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<p>This article explores the application of conceptual density functional theory (CDFT) and information-theoretic approach (ITA) to various chemical phenomena, demonstrating their predictive power in diverse molecular systems. IT descriptors have been employed to investigate conformational stability, molecular acidity, aromaticity, and electrophilicity/nucleophilicity, revealing strong correlations between information-theoretic measures and experimental observations. Moreover, CDFT-based QSAR and QSPR models have shown significant predictive capabilities in pharmacological toxicity and physicochemical properties, such as partition coefficient and enthalpy of vaporization. The integration of CDFT and IT descriptors has provided deeper insights into reactivity trends in pericyclic reactions, allowing for the classification of mechanisms based on electrophilicity indices. Additionally, periodic trends in CDFT and IT descriptors have been examined, reaffirming the fundamental chemical principles. The review article underscores the robustness of IT and CDFT methodologies in capturing electronic structure variations and predicting the chemical behavior of molecules. The integration of these descriptors offers a comprehensive approach to understanding chemical reactivity, stability, and molecular interactions, paving the way for future advancements in theoretical and computational chemistry. </p> Graphical abstract <p>The applications of Conceptual Density Functional Theory (CDFT) and the Information-Theoretic Approach (ITA) have been widely used in predicting the toxicity, activity, and reactivity of chemical systems. Moreover, Quantitative Structure–Activity Relationship (QSAR) studies are conducted using CDFT and ITA descriptors through regression equations.</p>

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Application of CDFT and IT-based descriptors in analyzing structure, properties, reactivity and toxicity

  • 期刊论文

  • 发表日期：

    2025年8月31日

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  • Arpita Poddar,
  • Pratim Kumar Chattaraj

摘要

This article explores the application of conceptual density functional theory (CDFT) and information-theoretic approach (ITA) to various chemical phenomena, demonstrating their predictive power in diverse molecular systems. IT descriptors have been employed to investigate conformational stability, molecular acidity, aromaticity, and electrophilicity/nucleophilicity, revealing strong correlations between information-theoretic measures and experimental observations. Moreover, CDFT-based QSAR and QSPR models have shown significant predictive capabilities in pharmacological toxicity and physicochemical properties, such as partition coefficient and enthalpy of vaporization. The integration of CDFT and IT descriptors has provided deeper insights into reactivity trends in pericyclic reactions, allowing for the classification of mechanisms based on electrophilicity indices. Additionally, periodic trends in CDFT and IT descriptors have been examined, reaffirming the fundamental chemical principles. The review article underscores the robustness of IT and CDFT methodologies in capturing electronic structure variations and predicting the chemical behavior of molecules. The integration of these descriptors offers a comprehensive approach to understanding chemical reactivity, stability, and molecular interactions, paving the way for future advancements in theoretical and computational chemistry.

Graphical abstract

The applications of Conceptual Density Functional Theory (CDFT) and the Information-Theoretic Approach (ITA) have been widely used in predicting the toxicity, activity, and reactivity of chemical systems. Moreover, Quantitative Structure–Activity Relationship (QSAR) studies are conducted using CDFT and ITA descriptors through regression equations.