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

ABSTRACT: 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.

SUBMITTER: Nowak J

PROVIDER: S-EPMC4966832 | biostudies-literature | 2016 May-Jun

REPOSITORIES: biostudies-literature

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

Nowak Jaroslaw J Baker Terry T Georges Guy G Kelm Sebastian S Klostermann Stefan S Shi Jiye J Sridharan Sudharsan S Deane Charlotte M CM

mAbs 20160501 4

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 me ...[more]

PMID: 26963563

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Project description:The rugged protein sequence-function landscape complicates efforts, both in nature and in the laboratory, to evolve protein function. Protein library diversification must strike a balance between sufficient variegation to thoroughly sample alternative functionality versus the probability of mutant destabilization below an expressible threshold. In this work, we explore the sequence-function landscape in the context of screening for molecular recognition from an Ig scaffold library. The fibronectin type III domain is used to explore the impact of two sequence diversification strategies: (a) partial wild-type conservation at structurally important positions within the paratope region and (b) tailored amino acid composition mimicking antibody binding-site composition at putative paratope positions. Structurally important positions within the paratope region were identified through stability, structural, and phylogenetic analyses and partially or fully conserved in sequence. To achieve tailored antibody-like diversity, we designed a set of skewed nucleotide mixtures yielding codons approximately matching the distribution observed in antibody complementarity-determining regions without incurring the expense of triphosphoramidite-based construction. These design elements were explored via comparison of three library designs: a random library, a library with wild-type bias in the DE loop only and tyrosine-serine diversity elsewhere, and a library with wild-type bias at 11 positions and the antibody-inspired amino acid distribution. Using pooled libraries for direct competition in a single tube, selection and maturation of binders to seven targets yielded 19 of 21 clones that originated from the structurally biased, tailored-diversity library design. Sequence analysis of the selected clones supports the importance of both tailored compositional diversity and structural bias. In addition, selection of both well and poorly expressed clones from two libraries further elucidated the impact of structural bias.

Project description:Previous analyses of the complementarity-determining regions (CDRs) of antibodies have focused on a small number of "canonical" conformations for each loop. This is primarily the result of the work of Chothia and coworkers, most recently in 1997. Because of the widespread utility of antibodies, we have revisited the clustering of conformations of the six CDR loops with the much larger amount of structural information currently available. In this work, we were careful to use a high-quality data set by eliminating low-resolution structures and CDRs with high B-factors or high conformational energies. We used a distance function based on directional statistics and an effective clustering algorithm with affinity propagation. With this data set of over 300 nonredundant antibody structures, we were able to cover 28 CDR-length combinations (e.g., L1 length 11, or "L1-11" in our CDR-length nomenclature) for L1, L2, L3, H1, and H2. The Chothia analysis covered only 20 CDR-lengths. Only four of these had more than one conformational cluster, of which two could easily be distinguished by gene source (mouse/human; ?/?) and one could easily be distinguished purely by the presence and the positions of Pro residues (L3-9). Thus, using the Chothia analysis does not require the complicated set of "structure-determining residues" that is often assumed. Of our 28 CDR-lengths, 15 have multiple conformational clusters, including 10 for which the Chothia analysis had only one canonical class. We have a total of 72 clusters for non-H3 CDRs; approximately 85% of the non-H3 sequences can be assigned to a conformational cluster based on gene source and/or sequence. We found that earlier predictions of "bulged" versus "nonbulged" conformations based on the presence or the absence of anchor residues Arg/Lys94 and Asp101 of H3 have not held up, since all four combinations lead to a majority of conformations that are bulged. Thus, the earlier analyses have been significantly enhanced by the increased data. We believe that the new classification will lead to improved methods for antibody structure prediction and design.

Dataset Information

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

Publications

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

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