Malaria is one of the three deadliest infectious diseases on Earth. The other two are HIV and tuberculosis. Plasmodium falciparum, the parasite that causes the deadliest form of malaria, kills more people than any other parasite on the planet. Half of the entire human population is at risk of being infected. In 2006, 247 million people became infected with malaria. Of the nearly one million deaths caused by malaria each year, 85% of those killed are children. In fact, it is the leading cause of death in Africa for those under five years of age: every 30 seconds another child dies of malaria. Even if malaria does not kill the infected person, it still causes impaired learning, absences in schools, lost work and increased poverty - effects that can last a lifetime. Where it is widespread, it can account for 40% of all public health costs. Thus, according to the World Health Organization, malaria is both a disease of poverty and a cause of poverty.
Even though malaria predominantly infects people in Africa, South-East Asia, and South America, in this era of globalization, it affects almost all sub-populations of the world, either physically, mentally, or monetarily. Millions of people from developed countries visit malaria-infested regions each year, and thus are exposed to malaria. As the global climate continues to change, the regions in which this disease flourishes could expand, since a mere half-degree Celsius increase in temperature can produce a 30-100% increase in the abundance of mosquitoes, which are the vectors that transmit malaria to humans.
Malaria is a disease that can actually be completely cured - not just "treated". Although there are many approved drugs that are able to cure malarial infections, multi-drug-resistant mutant "superbug" strains exist that are not being eliminated by the drugs currently available. Being "resistant" to a drug means that the specific target protein molecule, whose activity the drug blocks, has mutated (changed), which makes the drug lose its effectiveness at treating the infection. But at the same time, the mutation does not prevent the superbug from surviving and reproducing. The World Health Organization's 2001 report on "Drug Resistance in Malaria" indicates that the parasite Plasmodium falciparum has already developed resistance to nearly all anti-malaria drugs. As of 2004, drug resistance has reduced the usefulness of all currently available anti-malaria drugs, except for the artemisinin derivatives. Consequently, artemisinin derivatives have become a critical component of the recommended combination therapies. Unfortunately, malaria parasites resistant to artemisinin and its derivatives have recently started to appear at the Thai-Cambodian border. Because new mutant superbugs keep evolving and spreading throughout the world, discovering and developing new types of drugs that can eliminate these multi-drug-resistant mutants is a significant global health necessity.
The GO Fight Against Malaria project will use AutoDock 4.2 and the new AutoDock Vina computer software to evaluate how well each candidate compound (molecule) attaches ("docks" or "binds") against a malarial target (usually a protein molecule.) Millions of candidate compounds will be tested against 14 different molecular drug targets from the malaria parasite in order to discover new compounds that can block (inhibit) the activity of these multi-drug-resistant mutant superbugs. These candidates will be tested by docking flexible models of them against 3-D, atomic-scale models of different protein drug targets from the malaria parasite, to predict (a) how tightly these compounds might be able to bind, (b) where these compounds prefer to bind on the molecular target, and (c) what specific interactions are formed between the candidate and the drug target. In other words, these calculations will be used to predict the affinity/potency of the compound, the location where it binds on the protein molecule, and the mode it uses to potentially disable the target. Compounds that can bind tightly to the right regions of particular proteins from the malaria parasite have the potential to "gum up" the parasite's machinery and, thus, help advance the discovery of new types of drugs to cure malaria. Since these predictions are not perfectly accurate, the top-ranked candidate compounds discovered in these virtual experiments will then be tested in "biological assays" performed by research collaborators in test tubes and Petri dishes.
Once the collaborators have proven that some of these candidate compounds are definitely able to help eliminate the malaria parasite, then The Scripps Research Institute and other researchers throughout the world can try to optimize these promising compounds to increase their potency against the target while decreasing their ability to bind to human proteins (since binding to certain human proteins causes toxic side effects). Once it is known that a compound is a novel inhibitor of one of these drug targets, "medicinal chemists" can then extend and modify these compounds in order to accelerate the development of new anti-malaria drugs.
This project will use two different types of "docking" programs to search for new compounds that can bind to and block the activity of protein drug targets from the malaria parasite. Both of these docking programs were created and developed by the Olson lab at The Scripps Research Institute. The first phase of the project will computationally evaluate the potential potency of millions of compounds using the new software AutoDock Vina. The second phase of the project will computationally re-evaluate the potency of the same compounds using the program AutoDock4.2. These two different types of docking programs each use different algorithms when searching for the location where a compound binds and when predicting the detailed mode it uses to bind to that location of the protein target, and they both use different "scoring functions" to evaluate the potency of the binding mode they predicted. Since no computational tools are perfectly accurate, harvesting compounds that score well with multiple different types of computational tools can increase the probability of discovering promising new compounds. In the Olson lab's experience with the FightAIDS@Home project (see Volume 10), evaluating compounds with both AutoDock and Vina facilitated the discovery of novel inhibitors of HIV protease (which is a notoriously difficult protein to target).
Both AutoDock Vina and AutoDock4.2 will be used to screen millions of candidate compounds against 14 different "validated drug targets" and "potential drug targets" from the malaria parasite. Basically, these experiments will target every relevant protein from the malaria parasite that has an atomically-detailed 3-D structure available. GO Fight Against Malaria will screen candidate compounds against the following protein targets from the malaria parasite: dihydrofolate reductase, enoyl-acyl-carrier-protein reductase (also known as Fab I), purine phosphoribosyltransferase, purine nucleotide phosphorylase, M1 neutral aminopeptidase, falcipain (a cysteine protease), glutathione reductase, glutathione S-transferase, dihydroorotate dehydrogenase, orotidine 5'-phosphate decarboxylase, merozoite surface protein-1, profilin, 3-oxoacyl acyl-carrier-protein reductase (also known as Fab G), and beta-hydroxyacyl-acyl-carrier-protein dehydrase (also known as Fab A/Z).
Using World Community Grid to run the GO Fight Against Malaria project will greatly accelerate these experiments and will also enable very ambitious research goals that would not be feasible without it. Screening millions of compounds against at least 14 different malaria targets using two different docking programs would take far more resources and time than academic researchers can obtain or spend. What can be accomplished with one (1) year of calculations on World Community Grid could take at least one hundred (100) years to complete using the resources normally available to the researchers at The Scripps Research Institute. Without the tremendous resources provided by World Community Grid, the project goals would have to be significantly scaled back to only screening a few thousand compounds against a few of these different malaria targets using a single docking program. World Community Grid will expand this malaria research by at least three orders of magnitude, greatly accelerating the rate at which these computational results can be obtained.
All GO Fight Against Malaria results will be in the public domain in the form of the virtual screening data that will be generated on World Community Grid and will be freely available to the global community of malaria researchers. Consequently, many other labs throughout the world will be able to use these results to help them discover new anti-malaria compounds that they and The Scripps Research Institute can then develop into new classes of drugs to treat this severe and neglected disease.