A Mechanistic Interpretation, if Possible

This is the most controversial principle and the greatest source of disagreement and discussion among mechanistic and statistical QSAR modellers, also in the environmental field. 

On the other hand, the statistical approach is based on the fundamental conviction that the QSAR modeller should not influence a priori, or personally, the descriptor selection through mechanistic assumptions, but should apply unbiased mathematical tools to select, from a wide pool of input descriptors, 

Molecular structure can be represented in dilferent ways, some more comprehensible than others, but all with a chemical meaning, though not always clearly understood by the users in their QSAR modelling. Molecular descriptors normally have a detailed analysis of their structural meaning in specific literature, infrequently accessed by some QSAR model applicants. This is the main reason that some easier descriptors are considered historically interpretable or mechanistic , while others are defined as incomprehensible or not transparent. 

It has been demonstrated that none of the descriptors can independently explain the observed distribution of the biological data, it is only the combination of selected descriptor sets that allows the modelling of the studied endpoint. Describing the different mechanisms simultaneously makes it difficult to interpret their role in the model. Some descriptors are more obvious and easily interpretable, while others are more difficult to interpret, but their role is in ensuring the high overall predictive power of the models.  

The OECD Application Toolbox applies the mechanistic approach and reads across, categorizing chemicals a priori based on hypothesized mechanisms. Contemporaneously, based on the statistical approach, many models of properties and activities of environmental interest have been developed, and after review they can be inserted in a QSAR model database according to the QSAR Model Reporting Format (QMRF) on the JRC web site.  

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The most important one is that the model should be appropriately validated to confirm the reliability of its predictions. First rules of the validation were worked out in March 2002 at an international workshop held in Setubal, Portugal ( Setubal Rules ). In November 2004, the rules were discussed and modified by the OECD Work Program on QSAR they are now known as the OECD Principles. According to these principles, each QSAR model should be associated with (a) a well-defined endpoint (b) an unambiguous algorithm (c) a defined domain of applicability (d) appropriate measures of goodness-of-fit, robustness and predic-tivity and (v) a mechanistic interpretation, if possible [15, 16]. 

A mechanistic interpretation, if possible Models without mechanistic interpretation can be used in a regulatory context. However, consideration of the mechanistic association between descriptors used in the model and the predicted endpoint should be sought to improve the regulatory applicability of the (Q)SAR. Guides to (Q)SARs currently used in OECD member states has been published (OECD 2005a, 2005b). 

A mechanistic interpretation, if possible. The intent of this principle is to ensure that there is an assessment of the possibihty of a mechanis-... 

According to principle 5, a (Q)SAR should be associated with a mechanistic interpretation, if possible. The mechanistic interpretation refers to the assignment of physicochemical or biological meaning to the descriptors, and to the assignment of a plausible relationship between the descriptors and the modeled endpoint. 

QSAR-5 a mechanistic interpretation, if possible and realized through the present extended case studies as ... 

Principle 5 a mechanistic interpretation, if possible hierarchy of minimum paths across a spectrum of computed/predicted end-points towards identifying the specific influence of molecular descriptors within the orthogonal space of chemical-biological complex interaction by molecular structural characters/indices and of their algebraic behavior and predicted statistics. 

The choice of models is, at present, largely author dependent and not much influenced by an analysis of the published information. Sometimes, the available computer software restricts users to certain models (e.g., the 2-pK formalism is much easier to apply with the common codes than the 1-pK formalism). As is clear from the above statements, a general decision for a certain model would only be possible by disregarding opinions of certain authors. The choice of a model should therefore, as indicated in Section I, be largely associated to the objective of the modeling exercise and be considered in that way. If electrostatic features are of no interest whatsoever in a certain system, then why not use a nonelecfrostatic model However, in case a mechanistic interpretation of ion adsorption is the objective, then it would be difficult to understand why electrostatic interactions should be disregarded. 

This system is worthy of study because the chloride system studies give us several possibilities for predicting the reaction paths. First, in the acetate containing system acetate is both a ligand and a reactant, so different stereochemical results are possible if the mechanistic interpretations in the chloride system are correct. Thus, in the acetate system addition of acetate could occur cis as well as trans. Second, many reactions, such as olefin oxidation, occur more readily in this system (7, 8). Third, peculiar results (see Oxidation) which require explanation have already been reported for this system. Finally, acetate is likely to be quite... 

The interpretation of kinetic data begins with a hypothetical sequence of ele mentary reaction steps, each characterized by two microscopic rate constants, one for the forward and one for the reverse reaction. From this proposed mechanism a rate equation is derived, predicting the dependence of the observed reaction rate on concentrations and on microscopic rate constants, and its form is tested against the observations. If the form of the rate equation meets the test of experiment, it may be possible to derive from the data numerical values for the microscopic rate constants of the proposed elementary reaction steps. While inconsistency is clear grounds for modifying or rejecting a mechanistic hypothesis, agreement does not prove the proposed mechanism correct. 

Scheme 45.6 may not be the only possible mechanistic interpretation that accounts for II with these restrictions. If one plays a little with rejected intermediates VII and VIII, one might come up with at least one manner of... 

Formal potentials are frequently reported from cyclic-voltammetry (CV) measurements. If the system is reversible or quasireversible, the average of Ep and E [see Eq. (d) in 12.3.2.1.4] is used to compute E for the couple. However, unless the couple is reversible this procedure can lead to errors. For the cyclic scan in Fig. 1, two possible mechanistic interpretations can be considered. One is for a quasireversible couple ... 

We consider now the easiest ways in which the main types of unsaturation may be studied so that alternative paths become discemable. These ways are illustrated by examples in Table I without mechanistic interpretation, which will be attempted subsequently. If by this technique extraneous factors are removed, a valid comparison of mechanisms for the different classes of hydrogenation should be possible. 

The QSAR algorithm establishes correlation between the studied response and the molecular descriptors, but recently some concerns have been raised in the lit-erature, emphasizing that correlation between variables does not automatically imply that one causes the other and that chance correlation could occur, mainly if not understandable descriptors are used. However, correlation is a fundamental requirement for causation. The best way to exclude chance correlation is to carefully verify the statistical predictivity of the QSAR models by their validation, as requested by OECD principle 4, also externally on new chemicals, and by scrambling of the response, additionally, if possible, to mechanistically interpret the molecular descriptor (OECD Principle 5). If the correlation is confirmed after rigorous verification, it has a reason for existing and the problem is one of the human mind if the cause is not discovered or understood. 

The mechanistic evidence from relative kinetic data can be greatly enhanced when correlations with other independent quantities are constructed, and thus links between the catalytic processes and other phenomena are found. Boudart (7) was first to point out the possibilities of such correlations. When a relationship of a catalytic reaction to a noncatalytic chemical transformation is established in this way, the catalytic mechanism can be elucidated on the basis of analogy. Moreover, if the relationships are linear, the interpretation of their slopes yields additional information. 

Focusing on the shorter time-scale component, the characteristic recovery time shows a strong dependence on the pump-laser power or, equivalently, the number of electrons injected The higher the power, the shorter the recovery time. Similar behavior has been noted by Ford et al. [40]. If 1>app is plotted versus the number of electrons injected per particle (Fig. 4), a linear correlation is obtained. In other words, the reaction appears to be first order in electrons (and first order in the oxidized dye). What does this mean mechanistically The simplest interpretation—sketched in Scheme 1—is that the injected electrons are free to return to any available dye molecule, not just the molecule from which they originated. This would be the case if injected electrons avoided surface states (at least at these shorter times) and remained in the conduction band. (Notably, the power-dependent kinetic behavior persists in a rigid glass matrix. Consequently, possible... 

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