QSAR: Then and Now

Selassie, Cynthia Dias; Mekapati, Suresh Babu; Verma, Rajeshwar P.

doi:10.2174/1568026023392823

Cited by 69 publications

(21 citation statements)

References 138 publications

(177 reference statements)

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“…The three standard classifications routinely used in QSAR analysis: electronic, hydrophobic and steric including topological indices are invaluable in helping to delineate a large number of receptor-ligand interactions that are critical to biological processes [16]. QSAR models can stand alone, augment other modeling approaches or be examined in tandem with equations of a similar mechanistic genre to establish authenticity and reliability [18].…”

Section: Introductionmentioning

confidence: 99%

Comparative QSAR studies on PAMPA/modified PAMPA for high throughput profiling of drug absorption potential with respect to Caco-2 cells and human intestinal absorption

Verma

Hansch

Selassie

2007

J Comput Aided Mol Des

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Despite the dramatic increase in speed of synthesis and biological evaluation of new chemical entities, the number of compounds that survive the rigorous processes associated with drug development is low. Thus, an increased emphasis on thorough ADMET (absorption, distribution, metabolism, excretion and toxicity) studies based on in vitro and in silico approaches allows for early evaluation of new drugs in the development phase. Artificial membrane permeability measurements afford a high throughput, relatively low cost but labor intensive alternative for in vitro determination of drug absorption potential; parallel artificial membrane permeability assays have been extensively utilized to determine drug absorption potentials. The present study provides comparative QSAR analysis on PAMPA/modified PAMPA for high throughput profiling of drugs with respect to Caco-2 cells and human intestinal absorption.

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Section: Introductionmentioning

confidence: 99%

Comparative QSAR studies on PAMPA/modified PAMPA for high throughput profiling of drug absorption potential with respect to Caco-2 cells and human intestinal absorption

Verma

Hansch

Selassie

2007

J Comput Aided Mol Des

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“…Reformulation of this model and exclusion of three carboxylic acids from this analysis led to the development of the following model. 23) …”

Section: Rana Japonica Tadpolesmentioning

confidence: 99%

QSAR of toxicology of substituted phenols

Selassie

Verma

2015

J. Pestic. Sci.

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The quantitative structure activity relationship paradigm provides an excellent avenue for investigating ligand-receptor interactions in medicinal chemistry/toxicology. Lateral validation of models formulated using this approach allows for a cohesive understanding of the mechanistic underpinnings of a specific class of related molecules. The diverse biological activities of substituted phenols (X-phenols) in organisms that run the gamut from protozoa to animals are herein examined and compared. Correlations between biological activities and physicochemical attributes of X-phenols reveal strong consistencies between various models. Two parameters in particular, hydrophobicity and electronic terms dominate the extent of interactions between these chemical entities and their molecular targets. Hydrophobicity is represented by π values or partition coefficients while electronic contributions are delineated by molecular orbital indices or Hammett sigma constants. They help us to define the similarity in these mechanistic models that allow for an understanding of forces that are at play at the molecular level.

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“…Appropriate representation of the structural and physicochemical features of chemical agents is an essential key to the successful application of quantitative structure-activity relationship (QSAR) models [1][2][3][4][5] and to the elucidation of the underlying molecular mechanism of a particular biological activity from the derived statistical models. Therefore, finding different molecular descriptors including two-dimensional (2D) and three-dimensional (3D) parameters with higher correlation toward activity/property is in the frontier of QSAR/QSPR researches.…”

Section: Introductionmentioning

confidence: 99%

Application of MOLMAP approach for QSAR modeling of various biological activities using substituent electronic descriptors

et al. 2009

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When using quantum chemical descriptors in quantitative structure-activity relationship (QSAR) studies, there is always a challenge between accuracy of calculation and the complexity and time of computation. Very recently, we proposed the use of substituents electronic descriptors (SEDs) instead of the electronic properties of whole molecule as new and expedite source of electronic descriptors. For instance, SED parameters can be calculated with the highest degree of accuracy in very low computation time. In this article, we used SED parameters in QSAR modeling of six different biological data sets including (i) the dissociation constants for a set of substituted imidazolines, (ii) the pKa of imidazoles, (iii) inverse agonist activity of indoles, (iv) the influenza virus inhibition activities of benzimidazoles, (v) inhibition of alcohol dehydrogenase by amides, and (vi) the natriuretic activity of sulfonamide. For poly-substituted molecules, SED parameters produce a vector of electronic descriptors for each substituent, and thus a matrix of SED parameters is obtained for each molecule. Consequently, a three-dimensional (3D) array is obtained by staking the descriptor data matrices of molecules beside each others. In addition to simple unfolding of the SED parameters, molecular maps of atom-level properties (MOLMAP) approach, as a novel data analysis method, was also applied to transfer 3D array of SED into new two-dimensional parameters using Kohonen network, following by genetic algorithm-based partial least square (GA-PLS) to connect a quantitative relationship between the Kohonen scores and biological activity. Accurate QSAR models were obtained by both approaches. However, the superiority of three-way analysis of SED parameters based on MOLMAP approach with respect to simple unfolding was obtained.

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QSAR: Then and Now

Cited by 69 publications

References 138 publications

Comparative QSAR studies on PAMPA/modified PAMPA for high throughput profiling of drug absorption potential with respect to Caco-2 cells and human intestinal absorption

Comparative QSAR studies on PAMPA/modified PAMPA for high throughput profiling of drug absorption potential with respect to Caco-2 cells and human intestinal absorption

QSAR of toxicology of substituted phenols

Application of MOLMAP approach for QSAR modeling of various biological activities using substituent electronic descriptors

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