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 Concept Videos

Drug Discovery: Overview01:26

Drug Discovery: Overview

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...
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...

You might also read

Related Articles

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

Sort by
Same author

PegaPlus─Interactive Machine Learning by Human Observation for Efficient Clustering and Analysis of Structure-Activity Data.

Journal of chemical information and modeling·2026
Same author

Enabling Automatic Generation of Protein-Ligand Complex Data Sets with Atomistic Detail.

Journal of chemical information and modeling·2026
Same author

Guiding Similarity Search in Chemical Fragment Spaces with Weighted Fingerprints.

Journal of chemical information and modeling·2026
Same author

ActivityFinder: Toward the Fully Automatic Integration of Structural and Binding Affinity Data.

Journal of chemical information and modeling·2026
Same author

A bottom-up approach to find lead compounds in expansive chemical spaces.

Communications chemistry·2025
Same author

Correction: SAVI Space-combinatorial encoding of the billion-size synthetically accessible virtual inventory.

Scientific data·2025

Related Experiment Video

Updated: Jun 24, 2026

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Beyond the virtual screening paradigm: structure-based searching for new lead compounds.

Jochen Schlosser1, Matthias Rarey

  • 1Center for Bioinformatics, Research Group for Computational Molecular Design, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.

Journal of Chemical Information and Modeling
|April 10, 2009
PubMed
Summary

A new method, TrixX BMI, offers faster structure-based virtual screening by directly matching chemical and shape complementarity to protein active sites. This approach avoids sequential screening, enabling rapid identification of potential drug candidates.

More Related Videos

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin
06:29

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

Related Experiment Videos

Last Updated: Jun 24, 2026

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin
06:29

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Structural biology

Background:

  • Traditional structure-based high-throughput virtual screening (SB-HTVS) involves sequential screening of large compound libraries against target proteins.
  • This sequential process can be computationally intensive and time-consuming, limiting its efficiency in drug discovery pipelines.
  • There is a need for more rapid and efficient methods to identify potential drug candidates based on their interaction with protein targets.

Purpose of the Study:

  • To introduce a novel paradigm for virtual screening that bypasses the sequential screening pipeline.
  • To present a new method, TrixX BMI, for directly assessing chemical and shape complementarity between ligands and protein active sites.
  • To enable rapid identification of compounds with desired pharmacophore interactions.

Main Methods:

  • Development of a novel descriptor for direct ligand-target interaction assessment.
  • Integration of docking calculations within the search process, inherently providing ligand poses.
  • Utilization of innovative indexing technology to achieve sublinear runtimes relative to the number of ligands.

Main Results:

  • TrixX BMI correctly predicts ligand poses within 2.0 Å RMSD in 80% of 85 protein-ligand complexes from the Astex Diverse Set.
  • Comparative enrichment experiments demonstrate TrixX BMI's competitiveness with established virtual screening technologies.
  • The method achieves runtimes significantly below one second per compound, showcasing its speed advantage.

Conclusions:

  • TrixX BMI represents a significant advancement in structure-based virtual screening, offering a non-sequential and efficient approach.
  • The method's ability to directly query chemical and shape complementarity accelerates the identification of potential drug candidates.
  • TrixX BMI provides a competitive and faster alternative to existing virtual screening technologies, particularly for pharmacophore-driven screening.