five

A mutagenesis study of a catalytic antibody.

收藏
PubMed Central1991-01-01 更新2026-05-16 收录
下载链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC50747/
下载链接
链接失效反馈
官方服务:
资源简介:
We have generated seven site-specific mutations in the genes encoding the variable region of the heavy chain domain (VH) of the phosphocholine-binding antibody S107. S107 is a member of a family of well-characterized highly homologous antibodies that bind phosphorylcholine mono- and diesters. Two of these antibodies, MOPC-167 and T15, have previously been shown to catalyze the hydrolysis of 4-nitrophenyl N-trimethylammonioethyl carbonate. Two conserved heavy-chain residues, Tyr-33 and Arg-52, were postulated to be involved in binding and hydrolysis of 4-nitrophenylcholine carbonate esters. To more precisely define the catalytic roles of these residues, three Arg-52 mutants (R52K, R52Q, R52C) and four Tyr-33 mutants (Y33H, Y33F, Y33E, Y33D) of antibody S107 were generated. The genes encoding the VH binding domain of S107 were inserted into plasmid pUC-fl, and in vitro mutagenesis was performed. The wild-type and mutant S107 antibodies were expressed in P-3X63-Ag8.653 (P-3) myeloma cells by using a modified SV2 shuttle vector. The catalytic properties of wild-type antibody S107 are similar to those of the phosphocholine-specific antibody T15, which has the same VH protein sequence. In general, mutations at Tyr-33 had little effect on catalytic activity, whereas mutations at Arg-52 that result in loss of the positively charged side chain significantly lower the catalytic activity of S107. One mutant, Y33H, catalyzed the hydrolysis of 4-nitrophenyl N-trimethylammonioethyl carbonate with a kcat of 5.7 min-1 and a Km of 1.6 mM at pH 7.5. These results not only demonstrate the importance of electrostatic interactions in catalysis by antibody S107 but also show that catalytic side chains can be introduced into antibodies to enhance their catalytic efficiency.
提供机构:
National Academy of Sciences
创建时间:
1991-01-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作