Search Results for: ranking
How is my individual member rank calculated?
A member may see their individual stats on their My Contribution page for run time, points, and results returned. Your individual rank is based on the total number of members that have returned a result. You may see how many members there currently are on the Global Statistics page.
How is my team rank calculated?
A member may see their team stats on their My Team page for run time, points, and results returned. Your team rank is based on the total number of teams that have returned a result. You may see how many teams there currently are on the Team Statistics page.
What is molecular docking and virtual screening?
Docking is the process of bringing together two objects. For example, a ship docks with a pier in a harbor. Molecular docking refers to a computer simulation in which two molecules are brought together. In our case, we dock a "small" molecule (i.e., a possible drug) to a target molecule (i.e., the viral NS3 protease). A docking program predicts the orientation or pose of the small molecule when bound to the target. This is accomplished by maximizing favorable interactions and minimizing unfavorable interactions between the two molecules. In addition, the program gives each pose a score based on these interactions and the conformation of the small molecule.
Virtual screening is the process of systematically screening a database of small molecules against a defined target molecule. The scores provided by the docking programs rank how well the small molecule docks to the target protein relative to other molecules in the database. Unfortunately, these rankings typically produce a large number of false positives. In this project, binding free energy calculations, combined with docking scores, will provide an accurate prediction of compounds that most strongly bind to the target protease.
What is molecular docking and virtual screening?
Docking is the process of bringing together two objects. For example, a ship docks with a pier in a harbor. Molecular docking refers to a computer simulation in which two molecules are brought together. In our case, we dock a "small" molecule (i.e., a possible drug) to a target molecule (i.e., the viral NS3 protease). A docking program predicts the orientation or pose of the small molecule when bound to the target. This is accomplished by maximizing favorable interactions and minimizing unfavorable interactions between the two molecules. In addition, the program gives each pose a score based on these interactions and the conformation of the small molecule.
Virtual screening is the process of systematically screening a database of small molecules against a defined target molecule. The scores provided by the docking programs rank how well the small molecule docks to the target protein relative to other molecules in the database. Unfortunately, these rankings typically produce a large number of false positives. In this project, binding free energy calculations, combined with docking scores, will provide an accurate prediction of compounds that most strongly bind to the target protease.
What will World Community Grid's calculations produce?
The calculations done on World Community Grid will predict which small molecule compound, out of the millions contained in our library database, should be tested for their ability to inhibit the flavivirus protease. This is a major step towards our ultimate goal of discovering new drugs to stop flavivirus infections.
Phase 1 of this project will predict how each small molecule might bind to the active site of the viral protease. This phase also produces preliminary "energies" that coarsely rank the strength of the intermolecular interactions between the compound and viral protease.
Phase 2 will accurately predict free energies of binding between each compound and the viral protease. This calculation utilizes the binding orientations calculated in phase 1. Due to computation time required for each free energy of binding calculation, only compounds with "good" scores from phase1 will be selected for phase 2 calculations.
As analogy, phase 1 will tell us how two people might hold hands, whereas phase 2 will tell us whether or not they want to hold hands.
What will World Community Grid's calculations produce?
The calculations done on World Community Grid will predict which small molecule compounds, out of the millions contained in a library database, should be tested for their ability to inhibit the flavivirus protease. This is a major step towards the ultimate goal of discovering new drugs to stop flavivirus infections.
Phase 1 of this project predicted how each small drug molecule might bind to the active site of the viral protease. This phase also produced preliminary "energies" that coarsely rank the strength of the intermolecular interactions between the compounds and viral protease.
Phase 2 will accurately predict free energies of binding between each drug compound and the viral protease. This calculation utilizes the binding orientations calculated in Phase 1. Due to computation time required for each free energy of binding calculation, only compounds with "good" scores from Phase 1 will be selected for Phase 2 calculations.
As an analogy, Phase 1 will tell us how two people might hold hands, whereas Phase 2 will tell us whether or not they want to hold hands.
Phase 2 of our project is designed to reduce the number of Phase 1 false positives (i.e., dead ends) that are tested in our laboratory. Phase 2 will take several thousand Phase 1 hits, run each hit through computationally demanding free energy calculations, and remove many of the false positives from the hit list. Phase 2 is expected to produce an updated list of hits that contains ~80% true positives. Testing Phase 2 hits in the laboratory will be much more productive, efficient, and rewarding than testing Phase 1 hits. For instance, to find 25 small molecules that stop dengue virus replication in the laboratory, we would need to synthesize and test either 250-500 Phase 1 hits or ~30 Phase 2 hits.
How is Protinfo different from other approaches?
Protein structure prediction is an active area of research, and no one method or methodology is "best" for all situations. The public success of projects like Folding@Home, POEM@Home, Human Proteome Folding, and Rosetta@Home are evidence of the interest in solving this computationally challenging problem. We wish to offer another approach that differs in certain subtle but significant ways that can provide complementary and competitive results.
Some approaches (like Folding@Home and POEM@Home) simulate the protein folding process as we believe it occurs in real life, where physical energies are minimized. Protinfo (like Human Proteome Folding and Rosetta@Home) uses a minimization of "statistical energies" to identify likely protein structures, but with a slightly different approach. Rather than relying on a single complex energy function, Protinfo uses a simple, easily evaluated function and chooses the best structures by following up with a set of more sophisticated functions. Another difference is that Protinfo uses a novel continuous sampling methodology that enables us to explore good structures more finely. The continuous sampling methodology incurs little memory overhead and evaluating our compact energy function is very fast. This allows Protinfo to run on almost any computer.
The Protinfo structure predictions have been ranked as some of the best by the Critical Assessment of Structure Prediction (CASP) competition since 1994. You can read more about Protinfo on the researchers' page about this project.
Why is TB still a major global health problem?
One factor in the increase of TB infection is related to an increase in HIV infection. People with HIV/AIDS have a weakened immune system and are therefore more susceptible to TB. Once healthy people come into contact with the TB bacteria, the bacteria can usually be fought off effectively by their immune system without developing TB. However, a person with HIV is about 30 times more likely to develop TB disease, due to their weakened immune system. It is more difficult to detect and treat TB in an HIV-infected individual, and therefore those co-infected with TB and HIV often remain reservoirs of TB for extended times, with the potential of infecting more people.
Another factor in the increased TB infection is the TB bacteria becoming increasingly resistant to TB drugs. As drug resistance has increased, it has become more difficult to treat TB successfully, requiring much longer treatment times with combinations of drugs. Often, patients fail to continue treatments to the full term which can take up to two years. When treatment stops part-way, the bacteria evolve resistance to the drugs because it lets the bacteria that survived the initial portion of treatment live and infect others. This also results in people carrying TB for a longer time, potentially infecting more people with drug resistant strains of TB that are more difficult to treat. The World Health Organization recently ranked tuberculosis as nearly tied with HIV as the deadliest infectious disease in the world, mostly due to TB building its resistance to drugs.