Nat. Commun.| Machine learning jointly optimizes the affinity and specificity of mutagenic therapeutic antibodies

This article shares information from nature communications The last one is entitled 《Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space》 The article , From the Institute of biological interface at the University of Michigan 、 Department of biomedical engineering 、 From the project team of the Department of Chemical Engineering Peter M.Tessier The team .

Thesis link ：

https://www.nature.com/articles/s41467-022-31457-3

The development of therapeutic antibodies requires the selection of high affinity molecules and the biophysical properties of other drugs , The joint optimization of multiple antibody characteristics is still a difficult and time-consuming process , Seriously hindering drug development . In this article , The author's team proposed and developed a simple machine learning model , Multi objective optimization of affinity and specificity of therapeutic antibodies . It turns out that , The power of machine learning models has greatly expanded the exploration of new antibody sequence space , And accelerated the development of highly effective drug antibodies .