Molecular surface descriptors

Different physical properties and molecular models have been used to define the molecular surface the most common are reported below together with the descriptors proposed as measures of surface areas and molecular volume (- volume descriptors). Molecular surface area and volume are parameters of molecules that are very important in understanding their structure and chemical behaviour such as their ability to bind ligands and other molecules. An analysis of molecular surface shape is also an important tool in QSAR and - drug design-, in particular, both - molecular shape analysis and - Mezey 3D shape analysis were developed to search for similarities among molecules, based on their molecular shape. 

WHIM descriptors, GETAWAYdescriptors, EVA descriptors, GRIND descriptors, VolSutf descriptors, quantum-chemical descriptors, molecular transforms, charge descriptors. Charged Partial Surface Area descriptors, delocalization degree indices, chirality descriptors, hydrogen-bonding descriptors, molecular surface, combined descriptors, and symmetry descriptors. 

The MEP at the molecular surface has been used for many QSAR and QSPR applications. Quantum mechanically calculated MEPs are more detailed and accurate at the important areas of the surface than those derived from net atomic charges and are therefore usually preferable [Ij. However, any of the techniques based on MEPs calculated from net atomic charges can be used for full quantum mechanical calculations, and vice versa. The best-known descriptors based on the statistics of the MEP at the molecular surface are those introduced by Murray and Politzer [44]. These were originally formulated for DFT calculations using an isodensity surface. They have also been used very extensively with semi-empirical MO techniques and solvent-accessible surfaces [1, 2]. The charged polar surface area (CPSA) descriptors proposed by Stanton and Jurs [45] are also based on charges derived from semi-empirical MO calculations. 

D descriptors), the 3D structure, or the molecular surface (3D descriptors) of a structure. Which kind of descriptors should or can be used is primarily dependent on the si2e of the data set to be studied and the required accuracy for example, if a QSPR model is intended to be used for hundreds of thousands of compounds, a somehow reduced accuracy will probably be acceptable for the benefit of short processing times. Chapter 8 gives a detailed introduction to the calculation methods for molecular descriptors. 

Methods of analyzing the diversity of the selected subset ensure that an appropriate chemical space is covered. Descriptors such as fingerprints, and 2D, and 3D descriptors, as well as molecular surface properties, which can be... 

Values for hydrocarbons other than alkynes and alkadienes can be predicted by the method of Suzuki et al. The best model includes the descriptors T, P, the parachor, the molecular surface area (which can be approximated by the van der Waals area), and the zero-order connectivity index. Excluding alkynes and alkadienes, a studv for 58 alkanes, aromatics, and cycloalkanes showed an average deviation from experimental values of about 30 K. 

Bravi G, Wikel JH. Application of MS-WHIM descriptors 1. Introduction of new molecular surface properties and 2. Prediction of binding affinity data. 

PSA is also used as H-bond descriptor to predict various properties of chemicals and drugs. PSA is defined as that part of a molecular surface that arises from oxygen and nitrogen atoms, and also the hydrogens attached to them. Applications of PSA as a QSAR descriptor in correlations with permeability and absorption were carried out first by Van de Waterbeemd et al. [30] and Palm et al. [31]. Clark [32-34] developed this further. Chapter 5 in this book is completely devoted to... 

Haeberlein, M., Brinck, T. Prediction of water-octanol partition coefficients using theoretical descriptors derived from the molecular surface area and the electrostatic potential. J. Chem. Soc. 

In addition, the calculation of many different ID, 2D and 3D descriptors is possible using a range of commercially available software packages, such as Sybyl, Cerius2, Tsar, Molconn-Z and Hybot. Several new descriptor sets are based on quantification of 3D molecular surface properties, and these have been explored for the prediction of, e.g., Caco-2 permeability and oral absorption. It is pointed out here that a number of these new descriptors are strongly correlated to the more traditional physico-chemical properties. 

In conclusion, descriptors of molecular surface area, such as PSA, NPSA and PTSAs, are important molecular descriptors influencing different properties such... 

On the other hand, there is considerable interest to quantify the similarities between different molecules, in particular, in pharmacology [7], For instance, the search for a new drug may include a comparative analysis of an active molecule with a large molecular library by using combinatorial chemistry. A computational comparison based on the similarity of empirical data (structural parameters, molecular surfaces, thermodynamical data, etc.) is often used as a prescreening. Because the DFT reactivity descriptors measure intrinsic properties of a molecular moiety, they are in fact chemical fingerprints of molecules. These descriptors establish a useful scale of similarity between the members of a large molecular family (see in particular Chapter 15) [18-21],... 

P-gp substrate 22 substrates and 31 nonsubstrates 115 substrates and 157 nonsubstrates 61% substrates and 81% nonsubstrates correctly predicted. Overall accuracy 72.4% Transport Caco-2 cell line Size, shape (e.g. molecular surface and glo-bularity), hydrophilic and H-bonding related descriptors correlated positively with P-gp activity, log P0/w not significant [54]... 

The threshold value of 360 in Eq. 64 demonstrated that larger molecular weight produces lower permeation rates, but the effect takes effect only when the molecular weight is larger than 360. Since MW correlates well with molecular sizes, other similar descriptors such as molecular volume or molecular surface were also tried to be correlated with log BB but out of these the best model remained Eq. 64. 

We can also look at other literature datasets to gain an idea of how similar our compounds are to compounds for which QMPRPlus gives very good predictions. We have looked at four simple descriptors molecular weight, topological polar surface area [40], chemical complexity [41], and rotatable bond count, using John Bradshaw s... 

The major hurdle to overcome in the development of 3D-QSAR models using steric, electrostatic, or lipophilic fields is related to both conformation selection and subsequent suitable overlay (alignment) of compounds. Therefore, it is of some interest to provide a conformation-ally sensitive lipophilicity descriptor that is alignment-independent. In this chapter we describe the derivation and parametrization of a new descriptor called 3D-LogP and demonstrate both its conformational sensitivity and its effectiveness in QSAR analysis. The 3D-LogP descriptor provides such a representation in the form of a rapidly computable description of the local lipophilicity at points on a user-defined molecular surface. 

The Molecular Surface (MS) first introduced by Richards (19) was chosen as the 3D space where the MLP will be calculated. MS specifically refers to a molecular envelope accessible by a solvent molecule. Unlike the solvent accessible surface (20), which is defined by the center of a spherical probe as it is rolled over a molecule, the MS (19), or Connolly surface (21) is traced by the inwardfacing surface of the spherical probe (Fig. 2). The MS consists of three types of faces, namely contact, saddle, and concave reentrant, where the spherical probe touches molecule atoms at one, two, or three points, simultaneously. Calculation of molecular properties on the MS and integration of a function over the MS require a numerical representation of the MS as a manifold S(Mk, nk, dsk), where Mk, nk, dsk are, respectively, the coordinates, the normal vector, and the area of a small element of the MS. Among the published computational methods for a triangulated MS (22,23), the method proposed by Connolly (21,24) was used because it provides a numerical presentation of the MS as a collection of dot coordinates and outward normal vectors. In order to build the 3D-logP descriptor independent from the calculation parameters of the MS, the precision of the MS area computation was first estimated as a function of the point density and the probe radius parameters. When varying... 

The main idea of the 3D-LogP descriptor approach is to sample the molecular surface and then to sum the area of those points with similar MLP values. The 3D-LogP descriptor proposed here is a vector V with NBINS elements each element of which V, is the sum of the area of all surface elements whose MLP lies between two arbitrary discrete values. The number of bins to be used was chosen after experimentation with various values and 200 was found to be appropriate here, because it allowed the population of the bins with a significant number of area elements for both hydrophilic (MLP < 0) and hydrophobic (MLP > 0) surfaces. However, other values for NBINS may be more suitable in particular cases. In order to simplify things, in the following description it is... 

Three sets of molecular descriptors that can be computed from a molecular connection table are defined. The descriptors are based on the subdivision and classification of the molecular surface area according to atomic properties (such as contribution to logP, molar refractivity, and partial charge). The resulting 32 descriptors are shown (a) to be weakly correlated with each other (b) to encode many traditional molecular descriptors and (c) to be useful for QSAR, QSPAR, and compound classification. 

Key Words Biological activity molecular descriptor QSAR QSPR molecular surface area ... 

In the present work, we will use a relatively low level of theory to derive 32 weakly correlated molecular descriptors, each based on the subdivision and classification of the molecular surface area according to three fundamental properties contribution to ClogP, molar refractivity, and atomic partial charge. The resulting collection will be shown to have applicability in QSAR, QSPR, and compound classification. Moreover, the derived 32 descriptors linearly encode most of the information of a collection of traditional mathematical descriptors used in QSAR and QSPR. 

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