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QSPR Models for Prediction of Redox Potentials Using Optimal Descriptors
The redox potentialRedox potential is an important physicochemical property widely used for the characterization of chemical species, and, as a...
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The validation of predictive potential via the system of self-consistent models: the simulation of blood–brain barrier permeation of organic compounds
ContextTo apply the quantitative relationships “structure-endpoint” approach, the reliability of prediction is necessary but sometimes challenging to...
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The Goldilocks paradigm: comparing classical machine learning, large language models, and few-shot learning for drug discovery applications
Recent advances in machine learning (ML) have led to newer model architectures including transformers (large language models, LLMs) showing state of...
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Quantification of Antioxidants
With the advent of new and improved computational methods, quantitative structure-activity relationship, QSAR, is one of such exploring fields...
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Chemometric Modeling of Emerging Materials for the Removal of Environmental Pollutants
Widespread usage of pharmaceuticals, personal care productsPersonal care products (PPCPsPharmaceuticals and personal care products (PPCPs)), and...
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QSAR Approach in Study of Mutagenicity of Aromatic and Heteroaromatic Amines
In this chapter we give an overview on QSAR models for treating the mutagenicity of cyclic amines. An extensive discussion is focused on the...
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QSPR models for water solubility of ammonium hexafluorosilicates: analysis of the effects of hydrogen bonds
In the present study, adequate quantitative structure-activity relationship (QSAR) models were developed to analyze the water solubility of some...
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Predicting protection capacities of pyrimidine-based corrosion inhibitors for mild steel/HCl interface using linear and nonlinear QSPR models
Pyrimidine compounds have proven to be effective and efficient additives capable of protecting mild steel in acidic media. This class of organic...
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Building Up QSPR for Polymers Endpoints by Using SMILES-Based Optimal Descriptors
The general scheme of QSPR analysis of endpoints related to polymersPolymer is described. The basic idea of the approach is building up a model of a...
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Quantitative structure–property relationship (QSPR) modeling for evaluating fluorescence attributes across various aromatic heterocyclic compounds with ve-degree-based Sombor indices
Aromatic heterocyclic compounds have become highly sought-after for their diverse medicinal and biological uses. Their synthesis and adaptability...
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SMILES and Quasi-SMILES in QSAR Modeling for Prediction of Physicochemical and Biochemical Properties
QSAR modeling of diverse physicochemical and biochemical properties of organic chemicals and nanomaterialsNanomaterials utilizing the simplified...
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Tools, Applications, and Case Studies (q-RA and q-RASAR)
Java-based tools for quantitative read-across (Quantitative Read-Across v 4.2.1) and q-RASAR (RASAR v 3.0.2) have been developed and made available...
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A new perspective on the modeling and topological characterization of H-Naphtalenic nanosheets with applications
In the past few years, two-dimensional (2D) layered nanomaterials have greatly attracted the scientific community. Among 2D nanomaterials, the...
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The study of curve fitting models to analyze some degree-based topological indices of certain anti-cancer treatment
Topological indices are obtained from molecular graphs and are real numbers that can forecast the biological and physicochemical properties of...
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CORAL: Predictions of Quality of Rice Based on Retention Index Using a Combination of Correlation Intensity Index and Consensus Modelling
The purpose of this study is to utilize the Monte Carlo technique of CORAL softwareCORAL software for establishing a quantitative structure-retention...
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Identifying uncertainty in physical–chemical property estimation with IFSQSAR
This study describes the development and evaluation of six new models for predicting physical–chemical (PC) properties that are highly relevant for...
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Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications
Ensemble learning helps improve machine learning results by combining several models and allows the production of better predictive performance...
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Quasi-SMILES as a Tool for Peptide QSAR Modelling
PeptidesPeptides have played an attractive role since a few decades in the discovery of new drugs in various areas involving hormones,...
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Development of scoring-assisted generative exploration (SAGE) and its application to dual inhibitor design for acetylcholinesterase and monoamine oxidase B
AbstractDe novo molecular design is the process of searching chemical space for drug-like molecules with desired properties, and deep learning has...
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3D molecular structural modeling and characterization of indium phosphide via irregularity topological indices
Indium phosphide (InP) is a binary semiconductor composed of indium and phosphorus. It has a zinc blende crystal structure, which is a type of cubic...
