VolSurf calculation

VolSurf—calculate ADME properties and create predictive ADME models Available at ... 

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/... 

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]. 

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. 

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. 

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.

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. 

This procedure led to a predictive 4 component PLS model for 72 VolSurf descriptors and 51 thrombin inhibitors. A crossvalidated r2(cv) value of 0.599 after leave-one-out crossvalidation and a conventional r2 value of 0.812 were obtained. Statistical validation using leave-two-out and leave-multiple-groups-out crossvalidation procedures underscores the significance of the final model. The graph of experimental versus calculated log(ESA) permeability values is shown in Figure 8 on the left. The overall model quality corresponds to the model reported by Sugano etal. (2000). 

Alternatively, calculated molecular properties from 3D molecular fields of interaction energies represent a valuable approach to correlate 3 D molecular structures with physicochemical and pharmacodynamic properties. In contrast, their use in correlations with pharmacokinetic properties is still poorly explored and exploited. The rather new VolSurf approach [5-7] is able to compress the relevant information present in 3D maps into a few descriptors characterized by the simplicity of... 

Does the above described complexity allow one to reliably predict thermodynamic solubility for drug candidates While we think that this is impossible at present, we believe it is realistic to make compound rankings for solubility behavior, provided that the model used is trained appropriately. VolSurf offers a solubility model developed with controlled literature data and in-house solubility data. Although the solubility error in the prediction phase can be evaluated in 0.7 log units (not suitable to rank the solubility of very similar compounds), the model can still be valid to filter compounds with calculated solubility below a certain threshold. 

Figure 8.3. Plot of calculated versus experimental —logS values forthe 1028 training set molecules used for building the VolSurf solubility library model (grey dots). Projections of the predictions forthe 105 compounds of the test set are shown as black dots.

On the basis of the above considerations we used a test set of 105 compounds for external validation of the VolSurf model. Test set compounds are listed together with their experimental and calculated aqueous solubility values in Table 8.2. Projection of the test set predictions into the VolSurf training set model is documented in Fig. 8.3 the SDEP (standard deviation of the error of prediction) value amounts to 0.99. The black dots nicely prove that the majority of the 105 test set structures were well predicted. 

LogP has been introduced as an additional descriptor in the new release of VolSurf A training set of 7871 diverse chemical structures was used to build a linear equation to calculate the logP values by fitting the structures with the other VolSurf descriptors. Using a five-component PLS regression, statistics give an r = 0.82, a = 0.82, and a SDEC [13] value = 0.74. The structures and data stem from Hansch et al. [18]. 

It is extremely difficult to find compounds with experimental VD equivalent to those collected by Lombardo. We could detect only 10 compounds, which were in turn used as test set for external validation of the VolSurf library model. Test set compounds are listed together with their experimental and calculated VD values in Table 8.4 the projection of their predictions is plotted in Figure 8.5 (filled dots) the SDEP value amounts to 0.53. 

Keseru [35] used literature data on 55 compounds to train a QSAR model based on a number of calculated descriptors. Five descriptors were used clogP, calculated molar refractivity (CMR), partial negative surface area, and the VolSurf W2 (polarizability) and D3 (hydrophobicity) descriptors. A model of acceptable quality was obtained (f = 0.94, SSE = 0.82) and tested on a 13 compound holdout set (r2 = 0.56, SSE = 0.98). An HQSAR model was then created that made use of 2D fragment fingerprints (threshold hERG IC50 = lpM). The best HQSAR model was validated on a holdout set of 13 compounds (f = 0.81, SSE = 0.67). 

VolSurf descriptors, such as G-WHIM and GRIND, encode information present in molecular interactionfields (MIF) calculated by the GRID force field parametrization [Grivori, Gruciani et al, 2000 Crudani, Grivori et al, 2000 Grudani, Pastor et al, 2000 Mannhold, Berellini et al, 2006]. 

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