Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Molecular Orbital Theory II

Molecular Orbital Theory II

Molecular Orbital Energy Diagrams

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

Molecular Models

Molecular Models

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.

End Point Prediction: Gran Plot

End Point Prediction: Gran Plot

A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...

Sensitivity, Specificity, and Predicted Value

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...

You might also read

Related Articles

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

Sort by

Same author

Virtual screening-guided repurposing of fluorescent probes to detect EGFR expression in renal cells.

Bioorganic chemistry·2026

Same author

MINERVA: a public XAI-powered platform advancing multi-target discovery in Alzheimer's disease.

Journal of cheminformatics·2026

Same author

Explainable Bidirectional Long Short-Term Memory Networks Learn Chemistry from SMILES for Predicting Toxicity of Androgen and Estrogen Receptor Chemicals.

ACS omega·2026

Same author

MD Simulations of Human Sigma-1 Receptor Trimer Uncover Cholesterol-Dependent Stabilization and Ligand-Specific Dynamics.

Journal of chemical information and modeling·2026

Same author

Targeting GPR18: Structural modelling, ligand discovery, and therapeutic potential in neuroinflammatory disorders.

Biochemical pharmacology·2026

Same author

A Reinforcement Learning-Guided Genetic Algorithm Integrating Medicinal Chemistry-Inspired Molecular Transformations.

Journal of chemical information and modeling·2026

Search research articles

Related Experiment Video

Updated: Feb 8, 2026

Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16

Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16

Published on: July 15, 2019

Molecular Docking for Predictive Toxicology.

Daniela Trisciuzzi¹, Domenico Alberga¹, Francesco Leonetti¹

¹Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari "Aldo Moro", Bari, Italy.

Methods in Molecular Biology (Clifton, N.J.)

|June 24, 2018

Summary

Molecular docking, a computational method, is now used in predictive toxicology to assess chemical risks. This study details adapting this technique for regulatory toxicology applications, enhancing chemical safety assessments.

Keywords:

Applicability domain Classification model Endocrine potential Molecular docking Predictive toxicology

More Related Videos

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Screening Traditional Chinese Medicine Compounds for Inhibiting UCHL3 Activity Based on Molecular Docking and Deubiquitinating Enzyme Probe Technology

Screening Traditional Chinese Medicine Compounds for Inhibiting UCHL3 Activity Based on Molecular Docking and Deubiquitinating Enzyme Probe Technology

Published on: November 22, 2024

Related Experiment Videos

Last Updated: Feb 8, 2026

Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16

Use of Viral Entry Assays and Molecular Docking Analysis for the Identification of Antiviral Candidates against Coxsackievirus A16

Published on: July 15, 2019

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Screening Traditional Chinese Medicine Compounds for Inhibiting UCHL3 Activity Based on Molecular Docking and Deubiquitinating Enzyme Probe Technology

Screening Traditional Chinese Medicine Compounds for Inhibiting UCHL3 Activity Based on Molecular Docking and Deubiquitinating Enzyme Probe Technology

Published on: November 22, 2024

Area of Science:

Computational chemistry
Toxicology
Drug discovery

Background:

Molecular docking is a key in silico technique in drug discovery for predicting molecular interactions with biological targets.
This computational method is increasingly adopted in predictive toxicology for regulatory applications.
It has shown success in developing models to predict the endocrine disruptor potential of chemicals.

Purpose of the Study:

To describe a protocol for adapting molecular docking for predictive toxicology.
To facilitate the use of molecular docking in regulatory toxicology assessments.
To support the development of computational models for chemical safety evaluation.

Main Methods:

Adaptation of standard molecular docking protocols.
Application of computational modeling for toxicological endpoints.
Development of classification models for chemical risk assessment.

Main Results:

Demonstration of a feasible protocol for applying molecular docking in toxicology.
Successful application in predicting endocrine disruptor potential.
Establishment of a framework for computational toxicology using docking.

Conclusions:

Molecular docking is a valuable tool for predictive toxicology and regulatory science.
The described protocol enables the application of docking for assessing chemical safety.
This approach supports data-driven regulatory decision-making in chemical risk assessment.