Molecular descriptors toxicity

Gute, B. D., Basak, S. C. Predicting acute toxicity of benzene derivatives using theoretical molecular descriptors A hierarchical QSAR approach. SAR QSAR Environ. Res. 1997, 7, 117-131. 

In many cases of practical interest, no theoretically based mathematical equations exist for the relationships between x and y we sometimes know but often only assume that relationships exist. Examples are for instance modeling of the boiling point or the toxicity of chemical compounds by variables derived from the chemical structure (molecular descriptors). Investigation of quantitative structure-property or structure-activity relationships (QSPR/QSAR) by this approach requires multivariate calibration methods. For such purely empirical models—often with many variables—the... 

Chemical reactivity and biological activity can be related to molecular structure and physicochemical properties. QSAR models can be established among hydrophobic-lipophilic, electronic, and steric properties, between quantum-mechanics-related parameters and toxicity and between environmental fate parameters such as sorption and tendency for bioaccumulation. The main objective of a QSAR study is to develop quantitative relationships between given properties of a set of chemicals and their molecular descriptors. To develop a valid QSAR model, the following steps are essential ... 

Schuurmann, G., QSAR analysis of the acute toxicity of organic phosphorothionates using theoretically derived molecular descriptors, Environ. Toxicol. Chem., 9, 417-428, 1990. 

Many thousands of descriptor types have been developed over the years of chemical research. This short review is not intended to summarize these efforts in detail. Todeschini and Consonni have already provided a reference book for this purpose. Commercial and academic software for generating molecular descriptors has proliferated over the recent years. Todeschini s book lists software packages known in the year 2000. Speed of calculation, descriptor quality and diversity should be considered in selecting software. For example, absorption, distribution, metabolism, excretion, toxicity (ADMET) Predictor (Simulations Plus, Inc.) works at a rate of 250,000 molecules per horn calculating 272 molecular and 44 atomic descriptors in the following categories ... 

Gute, B.D. and Basak, S.C. (1997). Predicting Acute Toxicity of Benzene Derivatives Using Theoretical Molecular Descriptors A Hierarchical QSAR Approach. SAR QSAR Environ.Res., 7,117-131. 

Multiple linear regression (MLR) is one of the most common and simplest method for QSAR modeling. MLR has been used for the prediction of geno-toxicity [12], Daphnia magna toxicity [13], photobacterium phosphoreum toxicity [14], aquatic toxicity [15], eye irritation [16], mutagenicity, and carcinogenicity [17], An MLR model assumes that there is a linear relationship between the molecular descriptors of a compound, which is usually expressed as a feature vector x (with each descriptor as a component of this vector), and... 

Partial least squares (PLS) is similar to MLR in that it also assumes a linear relationship between a vector x and a target property y. However, it avoids the problems of collinear descriptors by calculating the principal components for the molecular descriptors and target property separately. The scores for the molecular descriptors are used as the feature vector x and are also used to predict the scores for the target property, which can in turn be used to predict y. An important consideration in PLS is the appropriate number of principal components to be used for the QSAR model. This is usually determined by using cross-validation methods like fivefold cross validation and leave-one-out. PLS has been applied to the prediction of carcinogenicity [19], fathead minnow toxicity [20], Tetrahymena pyriformis toxicity [21], mammalian toxicity [22], and Daphnia magna toxicity [23],... 

A quantitative structure-activity relationship (QSAR) is a measurable relationship between a biological activity (e.g., toxicity) and one or more molecular descriptors that are used to predict the activity. A molecular descriptor is a structural or physicochemical property of a molecule, or part of a molecule, which specifies a particular characteristic of the molecule and is used as an independent variable in a QSAR. 

Numerical quantities, experimentally determined or estimated by statistical or computational approaches, which measure the environmental behavior, fate, and toxicity of chemicals, are molecular descriptors usually referred to as environmental indices. The octanol-water partition coefficient (Kqw, log P) is the most well-known environmental index used as the measure of lipophilicity of compounds. Together with log P and the soil sorption partition coefficient (Koc) [Baker, Mihelcic et al, 2001 Uddameri and Kuchanur, 2004], other quantities have to be considered as relevant for environmental studies. Some of these have been defined to describe mobility, biodegradabUity, bioaccumulation, metabolism, partition, and toxicity of chemicals, thus becoming relevant to human health and environmental safety assessment. 

Property filters usually are binary variables assuming a value equal to 1, if the molecule shows a specific property (drug-likeness, ADME properties, and toxicities) and equal to zero otherwise. These filters are not comprised of many molecular descriptors and a threshold or a range of values is associated to each descriptor together with a condition on the descriptor value if the... 

Prediction of partition coefficient and toxicity for benzaldehyde compounds by their capacity factors and various molecular descriptors. Chemosphere, 42, 899-907. 

Di Marzio, W., Galassi, S., Todeschini, R. and Consolaro, F. (2001) Traditional versus WHIM molecular descriptors in QSAR approaches applied to fish toxicity studies. Chemosphere, 44, 401-406. 

Ren, S. (2002d) Use of molecular descriptors in separating phenols by three mechanisms of toxic action. Quant. Struct. -Act. Relat., 21, 486-492. 

In the chapter of Pavan et al. the reader may leam more about the theoretical handling of partial order. Especially a useful description of partial order by matrices can be found here. The main topic, however, is devoted to the QSAR problem. The authors suggest and describe how molecular descriptors can be found in order to find useful partial orders. They describe genetic algorithms to find the best model poset and to derive from these unknown properties. "Experimental ranking and Model ranking" are at the heart of this chapter. The interpolation problem, already discussed in the first section by Klein Ivanciuc, and later within this section by Carlsen, plays an important role in the chapter of Pavan et al. A discussion of the prediction uncertainty rounds this chapter. As examples phenyl urea herbicides and their toxicity is chosen. 

The fundamental idea of QSAR consists of the possibility of a relationship between a set of descriptors, which are derived from molecular structure, and a molecular response. Within this scope, several molecular descriptors, which discretely parameterize a given molecular set, have been devised. From the early work of Cross [1], where a relationship between toxicity and water solubility was observed, several other parameters have been proposed, such as Hammett s sigma [5], which accounts for electronic effects due to molecular backbone substitution, or the octanol/water partition coefficient [6], widely used to describe lipophilicity. Later on, other frameworks have been formulated in order to include molecular shape, size, polarizability, and many other structural features, also based on the three-dimensional molecular character. A number of reviews have been published [7-9], concerning the historical development, descriptor generation, and their application into the QSAR field. 

Quantum-chemical molecular descriptors have been actively used in the quantitative structure-activity relationship studies of biological activities [1,2,72]. In the following, examples of QSARs involving quantum-chemical descriptors and applied on the enzymatic reactivity, pharmacological activity, and toxicity of compounds are discussed. 

Perhaps the most obvious way to characterise different chemical structures is to use experimental measurements of some characteristic properties, such as melting point, boiling point or refractive index for example. This approach has the advantage that these properties are unambiguously and easily defined and in many cases easily measured to any desired precision. Solubility is clearly an important factor in the biological activity of any compound, and indeed this was found to be one of the earliest successful molecular descriptors, where toxicity... 

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