Indirect QSAR

A challenging task in material science as well as in pharmaceutical research is to custom tailor a compound s properties. George S. Hammond stated that the most fundamental and lasting objective of synthesis is not production of new compounds, but production of properties (Norris Award Lecture, 1968). The molecular structure of an organic or inorganic compound determines its properties. Nevertheless, methods for the direct prediction of a compound s properties based on its molecular structure are usually not available (Figure 8-1). Therefore, the establishment of Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) uses an indirect approach in order to tackle this problem. In the first step, numerical descriptors encoding information about the molecular structure are calculated for a set of compounds. Secondly, statistical and artificial neural network models are used to predict the property or activity of interest based on these descriptors or a suitable subset. 

QSPR and QSAR are useful techniques for predicting properties that would be very dilficult to predict by any other method. This is a somewhat empirical or indirect calculation that ultimately limits the accuracy and amount of information which can be obtained. When other means of computational prediction are not available, these techniques are recommended for use. There are a variety of algorithms in use that are not equivalent. An examination of published results and tests of several techniques are recommended. 

Menziani, M.C. and De Benedetti, P. (1991) Direct and indirect theoretical QSAR modelling in sulfonamide carbonic anhydrase inhibitors, in QSAR Rational Approaches on the Design of Bioactive Compounds (eds C. Silipoand A. Vittoria), Elsevier, Amsterdam, pp. 331. 

Since QSAR models for narcosis toxicity based on Kn/W are available for many endpoints and species, it has become a popular approach applied for screening the ecological risk posed by substances for which no data are available. ECOSAR itself, with 150 relationships defined for over 50 chemical classes, has been used to predict toxicity and estimate hazards for chemical warfare agents in marine environments [96], pharmaceuticals [102-104], direct and indirect food additives, and industrial chemicals [105]. Although there are several QSAR and other predictive tools currently available, this section focuses on ECOSAR as it is one of the most widely and easily used. 

Walker, J.D., Knaebel, D., Mayo, K., Tunkel, J. and Gray, D.A. (2004) Use of QSARs to promote more cost-effective use of chemical monitoring resources. 1. Screening industrial chemicals and pesticides, direct food additives, indirect food additives and pharmaceuticals for biodegradation, bioconcentration and aquatic toxicity potential, Water Quality Research Journal of Canada 39, 35-39. 

If the chemical composition of the samples is known or at least partly known (in a stepwise TIE approach) or existing data allow for QSAR calculation, the samples can be ranked by TUs. Arts et al. (2006) studied, in 12 outdoor ditch mesocosms, the effects of sequential contamination with 5 pesticides in a regression design. They applied dosages equivalent with 0.2%, 1%, and 5% of the predicted environmental concentration (PEC) subsequently over 17 weeks. Endpoints recorded over 30 weeks included community composition of macroinvertebrates, plankton, and macrophytes, and leaf litter decomposition as functional ecosystem parameters. TUs were calculated in relation to acute toxicity data for the most sensitive standard species Daphnia magna and Lemna minor. Principal response curves (PRCs), a special form of constrained PCA, and Williams test (NOEC, class 2 LOEC) were used to identify the most sensitive taxa. Next to direct effects on certain species, also indirect effects, for example, how the change in abundance of a sensitive species affects the abundance of another, more tolerant species, can be detected only in mesocosm or in situ experiments. All observed effects were summarized in effect classes in a descriptive manner. 

We reiterate that we do not have knowledge of the experimental configurational states, or the extent of carboxyl ionization, of the cyclic nitrosoamines. The self-consistency of the QSAR is the only indirect evidence for predicting configurational, conformer, and ionization states of the molecules. 

The QSPR/QSAR methods have many direct benefits like property prediction, target molecular design, and structural refinement, and indirectly it can help to... 

The normalized occupancy of each grid cell by each IPE type over the CEP of each molecule, for a given alignment, constitutes a unique set of molecular descriptors referred to as Grid Cell Occupancy Descriptors (GCODs). These descriptors were used directly to estimate QSAR models and indirectly in 4D-Molecular Similarity Analysis to generate a set of spectral indices. 

Heimstad, E.S. and Andersson, P.L. (2002) Docking and QSAR studies of an indirect estrogenic effect of hydroxylated PCBs. Quant. Struct. -Act. Rdat., 21, 257-266. 

---