Biomedical subjects
Publications and source records attributed to Michael H Abraham.
This paper deals with a Quantitative Structure-Activity Relationship (QSAR) study on a large set of 123 compounds using a combination of topological indices as well as Abraham's molecular descriptors. The results have shown that an excellent model (R=0.9542) is obtained in hexa-parametric correlation containing W, logRB (topological indices) along with R2, sigmapi2H, sigmabeta2O and Vx as the correlating parameters. The results are discussed critically.
The van der Waals volume is a widely used descriptor in modeling physicochemical properties. However, the calculation of the van der Waals volume (V(vdW)) is rather time-consuming, from Bondi group contributions, for a large data set. A new method for calculating van der Waals volume has been developed, based on Bondi radii. The method, termed Atomic and Bond Contributions of van der Waals volume (VABC), is very simple and fast. The only information needed for calculating VABC is atomic contributions and the number of atoms, bonds, and rings. Then, the van der Waals volume (A(3)/molecule) can be calculated from the following formula: V(vdW) = summation operator all atom contributions - 5.92N(B) - 14.7R(A) - 3.8R(NR) (N(B) is the number of bonds, R(A) is the number of aromatic rings, and R(NA) is the number of nonaromatic rings). The number of bonds present (N(B)) can be simply calculated by N(B) = N - 1 + R(A) + R(NA) (where N is the total number of atoms). A simple Excel spread sheet has been made to calculate van der Waals volumes for a wide range of 677 organic compounds, including 237 drug compounds. The results show that the van der Waals volumes calculated from VABC are equivalent to the computer-calculated van der Waals volumes for organic compounds.
In a series of experiments, we have explored the rules of olfactory detection agonism between the odorants butyl acetate and toluene. First, we obtained the concentration-detection function for the odor of the individual compounds. Second, we selected the concentrations of the two substances producing three levels of detectability (low, medium, and high) and, for each level, tested the comparative detectability of the two single chemicals and three mixtures of varying proportions. In each case, the mixtures were prepared in such a way that, if a rule of complete dose addition were to hold, all five stimuli (two single, three mixtures) should be equally detected. The outcome revealed complete dose addition at relatively low detectability levels but fell short of dose addition at medium and high levels. A recent analogous study on trigeminal chemosensory detection via nasal pungency and eye irritation of these same stimuli have shown a similar trend but showed a less dramatic loss of dose additivity with increased detectability. These results on detection of mixtures suggest a more selective window of chemical tuning (i.e. less dose addition) in olfaction than in trigeminal chemoreception.
The absorption of 111 drug and drug-like compounds was evaluated from 111 references based on the ratio of urinary excretion of drugs following oral and intravenous administration to intact rats and biliary excretion of bile duct-cannulated rats. Ninety-eight drug compounds for which both human and rat absorption data were available were selected for correlation analysis between the human and rat absorption. The result shows that the extent of absorption in these two species is similar. For 94% of the drugs the absorption difference between humans and rats is less than 20% and for 98% of drugs the difference is less than 30%. There is only one drug for which human absorption is significantly different from rat absorption. The standard deviation is 11% between human and rat absorption. The linear relationship between human and rat absorption forced through the origin, as determined by least squares regression, is %Absorption (human)=0.997%Absorption (rat) (n=98, SD=11). It is suggested that the absorption in rats could be used as an alternative method to human absorption in pre-clinical oral absorption studies.
Studies of olfaction and chemesthesis often rely on nominal, liquid-phase dilutions to quantify the chemicals tested, even though the associated vapor concentrations constitute the actual stimuli. For more than a decade now, our systematic studies of the olfactory and chemesthetic potency of members of homologous chemical series have routinely included quantification of vapors via gas chromatography. This article depicts the relationships between liquid- and vapor-phase concentrations for 60 volatile organic compounds and summarizes the theoretical and technical factors influencing these relationships. The data presented will allow other investigators working with these materials to express them as vapor concentrations even when they lack the resources to perform the analytical measurements. The paper represents a step toward creation of a practical archive for vapor quantification in chemosensory science.
A drug can be characterized by "descriptors" that include size (volume) and H-bond acidity and H-bond basicity. These descriptors can be rapidly estimated from structure by a fragment scheme and used to predict physicochemical and transport properties of drug candidates (e.g. logP, solubility, gastrointestinal absorption, permeability and blood-brain distribution). The solvation equations can be interpreted to provide a qualitative chemical insight into biological partition and transport mechanisms. Applications to blood-brain partition and human intestinal absorption (HIA) are discussed.
A simple chloroalkane or chlorocycloalkane has a very small hydrogen bond basicity, B = 0.1 units. Since B is often an additive function, it is possible that polychloro-alkanes or -cycloalkanes could have quite large hydrogen bond basicities. Literature data on the 1,2,3,4,5,6-hexachlorocyclohexanes (HCHs) have been analyzed by Abraham's linear free energy relationships to obtain solvation descriptors. These are not extraordinary except for the hydrogen bond basicity, B, which is indeed very large. Values of B for the HCHs are larger than many functionally substituted aliphatic compounds and as large as that of aliphatic amines. We find that B is 0.62-0.72 for the HCHs compared to 0.45 for propanone and 0.70 for ethylamine, the first time that such large hydrogen bond basicities have been identified in compounds with no functional groups. Hydrogen bond basicities are analyzed in order to examine what types of polychlorocompounds give rise to these elevated B values.
Marmur has claimed that large values of activity coefficients for nonelectrolytes, particularly in the context of hydrophobic interactions between solutes in aqueous solution at ambient temperature and pressure, cannot be accounted for by thermodynamics, and has suggested that association (self-assembly) of solute molecules in solution solves this dilemma. We show that the analysis of Marmur is incorrect, specifically because the equilibrium in solution between monomeric solute molecules and associated solute molecules is entirely ignored. We show further that activity coefficients such as that for nitromethane solute in hexane solvent, 39.7, and that for solute hexane in solvent water, 4.48 x 10(5), can be calculated as 31.9 and 4.71 x 10(5), respectively, by methods based on well-known molecule-molecule interactions. No assumption of self-assembly is required.
Several micellar electrokinetic chromatography (MEKC) systems (sodium dodecyl sulfate, lithium dodecyl sulfate, lithium perfluorooctanesulfonate, sodium cholate, sodium deoxycholate, tetradecyltrimethylammonium bromide and hexadecyltrimethylammonium bromide) have been characterized by means of the solvation parameter model. It has been observed that the coefficients of the correlation equations depend strongly on the particular set of compounds analyzed. Principal component analysis has been used to characterize the 2975 compounds with available solute descriptors and to select an appropriate subset of compounds to be analyzed by MEKC. With this set of compounds, the MEKC systems have been characterized. Principal component analysis has also been used to show the similarities and differences between the properties of the surfactants characterized by MEKC.
In order to investigate whether the main step in intestinal absorption in humans is dominated by partition or by diffusion, we have transformed % human intestinal absorption into a first-order rate constant, and have regressed the latter, as logk, against our solvation parameters. The obtained regression coefficients are compared with those for diffusion and partition processes. The coefficients in the logk equation are completely different to those for water/solvent partitions, but are very similar to those for processes (not involving transport through membranes) in which diffusion is the major step. It is suggested that the main step in the absorption process is diffusion through a stagnant mucus layer, together with transfer across the mucusmid R:membrane interface. It is further shown that for strong Bronsted acids and bases, the rate constant for absorption of ionic species is close to that for absorption of the corresponding neutral species, so that to a first approximation the % intestinal absorption can be calculated from properties of the neutral species.
PURPOSE: To classify the dissolution and diffusion rate-limited drugs and establish quantitative relationships between absorption and molecular descriptors. METHODS: Absorption consists of kinetic transit processes in which dissolution, diffusion, or perfusion processes can become the rate-limited step. The absorption data of 238 drugs have been classified into either dissolution or diffusion rate-limited based on an equilibrium method developed from solubility, dose, and percentage of absorption. A nonlinear absorption model derived from first-order kinetics has been developed to identify the relationship between percentage of drug absorption and molecular descriptors. RESULTS: Regression analysis was performed between percentage of absorption and molecular descriptors. The descriptors used were ClogP, molecular polar surface area, the number of hydrogen-bonding acceptors and donors, and Abraham descriptors. Good relationships were found between absorption and Abraham descriptors or ClogP. CONCLUSIONS: The absorption models can predict the following three BCS (Biopharmaceutics Classification Scheme) classes of compounds: class I, high solubility and high permeability; class III, high solubility and low permeability; class IV, low solubility and low permeability. The absorption models overpredict the absorption of class II, low solubility and high permeability compounds because dissolution is the rate-limited step of absorption.
Literature data on various physicochemical properties of N-nitrosodialkylamines have been analyzed using our general solvation equations, to yield properties or descriptors for these compounds, viz. S the dipolarity/ polarizability, A hydrogen bond acidity, B the hydrogen-bond basicity, and L the logarithm of the gas-hexadecane partition coefficient. Descriptors for 35 nitrosocompounds have been evaluated. From these descriptors, various important properties of environmental interest have been estimated, including the gas-water and water-octanol partition coefficients, and solubilities in water.
Odour detection thresholds, that we have previously obtained, have been analysed by a general equation for selective transport. It is shown that such selective transport can account for some 77% of the total effect. The remainder is due to a specific size effect, that might involve odour-binding proteins, and a specific effect for aldehydes and carboxylic acids. Our analysis raises the question of whether selective transport is physically separable from the specific effects of receptor activation. The model predicts a chemical cut-off in odour detection along any homologous series.
We measured psychometric (i.e. concentration-response) functions for the detection of odor, nasal pungency and eye irritation from butyl acetate and toluene. Olfactory detection was measured in subjects with normal olfaction (i.e. normosmics) for whom nasal trigeminal detection does not interfere because it requires much higher concentrations. Nasal trigeminal detection, called nasal pungency, was measured only in subjects lacking olfaction (i.e. anosmics) in order to avoid odor interference. Ocular trigeminal detection, called eye irritation, was measured in both groups. The method employed entailed a two-alternative, forced-choice procedure with presentation of increasing concentrations. The outcome showed, for both chemicals, similar ocular trigeminal chemosensitivity in normosmics and anosmics and similar overall ocular and nasal trigeminal chemosensitivity. Olfactory sensitivity was much higher than both forms of trigeminal sensitivity by concentration differences of six and four orders of magnitude for butyl acetate and toluene, respectively. Detectability plots (i.e. detection performance vs log concentration) for the three sensory endpoints followed an S-shaped function with a middle range section that showed a robust linear fit (r > 0.94) on graphs of z-score vs log concentration. These detectability functions allow the calculation of olfactory and trigeminal thresholds at various levels of performance. At a point half-way between random and perfect detection, trigeminal and olfactory threshold concentrations were, respectively, 0.67 (+/-0.32) and 2.28 (+/-1.77) log units lower than those measured by us in the past for the same chemicals using an analogous procedure but under just one, fixed, level of performance. The available data suggest that, although considerably laborious, detectability functions provide chemosensory thresholds of closer relevance to environmentally realistic conditions (e.g. whole-body exposures).
Two sets of molecular descriptors, the five experimental Abraham, and the five COSMOments of Klamt's COSMO-RS, have been compared for a data set of 470 compounds. Both sets are considered as almost complete sets of LFER. The two sets of descriptors are shown to exhibit a large overlap as far as their chemical content. The chemical information however is distributed differently in each set with the Abraham set incorporating extra information in the excess molar refraction descriptor E. Regression equations have been constructed to predict the experimental Abraham descriptors from theoretically calculated COSMOments. The chemical interpretation of these equations is however difficult because of the lack of clustering which characterizes the distribution of chemical information through the two sets of descriptors. The predictability of the regression equations is tested successfully using a reasonably large set of data, and the method is compared to recent attempts to calculate the Abraham descriptors from various theoretical bases.