Computational design of antibody-affinity improvement beyond in vivo maturation
Computational design of antibody-affinity improvement beyond in vivo maturation
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DOI：
10.1038/nbt1336
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发表时间：
2007-10-01
影响因子：
46.9
通讯作者：
Tidor, Bruce
中科院分区：
文献类型：
--
作者：
Lippow, Shaun M.;Wittrup, K. Dane;Tidor, Bruce
抗体广泛用于诊断和作为治疗剂。实现高亲和力结合对于扩大检测限、延长解离半衰期、降低药物剂量和增加药物功效是重要的。然而，体内抗体亲和力成熟通常不能产生具有靶向效力的抗体药物（1），使得通过定向进化或计算设计在体外进行进一步亲和力成熟是必要的。在这里，我们提出了一个迭代的计算设计程序，重点是静电结合的贡献和单突变体。通过组合多个设计的突变，将亲和力提高10倍至52 pM工程化到抗表皮生长因子受体药物西妥昔单抗（爱必妥）中，并且获得抗溶菌酶模型抗体D44.1亲和力提高140倍至30 pM。通过鉴定已知的亲和力增强突变、治疗性抗体贝伐单抗（Avastin）和抗荧光素抗体4-4-20进一步证明了方法的通用性。这些结果证明了增强和加速蛋白质试剂和治疗剂开发的计算能力。
Antibodies are used extensively in diagnostics and as therapeutic agents. Achieving high-affinity binding is important for expanding detection limits, extending dissociation half-times, decreasing drug dosages and increasing drug efficacy. However, antibody-affinity maturation in vivo often fails to produce antibody drugs of the targeted potency(1), making further affinity maturation in vitro by directed evolution or computational design necessary. Here we present an iterative computational design procedure that focuses on electrostatic binding contributions and single mutants. By combining multiple designed mutations, a tenfold affinity improvement to 52 pM was engineered into the anti-epidermal growth factor receptor drug cetuximab (Erbitux), and a 140-fold improvement in affinity to 30 pM was obtained for the anti-lysozyme model antibody D44.1. The generality of the methods was further demonstrated through identification of known affinity-enhancing mutations the therapeutic antibody bevacizumab (Avastin) and the anti-fluorescein antibody 4-4-20. These results demonstrate computational capabilities for enhancing and accelerating the development of protein reagents and therapeutics.