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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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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 structure and computational drug discovery.

Tracy L Nero1, Michael W Parker2,3, Craig J Morton1

  • 1Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia.

Biochemical Society Transactions
|September 23, 2018
PubMed
Summary
This summary is machine-generated.

Structure-based drug discovery uses protein structures to find small molecule ligands. This computational approach, computer-aided drug discovery, has led to marketed drugs and continues to evolve.

Keywords:
computational biochemistrydrug discovery and designstructural biology

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Area of Science:

  • Biochemistry and Structural Biology
  • Computational Chemistry and Cheminformatics
  • Pharmacology and Drug Discovery

Background:

  • Protein structures are stabilized by intricate networks of weak molecular interactions.
  • Small molecule ligands bind to proteins via these weak interactions, influencing protein function or acting as substrates.
  • Understanding ligand-protein binding is crucial for developing targeted therapeutics.

Purpose of the Study:

  • To provide an overview of current methodologies in structure-based computer-aided drug discovery.
  • To discuss the evolution of predicting and identifying small molecule ligands for protein targets.
  • To comment on future directions and potential advancements in the field.

Main Methods:

  • Leveraging known protein three-dimensional structures for computational analysis.
  • Predicting potential binding sites and interactions of small molecules with target proteins.
  • Utilizing computational tools to identify or design novel drug candidates.

Main Results:

  • Structure-based computer-aided drug discovery is an established technique yielding successful marketed drugs.
  • The field has progressed from understanding binding events to predicting and identifying ligands.
  • Various computational methodologies are currently employed for drug discovery.

Conclusions:

  • Computer-aided drug discovery, grounded in protein structural data, has proven efficacy in therapeutic development.
  • Continued advancements in computational methods promise further innovation in identifying novel drug candidates.
  • The field is poised for future developments that will enhance the efficiency and success of drug discovery.