Reference molecule molecular similarity measurements

A QSAR approach based on a set of methods that combines molecular shape similarity and commonality measures with other - molecular descriptors both to search for similarities among molecules and to build QSAR models [Hopfinger, 1980 Burke and Hopfinger, 1993], The term molecular shape similarity refers to molecular similarity on the basis of a comparison of three-dimensional molecular shapes represented by some property of the atoms composing the molecule, such as the van der Waals spheres. TTie molecular shape commonality is the measure of molecular similarity when conformational energy and molecular shape are simultaneously considered [Hopfinger and Burke, 1990]. 

With all of these new tools, it is no wonder that there has been an explosion of papers on photochemical dynamics, so much so that in this review we shall limit ourselves to those papers that have appeared over the last three years. Earlier reviews cover the work before this time, and the papers that are cited also give references to the earlier work. The papers that are covered are further limited to those that measure and discuss the detailed quantum state distribution of one or more of the photochemical fragments. Those papers that are limited to final product analysis are discussed only if the results bear directly upon the dynamics of the photochemical process. The review is organized so that molecules with similar chromo-phore groups are all discussed at the same time. This emphasizes the similarities and differences between these molecules. The discussion of the molecular systems begins after a brief discussion of some of the newer experimental techniques. In this review any earlier reviews that cover that molecule are cited along with the later papers on the subject. 

A powerful extension to the potential pharmacophore method has been developed, in which one of the points is forced to contain a special pharmacophore feature, as illustrated in figure 4. All the potential pharmacophores in the pharmacophore key must contain this feature, thus making it possible to reference the pharmacophoric shapes of the molecule relative to the special feature. This gives an internally referenced or relative measure of molecular similarity/diversity. The special feature can be assigned to any atom-type or site-point, or to special dummy atoms, such as those added as centroids of privileged substructures [7, 10]. With one of the points being reserved for this special feature, it would seem even more necessary to use the 4-point definition to capture enough of the... 

In systematic SAR analysis, molecular structure and similarity need to be represented and related to each other in a measurable form. Just like any molecular similarity approach, SAR analysis critically depends on molecular representations and the way similarity is measured. The nature of the chemical space representation determines the positions of the molecules in space and thus ultimately the shape of the activity landscape. Hence, SARs may differ considerably when changing chemical space and molecular representations. In this context, it becomes clear that one must discriminate between SAR features that reflect the fundamental nature of the underlying molecular structures as opposed to SAR features that are merely an artifact of the chosen chemical space representation. Consequently, activity cliffs can be viewed as either fundamental or descriptor- and metrics-dependent. The latter occur as a consequence of an inappropriate molecular representation or similarity metrics and can be smoothed out by choosing a more suitable representation, e.g., by considering activity-relevant physicochemical properties. By contrast, activity cliffs fundamental to the underlying SARs cannot be circumvented by changing the reference space. In this situation, molecules that should be recognized as... 

Tlie main assumption of this approach is that the shape of the molecule is closely related to the shape of the - binding site cavity and, as a consequence, to the biological activity. Therefore, a shape reference compound is chosen which represents the binding site cavity, and the similarity (or commonality) measured between the reference shape and the shape of other compounds is used to determine the biological activity of these compounds. As well as the shape similarity measures, other molecular descriptors such as those in - Hansch analysis can be used to evaluate the biological response. The MSA model is thus defined as ... 

As a quantitative performance measure of a similarity descriptor, the number of molecules from a database belonging to the same class as a reference molecule can be used. The enrichment factor is such a measure, and this takes the ratio of hits to the entire database size into account. It is defined as number of hits in the first percent of the database sorted according to the similarity measure, divided by the expected number of hits retrieved with a random selection. Intuitively, the enrichment factor describes how much is gained by using a similarity measure for selecting molecules compared to a random selection. For the design of diverse libraries, the detection of molecular classes is a necessary feature of the similarity measure. 

Relative descriptors are usually defined with respect to a reference structure. In some applications, this reference is an experimental conformation or a minimum energy conformer (a OD or ID model). The relative descriptors allow one to quantify the deviations from the desired structure and thus establish a measure of conformational stability.In applications relevant to molecular similarity, the reference structure can be another compound (e.g., a lead in drug design27) or a particular array of atoms (e.g., the pharmacophore ) against which any new molecule is compared. In this latter case, the analysis involves 2D or 3D models. 

In 1980, Carbo, Arnau and Leyda were the first to use molecular quantum similarity. As an anecdote, in the submitted version of the manuscript, the title was How far is one molecule from another After a reviewer s comment, this title was changed to How similar is one molecule to another The revised title has a much more obvious reference to similarity. In a sense, both titles are descriptive, because in that manuscript, the first degree of molecular similarity with a distance measure was presented. More precisely, a distance measure was introduced as... 

To choose the reference shape for MSA, each available conformation is used in turn as a reference to calculate the pairwise molecular similarity to all other conformations of all other molecules. The conformation of each molecule that has the highest overlap volume with the current reference is used as the similarity measure for that reference. Thus, given M conformations in the database, there will be M MSA parameters that describe the shapes of the compounds. In a 1994 study, the overlapped structures of four molecules were merged to define a reference shape. 

With respect to a reference shape T, the T-hull of a molecular body M is computed as the intersection of all rotated and translated versions of T, which contains M. T-hulls provide shape similarity measures for molecules and for their solvent accessible surfaces. T-hulls are also the basis for a shape quantization . ... 

Molecular emission is referred to as luminescence or fluorescence and sometimes phosphorescence. While atomic emission is generally instantaneous on a time scale that is sub-picoseconds, molecular emission can involve excited states with finite, lifetimes on the order of nanoseconds to seconds. Similar molecules can have quite different excited state lifetimes and thus it should be possible to use both emission wavelength and emission apparent lifetime to characterize molecules. The instrumental requirements will be different from measurements of emission, only in detail but not in principles, shared by all emission techniques. 

To continue the investigation, carbon detected proton T relaxation data were also collected and were used to calculate proton T relaxation times. Similarly, 19F T measurements were also made. The calculated relaxation values are shown above each peak of interest in Fig. 10.25. A substantial difference is evident in the proton T relaxation times across the API peaks in both carbon spectra. Due to spin diffusion, the protons can exchange their signals with each other even when separated by as much as tens of nanometers. Since a potential API-excipient interaction would act on the molecular scale, spin diffusion occurs between the API and excipient molecules, and the protons therefore show a single, uniform relaxation time regardless of whether they are on the API or the excipients. On the other hand, in the case of a physical mixture, the molecules of API and excipients are well separated spatially, and so no bulk spin diffusion can occur. Two unique proton relaxation rates are then expected, one for the API and another for the excipients. This is evident in the carbon spectrum of the physical mixture shown on the bottom of Fig. 10.25. Comparing this reference to the relaxation data for the formulation, it is readily apparent that the formulation exhibits essentially one proton T1 relaxation time across the carbon spectrum. This therefore demonstrates that there is indeed an interaction between the drug substance and the excipients in the formulation. 

The sizes determined in this work are the apparent molecular sizes and not necessarily the sizes of the asphaltene and maltene molecules at process conditions. Association efforts for asphaltene molecules have been observed for both vapor-phase osmometry molecular weight and viscosity measurements (14, 15). The sizes reported here were measured at 0.1 wt % in tetrahydrofuran at room temperature. Other solvent systems (chloroform, 5% methanol-chloroform, and 10% trichlorobenzene-chloroform) gave similar size distributions. Under these conditions, association effects should be minimized but may still be present. At process conditions (650-850°F and 5-30% asphaltene concentration in a maltene solvent), the asphaltene sizes may be smaller. However, for this work the apparent sizes determined can be meaningfully correlated with catalyst pore size distributions to give reasonable explanations of the observed differences in asphaltene and maltene process-abilities (vide infra). In addition, the relative size distributions of the six residua are useful in explaining the different processing severities required for the various stocks. Therefore, the apparent sizes determined here have some physical significance and will be referred to just as sizes. 

---