Literature DB >> 32146657

Polarizability: a promising descriptor to study chemical-biological interactions.

Hiteshi Tandon1, Prabhat Ranjan2, Tanmoy Chakraborty3, Vandana Suhag4.   

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.

Keywords:  Chemical reactivity descriptor; Chemical–biological interactions; Conceptual density functional theory (CDFT); Depolarization; Polarizability; Quantitative structure–activity relationship (QSAR)

Year:  2020        PMID: 32146657     DOI: 10.1007/s11030-020-10062-w

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  25 in total

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4.  ED50 AP block predictions for phenyl substituted and unsubstituted n-alkanols.

Authors:  R Hahin; A Kondratiev
Journal:  J Membr Biol       Date:  2001-03-15       Impact factor: 1.843

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Journal:  Pharmacol Rev       Date:  1972-12       Impact factor: 25.468

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9.  Smoothed Spherical Truncation based on Fuzzy Membership Functions: Application to the Molecular Encoding.

Authors:  César R García-Jacas; Yovani Marrero-Ponce; Carlos A Brizuela; José Suárez-Lezcano; Felix Martinez-Rios
Journal:  J Comput Chem       Date:  2019-10-24       Impact factor: 3.376

10.  Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets.

Authors:  César R García-Jacas; Ernesto Contreras-Torres; Yovani Marrero-Ponce; Mario Pupo-Meriño; Stephen J Barigye; Lisset Cabrera-Leyva
Journal:  J Cheminform       Date:  2016-02-25       Impact factor: 5.514

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Authors:  Lina S Prieto Cárdenas; Karen A Arias Soler; Diana L Nossa González; Wilson E Rozo Núñez; Agobardo Cárdenas-Chaparro; Pablo R Duchowicz; Jovanny A Gómez Castaño
Journal:  Pharmaceuticals (Basel)       Date:  2022-05-31

2.  Predicting Pharmacokinetic Properties of Potential Anticancer Agents via Their Chromatographic Behavior on Different Reversed Phase Materials.

Authors:  Małgorzata Janicka; Anna Mycka; Małgorzata Sztanke; Krzysztof Sztanke
Journal:  Int J Mol Sci       Date:  2021-04-20       Impact factor: 5.923

  2 in total

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