The FightAIDS@Home Research Team We’re all members of Prof. Olson’s Molecular Graphics Lab

The Personnel Touch FightAIDS@Home has evolved considerably over the past year, both in terms of personnel and in new directions for our research. In addition, we have received the good news that we have been awarded a five year National Institute of Health grant to support our Program Project “Resistance Driven Design of HIV Therapeutics.” This Program Project, directed by Prof. Olson, enables the computational results from FightAIDS@Home to be integrated, tested, and utilized in the context of experimental and clinical research. The other labs participating in the program project include those of Prof. Elder, in Molecular Biology, Prof. Torbett, in Cell Biology, Prof. Stout, in X-ray crystallography, and Profs. Sharpless, Finn

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FightAIDS@Home News

Volume 5: June 12th, 2008

and Folkin, in synthetic organic chemistry. In addition, we have added to the project Dr. David Looney, who is a clinical AIDS physician at the VA hospital in La Jolla. Last August, Dr. William “Lindy” Lindstrom left the Olson Laboratory to take a position at a biotech company. Fortunately, we were able to recruit Dr. Alex L. Perryman to take over the lead role in the FightAIDS@Home project. Dr. Perryman’s prior experience with HIV drug design and his role in developing advanced drug design protocols has had significant influence on the new directions that the project is taking. In addition, we have also added new talent to the team in the person of Dr. Stephano Forli, a medicinal chemist, trained in structure-based drug design. Using New Tools & New Strategies to Build on a Solid Foundation In addition to the personnel changes, we have made changes to our computational strategies, based on our early results from FightAIDS@Home. Our previous virtual High Throughput Screening (vHTS) experiments used the “NCI Diversity Set” of compounds to probe both the active site and the exo site of wild type and multi-drug-resistant mutant “super bugs” of HIV protease. Although the ligands in this particular library have been useful in virtual experiments, as was displayed in a publication that resulted from the FAAH project1, Max Chang’s wet-lab experiments that tested his virtual results demonstrated that many of the members of this “NCI Diversity Set” displayed poor solubility and other undesirable properties that would make them unsuitable as leads in the drug discovery and design process. As a result of Max Chang’s in silico and in vitro experiments, we are now using different libraries of ligands in the virtual High-Throughput Screens we perform with FightAIDS@Home. Additionally, the results of this research have shown us that we can identify spanning mutants that characterize the extremes of the many thousands of possible HIV protease mutant proteins. This discovery has enabled us to focus our computations more intensively on a smaller set of mutant targets and to utilize a new, more effective docking strategy termed “The Relaxed Complex Method,” as described below. Following from Max Chang’s experiences, we created our own virtual representation of the library of ligands that he found to be much more suitable. In our current and future experiments with FightAIDS@Home, the “DTP library of moderately-active compounds” is being used. Creating a new virtual version of this DTP library was the first major task undertaken by our brand new Research Associate, Dr. Stefano Forli. Dr. Stefano Forli joined Prof. Olson's laboratory at TSRI on March 2008. He received his Ph.D. in 2006 in Pharmaceutical Sciences at the Universita' degli Studi di Siena, Italy, after an industrial fellowship in SienaBiotech. His main expertise is in docking, virtual High-Throughput Screening and structure-activity relationships. The aims of his research are to exploit protein structural information to identify novel, potentially active molecules and to overcome multi-drug resistance. Thus, Stefano’s experiences, skills, and research goals are a perfect match to complement our FightAIDS@Home team. In collaboration with Dr. Qing Zhang and Dr. Alex L. Perryman of Prof. Art Olson’s Laboratory at TSRI, Dr. Stefano Forli has now developed and implemented a good protocol for generating and refining a thorough virtual representation of the “DTP library of moderately-active” compounds. Our new virtual version of this library includes all of the different tautomers, different protonation states, and different enantiomers that these compounds might display in solution. We are now investigating alternative

1 Max W. Chang, William “Lindy” Lindstrom, Arthur J. Olson, and Richard K. Belew. “Analysis of HIV Wild-Type and Mutant Structures via in Silico Docking Against Diverse Ligand Libraries.” Journal of Chemical Information and Modeling, 47(3): 1258-1262 (2007).

methods and protocols for adding partial charges to each of the atoms within all of these compounds, a requirement before these compounds can be docked. Improving and Applying the Relaxed Complex Method Dr. Alex L. Perryman has now created, developed, and implemented the tools and protocols necessary for applying the Relaxed Complex method of drug design in the virtual High-Throughput screens performed in the FightAIDS@Home project. Our new virtual representation of the “DTP library of moderately-active compounds” is already being used in Relaxed Complex experiments that are currently crunching on the FightAIDS@Home project. The Relaxed Complex method is a relatively new approach to drug design that allows us to evaluate potential drugs by docking fully flexible versions of known and potential inhibitors against an ensemble of hundreds to thousands of conformations of the target protein. That is, we examine how good a potential drug is at binding to and blocking a massive collection of many of the different shapes that the drug target can sample as it wiggles and jiggles in a warm, watery environment. Proteins are very flexible polymers, and some potential drugs might not bind well to the average conformation that is represented in a particular crystal structure.

“You cannot extract a single frame from a movie, examine it in detail, and expect to understand the plot of the full film. You cannot remove one chord, study it to death, and comprehend the meaning of a song. You have to look at all of the shapes and motions that the system samples in order to understand and fully exploit the intricate dance that proteins display.” [quote from Dr. Alex L. Perryman]

By including the many different shapes that the target protein can display when we evaluate potential drugs, the drug design process can become more realistic and much more accurate. Molecular Dynamics simulations are first used to generate the collection of hundreds to thousands of different snapshots of the shapes that the target protein can sample as it vibrates and changes shape. By using AutoDock to dock fully-flexible inhibitors to the series of snapshots of the conformations that we harvest from these MD simulations, the flexibilities of both the potential drugs and their target can be incorporated into the drug design and evaluation process. Including this flexibility can be especially important when one is trying to inhibit a highly variable target such as HIV protease. To help us improve the Relaxed Complex protocols used in the vHTS that we perform with the FightAIDS@Home project’s share of the World Community Grid, we recently submitted an experiment that involves the use of all of the current FDA-approved HIV protease inhibitors (and a few compounds in development) as reference compounds. These calculations will also provide a baseline against which to compare the performance of the compounds we use in other FAAH experiments. Different protocols for preparing the input files of these current drugs were used (such as using different protocols to calculate the charges on the atoms within each ligand, using different "atom types" to describe the ligands, and using different protocols for minimizing the structures of the ligands). Thus, this experiment will allow us to investigate the best way(s) for preparing ligands that will be used in subsequent Relaxed Complex experiments that focus on hit-to-lead development (i.e., that focus on examining which modifications of current drugs help increase their affinities against the multi-drug-resistant “super bugs” of HIV). Slightly different protocols will likely be optimal in these hit-to-lead studies than those protocols that perform the best in vHTS experiments that look for weakly-binding “hits,” but this assumption will be tested. The reference compounds used include the FDA-approved drugs amprenavir, atazanavir, darunavir, indinavir,

lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, while the compounds in development that we are testing include AB2, AB3, JE-2147, KNI-272, TL3, and TMC-126. For an image of one of these reference compounds bound to a multi-drug-resistant mutant of HIV protease, see Figure 1.

Figure 1: The crystallographic binding mode of the reference compound “amprenavir” (an FDA-approved anti-AIDS drug) is shown as green sticks. Two common multi-drug-resistance mutations are shown in red sticks surrounded by mesh. To improve the efficiency of the Relaxed Complex method in virtual High-Throughput Screens against different multi-drug-resistant mutants of HIV protease (and against any other target), we have been exploring different methods of clustering the ensemble of snapshots harvested from MD simulations (i.e., we are examining different methods to select a smaller number of the most useful snapshots from the massive ensemble of the drug target’s conformations, instead

of having to dock the libraries of ligands against most of the snapshots produced by MD). One of our newest Relaxed Complex experiments is testing both a new library of ligands and a new method for selecting the snapshots of the target from MD against which to dock these compounds. The first third of the ligands from the NCI’s “DTP library of moderately-active” compounds is being tested now, while we prepare the files that describe the remaining two thirds of this library. These compounds were “moderately active” in cell-based assays at the NCI, but no one knows which targets in the Human Immunodeficiency Virus (or in the human cells) these bind to or how they are able to inhibit them. These compounds are being docked against the active site of a “QR-selected” subset of conformations harvested from Molecular Dynamics simulations of the V82F/I84V multi-drug-resistant mutant of HIV protease (i.e., a target from one of the worst “super bugs” of HIV). The Structure QR method is a new tool for selecting a “structurally diverse, non-redundant set” of conformations from a group of different structures that have similar sequences. We thank John Eargle of the Luthey-Schulten lab at UIUC (University of Illinois at Urbana-Champaign) for helping us learn how to apply this method. For a representation of the structural diversity present in our QR-selected subset of conformations of the V82F/I84V multi-drug-resistant mutant, see Figures 2, 3, and 4.

Figure 2: One monomer of 23 of the 103 snapshots in the structurally-diverse, non-redundant set of QR-selected conformations of the V82F/I84V multi-drug-resistant mutant of HIV protease are shown in ribbon mode. The variability in the structure of the active site flap is apparent in the top left quadrant of this molecular image.

In our future FAAH experiments, we will explore other methods for selecting the snapshots of drug targets from the ensembles generated by Molecular Dynamics simulations. For example, we will explore novel applications of the new AutoLigand program to select a diverse, non-redundant set of snapshots according to their atomic affinity maps. We also plan to investigate the new clustering algorithms from a collaborator at MedIT, which uses the geometric locations of different functional groups to cluster large databases of different types of proteins. The best method for selecting these snapshots will then be applied in vHTS experiments that target other multi-drug-resistant mutants of HIV protease, such as the spanning mutants that resulted from the previous FightAIDS@Home experiments.1

Figure 3: This depicts the variability in the conformation of Arg8 (shown as sticks in the middle), which is known to block part of the active site and cause false negative results when docking some current drugs to some of the crystal structures of HIV protease. These are the same structures of the super bug of protease that were displayed in Figure 2 (and will be displayed in Figure 4).

Figure 4: The dynamic differences displayed by the multi-drug-resistance mutations V82F (the hexagonal rings on a stick) and I84V (the V’s on a stick) within the QR-selected set of snapshots from MD are depicted. It would be very useful to find compounds that bind well to this super bug, regardless of which of the many different conformations of V82F it wants to display. Presenting the Promising New Results to the Public Two new papers that have depended on the results of FightAIDS@Home have now been submitted for publication. Titles and descriptions are as follows: “Interleaved virtual and experimental screening for HIV protease inhibitors” Max W. Chang, Michael J. Giffin, William M. Lindstrom, Arthur J. Olson, Richard K. Belew, and Bruce E. Torbett Searching for HIV protease inhibitors in a large, random collection of chemical compounds requires expensive machinery and other materials. Even then, the odds of finding a promising “hit” are low—somewhere between 1/1,000 and 1/10,000. One alternative is the use of virtual screening, which can select likely inhibitors based on computer modeling. This allows experimental testing of a much smaller

set of compounds. However, potential inhibitors selected through virtual screening may have undesirable properties that make them difficult to test experimentally or that make them poor drug candidates. To improve the chances of finding promising inhibitor candidates, we took advantage of a large chemical library that had already been tested against HIV (i.e. the “DTP moderately-active library”). Approximately 1,500 compounds were found to provide some protection for human cells against HIV infection, although these compounds could target any part of the virus, or even something present in human cells. We used AutoDock to screen virtually these compounds against a wild-type HIV protease structure, and we incorporated the previously published FightAIDS@Home work1 to choose 36 candidates. After experimental testing with HIV protease, we were able to confirm 5 of these compounds as inhibitors. While these new inhibitors are not nearly as potent as FDA-approved drugs, this approach has proven to be useful in finding new inhibitors with a relatively small amount of work in the “wet lab.” We look forward to extending this work in further screens against HIV protease mutants and other targets. “Combining molecular docking and sequence analysis to predict resistance mutations for novel inhibitors of HIV protease” Max W. Chang, Michael J. Giffin, Ying-Chuan Lin, John H. Elder, Arthur J. Olson, Bruce E. Torbett, Richard K. Belew Current anti-HIV drugs often become less potent over time because of the development of drug resistance mutations. In many cases, these mutations in HIV affect multiple drugs, making all of them less useful. As newer drugs are being developed, it would be helpful to be able to (1) predict likely mutations that might lower a drug’s potency and (2) focus on potential drugs which are not affected by existing and predicted drug resistance mutations. We used structural modeling based on AutoDock and our previous work with FAAH to predict three resistance mutations against a new inhibitor called AB2. Using molecular biology techniques, we synthesized HIV protease mutants with every combination of these mutations, and then we tested their resistance against AB2. We found higher resistance as the number of mutations increased, indicating that our predictions were correct. As this technique is refined, we hope to apply it to the best compounds produced from the FightAIDS@Home research and directly address drug resistance during the early stages of drug design.

We could not perform this research without your help. Thank you very much for helping us advance the fight against multi-drug-resistant “super bugs” of HIV and

for helping us improve the tools and techniques used in the entire field of structure-based drug design.

Prof. Arthur J. Olson Dr. Alex L. Perryman

Dr. Stefano Forli Dr. Garrett M. Morris Dr. Alexandre Gillet

http://fightaidsathome.scripps.edu/http://fightaidsathome.scripps.edu/