Institute for Cancer Research, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111, USA.
J Mol Biol. 2011 Feb 18;406(2):228-56. doi: 10.1016/j.jmb.2010.10.030. Epub 2010 Oct 28.
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; κ/λ) 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.
先前对抗体互补决定区（CDR）的分析主要集中在每个环的少数“典型”构象上。这主要是 Chothia 及其同事工作的结果，最近一次是在 1997 年。由于抗体的广泛应用，我们重新审视了目前可用的大量结构信息中六个 CDR 环构象的聚类。在这项工作中，我们通过消除低分辨率结构、高 B 因子或高构象能的 CDR，仔细使用高质量数据集。我们使用基于方向统计的距离函数和带有亲和力传播的有效聚类算法。使用这个超过 300 个非冗余抗体结构的数据集，我们能够覆盖 L1、L2、L3、H1 和 H2 的 28 个 CDR 长度组合（例如，L1 长度 11，或我们的 CDR 长度命名法中的“L1-11”）。Chothia 分析仅涵盖 20 个 CDR 长度。其中只有四个有多个构象簇，其中两个可以很容易地通过基因来源（鼠/人；κ/λ）区分，一个可以很容易地仅通过存在和脯氨酸残基的位置（L3-9）区分。因此，使用 Chothia 分析不需要通常假设的复杂的“结构决定残基”集。在我们的 28 个 CDR 长度中，有 15 个具有多个构象簇，其中 10 个在 Chothia 分析中只有一个典型类别。我们有 72 个非 H3 CDR 簇；大约 85%的非 H3 序列可以根据基因来源和/或序列分配到构象簇。我们发现，基于 H3 中 Arg/Lys94 和 Asp101 锚定残基的存在或不存在，对“膨出”与“非膨出”构象的早期预测并不成立，因为所有四种组合都导致大多数构象膨出。因此，增加的数据极大地增强了早期分析。我们相信，新的分类将导致改进的抗体结构预测和设计方法。
