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Binding affinities at I 1 and I 2 Imidazoline Binding Sites (IBS) of a number of properly substituted imidazoline, oxazoline and pyrroline ligands were studied through an integrated modelling approach based on a coordinated application of 2D- (MGZ) and 3D-QSAR (CoMFA-and GRID-GOLPE) analyses and on the development of a quantitative pharmacophore (HypoGen). Congruent and significant cross-validated 2D and 3D correlations, having promising predictive ability, indicated that electrostatic and steric interactions differently modulate the binding affinities at I 1 /I 2 IBS. Stereoselective interactions of chiral a or β substituted imidazolines, leading to diverse I 1 /I 2 binding affinities and selectivities, were correctly predicted by the models. Slightly different pharmacophore features were detected by means of Hypogen for I 1 and I 2 -IBS ligands.

Interest in the inhibitors of type-B monoamine oxidase has grown in recent years, due to the evidence for multiple roles of one such agent (selegiline) in the pharmacological management of neurodegenerative disorders. A set of 130 reversible and selective inhibitors of MAO-B (including tetrazole, oxadiazolone, and oxadiazinone derivatives) were taken from the literature and subjected to a three-dimensional quantitative structure-activity relationship (3D-QSAR) study, using CoMFA and GOLPE procedures. The steric and lipophilic fields, alone and in combination, provided us with informative models and satisfactory predictions (q2 = 0.73). The validity of these models was checked against the 3D X-ray structure of human MAO-B. Flexible docking calculations, performed by using a new approach which took advantage from QXP and GRID computational tools, showed the diverse inhibitors to interact with MAO-B in a similar binding mode, irrespective of the heterocycle characterizing them. A significant trend of correlation was observed between estimated energies of the complexes and the experimental inhibition data.

The work describes the development of novel software supporting synchronous distant collaboration between scientists involved in drug discovery and development projects. The program allows to visualize and share data as well as to interact in real time using standard intranets and Internet resources. Direct visualization of 2D and 3D molecular structures is supported and original tools for facilitating remote discussion have been integrated. The software is multiplatform (MS-Windows, SGI-IRIX, Linux), allowing for a seamless integration of heterogeneous working environments. The project aims to support collaboration both within and between academic and industrial institutions. Since confidentiality is very important in some scenarios, special attention has been paid to security aspects. The article presents the research carried out to gather the requirements of collaborative software in the field of drug discovery and development and describes the features of the first fully functional prototype obtained. Real-world testing activities carried out on this prototype in order to guarantee its adequacy in diverse environments are also described and discussed.

Based on the results obtained with different automated computational approaches as applied to the study of eleven high-affinity agonists of the neuronal nicotine acetylcholine receptor (nAChR), belonging to different chemical classes, new relevant features were detected which complement the existing pharmacophores. Convergent results from DISCO (Distance Comparison), QXP (Quick Explore), Catalyst/HipHop, and MIPSIM (Molecular Interaction Potential Similarity) allowed us to identify and locate, in a well defined spatial arrangement, three geometrically independent key structural features: (i) a positively charged nitrogen atom for ionic or hydrogen bond interactions, (ii) a lone pair of the pyridine nitrogen or a specific lone pair of a carbonyl oxygen, as a hydrogen bond acceptor, and (iii) a centre of a hydrophobic area generally occupied by aliphatic cycles. The pharmacophore presented herein, along with predictive 2D and 3D QSAR models recently developed in our group, could represent valuable computational tools for the design of new nAChR agonists having therapeutical potential.

The authors regret that the Catalyst/Hiphop outcome has been erroneously reported, though this does not involve any change in the discussion of results and conclusions. On p. 867 Figure 5 is incorrect, the correct figure is given below: includegraphics10347f1.eps includegraphics10347f1b.eps