4.1. 3D maps

A three dimensional map (3D map) may be viewed as a 3D matrix which contains attractive and repulsive forces between a chemical probe and a target molecule. A 3D map is an image of the target-probe molecular interaction, in which each pixel contains information about the cartesian coordinates x,y,z and a chemical property.

The amount of information contained in a 3D map is related to the interacting molecular partners. Sometimes visual inspection is not sufficient to extract useful information since a large amount of information is coded and hidden in the sign and magnitude of the grid node forces, in the position of the grid nodes, in the relationships between grid nodes and in other functional relationships.

Although 3D-QSAR models can be obtained from these 3D maps (CoMFA [6] or GOLPE [7] procedures), the usefulness of the models is limited by their difficult interpretation. Further problems arise because of alignment and molecular flexibility.

Specialized tools are required in order to facilitate the extraction of useful descriptors from 3D Molecular Interaction Field images and to link experimental observations with molecular structures.

4.2. From 3D maps to 2D descriptors

VolSurf is a computational procedure aimed to produce and to explore the physicochemical property space of a molecule starting from 3D interaction energy maps. The basic concept of VolSurf is to compress the information present in 3D maps into few quantitative numerical descriptors very simple to understand and to interpret.

Compression of information is made using image analysis software. Each 3D map is considered as 3D image, but the image compression process is made adding chemical knowledge. VolSurf realizes so by selecting the most appropriate descriptors and parameterization according to the type of the 3D map under study.

In the standard procedure, interaction fields with a water probe (OH2) and a hydrophobic probe (DRY) are calculated all around the target molecules as in the programme GRID. Furthermore, additional polar or charged probes can be used for extracting more specific information, according to the Target under investigation. A brief overview of the GRID programme is included in this Manual to highlight the GRID features used by VolSurf. However, other maps produced by different probes or by different molecular mechanics or semiempirical methods can be used. VolSurf has the nice advantage of producing descriptors using the 3D information embedded in any map. Not all the information can be transferred from 3D to 2D descriptors, but practical examples do exist showing that relevant information is extracted. Moreover, the VolSurf transformation is easy to understand, fast to compute, the descriptors have a clear chemical meaning and are lattice independent, and some of them can be projected back into the original 3D map from which they were obtained. VolSurf descriptors can be obtained for small, medium and large molecules, as well as for biopolymers such as DNA sequences, peptides and proteins.

4.3. Multivariate analysis of VolSurf descriptors

When a set of molecules is undergone to VolSurf, for all the molecules ofthe set several descriptors are produced, according to the number ofprobes.

Thereby, the User can easily handle the information obtained for the whole set by using the chemometric packages of VolSurf. In fact, VolSurf includessome valuable tools to enable a simple and straightforward chemical interpretation of the descriptor matrix.

Principal Component Analysis (PCA) and Partial Least Squares (PLS) are chemometric tools for extracting and rationalizing the information from any multivariate description of a biological system. Complexity reduction and data simplification are two of the most important features of such tools. PCA and PLS condense the overall information into two smaller matrixes, namely the score plot and the loading plot. Because the chemical interpretation of score and loading plots is simple and straightforward, PCA and PLS are usually preferred to other nonlinear methods.

A brief introduction of the statistical tools available in VolSurf programme is presented in Chapter 7.

4.4. References

1. S.Clementi, G.Cruciani, P.Fifi, D.Riganelli, R.Valigi, G.Musumarra. A New Set of Principal Properties for Heteroaromatics Obtained by GRID. Quant. Struct. Act. Relat., 15, 108-120 (1995).

2. W.Guba, G.Cruciani. Molecular Field-Derived Descriptors for the Multivariate Modeling of Pharmacokinetic Data. In: Molecular Modeling and Prediction of Bioactivity, Guntertofte and Jorgensen, eds. Kluwer, New york, p. 89-94 (2000).

3. G.Cruciani, M.Pastor, S.Clementi. Handling Information from 3D GRID Maps for QSAR Studies. In: Molecular Modeling and Prediction of Bioactivity, Guntertofte and Jorgensen, eds. Kluwer, New york, p. 73-83 (2000).

4. R.Mannhold, G.Cruciani, H.Weber, H.Lemoine, A.Derix, C.Weichel, M.Clementi. 6-Substituted Benzopyrans as Potassium Channel Activators: Synthesis, Vasodilator Properties and Multivariate Analysis. J.Med.Chem., 42, 981-991 (1999).

5. G.Cruciani, M.Pastor, W.Guba. VolSurf, a new tool for the pharmacokinetic optimization of lead compounds. Europ.J.Pharm.Sci. 11, S29 - S39 (2000).

6. R.D.Cramer, D.E.Patterson, J.D.Bunce. Comparative Molecular Field Analysis (CoMFA). 1. Effect of Shape on Binding of Steroids to Carrier Proteins. J.Am.Chem.Soc., 110, 5959-5967 (1988).

7. M.Baroni, G.Costantino, G.Cruciani, D.Riganelli, R.Valigi, S.Clementi. Generating Optimal Linear PLS Estimations (GOLPE): an Advanced Chemometric Tool for Handling 3D-QSAR Problems. Quant.Struct.-Act.Relat., 12, 9-20 (1993).

8. P.J.Goodford. A Computational Procedure for Determining Energetically Favorable Binding Sites on Biologically Important Macromolecules. J.Med.Chem., 28, 849-857 (1985).

9. GRID 22 - Molecular Discovery Ltd. - http://www.moldiscovery.com

10. K.J.Miller. Additivity Methods in Molecular Polarizability. J.Am.Chem.Soc. 112, 8533-8542, (1990).