Venkata Giridhar Poosarla, Tong Li, Boon Chong Goh, Klaus Schulten, Thomas K.
Wood, and Costas D. Maranas.
Computational de novo design of antibodies binding to a peptide with
high affinity.
Biotechnology and Bioengineering, 114:1331-1342, 2017.
(PMC: PMC5726764)
POOS2017
Antibody drugs play a critical role in infectious diseases, cancer, autoimmune
diseases, and inflammation. However, experimental methods for the generation
of therapeutic antibodies such as using immunized mice or directed evolution
remain time consuming and cannot target a specific antigen epitope. Here, we
describe the application of a computational framework called OptMAVEn
combined with molecular dynamics to de novo design antibodies. Our reference
system is antibody 2D10, a single-chain antibody (scFv) that recognizes the
dodecapeptide DVFYPYPYASGS, a peptide mimic of mannose-containing
carbohydrates. Five de novo designed scFvs sharing less than 75similarity to all existing natural antibody sequences were generated using
OptMAVEn and their binding to the dodecapeptide was experimentally
characterized by biolayer interferometry and isothermal titration calorimetry.
Among them, three scFvs show binding affinity to the dodecapeptide at the nM
level. Critically, these de novo designed scFvs exhibit considerably diverse
modeled binding modes with the dodecapeptide. The results demonstrate the
potential of OptMAVEn for the de novo design of thermally and conformationally
stable antibodies with high binding affinity to antigens and encourage the
targeting of other antigen targets in the future.
Download Full Text
The manuscripts available on our site are provided for your personal
use only and may not be retransmitted or redistributed without written
permissions from the paper's publisher and author. You may not upload any
of this site's material to any public server, on-line service, network, or
bulletin board without prior written permission from the publisher and
author. You may not make copies for any commercial purpose. Reproduction
or storage of materials retrieved from this web site is subject to the
U.S. Copyright Act of 1976, Title 17 U.S.C.
