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Advances in Bioinformatics and Computational Biology

Volume 5676 of the series Lecture Notes in Computer Science pp 143-146

FReDD: Supporting Mining Strategies through a Flexible-Receptor Docking Database

  • Ana T. WinckAffiliated withPPGCC, Faculdade de Informática, PUCRS
  • , Karina S. MachadoAffiliated withPPGCC, Faculdade de Informática, PUCRS
  • , Osmar Norberto-de-SouzaAffiliated withPPGCC, Faculdade de Informática, PUCRS
  • , Duncan D. D. RuizAffiliated withPPGCC, Faculdade de Informática, PUCRS

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Abstract

Among different alternatives to consider the receptor flexibility in molecular docking experiments we opt to execute a series of docking using receptor snapshots generated by molecular dynamics simulations. Our target is the InhA enzyme from Mycobacterium tuberculosis bound to NADH, TCL, PIF and ETH ligands. After testing some mining strategies on these data, we conclude that, to obtain better outcomes, the development of an organized repository is especially useful. Thus, we built a comprehensive and robust database called FReDD to store the InhA-ligand docking results. Using this database we concentrate efforts on data mining to explore the docking results in order to accelerate the identification of promising ligands against the InhA target.

Keywords

Molecular docking database data preparation data mining