More Like this

1. Antibody nanocarriers for cancer management

   https://doi.org/10.1016/j.cobme.2021.100295  

   Dang, Megan N.; Hoover, Elise C.; Scully, Mackenzie A.; Sterin, Eric H.; Day, Emily S. (September 2021, Current Opinion in Biomedical Engineering)
2. Review of COVID-19 Antibody Therapies

   https://doi.org/10.1146/annurev-biophys-062920-063711  

   Chen, Jiahui; Gao, Kaifu; Wang, Rui; Nguyen, Duc Duy; Wei, Guo-Wei (May 2021, Annual Review of Biophysics)

   null (Ed.)

   In the global health emergency caused by coronavirus disease 2019 (COVID-19), efficient and specific therapies are urgently needed. Compared with traditional small-molecular drugs, antibody therapies are relatively easy to develop; they are as specific as vaccines in targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); and they have thus attracted much attention in the past few months. This article reviews seven existing antibodies for neutralizing SARS-CoV-2 with 3D structures deposited in the Protein Data Bank (PDB). Five 3D antibody structures associated with the SARS-CoV spike (S) protein are also evaluated for their potential in neutralizing SARS-CoV-2. The interactions of these antibodies with the S protein receptor-binding domain (RBD) are compared with those between angiotensin-converting enzyme 2 and RBD complexes. Due to the orders of magnitude in the discrepancies of experimental binding affinities, we introduce topological data analysis, a variety of network models, and deep learning to analyze the binding strength and therapeutic potential of the 14 antibody–antigen complexes. The current COVID-19 antibody clinical trials, which are not limited to the S protein target, are also reviewed. 

   more » « less
3. Improving antibody drug development using bionanotechnology

   https://doi.org/10.1016/j.copbio.2021.10.027  

   Makowski, Emily K; Schardt, John S; Tessier, Peter M (April 2022, Current Opinion in Biotechnology)
4. ANTIBODY DESIGN WITH CONSTRAINED BAYESIAN OPTIMIZATION

   Zeng, Yimeng; Elliott, Hunter; Maffettone, Phillip; Greenside, Peyton; Bastani, Osbert; Gardner, Jacob R (May 2024, GEM workshop, ICLR 2024)

   In therapeutic antibody design, achieving a balance between optimizing binding affinity subject to multiple constraints, and sequence diversity within a batch for experimental validation presents an important challenge. Contemporary methods often fall short in simultaneously optimizing these attributes, leading to ineffi- ciencies in experimental exploration and validation. In this work, we tackle this problem using the latest developments in constrained latent space Bayesian op- timization. Our methodology leverages a deep generative model to navigate the discrete space of potential antibody sequences, facilitating the selection of diverse, high-potential candidates for synthesis. We also propose a novel way of training VAEs that leads to a lower dimensional latent space and achieves excellent per- formance under the data-constrained setting. We validate our approach in vitro by synthesizing optimized antibodies, demonstrating consistently high binding affini- ties and preserved thermal stability. 

   more » « less
5. Microdroplet Ultrafast Reactions Speed Antibody Characterization

   https://doi.org/10.1021/acs.analchem.0c04974  

   Zhao, Pengyi; Gunawardena, Harsha P.; Zhong, Xiaoqin; Zare, Richard N.; Chen, Hao (March 2021, Analytical Chemistry)

   null (Ed.)