IsAb: a computational protocol for antibody design

Author:

Liang Tianjian1,Chen Hui1,Yuan Jiayi1,Jiang Chen1,Hao Yixuan1,Wang Yuanqiang2,Feng Zhiwei1,Xie Xiang-Qun3

Affiliation:

1. School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA

2. School of Pharmacy and Bioengineering, Chongqing University of Technology, Pittsburgh, PA 15261, USA

3. Computational Drug Abuse Research and Computational Chemogenomics Screening Center at the University of Pittsburgh, Pittsburgh, PA 15261, USA

Abstract

Abstract The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody–antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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