3D-QSAR and Molecular Mechanics Study for the Differences in the Azole Activity against Yeastlike and Filamentous Fungi and Their Relation to P450DM Inhibition. 1. 3-Substituted-4(3H)-quinazolinones Filip Fratev* and Emilio Benfenati Istituto di Ricerche Farmacologiche “Mario Negri”, Via Eritrea, 62, 20157 Milano, Italy Received November 22, 2004 A combination between 3D-QSAR and molecular mechanics (MM)-docking study was used as a tool to detail and model the mechanism of action of 46 antifungal azoles. Two methods of alignment of the ligands were performed: (i) alignment of the main skeleton without substituents and (ii) alignment of a defined substructure. The best model is characterized by q 2 with the values of 0.70 for yeastlike (yeast), 0.66 for filamentous fungi, and 0.70 for the selectivity against filamentous fungi. 3D-QSAR regression maps derived from six models were used to identify the regions responsible for the differences in the compounds activity against yeast and filamentous fungi. The binding energy of the important substructures (Local Binding Energy-LBE) and its standard deviation were calculated in order to demonstrate quantitatively the contribution of substituents reflecting the diversity of the antifungal activity. The comparisons of these results with the same regions of the contour maps indicated a good correspondence between the 3D-QSAR and MM (LBE) approaches allowing association between the maps and the participating residues in the active sites of P450DM of C. albicans and A. fumigatus. The π-π interactions of two or more aromatic groups of the ligands with Phe228 and Tyr132 prove to be most important for the differences in activity against C. albicans. In A. fumigatus there was a better occupation of the inner central I-spiral in the areas around the heme. For the activity against A. fumigatus the π-π interactions of aromatic groups of the compounds with Phe509, Phe228, and Tyr132 are significant for the activity. INTRODUCTION Yeastlike (yeast) and filamentous fungi cause between 80% and 90% of the fungal infections that have been treated with azole compounds for many years. 1-3 There are many reports of systematic searches for new ligands. 4-7 However, the difficulties in these studies are related to the design of compounds with high activity against filamentous fungi. 8,9 The mechanism of action of the triazole antifungals involves the inhibition of the natural substrate lanosterol binding to P450DM (CYP51) through coordinating their triazole N4 atom to the sixth coordination position of the heme iron atom. The differences in the residues of CYP51 of Candida albicans and Aspergillus fumigatus and their relation to the ligand-protein interactions 10,11 has been used to explain the selectivity of fluconazol and other agents to these fungi. 12,13 The 3D-models of Candida albicans CYP51 based on the homology models with X-ray template of other P450 members are available. 14-17 A number of 3D-QSAR and docking analysis was done 17-19 for a series of antifungal azoles with Candida albicans activity data, specifying some important ligand-enzymes interactions. In the present study, we focus on filamentous fungi (in particular Aspergillus fumigatus), the differences in the activity against yeast and filamentous fungi and their relation to the inhibition of CYP51. We used the combination of 3D-QSAR analysis and molecular mechanics binding energy calculation in the active site of Candida albicans and Aspergillus fumigatus to detail and model the differences in the azole-CYP51 complexes. Our methodology combines the computational approaches applied here. For this purpose we modified some methods and descriptors. The ligand-receptor binding energy is the descriptor normally utilized for correlation with biological activity. 20 In the present paper we transformed this formulation for the substructures of the ligands involved in the ligand-enzymes interactions, and we calculated their local binding energy (LBE). The “structure-based 3D-QSAR” approach is a common adopted combination of the 3D-QSAR and docking analy- sis. 21 The molecular mechanics optimization of the ligand- receptor complex after the preliminary docking procedure is often applied in this methodology and achieves more precision in the selection of the ligand conformation. 22 The next step is the compounds alignment using the obtained and optimized docking lowest energy conformers. However, when the experimental data are measured as a geometric means of “in vitro” values from different species (i.e. mix of various receptors data) this 3D-QSAR alignment is not applicable. In this study, we try to link and discuss below the combination between 3D-QSAR and MM-docking ap- proaches without the use of docking conformers for the classes of yeast and filamentous fungi. * Corresponding author phone: +39-02-39014499; fax: +39-02- 39001916; e-mail: fratev@marionegri.it. 634 J. Chem. Inf. Model. 2005, 45, 634-644 10.1021/ci0496494 CCC: $30.25 © 2005 American Chemical Society Published on Web 04/20/2005