ArticleMolecular diversity2021
Polarizability: a promising descriptor to study chemical-biological interactions.
Article in Molecular diversity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Hybrid Computational Framework Integrating Ensemble Learning, Molecular Docking, and Dynamics for Predicting Antimalarial Efficacy of Malaria Box Compounds.International journal of molecular sciences · 2026Article
- QSAR machine learning-guided discovery of renieramycin right-half derivatives with cytotoxic activity against NSCLC cells.Scientific reports · 2025Article
- Conceptual density functional theory in drug discovery: an overview.Journal of molecular modeling · 2025Review
- Multitarget Design of Steroidal Inhibitors Against Hormone-Dependent Breast Cancer: An Integrated In Silico Approach.International journal of molecular sciences · 2025Article
- Synthesis, characterization and cytotoxic evaluation of metal complexes derived from new N'-(2-cyanoacetyl)isonicotinohydrazide.Scientific reports · 2025Article
- Modulation of PI3K/AKT signaling and DFT modeling via selected pharmaceutical compounds attenuates carrageenan-induced inflammation and oxidative stress in rats.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Biomimetic Chromatography/QSAR Investigations in Modeling Properties Influencing the Biological Efficacy of Phenoxyacetic Acid-Derived Congeners.Molecules (Basel, Switzerland) · 2025Article
- Piperazine amides with desirable solubility, physicochemical and drug-like properties: Synthesis and evaluation of the anti-Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023Article
- In Silico Antiprotozoal Evaluation of 1,4-Naphthoquinone Derivatives against Chagas and Leishmaniasis Diseases Using QSAR, Molecular Docking, and ADME Approaches.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Pharmacokinetics in Zebrafish Embryos (ZFE) Following Immersion and Intrayolk Administration: A Fluorescence-Based Analysis.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Predicting Pharmacokinetic Properties of Potential Anticancer Agents via Their Chromatographic Behavior on Different Reversed Phase Materials.International journal of molecular sciences · 2021Article
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Authors and funding
4 authors.
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Abstract
Recently, we have defined atomic polarizability, a Conceptual Density Functional Theory (CDFT)-based reactivity descriptor, through an empirical method. Though the method is empirical, it is competent enough to meet the criteria of periodic descriptors and exhibit relativistic effect. Since the atomic data are very accurate, we have applied them to determine molecular polarizability. Molecular polarizability is an electronic parameter and has an impact on chemical-biological interactions. Thus, it plays a pivotal role in explaining such interactions through Structure Activity Relationships (SAR). In the present work, we have explored the application of polarizability in the real field through investigation of chemical-biological interactions in terms of molecular polarizability. A Quantitative Structure-Activity Relationship (QSAR) model is constructed to account for electronic effects owing to polarizability in ligand-substrate interactions. The study involves the prediction of various biological activities in terms of minimum block concentration, relative biological response, inhibitory growth concentration or binding affinity. Superior results are presented for the predicted and observed activities which support the accuracy of the proposed polarizability-QSAR model. Further, the results are considered from a biological viewpoint in order to understand the mechanism of interactions. The study is performed to explore the efficacy of the computational model based on newly proposed polarizability and not to establish the finest QSAR. For future studies, it is suggested that the descriptor polarizability should be contrasted with the use of other drug-like descriptors.
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