3AUV

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

Summary for 3AUV

• Entry DOI: 10.2210/pdb3auv/pdb
• Descriptor: sc-dsFv derived from the G6-Fab (2 entities in total)
• Functional Keywords: sc-dsfv (disulfide-stabilized scfv), scfv, monovalent antibody, vegf, antibody engineering, immune system
• Biological source: Homo sapiens (human)
• Total number of polymer chains: 6
• Total formula weight: 174938.09

Authors

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. (deposition date: 2011-02-16, release date: 2012-02-22, Last modification date: 2024-11-13)

Primary citation

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

Experimental method

X-RAY DIFFRACTION (2.4 Å)