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WISDOM-II: screening against multiple targets implicated in malaria using computational grid infrastructures.

Kasam V, Salzemann J, Botha M, Dacosta A, Degliesposti G, Isea R, Kim D, Maass A, Kenyon C, Rastelli G, Hofmann-Apitius M, Breton V - Malar. J. (2009)

Bottom Line: Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.The modeling results obtained are very promising.Based on the modeling results, In vitro results are underway for all the targets against which screening is performed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754 Sankt Augustin, Germany. kasam@scai.fraunhofer.de

ABSTRACT

Background: Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery.

Motivation: Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.

Methods: In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures.

Results: On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed.

Conclusion: The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

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Related in: MedlinePlus

Illustrates the ligand plots of targets used in the current study. displays: A. Ligand plot of GST; B. Ligand lot of 2BLC; C. Ligand plot of 2Bl9; D. Ligand plot of 1J3I; E. Ligand plot of 1J3K. Ligand plots are obtained from Brookhaven protein database.
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Figure 1: Illustrates the ligand plots of targets used in the current study. displays: A. Ligand plot of GST; B. Ligand lot of 2BLC; C. Ligand plot of 2Bl9; D. Ligand plot of 1J3I; E. Ligand plot of 1J3K. Ligand plots are obtained from Brookhaven protein database.

Mentions: Re-docking can be defined as the removal of the co-crystallized compound (inhibitor or substrate) and then using a specific parameter set to dock this compound back into the active site of its target protein to validate the programs ability to dock novel compounds into the active site. These experiments serve as positive controls before large scale docking since aids in defining the active site and other simulation conditions. The docking pose during these experiments is validated by comparing the pose based on the RMSD between the atoms of the co-crystallized pose and the docking pose, as well as visual inspection of the orientation of the ligand. The lower the RMSD value and the more similar the docking pose to the co-crystallized ligand the better the docking results. Ligand plot information obtained from Brookhaven database serves as a template to validate the docking pose. The ligand plots of all the targets used in the current project are displayed in Figure 1. Ligand plots displays the binding mode of the co-crystallized ligand within the active site of the receptor, besides this it also describe the atom-to-atom interaction between the co-crystallized ligand to its respective receptor. This information is later compared with the docking poses before large-scale screening.


WISDOM-II: screening against multiple targets implicated in malaria using computational grid infrastructures.

Kasam V, Salzemann J, Botha M, Dacosta A, Degliesposti G, Isea R, Kim D, Maass A, Kenyon C, Rastelli G, Hofmann-Apitius M, Breton V - Malar. J. (2009)

Illustrates the ligand plots of targets used in the current study. displays: A. Ligand plot of GST; B. Ligand lot of 2BLC; C. Ligand plot of 2Bl9; D. Ligand plot of 1J3I; E. Ligand plot of 1J3K. Ligand plots are obtained from Brookhaven protein database.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2691744&req=5

Figure 1: Illustrates the ligand plots of targets used in the current study. displays: A. Ligand plot of GST; B. Ligand lot of 2BLC; C. Ligand plot of 2Bl9; D. Ligand plot of 1J3I; E. Ligand plot of 1J3K. Ligand plots are obtained from Brookhaven protein database.
Mentions: Re-docking can be defined as the removal of the co-crystallized compound (inhibitor or substrate) and then using a specific parameter set to dock this compound back into the active site of its target protein to validate the programs ability to dock novel compounds into the active site. These experiments serve as positive controls before large scale docking since aids in defining the active site and other simulation conditions. The docking pose during these experiments is validated by comparing the pose based on the RMSD between the atoms of the co-crystallized pose and the docking pose, as well as visual inspection of the orientation of the ligand. The lower the RMSD value and the more similar the docking pose to the co-crystallized ligand the better the docking results. Ligand plot information obtained from Brookhaven database serves as a template to validate the docking pose. The ligand plots of all the targets used in the current project are displayed in Figure 1. Ligand plots displays the binding mode of the co-crystallized ligand within the active site of the receptor, besides this it also describe the atom-to-atom interaction between the co-crystallized ligand to its respective receptor. This information is later compared with the docking poses before large-scale screening.

Bottom Line: Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.The modeling results obtained are very promising.Based on the modeling results, In vitro results are underway for all the targets against which screening is performed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754 Sankt Augustin, Germany. kasam@scai.fraunhofer.de

ABSTRACT

Background: Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery.

Motivation: Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.

Methods: In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures.

Results: On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed.

Conclusion: The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

Show MeSH
Related in: MedlinePlus