New Computational Biology Method Promises Better Drugs

MIT Professors Dane Wittrup, Bruce Tidor and colleagues are reporting in the Sept. 23 issue of Nature Biotechnology on a novel computer modeling method, that they’ve already tested, to develop new drugs:

MIT researchers have developed a computer modeling approach that could improve a class of drugs based on antibodies, molecules key to the immune system. The model can predict structural changes in an antibody that will improve its effectiveness.
The team has already used the model to create a new version of cetuximab, a drug commonly used to treat colorectal cancer, that binds to its target with 10 times greater affinity than the original molecule…
Traditionally, researchers have developed antibody-based drugs using an evolutionary approach. They remove antibodies from mice and further evolve them in the laboratory, screening for improved efficacy. This can lead to improved binding affinities but the process is time-consuming, and it restricts the control that researchers have over the design of antibodies.
In contrast, the MIT computational approach can quickly calculate a huge number of possible antibody variants and conformations, and predict the molecules’ binding affinity for their targets based on the interactions that occur between atoms.
Using the new approach, researchers can predict the effectiveness of mutations that might never arise by natural evolution.
“The work demonstrates that by building on the physics underlying biological molecules, you can engineer improvements in a very precise way,” said Tidor.
The team also used the model with an anti-lysozyme antibody called D44.1, and they were able to achieve a 140-fold improvement in its binding affinity. The authors expect the model will be useful with other antibodies as well.

Picture caption: “In this image, a fragment of the antibody Erbitux (cetuximab) binds to its target, a fragment of epidermal growth factor receptor (EGFR). The blue ribbon at the top is the backbone of the EGFR fragment, and the red and gray ribbons at the bottom are the backbone of the antibody fragment. The licorice sticks and the balls in the central portion represent protein side chains making close interactions between the antigen (EGFR) and the antibody, with the balls representing one of the mutations designed computationally.”
Press release: MIT model could improve some drugs’ effectiveness …
More from the MIT Technology Review: Computers Boost Antibody-Based Drugs …
The Tidor Group …