QSAR Equations and Interpolation vs Extrapolation

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Questions and Answers

Which equation is used to quantify the electronic characteristics of a molecule in QSAR?

σ = appropriate Hammett substitution parameter

What did Hansch and Fujita use QSARs for?

To explain the biological activity of structurally related molecules

What is the relationship between the substituent parameter σ and the activity of a molecule?

σ is determined by the nature of the substituent and its position relative to the –COOR group

Which of the following is the correct way to calculate the mean of 5 values?

Sum all the values and divide by 5 Signup and view all the answers

What does Q^2 represent in this context?

The difference between FEcalc and FEobs Signup and view all the answers

What does the scatter plot with trendline show?

The relationship between FEcalc and FEobs Signup and view all the answers

Which technique is the most widely used to derive QSAR models?

Multiple Linear Regression Signup and view all the answers

What is the aim of linear regression?

To find the values for the coefficient m and the constant c Signup and view all the answers

What does the squared correlation coefficient R2 assess?

The quality of a linear regression Signup and view all the answers

Which statistical test is used to determine the significance of individual terms in a linear regression equation?

t statistic Signup and view all the answers

What measure indicates how well the regression function predicts the observed data?

Standard error of prediction Signup and view all the answers

What does it mean for a model to be parsimonious in the context of QSAR?

It uses a small number of independent variables to explain the data Signup and view all the answers

Which experimental design technique can help extract maximum information from a small number of molecules?

Factorial design Signup and view all the answers

What type of model is more appropriate for complex assays where the drug must cross several barriers?

Hansch parabolic model Signup and view all the answers

Which method is generally more reliable for predicting properties within the range of molecules used to derive the QSAR equation?

Interpolative prediction Signup and view all the answers

What does a larger value of the Hammett constant for meta substituents (σmeta) indicate in terms of enzyme inhibition constant (Ki)?

Larger σmeta value leads to larger Ki Signup and view all the answers

What is the difference between Principal Components Regression (PCR) and Partial Least Squares (PLS)?

PCR uses principal components as variables in a multiple linear regression, while PLS uses latent variables Signup and view all the answers

How can the quality of a Partial Least Squares (PLS) model be assessed graphically?

By plotting the predicted values against the measured values Signup and view all the answers

Which parameter is used by some practitioners to measure the standard deviation of the error of predictions?

sPRESS Signup and view all the answers

Which technique derives a correlation between the activity of molecules and their 3D shape, electrostatic, and hydrogen-bonding characteristics?

CoMFA Signup and view all the answers

What are the standard fields used in CoMFA?

Electrostatic and steric Signup and view all the answers

What is the general form of the equation used in CoMFA?

$c_{ij}$ corresponds to placing probe $j$ at lattice point $i$, $S_{ij}$ is the energy value, $C$ is a constant Signup and view all the answers

Study Notes

QSAR Equations

The Hansch-Fujita equation is used to quantify the electronic characteristics of a molecule in QSAR.
Hansch and Fujita used QSARs to analyze the relationship between the structure of pesticides and their biological activity.

Substituent Parameters

The substituent parameter σ is directly related to the activity of a molecule.
A larger value of σ indicates a greater effect on the activity of a molecule.

Statistical Analysis

The mean of 5 values can be calculated using the formula: (x1 + x2 + x3 + x4 + x5) / 5.
Q^2 represents the cross-validated R2, which is a measure of the predictive ability of a QSAR model.
A scatter plot with a trendline shows the relationship between the predicted and observed values.
The aim of linear regression is to create a model that predicts the activity of a molecule based on its descriptors.
The squared correlation coefficient R2 assesses the goodness of fit of the linear regression model.
The t-test is used to determine the significance of individual terms in a linear regression equation.
R2 measures how well the regression function predicts the observed data.

QSAR Model Development

Multiple Linear Regression (MLR) is the most widely used technique to derive QSAR models.
A parsimonious model is one that uses the fewest descriptors necessary to achieve a good predictive ability.
Experimental design techniques, such as fractional factorial design, can help extract maximum information from a small number of molecules.

Model Selection

Physiologically-based pharmacokinetic (PBPK) models are more appropriate for complex assays where the drug must cross several barriers.
The method of interpolation is generally more reliable for predicting properties within the range of molecules used to derive the QSAR equation.

Hammett Constant

A larger value of the Hammett constant for meta substituents (σmeta) indicates a stronger enzyme inhibition constant (Ki).

Principal Components Regression and Partial Least Squares

The difference between Principal Components Regression (PCR) and Partial Least Squares (PLS) lies in the way they handle collinear descriptors.
The quality of a PLS model can be assessed graphically using plots of predicted vs. observed values and residuals.

CoMFA

The method of Comparative Molecular Field Analysis (CoMFA) derives a correlation between the activity of molecules and their 3D shape, electrostatic, and hydrogen-bonding characteristics.
The standard fields used in CoMFA are steric, electrostatic, hydrophobic, and hydrogen-bonding fields.
The general form of the equation used in CoMFA is: Biological activity = c + Σk ( coefficient k * field k) + error.

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