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Updated: Apr 22, 2026

Measuring Cation Transport by Na,K- and H,K-ATPase in Xenopus Oocytes by Atomic Absorption Spectrophotometry: An Alternative to Radioisotope Assays
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Measuring Cation Transport by Na,K- and H,K-ATPase in Xenopus Oocytes by Atomic Absorption Spectrophotometry: An Alternative to Radioisotope Assays

Published on: February 19, 2013

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KAISO inhibition: an atomic insight

Naveed Anjum Chikan1, Bhavaniprasad Vipperla

  • 1a Medical Biotechnology Division, School of Bio Sciences and Technology , VIT University , Vellore 632014 , Tamilnadu , India.

Journal of Biomolecular Structure & Dynamics
|October 10, 2014
PubMed

Insights

Researchers identified a promising natural compound (chem. ID 28127) as a potential anti-cancer agent. This compound targets the kaiso protein, a key player in epigenetics, showing high binding affinity and stability in simulations.

Area of Science:

  • Oncology
  • Epigenetics
  • Computational Chemistry

Background:

  • The increasing global cancer burden necessitates novel therapeutic strategies.
  • Epigenetics, involving gene methylation, plays a crucial role in cancer development.
  • Kaiso, a methyl-CpG binding protein, is a significant target in epigenetic cancer research.

Purpose of the Study:

  • To identify novel inhibitors targeting the kaiso protein using computational methods.
  • To explore the potential of natural compounds as anti-cancer agents.
  • To investigate the binding interactions of potential inhibitors with the kaiso protein.

Main Methods:

  • Virtual screening of a natural compound database (48,531 compounds) against the X-ray crystallographic structure of kaiso.
  • Focusing on the C2H2 domain and LYS539 residue for inhibitor screening.
  • Utilizing computer-aided drug design (CADD) for compound selection and molecular dynamics (MD) simulations (20 ns).

Main Results:

  • Computer-aided drug design effectively filtered out unsuitable compounds.
  • The top-ranked compound (chem. ID 28127) demonstrated the highest binding affinity to kaiso.
  • Compound 28127 remained stable during the 20 ns molecular dynamics simulation.

Conclusions:

  • Compound 28127 shows significant potential as a starting point for developing potent anti-cancer inhibitors.
  • This study highlights the efficacy of CADD in identifying novel epigenetic drug candidates.
  • Targeting kaiso offers a promising avenue for novel cancer therapies.
Keywords:
Kaisodrug designingfree energy landscapemolecular dockingmolecular dynamics simulations

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