1Department of Chemistry and National Center for Supercomputing Applications, University of Illinois at UrbanaChampaign, Urbana, IL 61801 and 3Department of Bioengineering, Department of Chemistry and Biochemistry and San Diego Supercomputing Center, University of California at San Diego, La Jolla, CA 92037, USA
4 To whom correspondence should be addressed. E-mail: shankar{at}ucsd.edu
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Abstract |
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Keywords: antibodyantigen complex/antibodyhapten complex/immunoglobulin superfamily/molecular recognition
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Introduction |
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Point mutants at combining site residues of the Ab or antigen generally result in large specificity losses (Knossow et al., 1984; Alegre et al., 1992
; Chacko et al., 1995
). Charged residues frequently mediate Abantigen association, hence pH, ionic strength and the presence of cosolutes affect association specificity. Continuum electrostatic theory has been used to study a wide variety of Abantigen and Abhapten complexes (for a review, see Gibas et al., 2000
). The method provides detailed pKa data for each titratable residue, in addition to overall pH-dependent energetics. We have thoroughly examined two Ablysozyme complexes (Slagle et al., 1994
; Gibas et al., 1997
) and one Abhapten complex (Livesay et al., 1999
) using such methods. In all three examples, association is mediated by complementary chargecharge interactions at the combining site. Therefore, the local environment surrounding the combining site has a significant effect on the association energetics. Factors affecting association energetics include minor structural rearrangements, buried interfacial area, dielectric environment of key residues and geometry of the interacting residues. Comparisons of calculated pH-dependent behavior show good agreement with experimental results.
In addition to providing an overall titration profile, continuum methods quantitatively assess the relative influence of individual charged groups. Models of site-directed mutants have been constructed to probe the influence of each charged interface residue (Slagle et al., 1994; Gibas et al., 1997
; Livesay et al., 1999
). Examination of the electrostatic contribution to the association energy in mutant complexes confirms that charge complementarity at the combining site is an important requirement for antigen binding. Also, aromatic
-stacking and van der Waals contacts between Ab and antigen residues contribute to specificity.
Experimental structures for a host of Abantigen complexes have now been solved, allowing the comprehensive investigation of a wide variety of Abantigen interfaces. Vargas-Madrazo et al. (1995) used the canonical structure model to conclude that the antibody structural repertoire is limited to a small number of canonical structural classes. Two sets of preferential canonical classes were identified, each associated with a particular antigen specificity. MacCallum et al. (1996)
compared the topology of ten structural pairs of antigen-bound and apo Ab structures. They found that Ab binding sites could be divided into four topographical classes: concave, moderately concave, rigid and planar. Further, four of the 10 binding sites changed class on antibody binding. Several other studies have attempted to analyze antigen specificity vis-à-vis a variety of phenomena, including somatic hypermutation (Ramirez-Benitez and Almagro, 2001
), CDR length and sequence composition (Collis et al., 2003
; Almagro, 2004
) and conformational changes on binding (Pellequer et al., 1999
). Here, we used continuum electrostatic methods to probe thoroughly the electrostatic association requirements of a wide variety Abprotein and Abhapten complexes. Residues that show significant changes in pKa values on complex formation are scrutinized to understand the chemical basis of each shift. Further, results from all complexes are compared in order to identify conserved association motifs.
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Materials and methods |
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The continuum electrostatic methods used here are included in the University of Houston Brownian Dynamics (UHBD) suite of programs (Madura et al., 1995). For all calculations, partial charges were taken from the CHARMM parameter set (Brooks et al., 1983
) and radii from the Optimized Parameters for Liquid Systems (Jorgensen and Tirado-Rives, 1988
). Partial charges of non-protein substrates were calculated using Gaussian 96 with the 631G basis set. Model pKa values were taken from Antosiewicz et al. (1994)
. Temperature, ionic strength and ionic radius remained constant throughout all calculations at 298 K, 150 mM and 2.0 Å, respectively. A solvent and interior dielectric of 80 and 20, respectively, (Antosiewicz et al., 1994
; Gibas and Subramaniam, 1996
) were used throughout. Finite grid spacing began at 1.5 Å and was focused to 1.2, 0.75 and 0.25 Å. Using a probe radius of 1.4 Å, the boundary between solvent and protein dielectrics was differentiated using the method of Shrake and Rupley (1957)
.
Antibody structures
Ab structures used in the pKa calculations are modified versions of the coordinates available from the Protein Data Bank (Bernstein et al., 1977). Currently, there are 459 Ig structures stored within the Protein Data Bank with resolutions better than 3.0 Å; 348 of those are solved in the antigen-bound form. However, many of these structures are either redundant or theoretical models. A non-redundant dataset (eliminating mutant equivalent structures and theoretical models) reduces the number of structures to 97. In this work, our dataset is composed of 25 Abantigen complexes (13 Abprotein and 12 Abhapten) taken from Ioerger et al. (1999)
(Table I). Figure 1 shows phylogenetic trees that describe the diversity within the entire antibody structural proteome (antigen-bound or otherwise). Figure 1 also clearly indicates that our dataset is representative of that diversity and that general conclusions from our analysis can be made.
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Bioinformatics
Sequence alignment was based on structural superposition using the All-to-All Protein Structure Alignment server from the San Diego Supercomputer Center (Shindyalov and Bourne, 1998). Consensus sequence was determined using CLUSTALW (Thompson et al., 1994
). Probability density functions (PDFs) counted the occurrence of target atoms within a 16 Å sphere about the mean hapten center of mass position. Residue target atoms were either the titrating atom (NZ of Lys; OH for Tyr) or atoms central to resonance-equivalent charged atoms (CG of Asp, CD of Glu, CZ of Arg and CD2 of His). CLUSTALW (Thompson et al., 1994
) was used to align sequences from the complete antibody structural proteome. This alignment was used to compare the results from our representative dataset. Further, our results were compared with the Kabat database using KabatMan (Martin, 1996
). The Kabat numbering scheme is used throughout.
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Results |
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Substrate antigens investigated are divided into two classes, protein-based and small-molecule haptens. Protein antigens are further subdivided into complete structures and fragments. Four of the five complete protein antigens are lysozyme orthologs (all have 129 residues); the remaining one is a histidine-containing protein (85 residues). Protein fragments range in length from 7 to 12 residues and contain nearly identical contacts as the complete proteinantigen complexes. One Ab (1IKF) included here is specific for the cyclic peptide cyclosporin; we classify cyclosporin as a protein fragment. Table II summarizes the interfacial region of each Abantigen complex. In general, there are two less interfacial H-bonds and one less interfacial tyrosine residue in each of the Abprotein fragment complexes. The number of salt bridges per complex (regardless of antigen type) is nearly constant.
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Figure 3 maps calculated pKa shifts to sequence. The shifts are generally isolated to CDRs. In a previous study (Livesay et al., 1999), we found that there is a discrete number of pKa shifts in the monoclonal antibody (mAb) NC6.8. The shifts are localized to titrating residues at the combining site, whereas those further away remain unchanged. This result is generally conserved in all Abantigen complexes investigated here. Figure 4 shows the number of pKa shifts occurring at each position in the alignment. The pKa shifts are isolated to a handful of positions in much the same way as seen in the mAb NC6.8 study.
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The remaining alignment positions undergoing changes in pKa on association are largely isolated to the CDRs. There are significantly more (67.8% more) pKa shifts occurring on the heavy than on the light chain. It follows that there are also more individual alignment positions with higher total pKa shift numbers. These hot-spots are defined as alignment positions with total pKa shifts more than 1.5 standard deviations beyond the average. There are 15 so-called hot-spots on the heavy chain, whereas there are only eight on the light chain. Tyrosine is the consensus residue for five of the 23 hot-spot positions. There are two hot-spots in CDR-H3; one is a highly conserved arginine and the other is an aspartate residue. None of the remaining 16 hot-spots are conserved more than 50%, our criterion for consensus.
Probability density functions
Probability density functions (PDFs) describe the spatial distribution of a particular residue or atom about some target. At close distances (e.g. less than 5 Å), PDFs describe the contact probability between residue and target across our dataset, meaning that PDFs are an efficient way to collate visually multiple structural contact analyses. At larger distances (e.g. 1015 Å), PDFs describe the likelihood of residues being spatially distributed around the substrate beyond normal contact cutoffs. Frequently, conserved features at larger distances describe spatially conserved residues one shell of residues removed from the target. We have used PDFs to probe the conserved spatial distribution of charge across multiple enzyme families and superfamilies (Livesay et al., 2003). In each of the cases investigated, the spatial distribution of charge is conserved within the active site. No conservation in the spatial distribution of charge or the spatial distribution of pKa shifts is observed across our Abantigen dataset. This result is surprising in view of the general importance of acidbase interactions at the Ab-combining site. However, analysis of the spatial distribution of tyrosine residues (specifically, tyrosine hydroxyl oxygens) at the combining site does yield interesting results. Figure 5 indicates that the overall shape of the tyrosine PDFs is conserved. This result advocates that tyrosine structural positions are more conserved than acidic and basic residues.
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Discussion |
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Comparison of the interfacial regions between anti-protein and anti-hapten antibodies reveals few novel results. Numbers of aromatic residues and salt bridges are nearly constant. The average number of hydrogen bonds does, however, vary between anti-hapten (2.4) and anti-protein antibodies (6.2). There is also a 33% increase in pKa shifts from anti-protein to anti-hapten antibodies. These differences are a reflection of the size differences (and therefore contact probability differences) between large protein antigens and small-molecule haptens. Changes in solvent exposure on protein binding also contribute to the increased pKa shift number. Otherwise, no consistent differences leading to Ab specificity between antigen classes are observed.
Combining site tyrosine residues
Complex formation significantly affects the pKa value of five conserved tyrosine residues. These residues are located at L:32, L:36, L:49, H:27 and H:32. The three light-chain tyrosines are highly conserved across our structural dataset (76, 76 and 84%, respectively). The two heavy-chain tyrosines are more variable and commonly substituted by phenylalanine. The tyrosine residue that occurs at L:36, just past CDR-L1, has the most conserved pKa shift of any alignment position. This is noteworthy for three reasons: (1) the residue occurs outside the CDRs; (2) the residue is buried deep in the binding pocket of the Fv fragment; and (3) the residue displays a large amount of conformational freedom (see Figure 6A). Despite the observed conformational variability, the crystallographic temperature factor of each residue is low. The role of the conserved Tyr L:36 appears to be mostly electrostatic. For example, in the mAb NC6.8hapten complex, Tyr L:36 forms a stabilizing dipoledipole interaction with the cyanophenyl moiety of the hapten. The spatial freedom maximizes the electrostatic interactions between the tyrosine residue and substrate (see Figure 6B).
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Interfacial acidic or basic residues are rarely conserved. However, conserved pKa shifts at specific alignment positions are frequently observed. Residue identity at these non-tyrosine hot-spots is indiscriminate. In fact, most are not even conserved enough for a consensus residue to be identified. Analysis of these positions within a sequence alignment of all known antibody structures confirms the generality of this result. Structural scrutiny reveals that residue identity is determined by antigen structural characteristics. Acidic and basic residues tend to arise to satisfy hydrogen bonding, dipoledipole and salt bridge requirements of the antigen.
Unlike most other non-tyrosine hot-spots, H:94 is highly conserved. An arginine residue occurs 76% of the time. Additionally, a conserved pKa shift occurs in 61% of these arginine residues. The conserved arginine interacts directly with many of the various substrates through hydrogen bonding, dipoledipole or salt bridge interactions. Like Tyr L:36, Arg H:94 displays significant structural variability. Unlike Tyr L:36, the structure variability includes -carbon positions. Tyr L:36 is buried deep in the core and outside the CDR loops. Therefore, conformational changes are generally limited to side-chain torsion angles. Arg H:94 occurs in the third heavy-chain CDR whose structural plasticity allows both main- and side-chain conformational changes. These conformational changes optimize Arg H:94substrate interactions.
Most of the hapten molecules have various charged groups (i.e. phosphates, carboxylic acids, guanidinium bases and chelated ions). Phosphates are the most common; one-third of the hapten molecules have a phosphate group. No conserved interaction motif is seen between the Ab and phosphate. Despite no particular sequence conservation, cationic combining site residues are always involved in salt bridges with the anionic phosphate. Further, there is little sequence conservation in the remaining acidbase interactions between Ab and hapten. However, most of the charged groups are involved in some sort of stabilizing interaction largely defined by the requirements of the particular antigen.
Antibody design implications
Although it is tempting to view these results in the framework of Ab maturation, we believe that this study has a more direct impact on Ab design. These results suggest that there is a general combining site scaffolding defined by tyrosine and a few other residues (including Arg H:94). Because of conservation, these positions are less attractive from a protein design point of view. On the other hand, Nature frequently optimizes sequences at the pKa shift hot-spots to maximize antigen specificity. It follows that mutant screening (in silico or otherwise) at these positions is more likely to increase substrate specificity than at other positions. These conclusions hold for both anti-protein and anti-hapten Abs.
Conclusions
This study firmly identifies common association motifs across Abantigen complexes. The association motif consists of five conserved tyrosine residues and a conserved arginine from CDR-H3. The conserved residues initiate substrate specificity through a host of Abantigen interactions and maintain combining site structure. Owing to structural and chemical flexibility, the exact nature of these interactions is not strictly conserved. Substrate specificity is refined by a heterogeneous group of non-covalent Abantigen interactions. There is little sequence conservation in these refining interactions; however, they are conserved with alignment hot-spot positions. Through a reduction in mutation space, these hot-spots should improve Ab design experimentation.
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Notes |
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Acknowledgments |
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References |
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Received March 26, 2004; revised June 24, 2003; accepted July 8, 2004.
Edited by Anthony Rees
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