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

Molecular Models02:00

Molecular Models

43.0K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.0K

You might also read

Related Articles

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

Sort by
Same author

Machine Learning-Driven Ensemble Screening of Multitarget Kinase Inhibitors for Tauopathy-Associated Neurodegeneration Using All-Atom and Steered MD Simulations.

ACS chemical neuroscience·2026
Same author

Integrated Virtual Screening and Molecular Dynamics Simulation Study to Discover Potential Activators of γ-Aminobutyric Acid B Receptor 1 for Therapeutic Targeting of Neurodegenerative Diseases.

Chemical biology & drug design·2026
Same author

Multi-Omics and Machine Learning-Driven Discovery of ABCC8 (SUR1) for Diabetes Mellitus: Integrating Molecular Insights on Nigella sativa Bioactives and Sulfonylurea.

Chemical biology & drug design·2026
Same author

Stability and Conformational Dynamics of Interferons: Structural Insights into the Urea- and Guanidinium Chloride-Induced Unfolding.

ACS omega·2026
Same author

Identification of FDA-Approved Drugs as Potential Inhibitors of WEE2: Structure-Based Virtual Screening and Molecular Dynamics with Perspectives for Machine Learning-Assisted Prioritization.

Life (Basel, Switzerland)·2026
Same author

Structural and Functional Insights Into Lyn Kinase: From Immune Regulation to Therapeutic Targeting.

Journal of cellular biochemistry·2026
Same journal

Literature-informed gene extraction and ranking for multimodal data fusion.

Briefings in bioinformatics·2026
Same journal

SA-MTP: a structure-aware framework for multifunctional therapeutic peptide annotation.

Briefings in bioinformatics·2026
Same journal

Genome assemblies and annotations are not static and need support for tracking their evolution.

Briefings in bioinformatics·2026
Same journal

A historical journey of metabolite-protein interaction discovery: from data harmonization to AI-driven prediction.

Briefings in bioinformatics·2026
Same journal

Bridging local-global transmembrane protein contexts with contrastive pretraining for alignment-free pathogenicity prediction.

Briefings in bioinformatics·2026
Same journal

Prediction of drug hypersensitivity by comprehensive modeling of HLA-peptidomes.

Briefings in bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Dec 3, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

891

InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening.

Taj Mohammad1, Yash Mathur2, Md Imtaiyaz Hassan3

  • 1Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.

Briefings in Bioinformatics
|October 26, 2020
PubMed
Summary
This summary is machine-generated.

InstaDock simplifies molecular docking and virtual screening with an easy-to-use interface. This free tool aids researchers in drug discovery by efficiently predicting protein-ligand interactions.

Keywords:
AutoDock VinaInstaDockQuickVina-Wdocking GUIdocking tooldrug discoveryprotein–ligand interactionvirtual high-throughput screeningvirtual screening

More Related Videos

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

721
Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

3.4K

Related Experiment Videos

Last Updated: Dec 3, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

891
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

721
Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

3.4K

Area of Science:

  • Computational Biology
  • Drug Discovery
  • Structural Bioinformatics

Background:

  • Protein-ligand interactions are crucial for understanding molecular recognition and biological functions.
  • Predicting these interactions accurately is a significant challenge in computational chemistry.
  • Molecular docking is a key computational method for analyzing protein-ligand binding.

Purpose of the Study:

  • To develop an efficient and user-friendly tool for molecular docking and virtual screening.
  • To provide a simplified interface for non-bioinformaticians to perform complex analyses.
  • To facilitate rapid identification of potential drug leads through high-throughput virtual screening.

Main Methods:

  • Development of InstaDock, a Graphical User Interface (GUI) program.
  • Integration of QuickVina-W, a modified AutoDock Vina, for docking calculations.
  • Implementation of a single-click workflow for docking and analysis.

Main Results:

  • InstaDock offers an efficient platform for molecular docking and virtual screening.
  • The GUI is designed for ease of use, catering to non-expert users.
  • Onboard analysis and visual results are accessible with a single click.

Conclusions:

  • InstaDock provides a more interactive and user-friendly interface compared to existing tools.
  • The software is freely available for academic and industrial research.
  • InstaDock streamlines the process of exploring protein-ligand interactions for drug discovery.