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Protein-ligand binding site detection as an alternative route to molecular docking and drug repurposing

Protein-ligand binding site detection as an alternative route to molecular docking and drug... http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bio-Algorithms and Med-Systems de Gruyter

Protein-ligand binding site detection as an alternative route to molecular docking and drug repurposing

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Publisher
de Gruyter
Copyright
©2018 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1896-530X
eISSN
1896-530X
DOI
10.1515/bams-2018-0004
Publisher site
See Article on Publisher Site

Abstract

Journal

Bio-Algorithms and Med-Systems – de Gruyter

Published: May 26, 2018

References

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  • FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins
  • Computational protein-ligand docking and virtual drug screening with the AutoDock suite
  • AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading
  • The recognition of identical ligands by unrelated proteins
  • ZINC – a free database of commercially available compounds for virtual screening
  • Structural insights into the competitive binding of diclofenac and naproxen by equine serum albumin
  • LIBRA-WA: a web application for ligand binding site detection and protein function recognition
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  • Evidence that diclofenac and celecoxib are thyroid hormone receptor beta antagonists
  • Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches
  • NRGsuite: a PyMOL plugin to perform docking simulations in real time using FlexAID
  • The protein data bank
  • DrugBank 4.0: shedding new light on drug metabolism
  • Specific binding of non-steroidal anti-inflammatory drugs (NSAIDs) to phospholipase A2: structure of the complex formed between phospholipase A2 and diclofenac at 2.7 Å resolution
  • Octopus: a platform for the virtual high-throughput screening of a pool of compounds against a set of molecular targets
  • Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment
  • Scoring functions for prediction of protein-ligand interactions
  • Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment
  • Thyroid receptor ligands. 6. A high affinity “direct antagonist” selective for the thyroid hormone receptor