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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Knowledge-based virtual screening: application to the MDM4/p53 protein-protein interaction.

Edgar Jacoby1, Andreas Boettcher, Lorenz M Mayr

  • 1Novartis Institutes for BioMedical Research, Novartis Pharma AG, Basel, Switzerland.

Methods in Molecular Biology (Clifton, N.J.)
|September 4, 2009
PubMed
Summary
This summary is machine-generated.

Knowledge-based virtual screening successfully identified potential cancer drug candidates by applying insights from the MDM2-p53 interaction to the related MDM4-p53 target. This approach leverages multiple screening methods and automation for efficient drug discovery.

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Area of Science:

  • * Computational chemistry and drug discovery.
  • * Molecular modeling and cheminformatics.
  • * Cancer therapeutics research.

Background:

  • * Chemogenomics enables knowledge transfer between related biological targets for drug discovery.
  • * The MDM2-p53 and MDM4-p53 protein-protein interactions are critical targets in cancer therapy.
  • * Virtual screening methods are essential for identifying novel inhibitors.

Purpose of the Study:

  • * To demonstrate the efficacy of knowledge-based virtual screening for drug discovery.
  • * To apply insights from the MDM2-p53 system to identify inhibitors for the MDM4-p53 target.
  • * To discover novel, selective, and dual inhibitors for both MDM2-p53 and MDM4-p53 interactions.

Main Methods:

  • * Employed a combination of virtual screening techniques: homology-based similarity searching, Quantitative Structure-Activity Relationship (QSAR), High Throughput Docking (HTD), and UNITY pharmacophore searching.
  • * Utilized High Throughput Cherry-Picking (HTCP) automation and Medium Throughput Screening (MTS) fluorescence-based assays.
  • * Screened a corporate compound library of approximately 1.2 million compounds.

Main Results:

  • * Identified a virtual screening hit list of approximately 50,000 compounds.
  • * Discovered significantly more and stronger hits for the reference MDM2-p53 system compared to the MDM4-p53 system.
  • * Identified novel, selective, and dual inhibitors for both MDM2-p53 and MDM4-p53 interactions.
  • * Provided a hit rate analysis compared to full High-throughput Screening (HTS).

Conclusions:

  • * Knowledge-based virtual screening is a feasible and successful approach for discovering inhibitors of protein-protein interactions relevant to cancer.
  • * Automation and advanced screening assays are crucial for the success of large-scale virtual screening campaigns.
  • * The study identified promising hit compounds for further development as potential cancer therapeutics.