Biomedical subjects

Taravat Ghafourian

Publications and source records attributed to Taravat Ghafourian.

7 recordsLinked to original sources

PubMed2006

QSPR models for the prediction of apparent volume of distribution.

An estimate of volume of distribution (V(d)) is of paramount importance both in drug choice as well as maintenance and loading dose calculations in therapeutics. It can also be used in the prediction of drug biological half life. This study employs quantitative structure-pharmacokinetic relationship (QSPR) techniques for the prediction of volume of distribution. Values of V(d) for 129 drugs were collated from the literature. Structural descriptors consisted of partitioning, quantum mechanical, molecular mechanical, and connectivity parameters calculated by specialized software and pK(a) values obtained from ACD labs/log D database. Genetic algorithm and stepwise regression analyses were used for variable selection and model development. Models were validated using a leave-many-out procedure. QSPR analyses resulted in a number of significant models for acidic and basic drugs separately, and for all the drugs. Validation studies showed that mean fold error of predictions for the selected models were between 1.79 and 2.17. Although separate QSPR models for acids and bases resulted in lower prediction errors than models for all the drugs, the external validation study showed a limited applicability for the equation obtained for acids. Therefore, the universal model that requires only calculated structural descriptors was recommended. The QSPR model is able to predict the volume of distribution of drugs belonging to different chemical classes with a prediction error similar to that of the other more complicated prediction methods including the commonly practiced interspecies scaling. The structural descriptors in the model can be interpreted based on the known mechanisms of distribution and the molecular structures of the drugs.

Algorithms↗

PubMed2004

The effect of penetration enhancers on drug delivery through skin: a QSAR study.

Skin penetration enhancers are used to allow formulation of transdermal delivery systems for drugs that are otherwise insufficiently skin-permeable. A full understanding of the mode of action could be beneficial for the design of potent enhancers and for the choice of the enhancer to be used in the topical formulation of a special drug. In this study, the structural requirements of penetration enhancers have been investigated using the Quantitative Structure-Activity Relationship (QSAR) technique. Activities of naturally occurring terpenes, pyrrolidinone and N-acetylprolinate derivatives on the skin penetration of 5-fluorouracil, diclofenac sodium (DFS), hydrocortisone (HC), estradiol and benazepril have been considered. The resulting QSARs indicated that for 5-fluorouracil and diclofenac sodium, less hydrophobic enhancers were the most active. More precisely, molecular descriptors in the corresponding QSARs indicated the possible involvement of intermolecular electron donor-acceptor interactions. This was in contrast to the skin permeation promotion of hydrocortisone, estradiol and benazepril by enhancers, where a linear relationship between enhancement activity and n-octanol/water partition coefficients of enhancers was evident. The possible mechanisms of penetration enhancement as suggested by the QSARs will be discussed.

Administration, Cutaneous↗

PubMed2004

The use of molecular electrostatic potentials as hydrogen-bonding-donor parameters for QSAR studies.

Hydrogen bonding is an important interaction, which controls solubility, partitioning and transport of drugs and is an important force in drug-receptor interactions. Unfortunately it is difficult to quantify, and so inclusion of hydrogen bonding descriptors into quantitative structure-activity relationships (QSARs) is often restricted to indicator variables. The prime objective of this work was to devise readily accessible hydrogen bonding descriptors by means of theoretical chemistry to use in QSAR studies. Because of the dominantly electrostatic nature of this bond, molecular-electrostatic potential was considered and the highest electrostatic potential on the solvent accessible surface (ESP+) was used as the hydrogen-bonding-donor ability of the molecule. The ability of this descriptor to predict the measured hydrogen bonding parameter of sigmalphaH2 was compared with that of the empirically derived atomic charges. The efficiency of ESP+ in a QSAR was also examined. The results suggested that ESP+ was superior to the atomic charge descriptor and that the use of this parameter as the hydrogen bonding parameter in QSAR studies was successful.

Air Pollutants↗

PubMed2004

Comparison of electrotopological-state indices versus atomic charge and superdelocalisability indices in a QSAR study of the receptor binding properties of halogenated estradiol derivatives.

The structural requirements for the binding of steroids to the oestrogen receptor (ER) are important both for the design of new drugs and to assess the health risks of chemicals with ER affinity. In the present QSAR study of receptor binding affinity (RBA) for estradiol derivatives, the atom-level electrotopological state indices have been compared with molecular orbital derived, atom-level parameters for superdelocalisability and atomic charge. The AM1 Hamiltonian was used to calculate molecular orbital parameters. The predictive power of the QSARs indicated that the superdelocalisability indices provide a better model than the electrotopological state indices, and that the atomic charges resulted in the highest prediction error. The most accurate predictions were achieved when other molecular descriptors were also employed in the construction of the QSAR.

Animals↗

PubMed2004

Quantitative structure-pharmacokinetic relationship modelling: apparent volume of distribution.

The purpose of this study was to develop a quantitative structure-activity relationship (QSAR) for the prediction of the apparent volume of distribution (Vd) in man for a heterogeneous series of drugs. The relationship of many computed, and some experimental, structural descriptors with Vd, and the Vd corrected for protein binding (unbound Vd), was investigated. Models were constructed using stepwise regression analysis for all the 70 drugs in the dataset, as well as for acidic drugs and basic drugs separately. The predictive power of the models was assessed using half the chemicals as a test set, and revealed that the models for Vd yielded lower prediction errors than those constructed for the unbound Vd (mean fold error of 2.01 for Vd compared with 2.28 for unbound Vd). Moreover, the separation of the compounds into acids and bases did not reduce the prediction error significantly.

Algorithms↗

PubMed2003

Draize rabbit eye test compatibility with eye irritation thresholds in humans: a quantitative structure-activity relationship analysis.

Draize rabbit eye test scores, as modified maximum average score (MMAS), for 68 pure bulk liquids were adjusted by the liquid-saturated vapor pressure P. These 68 adjusted scores, as log (MMAS/P), were shown to be completely equivalent to eye irritation thresholds (EIT), expressed as log (1/EIT), for 23 compounds in humans. Thus, for the first time the Draize eye test in rabbits for pure bulk liquids is shown to be perfectly compatible with eye irritation thresholds in humans. The total data set for 91 compounds was analyzed by the general solvation equation of Abraham. Values of log (MMAS/P) or log (1/EIT) could be fitted to a five-parameter equation with R2 = 0.936, SD = 0.433, AD = 0.000, and AAD = 0.340 over a range of 9.6 log units. When divided into a training set of 45 compounds, the corresponding equation could be used to predict the remaining 46 compounds in a test set with AD = -0.037 and AAD = 0.345 log units. Thus, the 91-compound equation can now be used to predict further EIT values to around 0.4 log units. It is suggested that the mechanism of action in the Draize test and in the human EIT involves passive transfer of the compound to a biophase that is quite polar, is a strong hydrogen bond base, a moderate hydrogen bond acid, and quite hydrophobic. The biophase does not resemble water or plasma, but resembles an organic solvent such as N-methylformamide.

Animal Testing Alternatives↗

PubMed2002

Theoretical modeling of oral absorption of barbiturates.

The structural characteristics governing gastric absorption of barbiturates were studied using QSAR methodology. The results showed that the gastric absorption rate constant could be modeled using the theoretical parameters, accessible surface area, atomic charges and electrostatic potentials. Using molecular connectivity indexes was also satisfactory in modeling the absorption.

Absorption↗