RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
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DOI：
10.1371/journal.pcbi.1006112
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发表时间：
2018-04-01
影响因子：
4.3
通讯作者：
Dunbrack, Roland L., Jr.
中科院分区：
文献类型：
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作者：
Adolf-Bryfogle, Jared;Kalyuzhniy, Oleks;Dunbrack, Roland L., Jr.
一种基于结构生物信息学的计算方法和框架已经被开发出来，用于设计针对感兴趣的目标的抗体。RosettaAbbodyDesign(RAbD)以高度可定制的协议对抗体针对抗原的不同序列、结构和结合空间进行采样，以设计广泛应用中的抗体。该程序通过从一组被广泛接受的CDR典型簇中嫁接结构来采样抗体序列和结构(North等人，J.Mol Biol，406：228-256,2011)。然后，它根据每个簇的氨基酸序列谱进行序列设计，并使用结合基于簇的CDR约束的灵活骨架设计协议对CDR骨架进行采样。从现有的实验或计算模拟的抗原抗体结构出发，RAbD可用于重新设计具有不同长度、构象和序列的环的单个CDR或多个CDR。我们在一组60种不同的抗体-抗原复合体上严格地对RAbD进行了基准测试，使用了两种设计策略-优化总Rosetta能量和仅优化界面能量。我们使用了两个新的度量标准来衡量计算蛋白质设计的成功。设计风险比(DRR)等于在蒙特卡罗设计过程中，原始CDR长度和簇的恢复频率除以这些特征的抽样频率。比率大于1.0表示设计过程从采样率中挑选本机的频率比预期更高。我们实现了2.4到4.0之间的非H3 CDR的DRR。抗原风险比(ARR)是在存在和不存在抗原的情况下进行模拟的输出诱饵中天然氨基酸类型、CDR长度和簇的频率之比。对于CDR，我们获得了高达2.5的集群ARR(LL)和1.5的H2 ARR。对于没有CDR嫁接的序列设计模拟，在有抗原存在的模拟中，与天然结构中与抗原接触的残基的天然氨基酸类型的总回收率为72%，在没有抗原的模拟中，总回收率为48%，ARR为1.5。对于非接触性残留物，ARR为1.08。这表明序列图谱能够保持这些保守的、埋藏的位置的氨基酸类型，而恢复暴露的、接触的残基需要抗原-抗体界面的存在。我们在lambda和kappa抗体-抗原复合体上进行了RAbD实验测试，通过用新的CDR长度和簇替换天然抗体的单个CDR，成功地将它们的亲和力提高了10到50倍。
A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J. MoL BioL, 406:228-256, 2011). It then performs sequence design according to amino acid sequence profiles of each cluster, and samples CDR backbones using a flexible-backbone design protocol incorporating cluster-based CDR constraints. Starting from an existing experimental or computationally modeled antigen-antibody structure, RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody-antigen complexes, using two design strategies-optimizing total Rosetta energy and optimizing interface energy alone. We utilized two novel metrics for measuring success in computational protein design. The design risk ratio (DRR) is equal to the frequency of recovery of native CDR lengths and clusters divided by the frequency of sampling of those features during the Monte Carlo design procedure. Ratios greater than 1.0 indicate that the design process is picking out the native more frequently than expected from their sampled rate. We achieved DRRs for the non-H3 CDRs of between 2.4 and 4.0. The antigen risk ratio (ARR) is the ratio of frequencies of the native amino acid types, CDR lengths, and clusters in the output decoys for simulations performed in the presence and absence of the antigen. For CDRs, we achieved cluster ARRs as high as 2.5 for Ll and 1.5 for H2. For sequence design simulations without CDR grafting, the overall recovery for the native amino acid types for residues that contact the antigen in the native structures was 72% in simulations performed in the presence of the antigen and 48% in simulations performed without the antigen, for an ARR of 1.5. For the non-contacting residues, the ARR was 1.08. This shows that the sequence profiles are able to maintain the amino acid types of these conserved, buried sites, while recovery of the exposed, contacting residues requires the presence of the antigen-antibody interface. We tested RAbD experimentally on both a lambda and kappa antibody-antigen complex, successfully improving their affinities 10 to 50 fold by replacing individual CDRs of the native antibody with new CDR lengths and clusters.