Molecular based descriptors

Table 1 Calculation of some molecular-based descriptors for BOA, DIMBOA and MBOA. Physicochemical descriptor like logP (partition coefficient between octanol and water) constitutional descriptors like the number of a specified atoms or bonds (number of carbons, hydrogens, oxygens, nitrogens, single and aromatic bonds, the total number of atoms and bonds) and molecular weight quantum-mechanical descriptors like HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital).

A particularly good selection of physical properties may be spectra, because they are known to depend strongly on the chemical structure. In fact, different types of spectra carry different kinds of structural information, NMR spectra characterize individual carbon atoms in their molecular environment. They therefore correspond quite closely to fragment-based descriptors, as underlined by the success of approaches to predict NMR spectra by fragment codes (see Section 10.2.3). 

C, E E Hodgkin and Richards W G 1993. The Utilisation of Gaussian Functions for the Rapid nation of Molecular Similarity. Journal of Chemical Information and Computer Science 32 188-192. C and I D Kuntz 1995, Investigating the Extension of Pairwise Distance Pharmacophore sures to Triplet-based Descriptors, Journal of Computer-Aided Molecular Design 9 373-379. 

Purdy [91] used the technique to predict the carcinogenicity of organic chemicals in rodents, although his model was based on physicochemical and molecular orbital-based descriptors as well as on substructural features and it used only a relatively small number of compounds. His decision tree, which was manual rather than computer based, was trained on 306 compounds and tested on 301 different compounds it achieved 96% correct classification for the training set and 90% correct classification for the test set. 

We describe the molecularity with the familiar Latin-based descriptors uni = 1, bi = 2 and tri = 3. 

In this chapter, the genesis of SMILES-based descriptors (as well as perspectives of utilization of these characteristics for QSPR/QSAR analyses) is discussed. We concluded that in fact the SMILES-based optimal descriptors are derivatives of the graph-based optimal descriptors. In fact the SMILES-based descriptors are calculated with scheme that is similar to the well-known additive scheme (Zinkevich et al., 2004), but instead of contributions for the molecular fragments (chemical elements, different kinds of cycles, covalent bonds, etc.) contributions for the SMILES fragments (c, C, n, N, Cl, Br, =,, etc.) are using. 

Property-based descriptors, lipophilicity, molecular flexibility, PSA, and number of hydrogen-bond donors are the main parameters influencing the BBB permeability of compounds. 

Motoc, L, Marshall, G.R. Molecular shape descriptors. 2. Quantitative stmcture-activity relationships based upon three-dimensional molecular shape descriptor. Z. Naturforsch. 1985, 40a, 1114-1120. 

Fig. 14.5 Computation of VolSurf descriptors [155, 156] derived from GRID molecular interaction fields. Interactions of the example molecule with a water and dry probe at different contour levels are used to compute a vector of 72 volume-, size- and surface-based descriptors.

BB. Most molecule-based descriptors, such as logP, PSA, and molecular electronic properties, were used to construct models with a variety of statistical tools. The best performing models can approach the limit of experimental error, which was estimated to be 0.3 log units. 

Some of the earliest QSAR studies on CYPs were performed by Basak (257), Murray (258), and Marshall (205). Gao et al. (259) explored the influence of electronic parameters of CYP substrates in 1996. The findings of Basak that electronic terms would cancel out have been proven wrong by many research papers published in the following decades. Tyrakowska et al. (260) indicated via QSARs based on calculated molecular orbital descriptors that the cat (maximum velocity converted per nmol of P450 per min) for CYP catalyzed C4-hydroxylation rates of aniline derivatives of different species (rats, rabbit, mice, and human) are closely related to the highest occupied molecular orbital energy (EHOMo)> r - 0-97. Several reviews published by Lewis et al. (212,216,228,261-265) and Ekins (240) should also be mentioned. 

Table 13.1 Top section The mean value of descriptors. Model PC uses physicochemical molecular weight, calculated LogP and target hit based descriptors. Bottom section Sensitivity and rate for compounds originating from different specificity of promiscuous models applied to the disease areas. Middle section Sensitivity and drugs set. Model FP uses fingerprint based specificity of promiscuous models applied to descriptors. Model PC uses physicochemical the test set. Model FP uses fingerprint based based descriptors.

This section reviews the molecular shape descriptors developed by Amoore, Allinger, Simon et al. and Testa and Purcell. The illustrative examples discussed refer to the odour similarity and cardiotoxic aglycones. One has stressed the methods based on the reference structure because, correctly formulated, these methods seem to offer promising perspectives to model the steric effects in biological systems. Finally, a short discussion of possible connections between steric and other substituent constants (relevant in the context of multicollinearity in QSAR) is included. 

Nowadays, more than 4000 types of descriptors are known.17 There exist different ways to classify them. With respect to the type of molecular representation used for their calculations—chemical formula, molecular graph, or spatial positions of atoms—one speaks about ID, 2D, and 3D descriptors, respectively. Descriptors can be global (describing the molecule as a whole) and local (only selected parts are considered). One could distinguish information-based descriptors, which tend to code the information stored in molecular structures, and knowledge-based (or semiempir-ical) descriptors issued from the consideration of the mechanism of action. Most of those descriptors can be obtained with the DRAGON, CODESSA PRO, and ISIDA programs. 

Schuffenhauer et al. have used Similog keys in molecular complexity studies,1301 and other groups have used pharmacophore-based descriptors.1281... 

The first application of a surface-based pharmacophore correlation vector was reported by Stiefl and Baumann in 2003 [18] with the MaP (mapping property distributions of molecular surfaces) descriptor. They applied their MaP descriptor for QSAR applications. To our knowledge, an application of this descriptor to similarity searching has not been reported. 

The primary supposition of any toxicological QSAR is that the potency of a compound is dependent upon its molecular structure, which is typically quantified by chemical properties (Schultz et al., 2002). Chemical descriptors include a variety of types, including atom, substituent, and molecular parameters. The most transparent of these are the molecular-based empirical and quantum chemical descriptors. Empirical descriptors are measured descriptors and include physicochemical properties such as hydrophobicity (Dearden, 1990). Quantum chemical properties are theoretical descriptors and include charge and energy values (Karelson et al., 1996). Physicochemical and quantum chemical descriptors are for the most part easily interpretable with regard to how that property may be related to toxicity. The classic example of this, the partitioning of a toxicant between aqueous and lipid phases, has been used as a measure of hydrophobicity for over a century (Livingstone, 2000). 

Analog-filtering procedure was applied, based on the molecular physicochemical descriptors and optimum property ranges calculated for the set of known HIV PR inhibitors (Table 4.1), which permitted the selection of 100 most diverse cyclic urea analogs with suitable molecular properties. 

Bodor and Huang correlated the octanol/water partition coefficient, Po/w (unitless) at 298 K for a set of 302 compounds with a set of 58 descriptors to obtain Eq. [49]. These parameters include seven QM based descriptors that were calculated with the AMI method. The dipole moment is p(D) Qo and Qn are the square roots of the sum of the squares of charges on the O and N atoms, respectively. The parameter Qon is the sum of absolute values of charges on the O and N atoms, and ABSQ is the sum of the absolute values of the charges on all atoms. In addition to these QM descriptors, the surface area, A (A ), and the ovality, O, were calculated from the QM-optimized geometry. The ovality is defined by actual area/area as a sphere, O = A/[4ti(3V/ 4ti) ]. The molecular mass, M, and two indicator variables, Ngik and Nq, for alkanes and carbon atoms, respectively, were also employed. 

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