Game changers – The Google of Genomes and Antibodies as Therapy

Published online 09 August 2017

 

Basic Local Alignment Search Tool published in the Journal of Molecular Biology in 1990.

Inferring the function of a protein 40 years ago required finding a related protein with a known function. To determine the similarity between two proteins meant comparing their amino acid sequences using a time-consuming algorithm.

In 1983, biologist David Lipman and colleague W. John Wilbur reported a faster method to identify the similarity between two unrelated sections of DNA or protein. A year later, a global team of scientists used the technique to show that amino acid sequences from a human growth factor closely resembled sequences from a cancer gene in a chicken virus. The paper marked significant progress in the basic understanding of cancer development and revealed the value of computational tools for making biological discoveries …

Replacing the complementarity-determining regions in a human antibody with those from a mouse published in Nature in 1986.

In 1986, Greg Winter and colleagues at the UK’s Medical Research Council (MRC) described in Nature a method for swapping pieces of a mouse antibody with those from a human to create a chimeric antibody. This was the second essential step in the development of antibody-based therapies for human disease, which represented more than 40% of total sales of biopharmaceutical products in 2016.

The first step occurred a decade earlier when Nobel prize winning researchers Georges Köhler and César Milstein developed mouse antibodies that recognize a single foreign molecule. While such monoclonal antibodies, had a wide range of applications in medical research and diagnostics, their use in medicine was limited

Nature 548, S9–S11 (10 August 2017) doi:10.1038/548S9a


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