Related Experiment Video
Updated: Jun 25, 2025
10:22
Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
8.2K
Identifying uncertainty in physical-chemical property estimation with IFSQSAR
Trevor N Brown1, Alessandro Sangion2, Jon A Arnot2,3,4
1ARC Arnot Research & Consulting, Toronto, ON, M4C 2B4, Canada. trevor.n.brown@gmail.com.
Journal of Cheminformatics
|May 30, 2024
Summary
New Quantitative Structure-Activity Relationship (QSAR) models predict key physical-chemical properties for novel chemicals. These models, integrated into the IFSQSAR package, offer valuable insights for chemical hazard and risk assessment.
Area of Science:
- Computational chemistry and cheminformatics.
- Development of predictive models for chemical properties.
- Environmental science and risk assessment.
Background:
- Accurate prediction of physical-chemical (PC) properties is crucial for chemical hazard, exposure, and risk estimation.
- Existing models may lack robust validation for novel, data-poor chemicals.
- Quantitative Structure-Activity Relationships (QSARs) offer a powerful approach for property prediction.
Purpose of the Study:
- To develop and evaluate six new predictive models for solubility, vapor pressure, and partition ratios (KOW, KOA, KAW).
- To implement these models within the Iterative Fragment Selection Quantitative Structure-Activity Relationship (IFSQSAR) Python package.
- To assess the models' predictivity for novel chemicals using external datasets.
Main Methods:
- Development of Poly-Parameter Linear Free Energy Relationship (PPLFER) equations integrating experimental data and QSPR-predicted descriptors.
- Implementation of ancillary QSPR for Molar Volume and a physical state classifier.
- Utilization of IFSQSAR methods for applicability domain characterization and uncertainty estimation (95% prediction intervals).
- Validation using extensive external datasets of measured partition ratios, vapor pressure, and solubility.
Main Results:
- The IFSQSAR package (v1.1.0) now includes six novel PC property prediction models.
- Models demonstrate good predictivity for partition ratios (log KOW, log KAW, log KOA) with RMSEP of 0.7–1.4 for novel chemicals.
- Predictions for vapor pressure and solubility exhibit higher uncertainty, influenced by physical state determination.
- A scaling factor of 1.25 was required for prediction intervals of partition ratios to encompass 95% of external data.
Conclusions:
- The developed PPLFER-QSAR models provide a robust framework for predicting essential PC properties of novel chemicals.
- The IFSQSAR package facilitates seamless integration of experimental data and model predictions for risk assessment.
- The study highlights the importance of rigorous external validation and uncertainty quantification for reliable chemical safety assessments.
Related Concept Videos
01:05Estimation of the Physical Quantities
4.2K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
4.2K
00:59Uncertainty: Overview
550
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
550
01:10Propagation of Uncertainty from Systematic Error
516
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
516
01:192D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)
685
Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
685
02:46Uncertainty in Measurement: Reading Instruments
38.1K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
38.1K
03:25Free Energy Changes for Nonstandard States
11.4K
The free energy change for a process taking place with reactants and products present under nonstandard conditions (pressures other than 1 bar; concentrations other than 1 M) is related to the standard free energy change according to this equation:
where R is the gas constant (8.314 J/K·mol), T is the absolute temperature in kelvin, and Q is the reaction quotient. This equation may be used to predict the spontaneity of a process under any given set of conditions.
Reaction Quotient...
where R is the gas constant (8.314 J/K·mol), T is the absolute temperature in kelvin, and Q is the reaction quotient. This equation may be used to predict the spontaneity of a process under any given set of conditions.
Reaction Quotient...
11.4K