Literature DB >> 966250

Theoretical model-based equations for the linear free energy relationships of the biological activity of ionizable substances. 1. Equilibrium-controlled potency.

Y C Martin, J J Hackbarth.   

Abstract

Because of the ambiguities of how to treat ionization in empirical equations which relate biological activity to partition coefficient by use of a (log P)2 term, a theoretical approach to the problem is proposed. Based on a simplified view of assays of potency following in vitro or continuous infusion administration of drugs, equations have been derived from a combination of mass law, equilibrium, and extrathermodynamic assumptions. In general form the equations which relate potency to partition coefficient (P) and degree of ionization (alpha) are the following. If the neutral form reacts with the receptor, log (1/C) =-log [1 + SIGMAM(DIPci) + sigman[aj/Pb(1-alpha4y]] + X. If the ionic form reacts with the receptor, log (1/C) =-log [1 + (1 - Alphan)/(alphan)[sigmam(diPci) + sigman[aj/Pb(1-alphaj)]]] + X. In this generalized model there are m nonaqueous compartments and n aqueous compartments of different pH. The parameters a, b, c, and d can be interpreted in terms of the model. The shape of the log (1/C) vs. log P curve may be asymptotic, linear, or composed of two portions of unequal slope which meet at an optimum or a bend. With the use of these equations it is possible to examine whether the ion or the neutral form is the active species and whether there is hydrophobic bonding to the receptor and/or an inert compartment. The models may be further extended to include terms other than log P and alpha.

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Year:  1976        PMID: 966250     DOI: 10.1021/jm00230a012

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  9 in total

1.  Tautomerism, Hammett sigma, and QSAR.

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Review 2.  Modeling kinetics of subcellular disposition of chemicals.

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3.  QSAR modeling: where have you been? Where are you going to?

Authors:  Artem Cherkasov; Eugene N Muratov; Denis Fourches; Alexandre Varnek; Igor I Baskin; Mark Cronin; John Dearden; Paola Gramatica; Yvonne C Martin; Roberto Todeschini; Viviana Consonni; Victor E Kuz'min; Richard Cramer; Romualdo Benigni; Chihae Yang; James Rathman; Lothar Terfloth; Johann Gasteiger; Ann Richard; Alexander Tropsha
Journal:  J Med Chem       Date:  2014-01-06       Impact factor: 7.446

4.  Perspectives in QSAR: computer chemistry and pattern recognition.

Authors:  R M Hyde; D J Livingstone
Journal:  J Comput Aided Mol Des       Date:  1988-07       Impact factor: 3.686

5.  Rigorous treatment of multispecies multimode ligand-receptor interactions in 3D-QSAR: CoMFA analysis of thyroxine analogs binding to transthyretin.

Authors:  Senthil Natesan; Tiansheng Wang; Viera Lukacova; Vladimir Bartus; Akash Khandelwal; Stefan Balaz
Journal:  J Chem Inf Model       Date:  2011-04-08       Impact factor: 4.956

Review 6.  Rigorous incorporation of tautomers, ionization species, and different binding modes into ligand-based and receptor-based 3D-QSAR methods.

Authors:  Senthil Natesan; Stefan Balaz
Journal:  Curr Pharm Des       Date:  2013       Impact factor: 3.116

7.  Cellular quantitative structure-activity relationship (Cell-QSAR): conceptual dissection of receptor binding and intracellular disposition in antifilarial activities of Selwood antimycins.

Authors:  Senthil Natesan; Tiansheng Wang; Viera Lukacova; Vladimir Bartus; Akash Khandelwal; Rajesh Subramaniam; Stefan Balaz
Journal:  J Med Chem       Date:  2012-04-11       Impact factor: 7.446

Review 8.  Partitioning and lipophilicity in quantitative structure-activity relationships.

Authors:  J C Dearden
Journal:  Environ Health Perspect       Date:  1985-09       Impact factor: 9.031

9.  Let's not forget tautomers.

Authors:  Yvonne Connolly Martin
Journal:  J Comput Aided Mol Des       Date:  2009-10       Impact factor: 3.686

  9 in total

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