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Mission and description of GO Fight Against Malaria

On November 16, 2011, we launched our new Global Online Fight Against Malaria project on IBM's World Community Grid. For a brief description of the project, check out this two minute YouTube clip:

 

For a thorough summary of phase 1 of the project and of the progress we have made so far, please read the new project update, posted July 14, 2014.


For a new paper that we published on January 30, 2015, about the results from GO FAM experiment 5 that could lead to new directions in tuberculosis research, click here and check out the animation at the bottom of this page.


Malaria is one of the three deadliest infectious diseases on earth. Half of the entire human population is at risk of being infected with malaria.  Plasmodium falciparum, the parasite that causes the deadliest form of malaria, has killed more people than any other parasite on the planet. In 2006, 247 million people became infected with malaria.  New data indicate that over a million people die from this disease each year, and over half of them are children. In fact, it's the leading cause of death in Africa for those under age five. Every 30 seconds, another child dies of malaria. According to the World Health Organization, malaria is both a disease of poverty and a cause of poverty. The survivors of malaria infections are often subjected to impaired learning, other developmental disorders, school absences, lost work, and increased economic distress. Where it's prevalent, this disease can account for 40 percent of all public health costs.

 

The GO Fight Against Malaria project is part of Professor Art Olson's lab at The Scripps Research Institute in La Jolla, CA, U.S.A.  We are performing this project on World Community Grid in order to discover promising candidate compounds that can be developed into new drugs that cure drug-resistant strains of malaria. In this project we will computationally evaluate millions of chemical compounds against different molecular drug targets from the malaria parasite. These computations will estimate the ability of the chemical compounds to disable the particular proteins that the Plasmodium parasite needs to survive, multiply, and infect humans.  That is, these "docking calculations" predict whether a particular compound can bind to and disable key components of the molecular machinery that the malaria parasite needs to survive and reproduce. Data from these GO Fight Against Malaria experiments (and data from all World Community Grid projects) are available to the public.  If any scientists from around the world want a copy of the GO FAM results, all they have to do is ask.  How cool is that!  After we process, measure, sort, and visually examine these computational results, the best-ranked candidate compounds will then be evaluated in test tubes and Petri dishes by collaborators (scientists in other labs), to see how effective they are at killing this parasite.  When we discover promising compounds that are proven to disable key proteins from the malaria parasite, we will publish these results and share them with the global community of malaria researchers.  We and other scientists will then be able to build upon these results and try to develop these promising compounds into new drugs that can kill the multi-drug-resistant superbugs that cause this deadly infectious disease.  Please donate your unused computer power, and let your PCs work on the problems that plague humanity.  Please join World Community Grid and help us and other labs advance the research against several diseases!  As Frank Sinatra sang, "it's nice work if you can get it, and you can get it if you try!"

 

Because of the power of World Community Grid, what we accomplished with one year of the GO Fight Against Malaria project could have taken us well over one hundred years to achieve, using the resources we normally have available.

 

In just 19 months, over 27,385 CPU years of computer time were donated to the Global Online Fight Against Malaria!  We have performed over 1.16 billion different docking jobs for the GO FAM project!!  Your donated computer time enabled us to have the first academic research project to ever perform over a billion docking jobs.  The members of the GO FAM team at TSRI and at Rutgers University-NJ Medical School are very grateful for all of your interest and generous support!!!


We have started analyzing, testing, and extending the results that this Global Online Fight Against Malaria project generated, and we look forward to sharing with you the insights that we will gain from these calculations. As this project progresses, we will keep you informed about the details of the experiments we are performing, the progress achieved, and the results that we publish. As you may know from our experience with the FightAIDS@Home project ( http://fightaidsathome.scripps.edu ), we will do our best to keep you informed and up-to-date by posting to the World Community Grid Forum for the GO FAM project and by responding to the questions and comments that you write there.

 

GO FAM experiment 5 included docking calculations against a key drug target for curing tuberculosis called "InhA," which is shown as lavender ribbons. The most potent new compound we discovered is a small, "fragment-sized" molecule--its predicted binding mode is displayed as thick sticks with cyan carbon atoms. The parts of InhA with which this compound is predicted to form the strongest binding interactions are shown as thin, dark purple sticks. Since this compound can block the activity of InhA without requiring prior activation (processing) of it by the enzyme "KatG" from Mycobacterium tuberculosis (Mtb), it might enable the future development of larger, more potent compounds that can defeat some of the drug-resistant mutant "superbugs" of Mtb (the bacteria that causes TB). See our new paper here and learn more here.

 

Click on the links in the menu in the top-left corner to learn more about malaria, about who we are, and about how you can help us fight this deadly infectious disease.  And check out the images below, which are from "positive control" calculations that prove that we can accurately predict/reproduce the detailed "binding mode" that some known, current inhibitors use to interact with and disable some key protein targets from the malaria parasite.

The two images below compare the experimentally-determined, X-ray crystallographic binding mode of WR-99210 (in purple), a potent inhibitor of dihydrofolate reductase from Plasmodium falciparum (Pf DHFR), to the mode that we predicted with the new software "AutoDock Vina" (in cyan).  Although this inhibitor can bind to and disable the multi-drug-resistant quadruple mutant superbug version of Pf DHFR, this compound is not "orally bioavailable" (that is, its chemical properties mean that it can never be turned into a pill, which is why we need to find other new inhibitors of this drug target).

 

For Frequently Asked Questions, see the FAQs page at: 

http://www.worldcommunitygrid.org/research/gfam/faq.do

 

This GO FAM website was created by Alex L. Perryman, Ph.D., now a Research Teaching Specialist III in Prof. Joel S. Freundlich's lab at Rutgers University-NJ Medical School.  It was last modified on 2/06/2015 by Dr. Alex L. Perryman.  All of the molecular images were created by Dr. Perryman using PMV (the "Python Molecular Viewer") 1.5.6 release candidate 3.

The GO Fight Against Malaria logo was created by Stefano Forli, Ph.D., a Staff Scientist in Prof. Art Olson's lab at TSRI.

© 2011-2015 The Olson Laboratory, The Scripps Research Institute, All Rights Reserved.

Malaria is a global crisis

Malaria is one of the three deadliest infectious diseases on Earth. Over three billion people are at risk of becoming infected with malaria. There are over two hundred million clinical cases of malaria each year, and over one million people are killed by malaria infections every year. The groups of people who are especially vulnerable to malaria infections are children and pregnant women.  Every 30 seconds, another child dies of malaria.

Plasmodium falciparum, the protozoan parasite that causes the most severe form of malaria, kills more people than any other parasite on the planet. Four other species of Plasmodium can also cause malaria infections in people (Plasmodium vivax, Plasmodium malariae, Plasmodium ovale, and Plasmodium knowlesi), but these four species tend to cause a milder form of malaria that is rarely fatal. Plasmodium vivax causes the largest number of malaria infections each year, but Plasmodium falciparum causes about 90% of the deaths that result from malaria infections. Consequently, most of our research on GO Fight Against Malaria will focus on Plasmodium falciparum, but we will also perform some research against the molecular targets from Plasmodium vivax.

Malaria infections are transmitted to humans by certain types of mosquitoes. Female mosquitoes from the genus Anopheles are the specific kinds of mosquitoes that are responsible for hosting and then spreading malaria infections. Since male mosquitoes eat plant nectar instead of blood, only the females transmit malaria infections. Female mosquitoes become infected with the malaria parasite when they drink the blood of a human who has a malaria infection. After being ingested by a mosquito, the parasite progresses through specific stages of its life cycle that can only occur when it is inside a mosquito. When that infected female mosquito then feeds on a different person, its saliva contains the malaria parasite, which gets injected into the person’s skin.  When these parasites replicate themselves in our red blood cells (which the parasites use for food), the symptoms of malaria appear.  Malaria initially causes fevers and headaches, and in severe cases it leads to comas or death.

Detailed descriptions and amazing visualizations of the malaria parasite’s life cycle in both mosquitoes and humans were created by Drew Berry and are available at:  http://youtu.be/zqJIrhLCFgQ?hd=1  (part 1 = human stages) and http://youtu.be/I_qSrFPjtQw?hd=1 (part 2 = mosquito stages). Note: Drew Berry was a 2010 MacArthur Foundation Fellow (that is, he received one of those "genius grants").

The Drew Berry clip on the Plasmodium falciparum parasite's life cycle within humans (listed above):

 

The Drew Berry clip on the malaria parasite's life cycle within the mosquito host (listed above):

 

 

In very rare cases, blood transfusions can also transmit malaria infections, but female mosquitoes are the main culprit.

Malaria thrives in tropical and subtropical regions. Malaria infections are found in at least 106 different countries. It predominantly infects people in Africa, South-East Asia, and South America. However, 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 or work in malaria-infested regions each year.

After a person has become infected with malaria, "chemotherapeutic approaches" are employed (that is, a drug or a combination of different drugs is used to cure the malaria infection). There are many different drugs that can be used to cure malaria infections; however, the parasites that cause malaria eventually evolve “drug resistance” against the specific chemicals that are used to eliminate the parasites.  Being "resistant" to a drug means that the specific target protein molecule, whose activity the drug blocks, has changed (or "mutated"), and the drug is no longer effective at treating the infection.  But at the same time, the mutation does not prevent the superbug from surviving and reproducing.   Being multi-drug-resistant means that the pathogen has acquired mutations that allow it to escape several different types of drugs simultaneously, while still allowing the pathogen to thrive and spread itself.  Since the ability to escape treatment by the drugs helps the parasite survive and multiply, these drug-resistant strains have a selective advantage that helps them out-compete the regular (“wild type”) strain of the parasite, which allows the superbugs to become persistent and widespread.

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.  For example, in the past the drug chloroquine was very useful for curing malaria infections, but the Plasmodium parasites eventually evolved drug resistance against chloroquine. Later, the dual drug combination of sulfadoxine plus pyrimethamine was developed. For several years it was very useful for curing malaria infections, and it helped save millions of lives. But then the Plasmodium parasites evolved resistance to this dual drug combination, too. Since resistance to sulfadoxine plus pyrimethamine started becoming very prevalent, the World Health Organization now recommends that artemisinin-based combination therapies (“ACTs”) be used to treat malaria infections. Unfortunately, Plasmodium falciparum parasites that are able to resist treatment with 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 kill the multi-drug-resistant mutants is a significant global health necessity.  The drug resistance phenomenon is the reason why we created the GO Fight Against Malaria project.

 

The GO Fight Against Malaria logo was created by Stefano Forli, Ph.D., a Research Associate in Prof. Art Olson's lab at TSRI.

Join World Community Grid

You can help us advance the fight against multi-drug-resistant mutant superbugs of malaria by following a few simple steps.  It won't take much of your time or energy at all.  Just click on this link to join IBM's World Community Grid, follow the simple instructions on that page, and you'll be able to help us fight malaria.  It will also give you the opportunity to help the other projects on World Community Grid, such as our FightAIDS@Home project, and the research that other labs perform to find new treatments for cancer, find renewable energy materials, create clean water techniques, or develop healthier food staples.

Please volunteer your unused computer time to World Community Grid to help us advance the discovery of completely new anti-malaria drugs that can be used to kill these superbugs.

Detailed description of the project and the tools we use

General Description of the project

The Go Fight Against Malaria project uses AutoDock 4.2 and the new “AutoDock Vina” computer software to evaluate millions of candidate compounds against at least 15 different molecular drug targets from the malaria parasite in order to discover new inhibitors that can block the activity of these multi-drug-resistant mutant superbugs.  The first half of the project will search for these promising candidate compounds with Vina, and the second half of the project will use AutoDock 4.2.  These compounds 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.  These calculations will be used to predict the affinity/potency of the compound, the location where it binds on the protein molecule, and the "binding 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  molecular 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 we discover in these virtual experiments will then be tested in “biological assays” performed by our collaborators in test tubes and Petri dishes. 

Once our collaborators have proven that some of these candidate compounds are definitely able to help kill 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 unwanted binding to human proteins can cause toxic side effects).  Once it is known that a compound is a novel inhibitor of one of these drug targets, scientists  called "medicinal chemists" can then extend and modify these compounds in order to accelerate the development of new anti-malaria drugs. 

 

General description of the "docking" calculations we are performing

We computationally predict how potent these candidate compounds might be at disabling key target molecules from the malaria parasite by performing “docking” calculations.  Docking is a way of trying to figure out how well a small chemical compound can bind to and block the activity of a target protein.  These calculations predict how potent the small chemical compound might be at blocking the activity of the target molecule, the location where it binds on the protein target, and the detailed binding mode it uses to potentially disable that target.  It's like trying to find the right key to open a particular lock.  However, both the lock and the keys are flexible—they can change shape, or transform their conformation, as they wiggle, jiggle, dance, expand, and contract in the warm watery environment in which they reside.  In addition, some locks have multiple different types of keyholes, and only one or two of them might be useful at disabling the parasite's molecular machinery.  When, by chance, the lock's internal structure happens to change a bit, the potential for evolutionary improvement occurs.  If that change in the lock's guts happens to help the parasite escape the effects of a key/drug, then that new lock becomes a “drug-resistant mutant”.  To make it even trickier, the total number of potential keys that could exist in the universe (the size of “chemical space”) is estimated to be about 10 to the 60th power (that is, 1 with 60 zeros after it).  We obviously can't computationally evaluate flexible models of that many different keys, so we'll focus these experiments on the types of keys that are somewhat similar to the types of molecules that have already become approved drugs.  In the GO Fight Against Malaria project, we will computationally evaluate millions of chemical compounds (potential keys) against models of at least 15 different drug targets from the malaria parasite.  Compounds that can bind tightly to the right regions of particular proteins from Plasmodium falciparum have the potential to “gum up” the parasite's machinery and, thus, help advance the discovery of new types of drugs to cure superbugs of malaria.

 

Detailed, technical description of the "docking" calculations we use

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 (http://mgl.scripps.edu).  The first phase of the project will computationally evaluate the potential potency of millions of compounds using the new software “AutoDock Vina,” which was created by Oleg Trott and Arthur J. Olson. The second phase of the project will computationally re-evaluate the potency of the same compounds using the program “AutoDock4.2,” which was created by Garrett M. Morris, Ruth Huey, William E. Hart, William Lindstrom, Alexander Gillet, David S. Goodsell, and Arthur J. Olson. 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 at http://fightaidsathome.scripps.edu), evaluating compounds with both AutoDock and Vina facilitated the discovery of novel inhibitors of HIV protease (which is a notoriously difficult protein to target).

AutoDock is a suite of automated docking tools designed to predict how “small molecule compounds,” such as substrates or drug candidates, bind to a receptor (target) of known 3-D structure and to estimate how tightly that small molecule binds to that receptor.  That is, it predicts both the small molecules “binding mode” and estimates its potency against the target.  The AutoDock algorithm is essentially a high dimensional stochastic search utilizing a “Lamarckian genetic algorithm” approach with flexible models of the small molecules.  When docking any given drug candidate against a particular protein target, the space of all possible configurations must be explored to find the best energetic fit between the two molecules.  Any given docking protocol must explore all possible degrees of freedom that are specified in the system.  AutoDock consists of two main programs:  autodock performs the docking of each compound against a set of grid maps that describe the energetic landscape of the target protein, and autogrid pre-calculates these grid maps before autodock is ran, which greatly increases the speed of the autodock phase of these calculations.

AutoDock Vina also uses pre-calculated grid maps (which are generated internally, instead of using a separate program, such as autogrid).  Vina also uses flexible models of the small molecules, and it also treats the docking process as a stochastic global optimization of the scoring function.  But Vina utilizes a different scoring function and a different search algorithm than AutoDock, and Vina’s search process is guided by the gradients in the energetic landscape of the target protein (unlike AutoDock4.2).  However, Vina uses the same “pdbqt” file format that AutoDock4.2 uses to represent the atomic models of both the target protein and the small molecules, which makes the process of preparing and analyzing the Virtual Screening experiments for GO Fight Against Malaria that will use both docking programs much, much easier.

 

The naming convention for the GO Fight Against Malaria work units

If you click on the "advanced view" of BOINC for World Community Grid, the names of the jobs we send out start with the abbreviation for the project (GFAM), followed by my internal filename for the target, followed by a unique batch identification number, followed by a work unit identification number. Each batch involves docking 10,000 different compounds with Vina against a single target. The batch numbers are described on the page with "Experiments we're performing and our future plans."  The names of the targets start with "x" to indicate that they were superimposed onto a specific, single coordinate reference frame. The x is generally followed by the PDB ID code for the structure of the target being used (see the Protein Data Bank at http://www.rcsb.org/pdb). NDP refers to the cofactor that is bound to a region of the active site in dihydrofolate reductase (DHFR, the first target for this project). If the target has WATs in the name, then some of the waters from the crystallographic structure of the target were included. In "positive control" docking calculations that involve reproducing the known binding mode of current inhibitors of DHFR, these crystallographic waters can sometimes improve the accuracy of the calculations. Other targets have "dry" in the name, to indicate that all of the water molecules from the crystallographic structure of the target were removed. If a compound can displace these crystallographic waters (which we can help determine by docking against both wet and dry versions of the target), then it might receive an extra energetic boost during the binding process.

Most of the targets are from Plasmodium falciparum, the species of parasite that causes the deadliest form of malaria, but some of the jobs involve the same type of target from Plasmodium vivax, the species of malaria that causes the most malaria infections (but vivax infections tend to be less fatal than infections with falciparum). Finding new compounds that can inhibit the targets from both Plasmodium falciparum and Plasmodium vivax would be very clinically useful.

Some targets have TB in the name, which indicates that these targets are enzymes from Mycobacterium tuberculosis. The three deadliest infectious diseases are HIV, malaria, and tuberculosis. Some of these GO Fight Against Malaria experiments involve screening compounds against the versions of a particular drug target from both malaria and tuberculosis; thus, we'll be sneaking in some tuberculosis research while we fight against malaria. This is scientifically justified, since it is known that some potent inhibitors of dihydrofolate reductase (DHFR) from malaria are also able to inhibit DHFR from tuberculosis. Similarly, some of the inhibitors of malaria's enoyl-acyl-carrier-protein reductase (ENR) are also good inhibitors of the version of ENR from tuberculosis (which is called "InhA"). Consequently, searching for compounds that can inhibit these targets from both malaria and tuberculosis could be very useful against malaria, and it could help advance the research against two of the deadliest infectious diseases on the planet.

  

The two images above show the results of a "positive control" experiment with Vina against Pf ENR (enoyl-acyl-carrier-protein reductase).  The image on the right is a close-up of the active site region (the specific keyhole we are trying to disable), while the full target is displayed on the left.  These images demonstrate that we can accurately predict/reproduce the detailed "binding mode" that a known inhibitor uses to disable this key drug target.  The known, experimentally-determined, X-ray crystallographic binding mode of this inhibitor is shown in magenta, while the results from the Vina calculations are displayed in cyan.

 

A few experiments also involve the version of a particular enzyme from humans (such as DHFR). We want to find compounds that are predicted to inhibit the targets from malaria, but we don't want these compounds to strongly inhibit the enzymes in humans (since inhibiting certain human enzymes can cause toxic side effects). Thus, to advance research against malaria, we'll harvest compounds that dock well against the targets from malaria and that also score poorly against the human version of that enzyme. However, since all data from this project are in the public domain, the data on the compounds that happen to score very well against the human DHFR could help other scientists advance the search for new drugs against some types of cancer or new drugs to prevent the rejection of transplanted organs. I like to design experiments that can produce multiple bangs for the buck.  ;)

The molecular targets at which we are aiming

Both AutoDock Vina and AutoDock4.2 will be used to screen millions of candidate compounds against at least 15 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).

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.