Here's some interesting news from ScienceDaily: Researchers at MIT have developed a computational model that can predict how given changes to an antibody can influence its effects.
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.
The interesting bit is the prediction. It's presumably easy enough to model changes an antibody (essentially a protein), but predicting what the new version of the antibody will do is much harder. I can't wait to read the paper.