Molecular descriptor hydrogen-bonding donor atoms

Figure 5 Descriptor histograms and SE and SSE values from two different compound databases. Compared are distributions of descriptor values in a chemical (ACD) and pharmaceutical (MDDR) database. The top number in the upper part of each chart reports the SE value, and the number beneath is the SSE value. Descriptor abbreviations MW, molecular weight a don, number of hydrogen bond donor atoms b rotN, number of rotatable bonds in a molecule logP(o/w), logarithm of the octanol/water partition coefficient.

However, the CIMI/bc descriptors are relatively simplistic as they did not recognize differences between some important atom types (e.g., halogens). Based on the results of ARD approach, the octanol-water partition coefficient (log P), the molecular flexibility (number of rotatable bonds), the PSA, and the number of hydrogen bond donors were the most important descriptors in the model. None of the descriptors were significantly correlated with each other except log P and PSA for which the correlation was not high ( 0.5). The molecular weight was found to be the least significant descriptor in the model. 

Let SAd and SAa be the solvent accessible surface areas of hydrogen-bonding donors (d) and acceptors (a), respectively, and Qa the corresponding partial atomic charges, SASA the molecular solvent-accessible surface area the HB-CPSA descriptors are then defined as follows (note that the two different symbols encountered in the literature for some are considered as synonymous). 

These are simple molecular descriptors based on counting the defined elements of a compound. The most common chemical count descriptors are atom number A, bond number B, cyclomatic number C, -> hydrogen-bond acceptor number and -> hydrogen-bond donor number, -> distance-counting descriptors, -> path counts, walk counts. 

The Diverse Property-Derived method (DPD method) is based on the partitioning of six noncorrelated molecular descriptors and physico-chemical properties [Ashton, Jaye et al, 1996]. These are a lipophilicity descriptor (CLOGP), an electrotopological index calculated as normalized sum of the squares of the atomic electrotopological state indices, the number of hydrogen-bond acceptors (HBA), the number of hydrogen-bond donors (HBD), a flexibility index defined as the ratio of the —> Kier shape descriptors over k, and the aromatic density defined as the number of aromatic rings over the molecular volume (Table Cl). 

Fig. 9.1-7 Example of principle component analysis comparison of synthetic drugs and natural products. A set of 20 synthetic drugs, including the top 10 best-sellers in 2004, and 20 natural products was analyzed for nine molecular descriptors molecular weight, hydrophobicity (X log P or C log P), hydrogen-bond donors, hydrogen-bond acceptors, rotatable bonds, topological polar surface area [43], stereogenic centers, nitrogen atoms, oxygen atoms. PCA was used to reduce the nine-dimensional vectors to two-dimensional vectors, which were then replotted as shown. The first principal component accounts for 55.1% of the original information and the first two...

The descriptor uses readily calculable physicochemical properties from the topological structure. The descriptors used in this study were atomic weight, hydropho-bicity, molecular refractivity, atomic charge, polar surface area, hydrogen bond acceptors, and hydrogen bond donors. The authors note that Martin et al. [32] applied a similar approach for the design of diverse combinatorial libraries. 

In the above formula, D denotes that the summation goes over aU hydrogen donor surfaces, qo is the partial charge on H-bonding donor atoms, Sd is the solvent-accessible surface area of H-bonding donor atoms, and Stot is the total solvent-accessible molecular surface area. The electrostatic descriptors have intuitive interpretations. Their inclusion in QSAR models makes easy and clear analysis of the phenomenon under investigation. 

In actual applications of MSA, many different types of representations are utilized to compute molecular similarities [41, 52-54]. Johnson [55] has provided a detailed discussion of the manifold types of mathematical spaces and their associated representations. The information contained in the representations is usually in the form of molecular or chemical features called descriptors that are derived from the structural and chemical properties of molecules. Descriptors ate nominally classified as ID (one-dimensional), 2D, or 3D. ID descriptors are usually associated with whole molecule properties such as molecular weight, logP, solubility, number of hydrogen bond donors, nnmber of rotatable bonds, and so on. 2D descriptors are associated with the topological strnctnre of molecules as typically depicted in chemists drawings. Such depictions show the atoms, the bonds connecting them, and in some cases include stereochemical features, but they do not explicitly depict the 3D structures of molecules. 3D descriptors, as their name implies, are associated with the 3D structures of molecules. Todeschini and Consonni [56] have compiled an extensive reference containing many of the descriptors used in chemical informatics applications. 

For each molecule in these struetures, 131 molecular descriptors were calculated. These included simple atom, bond and group eounts, hydrogen bond donor and acceptor counts, topological indices, a variety of partitioned and charge weighted surface areas and deseriptors of molecular size, shape, polarity... 

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