Computational design and optimization of novel d -peptide TNFα inhibitors

FEBS Letters

article

Wei Yang¹  Qi Zhang²  Changsheng Zhang⁴  Annan Guo³  Yanyan Wang³  Hantian You⁴  Xiaoling Zhang⁵  Luhua Lai³ 

[1] School of Life Sciences, Tsinghua University;School of Life Sciences, Peking University;Peking-Tsinghua Center for Life Sciences, Peking University;College of Chemistry and Molecular Engineering, Peking University;Center for Quantitative Biology, Peking University

关键词: computational protein design;    D-helical peptide design;    peptides;    protein–protein interactions;    TNFa binding peptide;   

DOI  :  10.1002/1873-3468.13444

来源: John Wiley & Sons Ltd.

【 摘 要 】

Compared to small molecule drugs, peptide therapeutics provides greater efficacy, selectivity, and safety. The intrinsic disadvantages of peptides are their sensitivity to proteases. To overcome this, we have developed a general computational strategy for de novo design of protein binding helical D-peptides. A D-helical fragment library was established and used in generating flexible Dhelical conformations, which were then used to generate suitable sequences with the required structural and binding properties. Using this strategy, we successfully de novo designed D-helical peptides that bind to tumor necrosis factor-a (TNFa), inhibit TNFa-TNFR1 binding, reduce TNFa activity in cellular assays, and are stable against protease digestion. Our strategy of helical D-peptide design is generally applicable for discovering D-peptide modulators against protein–protein interactions.

【 授权许可】

Unknown