Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Modelling bound ligands in protein crystal structures.

P H Zwart1, G G Langer, V S Lamzin

  • 1European Molecular Biology Laboratory, c/o DESY, Notkestrasse 85, Building 25A, 22603 Hamburg, Germany.

Acta Crystallographica. Section D, Biological Crystallography
|December 2, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Scaffold hopping computational approach for searching novel β-lactamase inhibitors].

Biomeditsinskaia khimiia·2019
Same author

Novel non-β-lactam inhibitor of β-lactamase TEM-171 based on acylated phenoxyaniline.

Biochimie·2016
Same author

Tomography of a Cryo-immobilized Yeast Cell Using Ptychographic Coherent X-Ray Diffractive Imaging.

Biophysical journal·2015
Same author

Automated identification of crystallographic ligands using sparse-density representations.

Acta crystallographica. Section D, Biological crystallography·2014
Same author

Purification, biochemical characterization, and structure of recombinant endo-1,4-β-xylanase XylE.

Biochemistry. Biokhimiia·2012
Same author

From atoms to proteins.

Cellular and molecular life sciences : CMLS·2007
Same journal

Structural insights into the synthesis of FMN in prokaryotic organisms.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Native sulfur/chlorine SAD phasing for serial femtosecond crystallography.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Serial crystallographic analysis of protein isomorphous replacement data from a mixture of native and derivative microcrystals.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

The first crystal structure of the peptidase domain of the U32 peptidase family.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Atomic resolution crystal structure of Sapp2p, a secreted aspartic protease from Candida parapsilosis.

Acta crystallographica. Section D, Biological crystallography·2015
Same journal

Structural characterization of a mitochondrial 3-ketoacyl-CoA (T1)-like thiolase from Mycobacterium smegmatis.

Acta crystallographica. Section D, Biological crystallography·2015
See all related articles

This study introduces an automated method for identifying and building protein-bound ligands using electron-density maps. The approach utilizes a novel scoring function and graph-based search for efficient molecular model construction.

Area of Science:

  • Structural biology
  • Computational chemistry
  • Drug discovery

Background:

  • Accurate identification of protein-bound ligands is crucial for understanding biological processes and drug development.
  • Existing methods for ligand identification in electron-density maps can be labor-intensive and require significant prior knowledge.

Purpose of the Study:

  • To develop an automated, flexible, and efficient method for identifying and building protein-bound ligands directly from electron-density maps.
  • To reduce the reliance on extensive prior stereochemical knowledge in ligand model building.

Main Methods:

  • Development of an error model for ligand geometrical features based on simulated lattice distributions.
  • Construction of an approximate likelihood scoring function using the error model.

Related Experiment Videos

  • Integration of the scoring function with a graph-based search technique for automated model building.

    • Main Results:

    • Successful automated identification and building of several ligands (9-44 non-H atoms) in various X-ray structures.
    • Demonstration of promising initial results with the developed model-building scheme.
    • Validation of the method's ability to work with minimal stereochemical input.

    Conclusions:

    • The developed automated method offers a flexible and efficient approach for protein-bound ligand identification and building.
    • This technique has the potential to accelerate structural biology studies and drug discovery pipelines.
    • The method shows robustness across different ligand sizes and X-ray structures.