Related Experiment Video

Updated: Jun 11, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

2.6K

Cross-Species Molecular Docking Method to Support Predictions of Species Susceptibility to Chemical Effects

Peter G Schumann1, Daniel Chang2, Sally Mayasich3,4

  • 1Oak Ridge Institute for Science and Education, Duluth, Minnesota, USA.

Computational Toxicology (Amsterdam, Netherlands)
|October 9, 2024
PubMed
Abstract

No abstract available in PubMed .

Keywords:
Androgen receptorCross-speciesMolecular dockingNew Approach MethodologiesPredictive toxicologySequence Alignment to Predict Across Species Susceptibility (SeqAPASS)

More Related Videos

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
00:05

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

13.9K
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

2.4K

Related Experiment Videos

Last Updated: Jun 11, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

2.6K
In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
00:05

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

13.9K
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

2.4K

Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
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...
12.8K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
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...
4.2K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.8K
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
12.8K

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

Building the Toolkits to Examine the Expression and Associated Regulation of RBC Alloantigens.

Methods in molecular biology (Clifton, N.J.)·2026

Radiation Therapy for Pancreatic Cancer: An ASTRO Clinical Practice Guideline.

Practical radiation oncology·2026

Development and temporal validation of a machine-learning based risk prediction model for depression in older adults with chewing difficulty: evidence from the KNHANES.

BMC oral health·2026

Flow Asynchronies During Pressure Support Ventilation in Children: A Bench Model Study.

Respiratory care·2026

An Emerging Approach: The Use of Body Composition Measures Compared to Body Mass Index in Adult Living Kidney Donors to Assess Post Donation Outcomes.

Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation·2026

Methods2AOP: A Collaboration to Strengthen the Integration of Test Methods into the Adverse Outcome Pathway Framework.

F1000Research·2026

Development of machine learning-based multi-task quantitative structure-activity relationship models for predicting toxicities in six human organ systems.

Computational toxicology (Amsterdam, Netherlands)·2026

Building a compendium of expert driven read-across cases to facilitate an analysis of the contribution that different similarity contexts play in read-across performance.

Computational toxicology (Amsterdam, Netherlands)·2026

Can graph similarity metrics be helpful for analogue identification as part of a read-across approach?

Computational toxicology (Amsterdam, Netherlands)·2026

Development of the toxicity values database, ToxValDB: A curated resource for experimental and derived human health-relevant toxicity data.

Computational toxicology (Amsterdam, Netherlands)·2026

The FAIR AOP roadmap for 2025: Advancing findability, accessibility, interoperability, and re-usability of adverse outcome pathways.

Computational toxicology (Amsterdam, Netherlands)·2025

A comparative study of biostatistical pipelines for benchmark concentration modeling of in vitro screening assays.

Computational toxicology (Amsterdam, Netherlands)·2025

Benchmarking machine learning and molecular dynamics methods for the prediction of the thermophysical properties of organic liquids.

Digital discovery·2026

Using structure to evaluate the accuracy and transferability of machine learning potentials of biomolecules.

RSC advances·2026

The risk of over-interpreting in silico predictions as clinical evidence: a comment on Roy et al. (2024).

Genomics & informatics·2026

A brief review of orbital-free density functional theory methods: the fundamental and unique branches.

Physical chemistry chemical physics : PCCP·2026

Thermal conductivity predictions with foundation atomistic models.

Nature communications·2026

DFT-based computational screening of the ability of C60-based nanostructures to adsorb the diethylcyclidine drug.

Journal of molecular graphics & modelling·2026
See all related articles
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
Jove
Visualize
Contact Us