Rice writes rules for gene-therapy vectors

Rice University researchers are making strides toward a set of rules to custom-design Lego-like viral capsid proteins for gene therapy.

A new paper by Rice scientists Junghae Suh and Jonathan Silberg and their students details their use of computational and bioengineering methods to combine pieces of very different adeno-associated viruses (AAVs) to create new, benign viruses that can deliver DNA payloads to specific cells.

The research appears this month in the American Chemical Society journal ACS Synthetic Biology.

AAVs are found in nature and commonly infect humans but cause no disease. That makes them good candidates to serve as carriers that target cells and deliver genes to treat diseases.

The team, which included graduate student and lead author Michelle Ho and undergraduates Benjamin Adler and Michael Torre, wants to define rules to design a variety of viruses that deliver therapeutic genes. They used computer models to find likely AAV candidates for recombination and then tested the model predictions by engineering 17 unique virus capsid proteins and evaluating their ability to fold and assemble into capsid-encased viruses.

Gene therapy shows promise in the treatment of not only genetic disorders but also cancer and cardiovascular diseases, said Suh, an assistant professor of bioengineering at Rice’s BioScience Research Collaborative.

“But you need a mechanism to get the correct gene into the human body and to the target cells,” she said. “To do that, people use gene vectors, and viruses encompass the largest category of vectors. They’ve naturally evolved to deliver genes into the body. Our goal is to reprogram them to target specific organs or tissues.

“The big challenge is to go about this in a rational manner,” she said. “People have done a lot of work to solve the structure of viruses. We know what they look like. The question is: How can we use that information to guide the design of our viral vectors?”

The team’s answer starts with the “SCHEMA” algorithm they adapted to predict how parts of very large viruses can recombine by homing in on the viral protein sequences that work well together.

Silberg, an associate professor of biochemistry and cell biology, said approaches to virus design can lean either toward brute force – “Let’s make 1,000 of them and maybe we’ll get lucky” – or purely computational, where a biophysicist will try to predict the role of small changes to the virus capsid.

“We’re working on a hybrid approach,” he said. “Instead of making a random library (of viruses) or computationally designing a single virus, which has a low frequency of working, we’re trying to make smart libraries. We’re learning to adapt computer programs used for small proteins with a few thousand atoms for viruses with more than 100,000 atoms.”

Rather than target mutations in particular viruses, the researchers used the program to compare parts from different but related viruses to see if they would combine together to form new viruses.