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

Area of Science:

• Computational chemistry and bioinformatics
• Drug discovery and development
• Parasitology and infectious diseases

Background:

• Malaria remains a significant global health challenge, necessitating novel drug discovery efforts.
• The Plasmodium parasite's metabolic proteins are key targets for rational drug design.
• Grid computing offers a powerful infrastructure for large-scale computational tasks like virtual screening.

Purpose of the Study:

• To leverage grid-enabled virtual screening for large-scale molecular docking.
• To identify novel drug scaffolds against malaria targets, including Plasmodium falciparum glutathione-S-transferase (PfGST) and dihydrofolate reductase (PfDHFR).
• To explore drug discovery for wild-type and mutant forms of Plasmodium vivax dihydrofolate reductase (PvDHFR).

Main Methods:

• Utilized in silico drug design, specifically virtual high-throughput screening (vHTS) with molecular docking.
• Employed the FlexX software on a computational grid infrastructure for large-scale docking simulations.
• Integrated computational chemistry advancements with IT for efficient grid operations and data analysis.

Main Results:

• Developed a robust computational infrastructure for large-scale docking, result analysis, and data storage.
• Applied molecular dynamics refinement and MM-PBSA/MM-GBSA rescoring for enhanced accuracy.
• Obtained promising modeling results, with in vitro validation currently in progress for identified hits.

Conclusions:

• Demonstrated the efficacy of grid-enabled virtual screening for identifying drug hits against key malaria targets.
• Proposed this approach as a scalable solution for generating focused compound libraries against various infectious disease targets.
• Highlighted the potential of computational grids in accelerating rational drug discovery for neglected diseases.