Computational fishing of new DNA methyltransferase inhibitors from natural products


Abstract:

DNA methyltransferase inhibitors (DNMTis) have become an alternative for cancer therapies. However, only two DNMTis have been approved as anticancer drugs, although with some restrictions. Natural products (NPs) are a promising source of drugs. In order to find NPs with novel chemotypes as DNMTis, 47 compounds with known activity against these enzymes were used to build a LDA-based QSAR model for active/inactive molecules (93% accuracy) based on molecular descriptors. This classifier was employed to identify potential DNMTis on 800 NPs from NatProd Collection. 447 selected compounds were docked on two human DNA methyltransferase (DNMT) structures (PDB codes: 3SWR and 2QRV) using AutoDock Vina and Surflex-Dock, prioritizing according to their score values, contact patterns at 4 Å and molecular diversity. Six consensus NPs were identified as virtual hits against DNMTs, including 9,10-dihydro-12-hydroxygambogic, phloridzin, 2′,4′-dihydroxychalcone 4′-glucoside, daunorubicin, pyrromycin and centaurein. This method is an innovative computational strategy for identifying DNMTis, useful in the identification of potent and selective anticancer drugs.

Año de publicación:

2015

Keywords:

  • CLÚSTER
  • docking
  • screening
  • ANTICANCER
  • QSAR

Fuente:

googlegoogle
scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Bioquímica
  • Descubrimiento de fármacos

Áreas temáticas:

  • Ciencias de la computación
  • Economía financiera
  • Biología