3AUV

Predicting Amino Acid Preferences in the Complementarity Determining Regions of an Antibody-Antigen Recognition Interface

3AUV の概要

• エントリーDOI: 10.2210/pdb3auv/pdb
• 分子名称: sc-dsFv derived from the G6-Fab (2 entities in total)
• 機能のキーワード: sc-dsfv (disulfide-stabilized scfv), scfv, monovalent antibody, vegf, antibody engineering, immune system
• 由来する生物種: Homo sapiens (human)
• タンパク質・核酸の鎖数: 6
• 化学式量合計: 174938.09

構造登録者

Yu, C.M.,Peng, H.P.,Chen, I.C.,Lee, Y.C.,Chen, J.B.,Tsai, K.C.,Chen, C.T.,Chang, J.Y.,Yang, E.W.,Hsu, P.C.,Jian, J.W.,Hsu, H.J.,Chang, H.J.,Hsu, W.L.,Huang, K.F.,Ma, A.C.,Yang, A.S. (登録日: 2011-02-16, 公開日: 2012-02-22, 最終更新日: 2024-11-13)

主引用文献

Yu, C.M.,Peng, H.P.,Chen, I.C.,Lee, Y.C.,Chen, J.B.,Tsai, K.C.,Chen, C.T.,Chang, J.Y.,Yang, E.W.,Hsu, P.C.,Jian, J.W.,Hsu, H.J.,Chang, H.J.,Hsu, W.L.,Huang, K.F.,Ma, A.C.,Yang, A.S.
Rationalization and design of the complementarity determining region sequences in an antibody-antigen recognition interface
Plos One, 7:e33340-e33340, 2012

PubMed Abstract: Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes.

PubMed: 22457753
DOI: 10.1371/journal.pone.0033340

実験手法

X-RAY DIFFRACTION (2.4 Å)