Saturday 20 December, 2014

Computer model could improve some drugs’ efficacy

Published On: Mon, Sep 24th, 2007 | Bioinformatics | By BioNews

Sep 24 : A team of researchers has developed a computer model that could help advance a class of drugs based on antibodies, molecules key to the immune system.

According to researchers from the Massachusetts Institute of Technology, this model could help envisage structural changes in an antibody that will improve its effectiveness.

The team has already used the model to build a new version of cetuximab, a drug normally used to treat colorectal cancer, that binds to its target with 10 times greater affinity than the original molecule.

The work is a result of a partnership between MIT Professors Dane Wittrup and Bruce Tidor.

“New and better methods for improving antibody development represent critical technologies for medicine and biotechnology,” says Wittrup, who holds appointments in MIT’s Department of Biological Engineering and Department of Chemical Engineering.

Starting with a particular antibody, the MIT model observes many possible amino-acid substitutions that could happen in the antibody. It then calculates which substitutions would bring about a structure that would form a stronger interaction with the target.

“Combining information about protein (antibody) structure with calculations that address the underlying atomic interactions allows us to make rational choices about which changes should be made to a protein to improve its function,” said Shaun Lippow, lead author of the paper.

“Protein modeling can reduce the cost of developing antibody-based drugs, as well as enable the design of additional protein-based products such as enzymes for the conversion of biomass to fuel,” he added.

Janna Wehrle, who oversees computational biology grants at the National Institute of General Medical Sciences, which partially supported the research, said: “Making drugs out of huge, complicated molecules like antibodies is incredibly hard. Dr. Tidor’s new computational method can predict which changes in an antibody will make it work better, allowing chemists to focus their efforts on the most promising candidates.”

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 effectiveness. 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. (ANI)

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