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The goal now is to fill in a large matrix of potential drugs and known and potential HIV protease mutants in order to see which drugs are the most robust against which mutants.

The first step is to figure out which computations to run. A vast number of possible permutations of mutant and inhibitor combinations exist, so it would be impossible to run them all. Olson and his colleagues focus on mutations to the 10 amino acids in the protease monomer that have direct contact with the substrate or inhibitor in the binding site.

This still takes quite a bit of computing power.

So Olson and his colleagues try to rationally decide which computations are most important to run first. These, accordingly, are put higher up in the queue to be solved by FightAIDS@Home computers.

Rik Belew, who is a professor in the Department of Cognitive Science at the University of California, San Diego, and a member of the research consortium, is an expert in machine learning. Belew and his graduate student Chris Rosen developed a computational optimization scheme called co-evolution to find the best candidate mutant and inhibitor combinations to study.

The scheme roughly looks for the best inhibitor for the best mutant by using a simple docking of candidate molecules, assigning a numeric score for how well the molecules fit together. From that, ideally, comes information on which are the best inhibitors.

"His goal is to take a look at the matrix and see which results will give us the most information about the entire system," says Olson. "We're not going to be able to do all possible drugs against all mutants, so we try to use the most informative mutants to test the [most promising] drugs."

These computations can then guide the experimental biologists and chemists, who can make the mutant proteins, synthesize the inhibitors, and test whether they bind as expected.

All this information is then fed to the chemists who can use it to design inhibitors to test and to the biologists who can create the mutant proteases and design the experiments in which to test them. For instance, Elder can take whatever mutants are deemed to be the most informative and express them. Then, if what the computational group has predicted is not true at all or if it is, the team will get his experimental feedback

The computational group can also interact with Elder and Torbett, who are co-principal investigators on one of the four projects on the program project grant, and look at the viral dynamics that take place in tissue culture. Elder and Torbett have developed a panel of tissue culture assays with various mutant forms of HIV—with wild type and drug-resistant proteases.

"Before we try to predict viral dynamics in a patient, we may try to predict it in tissue culture," says Olson.

The Path of Most Resistance

Torbett and Elder are interested in the molecular biological consequences of mutations to the HIV protease as a result of drug therapy, and their project follows from work that they previously carried out with TSRI Professor Chi-Huey Wong who is the Ernest W. Hahn Professor and Chair in Chemistry.

Torbett used the TL3 protease inhibitor that was developed by Elder and Wong to develop protease-resistant mutants by treating HIV-infected cells with the drug and forcing mutants to arise. Torbett's lab isolated the protease genes after each mutation arose, and developed a chronological library of mutant forms of the HIV protease.

"We end up getting a mutation path of changes, from a little resistant to very resistant," says Torbett. In the laboratory, Torbett has generated a "supermutant" form of protease that has changed a half dozen animo acids and is resistant to protease inhibitors.

Along this path of most resistance, they put the various mutant forms into expression systems and asked how these sequential changes affect the biochemistry of the protein.

What they have observed is that the initial changes are, not surprisingly, directed against the particular inhibitor being used. This initial inhibitor selects for those mutants that have arisen spontaneously and can resist it.

However, over time, the protease continues to mutate.

One of the important observations that Torbett and other scientists have made is that the later mutants exhibit broad resistance against a number of drugs. This robust cross-resistance gives rise to the dangerous multiple-drug-resistant strains of HIV that have been emerging since the advent of antiretroviral therapy in the last decade.

"Why does the protease become cross-resistant when treated with a single drug?" asks Torbett.

Substrates and Aptamers

Torbett and Elder are also asking how the mutations to the viral protease affect the binding of the protease to substrate and how these changes map to structural changes that occur when HIV protease mutates.

Mutant forms of the protease are all different in terms of how they bind to substrate, and Torbett and his laboratory use a technique called phage display to see the range of structures to which the HIV protease can bind as it accumulates mutations.

Phage display is a method of generating large libraries of variant forms of a particular protein—in this case, the HIV protease substrate. In the technique, a protein is fused to a viral coat protein of the phage—a filamentous virus that infects bacteria. Then the virus is allowed to reproduce in culture, where it copiously makes new copies of itself.

Potentially, more than a billion variants of substrate can be generated in this way, and the substrate preferences of HIV protease can be checked against this library.

Torbett also uses RNA aptamers—a type of structural probe made out of RNA—to probe the outside structure of the protease to see how it has changed in response to the mutations. These aptamers are also generated in great numbers as well.

All of this is aimed at giving the investigators some idea of possible targets than will not mutate.

"If you can force the virus into a corner where it can replicate but at low efficiency, it will not be able to grow very well," says Torbett. "If the immune system's intact, then it should be able to control the virus.

Next week: Chemical Approaches

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Associate Professor Bruce Torbett says of the collaboration, "It forces us to think differently. Photo by Biomedical Graphics.











Scanning electron micrograph of human immunodeficiency virus (HIV), grown in cultured lymphocytes. Virions are seen as small spheres on the surface of the cells. Photo by C. Goldsmith, courtesy of CDC.