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Book chapter: World Community Grid will contribute to the future of HIV research
By: Dr. Arthur Olson
Professor, The Scripps Research Institute
8 Dec 2015   

Summary
We've been invited to write a chapter for an upcoming book: The Future of HIV-1 Therapeutics. Our chapter focuses on structure-based drug design, and discusses the benefits of "in silico" modeling for dramatically expanding the scope and effectiveness of structure-based research. We pay particular attention to the benefits of the large-scale computation network that we found in World Community Grid.

We have been invited to write a chapter for a book on the advancements of HIV therapy, entitled: The Future of HIV-1 Therapeutics: Resistance is futile?. Our chapter, entitled "Computational Challenges of Structure-Based Approaches Applied to HIV" provides a perspective on the application of computational methods to the design of new drugs, and discusses how World Community Grid is essential to our research efforts.

Layperson abstract

Structure-based drug design relies on the availability of crystallographic structures of the target proteins, which are used to test large libraries of compounds (often several millions) "in silico" to identify potential new drugs. In fact, the design of HIV protease inhibitors in the mid-1990s is often presented as the first successful example of the advantages of computational structure-based drug design.

Docking such a vast number of virtual compounds is a challenge in itself. Also, most of the target present various degrees of flexibility. Modeling this aspect adds another level of complexity, which can dramatically increase the number of calculations. However, when dealing with viruses, such the HIV-1, that mutate at a very high rate, things get even more problematic. In fact, many proteins produced by the virus during the infection can present mutations that render known powerful drugs ineffective.

In a specific section of the chapter ("Large Scale Modelling"), we describe in detail how IBM and World Community Grid made it possible to handle such an incredible amount of computation in FightAids@Home (FAAH). The computer time donated by the volunteers (over 300,000 computing years and counting!), and made available through World Community Grid, allowed us to design and perform experiments that would have been prohibitive with conventional computational resources.

We close the chapter discussing the new targets that are becoming available, and the new modeling techniques that are building larger and more detailed models of the whole virus. This will present new opportunities and yet more challenges for the design of HIV-1 drugs. With the help of World Community Grid and all the FAAH volunteers, we plan to face those challenges and to further extend the boundaries of research.

Technical abstract:

We review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.


 


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Dr. Arthur Olson
Professor, The Scripps Research Institute