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

Temperature Dependence on Reaction Rate02:55

Temperature Dependence on Reaction Rate

The Collision Theory
Atoms, molecules, or ions must collide before they can react with each other. Atoms must be close together to form chemical bonds. This premise is the basis for a theory that explains many observations regarding chemical kinetics, including factors affecting reaction rates.
The collision theory is based on the postulates that (i) the reaction rate is proportional to the rate of reactant collisions, (ii) the reacting species collide in an orientation allowing contact between...
Transition State Theory01:25

Transition State Theory

Transition-state theory, also known as activated-complex theory, provides a molecular-level explanation of reaction rates in both gas-phase and solution-phase reactions. It extends earlier kinetic models by considering the formation of a short-lived, high-energy configuration during a reaction.The progress of a chemical reaction can be represented using a reaction profile, which plots potential energy against the reaction coordinate. As two reactant molecules approach one another, their...
Thermodynamics: Activity Coefficient01:24

Thermodynamics: Activity Coefficient

Activity is the measure of the effective concentration of the species in solution. It can be expressed as the product of the molar concentration of the species and its activity coefficient. The activity coefficient is a dimensionless quantity and depends on the total ionic strength of the solution.
The activity coefficient is a measure of the deviation from ideal behavior. When the ionic strength of the solution is minimal, the activity coefficient of an ionic species is close to unity, making...
Adsorption Isotherms I01:29

Adsorption Isotherms I

Adsorption isotherms are mathematical models that describe how molecules in a gas or liquid phase interact with surfaces. Two of the most common isotherm models are the Langmuir and Freundlich isotherms, which relate to Type I monolayer chemisorption. The Langmuir model is based on four key assumptions:• Adsorption cannot exceed monolayer coverage.• All surface sites are equivalent.• Molecules adsorb only at vacant sites.• There are no interactions between adsorbed molecules.Consider the...
Thermodynamic Potentials01:26

Thermodynamic Potentials

Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...
Second Law of Thermodynamics02:49

Second Law of Thermodynamics

In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic models, the...

You might also read

Related Articles

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

Sort by
Same author

PyMolGen: Database-Driven Molecular Generation of Drug-Like Compounds.

Journal of chemical information and modeling·2026
Same author

Decoding the Blood-Brain Barrier: Innovative and Scalable Open-Source Machine Learning Model for Drug Permeability.

Current neuropharmacology·2026
Same author

Query Matters: How Selection Strategies Influence Active Learning in Drug Discovery.

Journal of chemical information and modeling·2026
Same author

Conformational dynamics at the pre-miR-377 Dicer site governs selective small-molecule recognition.

bioRxiv : the preprint server for biology·2026
Same author

Peptide-Tools-Web Server for Calculating Physicochemical Properties of Peptides.

Journal of chemical information and modeling·2025
Same author

A Multiomic Liquid Biopsy for the Earlier Detection of Colorectal Cancer.

Cancer prevention research (Philadelphia, Pa.)·2025

Related Experiment Video

Updated: Jun 2, 2026

Isothermal Titration Calorimetry for Measuring Macromolecule-Ligand Affinity
08:45

Isothermal Titration Calorimetry for Measuring Macromolecule-Ligand Affinity

Published on: September 7, 2011

Hydration thermodynamics using the reference interaction site model: speed or accuracy?

Andrey I Frolov1, Ekaterina L Ratkova, David S Palmer

  • 1Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, Leipzig, 04103, Germany.

The Journal of Physical Chemistry. B
|April 15, 2011
PubMed
Summary
This summary is machine-generated.

We developed a structural description correction (SDC) model to improve hydration free energy (HFE) predictions using 1D and 3D reference interaction site models (RISM). The 3D RISM/SDC model offers high accuracy, while the faster 1D RISM/SDC is suitable for high-throughput screening.

More Related Videos

Mapping the Binding Site of an Aptamer on ATP Using MicroScale Thermophoresis
08:09

Mapping the Binding Site of an Aptamer on ATP Using MicroScale Thermophoresis

Published on: January 7, 2017

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

Related Experiment Videos

Last Updated: Jun 2, 2026

Isothermal Titration Calorimetry for Measuring Macromolecule-Ligand Affinity
08:45

Isothermal Titration Calorimetry for Measuring Macromolecule-Ligand Affinity

Published on: September 7, 2011

Mapping the Binding Site of an Aptamer on ATP Using MicroScale Thermophoresis
08:09

Mapping the Binding Site of an Aptamer on ATP Using MicroScale Thermophoresis

Published on: January 7, 2017

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of Ni(II) and Zn(II) Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

Area of Science:

  • Computational Chemistry
  • Physical Chemistry
  • Molecular Modeling

Background:

  • Hydration free energies (HFEs) are crucial for understanding molecular behavior in aqueous solutions.
  • Traditional Reference Interaction Site Model (RISM) methods often have limitations in accurately predicting HFEs.
  • Errors in RISM calculations using Gaussian fluctuations (GF) can be systematically corrected based on molecular structure.

Purpose of the Study:

  • To develop and validate a structural description correction (SDC) model to enhance the accuracy of HFE predictions.
  • To compare the predictive performance and computational efficiency of 1D and 3D RISM approaches combined with the SDC model.
  • To establish guidelines for selecting the appropriate RISM-SDC model based on accuracy and computational cost requirements.

Main Methods:

  • The study combined 1D and 3D Reference Interaction Site Model (RISM) theory with a Gaussian fluctuations (GF) free energy functional.
  • A structural description correction (SDC) model was developed by fitting parameters to a training set of 53 simple organic molecules.
  • The SDC model's transferability and predictive accuracy were tested on a diverse set of 98 complex molecules, including polyfragment compounds.

Main Results:

  • The 3D RISM/SDC model achieved high accuracy in HFE prediction, with a root-mean-square error (RMSE) of 0.47 kcal/mol.
  • The 1D RISM/SDC model provided moderate accuracy (RMSE of 1.96 kcal/mol) but was significantly faster, completing calculations in seconds.
  • The SDC model parameters demonstrated transferability across different classes of organic molecules.

Conclusions:

  • The SDC model effectively corrects errors in RISM-based HFE calculations, significantly improving prediction accuracy.
  • A trade-off exists between accuracy and computational cost, with 3D RISM/SDC being more accurate and 1D RISM/SDC being faster.
  • The 1D RISM/SDC model is recommended for large-scale screening, while the 3D RISM/SDC model is suitable for detailed analysis of selected compounds.