VolSurf

PETRA (calculation of physicochemical parameters) Molecular Networks GmbH, Nagelsbachstrasse 25, D-91052 Erlangen, Germany http //www.mol-net.de/ VolSurf Molecular Discovery Ltd., West Way House, Elms Parade, Oxford 0X2 9LL, UK http //www.moldiscovery.com/... 

Cruciani G, Pastor M and Guba W. VolSurf a new tool for the pharmacokinetic optimization of lead compounds. Eur J Pharm Sci 2000 11 Suppl 2 S29-39. 

With only few exceptions, most log P programs refer to the octanol-water system. Based on Rekker s fragmental constant approach, a log P calculation for aliphatic hydrocarbon-water partitioning has been reported [96]. Another more recent approach to alkane-water log P and log D is based on the program VolSurf [97]. It is believed that these values may offer a better predictor for uptake in the brain. 

A, B and V are constant for a given solute (Eig. 12.4 shows the value of A, 0.78, for atenolol). This means that the balance between intermolecular forces varies with the system investigated as would be expected from a careful reading of Section 12.1.1.3. This can also be demonstrated by using a completely different approach to factorize log P, i.e. a computational method based on molecular interaction fields [10]. Volsurf descriptors [11] have been used to calculate log P of neutral species both in n-octanol-water and in alkane-water [10]. 

Crudani, G., Crivori, P., Carrupt, P. A., Testa, B. Molecular fields in quantitative structure-permeation relationships the VolSurf approach. J. Mol. Struct. Theochem. 2000, 503, 17-30. 

One of the first studies to predict log P by using potential energy fields calculated using the GRID and CoMFA approaches was done by Kim [60]. The author investigated H, CH3 and H2O probes, and calculated the best models using the hydro-phobic probe H2O for relatively small series (20 or less compounds each) of furans, carbamates, pyridines and pyrazines. A similar study was performed by Waller [61] who predicted a small series of 24 polyhalogenated compounds. Recently, Caron and Ermondi [62] used a new version of Cruciani s software, VolSurf [63], to predict the octanol-water and alkane-water partition coefficients for 152 compounds with r = 0.77, q = 0.72, SDEP = 0.60 for octanol-water and r = 0.76, q = 0.71, SDEP = 0.85 for alkane-water. 

L-type calcium channels (voltage-gated calcium channels L-subtype) Similarity to Diltiazem and a second ligand. ZINC db ( 50 K commercially available subset screened but most filtered to achieve desired PK profile using VolSurf). SHOP similarity, and feature-presence filtering down to 36 compounds 7 hits 18 tested, active in a vasorelaxant assay and some had novel structures. [67]... 

VOLSURF A Tool for Drug ADME-properties Prediction... 

Thus, a molecule can be characterized in terms of its potential hydrogen bonding, polar, hydrophobic and ionic interactions in 3D space. The size and the spatial distribution of these molecular interaction contours is translated into a quantitative scheme, the VolSurf descriptors, without the need to align the molecules in 3D space [8, 9] (Fig. 17.1). 

Fig. 17.1. Multivariate characterization with VolSurf descriptors. Molecular Interaction Fields (MIF shaded areas) are computed from the 3D-molecular structure. MIFs are transformed in a table of descriptors, and statistical multivariate analysis is performed.

The molecular descriptors refer to the molecular size and shape, to the size and shape of hydrophilic and hydrophobic regions, and to the balance between them. Hydrogen bonding, amphiphilic moments, critical packing parameters are other useful descriptors. The VolSurf descriptors have been presented and explained in detail elsewhere [8]. The VolSurf descriptors encode physico-chemical properties and, therefore, allow both for a design in the physico-chemical property space in order to rationally modulate pharmacokinetic properties, and for establishing quantitative structure-property relationships (QSPR). 

In the following section, the calculation of the VolSurf parameters from GRID interaction energies will be explained and the physico-chemical relevance of these novel descriptors demonstrated by correlation with measured absorption/ distribution/metabolism/elimination (ADME) properties. The applications will be shown by correlating 3D molecular structures with Caco-2 cell permeabilities, thermodynamic solubilities and metabolic stabilities. Special emphasis will be placed on interpretation of the models by multivariate statistics, because a rational design to improve molecular properties is critically dependent on an understanding of how molecular features influence physico-chemical and ADME properties. 

The VolSurf method was used to produce molecular descriptors, and PLS discriminant analysis (DA) was applied. The statistical model showed two significant latent variables after cross-validation. The 2D PLS score model offers a discrimination between the permeable and less permeable compounds. When the spectrum color is active (Fig. 17.2), red points refer to high permeability, whereas blue points indicate low permeability. There is a region in the central part of the plot with both red and blue compounds. In this region, and in between the two continuous lines, the permeability prediction is less reliable. The permeability model... 

Fig. 17.2. PLS score plot for the VolSurf Caco-2 model. Light open circles represent penetrating compounds dark open circles represent nonpenetrating compounds. Filled circles represent the projection (prediction) of compounds in Table 17.1 in the Caco-2 model.

Cefadroxyl and cefaclor are beta-lactam antibiotics which show high affinity for the PepTl carrier system, whereas the other two beta-lactams, cephalotin and cef-metazole, are not recognized by PepTl protein and are not actively transported in the intestine. However, as the VolSurf Caco-2 model predicts that all the beta-lactams are nonpenetrating compounds, it is very probable that, as they rely only the diffusion mechanism, cefadroxyl and cefaclor will not cross the cell monolayer. 

The model interpretation is in good agreement with the known molecular factors influencing Caco-2 permeability. In addition - and this outlines the originality of the method - VolSurf allows the relevant 3D molecular properties to be quantified. Once the model is developed, as reported above, simple projection of the compound descriptors into it allows predictions to be made for new compounds. 

As such, VolSurf affords much structural information of use in designing compounds with optimal permeability profile, and in defining an ideal property space in similarity searches. 

The VolSurf approach was used to correlate the 3D molecular descriptors by utilizing the water solubilities for as many compounds as could be found. Although over 2000 solubility values were identified, many showed contradictory results (both low and high values published). Moreover, some of the estimations had not been made by the authors and the original reference was not reported, while others were simply wrong, having not been measured under the standard conditions required. From the 2000 compounds, about 850 were carefully selected in addi-... 

Fig. 17.3. Experimental versus calculated solubility from VolSurf model. Lower left part, poor solubility central part, medium solubility upper right part, high-solubility compounds.

The correlation was made using PLS analysis within the VolSurf software. The solubility was quantified via the —log[Soly]-values, where Soly was expressed in mol L 1 at 25°C. The quantitative PLS analysis resulted in a two-component model. The recalculated versus experimental PLS plot (Fig. 17.3) shows the correlation obtained. From the objects pattern, a differentiation between very poorly/ poorly/medium/highly/very highly soluble compounds was seen to be possible, though fine quantitative predictions were difficult to achieve. 

A simple protocol was used to build the compounds compounds were modeled with the corresponding net charges, after which 2D-3D structure conversion was carried out using the program Concord [21]. The 3D dataset obtained was submitted to the VolSurf program, and principal component analysis (PCA) was applied for chemometric interpretation. No metabolic stability information was applied to the model. 

Calculated molecular properties from 3D molecular fields of interaction energies are a novel approach to correlate 3D molecular structures with pharmacodynamic, pharmacokinetic and physico-chemical properties. The novel VolSurf descriptors quantitatively characterize size, shape, polarity, hydrophobicity and the balance between them. 

It is also important to remember that, in contrast to other methods, VolSurf can calculate descriptors for small, medium and large molecules, as well as for biopolymers such as DNA fragments, peptides and proteins. 

GRID and VolSurf are free programs available from the Internet at the site http //moldiscovery.com. The Almond program is a available from the Internet at www.moldiscovery.com. 

Cabrera et al. [50] modeled a set of 163 drugs using TOPS-MODE descriptors with a linear discriminant model to predict p-glycoprotein efflux. Model accuracy was 81% for the training set and 77.5% for a validation set of 40 molecules. A "combinatorial QSAR" approach was used by de Lima et al. [51] to test multiple model types (kNN, decision tree, binary QSAR, SVM) with multiple descriptor sets from various software packages (MolconnZ, Atom Pair, VoSurf, MOE) for the prediction of p-glycoprotein substrates for a dataset of 192 molecules. Best overall performance on a test set of 51 molecules was achieved with an SVM and AP or VolSurf descriptors (81% accuracy each). 

Percent renal clearance was modeled for a set of 130 compounds from the literature using partial least squares applied to 3-D VolSurf or 2-D Molconn-Z descriptors [74]. The model based on VolSurf descriptors gave the best prediction... 

Apart from pharmacophore-based approaches, a variety of methods were applied to decipher important ligand features of PXR activation. VolSurf descriptor-based partial least squares (PLS) regression-based models pointed toward amide responsive regions that implicated good acceptor abilities as key variables [33]. 

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