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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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Conserved Binding Sites01:49

Conserved Binding Sites

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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.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Ligand Binding and Linkage00:49

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Metal-Ligand Bonds02:51

Metal-Ligand Bonds

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The hemoglobin in the blood, the chlorophyll in green plants, vitamin B-12, and the catalyst used in the manufacture of polyethylene all contain coordination compounds. Ions of the metals, especially the transition metals, are likely to form complexes.
In these complexes, transition metals form coordinate covalent bonds, a kind of Lewis acid-base interaction in which both of the electrons in the bond are contributed by a donor (Lewis base) to an electron acceptor (Lewis acid). The Lewis acid in...
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Crystal Field Theory - Octahedral Complexes02:58

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Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
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Ligand placement based on prior structures: the guided ligand-replacement method.

Herbert E Klei1, Nigel W Moriarty1, Nathaniel Echols1

  • 1Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

Acta Crystallographica. Section D, Biological Crystallography
|January 15, 2014
PubMed
Summary
This summary is machine-generated.

A new Guided Ligand Replacement (GLR) module in Phenix simplifies modeling ligands into protein structures. This computational tool leverages existing structural data to accelerate drug design and improve accuracy.

Keywords:
GLRguided ligand-replacement methodligand placement

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Area of Science:

  • Structural biology
  • Computational chemistry
  • Drug discovery

Background:

  • Iterative structure-based drug design relies on analyzing numerous X-ray crystal structures of ligands bound to protein targets.
  • Current ligand placement methods in electron density maps are time-consuming and do not effectively use information from similar, previously modeled ligands.
  • Improving ligand placement efficiency is crucial for accelerating the drug discovery pipeline and optimizing drug properties.

Purpose of the Study:

  • To develop a novel computational module, Guided Ligand Replacement (GLR), to enhance the ease and success rate of ligand placement in protein structures.
  • To leverage existing structural information of similar ligands and protein targets to expedite the modeling process.
  • To provide an efficient solution for modeling complex ligands and in scenarios with limited or no prior structural data.

Main Methods:

  • Development of the Guided Ligand Replacement (GLR) module within the Phenix software suite.
  • Implementation of a graph theory-based algorithm to identify analogous atoms between target and reference ligands.
  • Generation of target ligand coordinates based on the established atom correspondence from prior structures.

Main Results:

  • The GLR module successfully increases the ease and success rate of ligand placement, particularly for large, flexible, or macrocyclic compounds.
  • GLR efficiently models ligands even when no reference structure is available, by utilizing multiple ligand copies within the asymmetric unit.
  • The tool effectively leverages prior structural knowledge to facilitate accurate ligand modeling in new protein-ligand complexes.

Conclusions:

  • Guided Ligand Replacement (GLR) offers a significant advancement in computational drug design, streamlining the analysis of protein-ligand complexes.
  • The module's ability to utilize existing structural data makes it invaluable for iterative drug design and structure refinement pipelines.
  • GLR enhances the efficiency and accuracy of modeling diverse and complex ligands, accelerating the identification of improved drug candidates.