, N. M. (1992) Carbohydrate-protein interactions in antibodies and lectins. Curr. Opin.Struct. Biol. 2, 666-673. Chang, C. Y., Jeffrey, P. D.,Bajorath, J., Hellstrom, I., Hellstrom, K. E., and Sheriff, S. (1994) Crystallization and Preliminary X-ray Analysis of the Monoclonal Anti-Tumor Antibody BR96 and Its Complex with the Ley Determinant. J.Mol. Biol. 235, 372-376. Chothia, C., and Lesk, A. M. (1987) Canonical structures for the hypervariable regions of immunoglobulins. J.Mol. Biol.196, 901-971. Chothia, C., Lesk, A. M., Levitt, M., Amit, A. G., Mariuzza, R. A., Phillips, S. E. V., and Poljak, R. (1986). The Predicted Structure of Immunoglobulin D1.3 and Its Comparison with the Crystal Structure. Science 233, 755-758. Chothia, C., Lesk, A. M., Tramontano, A,, Levitt, M., SmithGill, S. J., Air, G., Sheriff, s.,Padlan, E. A., Davies, D., Tulip, W. R., Colman, P. M., Spinelli, S., Alzari, P. M., and Poljak, R. (1989) Conformations of immunoglobulin hypervariable regions. Nature 342, 877-883. Cygler, M., Rose, D. R., and Bundle, D. R. (1991) Recognition of a Cell-Surface Oligosaccharide of Pathogenic Salmonella by an Antibody Fab Fragment. Science 253, 442-445.

BR96 Monoclonal Antibody Variable Fragment

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