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Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Protein-ligand docking using FFT based sampling: D3R case study.

Dzmitry Padhorny1,2, David R Hall3, Hanieh Mirzaei4

  • 1Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, 11794, USA.

Journal of Computer-Aided Molecular Design
|November 5, 2017
PubMed
Summary
This summary is machine-generated.

A novel Fast Fourier Transform (FFT) method successfully models flexible protein-ligand interactions, performing among top methods in the D3R challenge. This approach offers global sampling of interactions for future drug discovery applications.

Keywords:
D3RDrug design data resourceFFT samplingProtein ligand docking

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Fast Fourier Transform (FFT) methods are established for modeling rigid protein-protein complexes.
  • Recent adaptations have enabled FFT for flexible protein-peptide interactions.
  • Flexible protein-ligand interactions remain a significant challenge in computational modeling.

Purpose of the Study:

  • To extend the Fast Fourier Transform (FFT) approach for modeling flexible protein-ligand interactions.
  • To evaluate the performance of the adapted FFT method in a drug discovery challenge.
  • To explore the potential of global interaction landscape sampling for drug design.

Main Methods:

  • Application of an adapted Fast Fourier Transform (FFT) methodology.
  • Integration with Monte Carlo minimization for off-grid refinement.
  • Testing on the D3R PL-2016-1 challenge dataset.

Main Results:

  • The FFT approach, combined with Monte Carlo minimization, achieved top-tier performance in the D3R PL-2016-1 challenge.
  • Demonstrated successful modeling of flexible protein-ligand interactions.
  • Indicated the method's capability for comprehensive interaction landscape exploration.

Conclusions:

  • The adapted FFT method is effective for modeling flexible protein-ligand interactions.
  • The approach shows promise for enhancing drug discovery pipelines through global sampling.
  • Further applications will investigate the full potential of this computational strategy.