Topological indices (TIs) are numerical representations of the topology of a molecule, and are calculated from the heavy atom graphical depiction of the molecule. One of the first TIs was that of Wiener in 1947, who showed that his index... more
Topological indices (TIs) are numerical representations of the topology of a molecule, and are calculated from the heavy atom graphical depiction of the molecule. One of the first TIs was that of Wiener in 1947, who showed that his index correlated well with the boiling points of alkanes. There are now many different TIs available, and many of them are discussed in this chapter, with respect largely to their use as descriptors in QSAR/QSPR modeling. Three types in particular stand out, molecular connectivities developed by Randic and Kier and Hall, electrotopological state (E-state) values developed by Kier and Hall, and information content indices developed by Basak and co-workers. New TIs are still appearing, despite some criticism that there are already too many types of TI, that they are difficult of interpretation, and that they are inferior to physicochemical descriptors in modeling.
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In the fourth part of the book, in a chapter on animal management, Wemelfelder writes a long chapter on animal boredom, and despite its length, makes some interesting points. We should be trying to assess behavioural parameters as opposed... more
In the fourth part of the book, in a chapter on animal management, Wemelfelder writes a long chapter on animal boredom, and despite its length, makes some interesting points. We should be trying to assess behavioural parameters as opposed to physiological parameters a.nd that ou.r denial of using these parameters IS a quasiscientific denial on the basis oflack of objectivity. Perhaps, she says, we should use our subjective experiences as an interpretational guide in evaluating behavioural reactions of animals to external stimuli or their environment. She suggests we shall ultimately be able to explai.n behaviour in terms of functioning of the basic units of the nervous system, but at present our scientific knowledge does not permit it. The same was true of physiology several decades ago and so does not mean this new discipline should not be pursued. The argument is often advanced that domestication of animals has selected for the "removal" of the natural behavioural repertoire for many species. She quotes several examples where this is blatently untrue; that given the right environmental circumstances, these animals still retain their (genetic) motivations, e.g. to burrow, to explore, to play. Therefore, we should consider far more seriously environmental deprivation and how we can measure it. She then addresses the intensive farming of pigs and chickens and, having established a case for why animals can be bored, she goes on to quote examples of how they are bored in these husbandry systems. She ends her paper by stating, "we might in this way be able to help create an environment for the animal which is healthy both physically and mentally, and which will benefit not only them, but ourselves as well". A further chapter in this section dealt with the measurement of stereotyped behaviour in sows and gilts housed in stalls, tethers and groups. Unfortunately, the assessment of behaviour f~r sows housed in groups was masked through their aggressive instincts to achieve a social order (socalled agonistic behaviour), which prevented other behaviour patterns from emerging. I think this highlights some of the arguments against extensive farming systems. Nonetheless, there IS some food for thought about how we should measure animal welfare in these intensive husbandry situations. Overall, I am sceptical that this series of books will achieve the recognition it deserves and I should prefer to see the contributions made !~ this volume being incorporated in more traditional scientific publications. However, perhaps public sympathies now demand recognition of such a discipline and to have it separated fr?m the general scientific establishment. Paradoxically, I wonder if the scientific establishment would embrace it in their own remit (despite their frequent claims to academic freedom) because of the consequent limitations which the results of such studies may impose.
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... Pitter (1984) found, for a series of anilines and phenols, a dependence of rate of biodegradation upon electronic factors ... between biodegradability and electrophilic superdelocalizability on the carbon atom to which the hydroxyl... more
... Pitter (1984) found, for a series of anilines and phenols, a dependence of rate of biodegradation upon electronic factors ... between biodegradability and electrophilic superdelocalizability on the carbon atom to which the hydroxyl group is attached: BOD= 0.930 x 10" 1 SE-3.163 (13 ...
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Although thousands of quantitative structure-activity and structure-property relationships (QSARs/QSPRs) have been published, as well as numerous papers on the correct procedures for QSAR/QSPR analysis, many analyses are still carried out... more
Although thousands of quantitative structure-activity and structure-property relationships (QSARs/QSPRs) have been published, as well as numerous papers on the correct procedures for QSAR/QSPR analysis, many analyses are still carried out incorrectly, or in a less than satisfactory manner. We have identified 21 types of error that continue to be perpetrated in the QSAR/QSPR literature, and each of these is discussed, with examples (including some of our own). Where appropriate, we make recommendations for avoiding errors and for improving and enhancing QSAR/QSPR analyses.
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Bioconcentration factor (BCF) is an important step in the uptake of environmental pollutants in the food chain. It is expensive and time-consuming to measure, so predictive methods are of value. We have used an artificial neural network... more
Bioconcentration factor (BCF) is an important step in the uptake of environmental pollutants in the food chain. It is expensive and time-consuming to measure, so predictive methods are of value. We have used an artificial neural network QSAR approach involving descriptors for hydrophobicity, hydrogen bonding and molecular topology, obtained from commercially available software, to predict the fish BCF values of a diverse data set of 624 chemicals. The training set statistics were: r²= 0.765, q²= 0.763, s = 0.610, and those of the external test set were: r²= 0.739, s = 0.627. The model complies with the OECD Principles for the Validation of (Q)SARs.
Research Interests: Chemistry, Forecasting, Water Pollution, Medicine, Biological Sciences, and 14 moreSoftware, Environmental Sciences, QSAR, Animals, Fishes, Quantitative Structure Activity Relationship, Hydrogen Bond, CHEMICAL SCIENCES, Hydrogen Bonding, Hydrophobicity, Food Chain, Artificial Neural Network, Environmental Exposure, and Bioconcentration factor
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Buccal absorption tests indicate that loss of drug from the oral cavity cannot be accounted for solely in terms of passive diffusion into the buccal membrane. A model involving protein-binding is proposed, which satisfactorily explains... more
Buccal absorption tests indicate that loss of drug from the oral cavity cannot be accounted for solely in terms of passive diffusion into the buccal membrane. A model involving protein-binding is proposed, which satisfactorily explains the observed loss. Studies on two different physical simulations of buccal absorption confirm that the proposed model is consistent with the in vivo results.
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Research Interests: Inorganic Chemistry, Organic Chemistry, Physical Chemistry, Aquatic Toxicology, Biology, and 12 moreChemical, Risk assessment, Medicine, Linear models, Toxicity, Quantitative Structure Activity Relationship, Chlorella, Risk Assessment, Toxicity Tests, Chlorella Vulgaris, Food and Chemical Toxicology, and Organic Chemicals
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Introduction: Numerous potentially controlling demographic factors such as age, poverty, obesity, and car- diovascular and respiratory co-morbidities have been suggested, and high vitamin D levels have been found, to be associated with... more
Introduction: Numerous potentially controlling demographic factors such as age, poverty, obesity, and car- diovascular and respiratory co-morbidities have been suggested, and high vitamin D levels have been found, to be associated with lower levels of COVID-19 infection. This study aimed to explore the correlation between vitamin D levels and socio-demographic characteristics with COVID-19 cases and deaths in 20 European countries. Methods: A quantitative ecological study was designed. Multiple linear regression analysis was used to examine which of vitamin D levels and 20 demographic factors correlated well with COVID-19 cases and deaths up to 9 May 2020 in 20 European countries. Data distributions were normalised by the Box and Cox approach and the Minitab routine 'Best Subsets' was used to select the best descriptor sets for each quantitative model of cases and deaths. Results: Cases were best modelled by vitamin D levels, stroke deaths, respiratory deaths, smoking, and h...
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ABSTRACT
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32 Quantitative Structure-Property Relationship (QSPR) models were constructed for prediction of aqueous intrinsic solubility of liquid and crystalline chemicals. Data sets contained 1022 liquid and 2615 crystalline compounds. Multiple... more
32 Quantitative Structure-Property Relationship (QSPR) models were constructed for prediction of aqueous intrinsic solubility of liquid and crystalline chemicals. Data sets contained 1022 liquid and 2615 crystalline compounds. Multiple Linear Regression (MLR), Support Vector Machine (SVM) and Random Forest (RF) methods were used to construct global models, and k-nearest neighbour (kNN), Arithmetic Mean Property (AMP) and Local Regression Property (LoReP) were used to construct local models. A set of the best QSPR models was obtained: for liquid chemicals with RMSE (root mean square error) of prediction in the range 0.50-0.60 log unit; for crystalline chemicals 0.80-0.90 log unit. In the case of global models the large number of descriptors makes mechanistic interpretation difficult. The local models use only one or two descriptors, so that a medicinal chemist working with sets of structurally-related chemicals can readily estimate their solubility. However, construction of stable local models requires the presence of closely related neighbours for each chemical considered. It is probable that a consensus of global and local QSPR models will be the optimal approach for construction of stable predictive QSPR models with mechanistic interpretation.
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New anxiolytics have been discovered by prediction of biological activity with computer programs PASS and DE DEREK for a heterogeneous set of 5494 highly chemically diverse heterocyclic compounds (thiazoles, pyrazoles, isatins, a fused... more
New anxiolytics have been discovered by prediction of biological activity with computer programs PASS and DE DEREK for a heterogeneous set of 5494 highly chemically diverse heterocyclic compounds (thiazoles, pyrazoles, isatins, a fused imidazoles and others). The majority of tested compounds exhibit the predicted anxiolytic effect. The most potent activity was found in 2 (4 nitro phenyl) 3 (4 phenylpiperazinomethyl)imidazo[1,2 a]pyridine 8, 1 [(4 bromophenyl) 2 oxoethyl] 3 (1,3 dioxolano) 2 indolinone 3, 5 hydroxy 3 methoxycarbonyl 1 phenylpyrazole 5 and 2 (4 fluorophenyl) 3 (4 methylpiperazinomethyl)imidazo[1,2 a]pyridine 7. The application of the computer assisted approach significantly reduced the number of synthesized and tested compounds and increased the chance of finding new chemical entities (NCEs).
Research Interests: Expert Systems, Organic Chemistry, Computational Biology, Learning, Computer Simulation, and 10 moreAnimals, Drug Design, Computer Program, Rats, Bioorganic and medicinal Chemistry, Biological activity, Structure activity Relationship, Heterocyclic compounds, Motor activity, and Pharmacology and pharmaceutical sciences
The binding of fifteen p‐substituted acetanilides to bovine serum albumin is examined at pH 7·2. An excellent correlation is obtained between the binding enthalpy and Hammett's substituent constant, s̀. This is interpreted to mean... more
The binding of fifteen p‐substituted acetanilides to bovine serum albumin is examined at pH 7·2. An excellent correlation is obtained between the binding enthalpy and Hammett's substituent constant, s̀. This is interpreted to mean that the binding is non‐specific in nature. A very good correlation is also obtained between the entropy of binding and s̀, which suggests that the extent of hydration of unbound drug is a function of the charge separation within the drug molecule. Of the compounds examined, those that have been used clinically as analgesics possess the best thermodynamic properties, being neither so fully bound as to give low free drug concentrations in the bloodstream, nor so little bound that there is no sustained action.
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Hydrogen-bonding, important in drugąreceptor interactions, also determines the solubility and partitioning of drugs between phases. It is, therefore, important to incorporate the effects of hydrogen-bonding in studies of quantitative... more
Hydrogen-bonding, important in drugąreceptor interactions, also determines the solubility and partitioning of drugs between phases. It is, therefore, important to incorporate the effects of hydrogen-bonding in studies of quantitative structureąactivity relationships (QSAR). In ...
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The use of alternative toxicity tests and computational prediction models is widely accepted to fill experimental data gaps and to prioritize chemicals for more expensive and time-consuming assessment. A novel short-term toxicity test... more
The use of alternative toxicity tests and computational prediction models is widely accepted to fill experimental data gaps and to prioritize chemicals for more expensive and time-consuming assessment. A novel short-term toxicity test using the alga Chlorella vulgaris was utilized in this study to produce acute aquatic toxicity data for 65 aromatic compounds. The compounds tested included phenols, anilines, nitrobenzenes, benzaldehydes and other poly-substituted benzenes. The toxicity data were employed in the development of quantitative structure-activity relationships (QSARs). Using multiple regression (MLR) and partial least squares (PLS) analyses, statistically significant, transparent and interpretable QSARs were developed using a small number of physicochemical descriptors. A two-descriptor model was developed using MLR (log(1/EC50)=0.73 log Kow-0.59 Elumo-1.91; n=65, r2=0.84, r2CV=0.82, s=0.43) and a four-descriptor model using PLS (log(1/EC50)=0.40 log Kow-0.23 Elumo+9.84 Amax+0.20 0chiv-5.40; n=65, r2=0.86, q2=0.84, RMSEE=0.40). The latter model was obtained by stepwise elimination of variables from a set of 102 calculated descriptors. Both models were validated successfully by simulating external prediction through the use of complementary subsets. The two factors, which were identified as being critical for the acute algal toxicity of this set of compounds were hydrophobicity and electrophilicity.
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Over half of known industrial pollutants have minimal toxic effect, in line with the concept of "baseline toxicity"; such toxicity usually correlates well with lipophilicity. The remainder require additional descriptors... more
Over half of known industrial pollutants have minimal toxic effect, in line with the concept of "baseline toxicity"; such toxicity usually correlates well with lipophilicity. The remainder require additional descriptors in order to model their toxicity by the QSAR approach. Hence, it has not been possible, to date, to develop common stable QSAR models for the toxicity of diverse chemicals with various modes of action on the basis of simple regression relationships. Any new methodology has to take such different modes of action into account. In our work, we used for this purpose an original combination of the similarity concept and physicochemical descriptors calculated by HYBOT, in order to construct stable QSAR models of guppy toxicity. The training set comprised 293 diverse chemicals. Experimental value(s) of one or more nearest related chemicals were used to take structural features and possible modes of toxic action into account. In addition, molecular polarisability and hydrogen bond descriptors for the chemicals of interest and related compounds were used to calculate any additional contribution in toxicity by means of linear regression relationships. Final comparison of calculated and experimental toxicity values gave good results, with standard deviation close to the experimental error.
Research Interests: Linear models, Biological Sciences, Environmental Sciences, Guppy, Standard Deviation, and 12 moreAnimals, Quantitative Structure Activity Relationship, Prediction Model, Hydrogen Bond, CHEMICAL SCIENCES, Hydrogen Bonding, Mode of action, Molecular Conformation, Toxicity Tests, Linear Regression, Structure activity Relationship, and Predictive value of tests
On the basis of computer prediction of biological activity by PASS and toxicity by DEREK, the most promising 32-alkylaminoacyl derivatives of 3-aminobenzo[d]isothiazole were selected for possible local anaesthetic action. This action was... more
On the basis of computer prediction of biological activity by PASS and toxicity by DEREK, the most promising 32-alkylaminoacyl derivatives of 3-aminobenzo[d]isothiazole were selected for possible local anaesthetic action. This action was evaluated using an in vitro preparation ...
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Many chemicals can induce skin sensitization, and there is a pressing need for non-animal methods to give a quantitative indication of potency. Using two large published data-sets of skin sensitizers, we have allocated each sensitizing... more
Many chemicals can induce skin sensitization, and there is a pressing need for non-animal methods to give a quantitative indication of potency. Using two large published data-sets of skin sensitizers, we have allocated each sensitizing chemical to one of ten mechanistic categories, and then developed good QSAR models for the seven categories with a sufficient number of chemicals to allow modeling. Both internal and external validation checks showed that each model had good predictivity.
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With the introduction of the REACH legislation in the European Union, there is a requirement for property and toxicity data on chemicals produced in or imported into the EU at levels of 1 tonne/year or more. This has meant an increase in... more
With the introduction of the REACH legislation in the European Union, there is a requirement for property and toxicity data on chemicals produced in or imported into the EU at levels of 1 tonne/year or more. This has meant an increase in the in silico prediction of such data. One of the chief predictive approaches is QSAR (quantitative structure-activity relationships), which is widely used in many fields. A QSAR approach that is increasingly being used is that of artificial neural networks (ANNs), and this chapter discusses its application to the range of physicochemical properties and toxicities required by REACH. ANNs generally outperform the main QSAR approach of multiple linear regression (MLR), although other approaches such as support vector machines sometimes outperform ANNs. Most ANN QSARs reported to date comply with only two of the five OECD Guidelines for the Validation of (Q)SARs.
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It is essential, in order to minimise expensive drug failures due to toxicity being found in late development or even in clinical trials, to determine potential toxicity problems as early as possible. In view of the large libraries of... more
It is essential, in order to minimise expensive drug failures due to toxicity being found in late development or even in clinical trials, to determine potential toxicity problems as early as possible. In view of the large libraries of compounds now being handled by combinatorial chemistry and high-throughput screening, identification of putative toxicity is advisable even before synthesis. Thus the use of predictive toxicology is called for. A number of in silico approaches to toxicity prediction are discussed. Quantitative structure-activity relationships (QSARs), relating mostly to specific chemical classes, have long been used for this purpose, and exist for a wide range of toxicity endpoints. However, QSARs also exist for the prediction of toxicity of very diverse libraries, although often such QSARs are of the classification type; that is, they predict simply whether or not a compound is toxic, and do not give an indication of the level of toxicity. Examples are given of all of...
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Biodegradation occurs mainly through microbial enzyme attack, and enzyme-catalysed reactions are known to depend on hydrophobic, electronic and steric effects. However, most QSBR studies involve correlation with a single parameter, but... more
Biodegradation occurs mainly through microbial enzyme attack, and enzyme-catalysed reactions are known to depend on hydrophobic, electronic and steric effects. However, most QSBR studies involve correlation with a single parameter, but there is no consistency regarding the class of parameter. This suggests that biodegradation occurs through a range of different mechanisms. A few QSBR studies have reported the need to include more than one class of parameter in correlations. As well as linear regression analysis, other correlation methods have been used in QSBR investigations. These include discriminant analysis, neural networks and comparative molecular field analysis (CoMFA).
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Gastric irritancies and anti-inflammatory potencies of 25 commercially available non-steroidal anti-inflammatory drugs (NSAIDs) have been measured in the rat. When irritancy is measured as the dose required to produce a specified level of... more
Gastric irritancies and anti-inflammatory potencies of 25 commercially available non-steroidal anti-inflammatory drugs (NSAIDs) have been measured in the rat. When irritancy is measured as the dose required to produce a specified level of gastric mucosal damage, it is found that irritancy increases with anti-inflammatory potency. However, when irritancy is measured as the level of gastric mucosal damage at the anti-inflammatory ED50 (which is a clinically realistic measure) then irritancy decreases as anti-inflammatory potency increases. Hence it should be possible to design high-potency, low-irritancy NSAIDs.
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Solubilities of crystalline organic compounds calculated according to AMP (arithmetic mean property) and LoReP (local one-parameter regression) models based on structural and physicochemical similarities are presented. We used data on... more
Solubilities of crystalline organic compounds calculated according to AMP (arithmetic mean property) and LoReP (local one-parameter regression) models based on structural and physicochemical similarities are presented. We used data on water solubility of 2615 compounds in un-ionized form measured at 25±5 °C. The calculation results were compared with the equation based on the experimental data for lipophilicity and melting point. According to statistical criteria, the model based on structural and physicochemical similarities showed a better fit with the experimental data. An additional advantage of this model is that it uses only theoretical descriptors, and this provides means for calculating water solubility for both existing and not yet synthesized compounds.
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The toxicities of benzoic acids to Vibrio fischeri, Daphnia magna and carp were measured. The results showed that the toxicity to V. fischeri and Daphnia decreased in the order of bromo > chloro > fluoro approximately equal to... more
The toxicities of benzoic acids to Vibrio fischeri, Daphnia magna and carp were measured. The results showed that the toxicity to V. fischeri and Daphnia decreased in the order of bromo > chloro > fluoro approximately equal to aminobenzoic acids. The toxicity of substituted benzoic acids to carp and Daphnia was much lower that to V. fischeri. The results also showed that the toxicity of benzoic acids to Daphnia decreased as the pH increased. It is suggested that ionized and non-ionized forms have different toxic responses. The non-ionized form may play an important role in toxicity because the toxicity of benzoic acids to Daphnia greatly decreases as the pH increases. The toxicity of benzoic acids to Daphnia may operate through non-polar narcosis, based on the regression results between the toxicities and partition coefficients (log P) and apparent partition coefficients (log D). However, toxicity cannot be predicted from non-polar baseline models because the ionized and non-i...
Research Interests: Ecotoxicology, Crustacea, Daphnia, Multidisciplinary, Toxicity, and 17 moreAnimals, Bacteria, Quantitative Structure Activity Relationship, Lipid metabolism, Partition Coefficient, Carp, Vibrio, Benzoic Acid, Pollutant, Daphnia Magna, Carps, Species Specificity, Vibrio Fischeri, Structure activity Relationship, Hydrogen-Ion Concentration, Ions, and Cell Membrane
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Research Interests: Water, Kinetics, Prediction, Risk assessment, Algorithm, and 24 moreIn Vitro, Humans, QSAR, Permeability, Animals, Quantitative Structure Activity Relationship, Skin, Absorption, Partition Coefficient, Solubility, Hydrophobicity, Penetration, Xenobiotics, In Vitro Toxicology, Risk Assessment, Molecular weight, Molecular Size, Experimental Data, Toxicokinetics, Aromatic Hydrocarbon, Serum albumin, Generic model, Skin Absorption, and Current Account
This article describes the use of quantitative structure-activity relationships (QSARs) to predict toxicity endpoints for ecologically relevant and human-surrogate species. The interrelationships between the endpoints, and the... more
This article describes the use of quantitative structure-activity relationships (QSARs) to predict toxicity endpoints for ecologically relevant and human-surrogate species. The interrelationships between the endpoints, and the possibilities of exploring the commonalities of chemical action from one species to another as well as from one endpoint to another, are evaluated. A number of toxic endpoints are discussed including mutagenicity and carcinogenicity; developmental toxicity (teratogenicity); acute toxicity; skin sensitization; skin, eye, and sensory irritation; and the modeling of membrane permeability. A number of electrophilic molecular substructures have been identified that are common to a number of toxicities. It is postulated that if such a substructure is observed in a molecule, it may exhibit a range of toxicities. Further, there appear to be relationships between the toxicity to ecologically relevant and human-surrogate species, which may allow for appreciation and possible extrapolation in both directions. Overall, however, QSARs are limited by the paucity of available toxicological data and information.