Three-dimensional quantitative structure-activity relationships of steroid aromatase inhibitors

Summary Inhibition of aromatase, a cytochrome P450 that converts androgens to estrogens, is relevant in the therapeutic control of breast cancer. We investigate this inhibition using a three-dimensional quantitative structure-activity relationship (3D QSAR) method known as Comparative Molecular Field Analysis, CoMFA [Cramer III, R.D. et al., J. Am. Chem. Soc., 110 (1988) 5959]. We analyzed the data for 50 steroid inhibitors [Numazawa, M. et al., J. Med. Chem., 37 (1994) 2198, and references cited therein] assayed against androstenedione on human placental microsomes. An initial CoMFA resulted in a three-component model for log(1/K_i), with an explained variance r² of 0.885, and a cross-validated q² of 0.673. Chemometric studies were performed using GOLPE [Baroni, M. et al., Quant. Struct.-Act. Relatsh., 12 (1993) 9]. The CoMFA/GOLPE model is discussed in terms of robustness, predictivity, explanatory power and simplicity. After randomized exclusion of 25 or 10 compounds (repeated 25 times), the q² for one component was 0.62 and 0.61, respectively, while r² was 0.674. We demonstrate that the predictive r² based on the mean activity (Y_m) of the training set is misleading, while the test set Y_m-based predictive r² index gives a more accurate estimate of external predictivity. Using CoMFA, the observed differences in aromatase inhibition among C6-substituted steroids are rationalized at the atomic level. The CoMFA fields are consistent with known, potent inhibitors of aromatase, not included in the model. When positioned in the same alignment, these compounds have distinct features that overlap with the steric and electrostatic fields obtained in the CoMFA model. The presence of two hydrophobic binding pockets near the aromatase active site is discussed: a steric bulk tolerant one, common for C4, C6-alpha and C7-alpha substitutents, and a smaller one at the C6-beta region.     

A comparative molecular field analysis of cytochrome P450 2A5 and 2A6 inhibitors

Structure-activity relationships of 23 P450 2A5 and 2A6 inhibitors were analysed using the CoMFA [1] and GOLPE/GRID with smart region definition (SRD) [2]. The predictive power of the resulting models was validated using five compounds not belonging to the model set. All models have high internal and external predictive power and resulting 3D-QSAR models are supporting each other. Both Sybyl and GOLPE highlight properties near lactone moiety to be important for 2A5 and 2A6 inhibition. Another important feature for pIC₅₀ was the size of the substituent in the 7-positon of coumarin. The models suggest that the 2A5 binding site is larger that that of 2A6 due to larger steric regions in the CoMFA coefficient maps and corresponding GOLPE maps. In addition, the maps reveal that 2A6 disfavours negative charge near the lactone moiety of coumarin.     

Receptor-based 3D QSAR analysis of estrogen receptor ligands – merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient (r ² = 0.617, q ² _LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained (r ² = 0.991, q ² _LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment (r ² = 0.951, q ² _LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.     

Development of a unique 3D interaction model of endogenous and synthetic peripheral benzodiazepine receptor ligands

Different classes of Peripheral-type Benzodiazepine Receptor (PBR) ligands were examined and common structural elements were detected and used to develop a rational binding model based on energetically allowed ligand conformations. Two lipophilic regions and one electrostatic interaction site are essential features for high affinity ligand binding, while a further lipophilic region plays an important modulator role. A comparative molecular field analysis, performed over 130 PBR ligands by means of the GRID/GOLPE methodology, led to a PLS model with both high fitting and predictive values (r² = 0.898, Q² = 0.761). The outcome from the 3D QSAR model and the GRID interaction fields computed on the putative endogenous PBR ligands DBI (Diazepam Binding Inhibitor) and TTN (Tetracontatetraneuropeptide) was used to identify the amino acids most probably involved in PBR binding. Three amino acids, bearing lipophilic side chains, were detected in DBI (Phe49, Leu47 and Met46) and in TTN (Phe33, Leu31 and Met30) as likely residues underlying receptor binding. Moreover, a qualitative comparison of the molecular electrostatic potentials of DBI, TTN and selected synthetic ligands indicated also similar electronic properties. Convergent results from the modeling studies of synthetic and endogenous ligands suggest a common binding mode to PBRs. This may help the rational design of new high affinity PBR ligands.     

Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors

The paper describes the construction, validation and application of a structure-based 3D QSAR model of novel acetylcholinesterase (AChE) inhibitors. Initial use was made of four X-ray structures of AChE complexed with small, non-specific inhibitors to create a model of the binding of recently developed aminopyridazine derivatives. Combined automated and manual docking methods were applied to dock the co-crystallized inhibitors into the binding pocket. Validation of the modelling process was achieved by comparing the predicted enzyme-bound conformation with the known conformation in the X-ray structure. The successful prediction of the binding conformation of the known inhibitors gave confidence that we could use our model to evaluate the binding conformation of the aminopyridazine compounds. The alignment of 42 aminopyridazine compounds derived by the docking procedure was taken as the basis for a 3D QSAR analysis applying the GRID/GOLPE method. A model of high quality was obtained using the GRID water probe, as confirmed by the cross-validation method (q² _LOO=0.937, q² _{L50% O}=0.910). The validated model, together with the information obtained from the calculated AChE-inhibitor complexes, were considered for the design of novel compounds. Seven designed inhibitors which were synthesized and tested were shown to be highly active. After performing our modelling study the X-ray structure of AChE complexed with donepezil, an inhibitor structurally related to the developed aminopyirdazines, has been made available. The good agreement found between the predicted binding conformation of the aminopyridazines and the one observed for donepezil in the crystal structure further supports our developed model.     

A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods

A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity.     

Development of biologically active compounds by combining 3D QSAR and structure-based design methods

One of the major challenges in computational approaches to drug design is the accurate prediction of the binding affinity of novel biomolecules. In the present study an automated procedure which combines docking and 3D-QSAR methods was applied to several drug targets. The developed receptor-based 3D-QSAR methodology was tested on several sets of ligands for which the three-dimensional structure of the target protein has been solved – namely estrogen receptor, acetylcholine esterase and protein-tyrosine-phosphatase 1B. The molecular alignments of the studied ligands were determined using the docking program AutoDock and were compared with the X-ray structures of the corresponding protein-ligand complexes. The automatically generated protein-based ligand alignment obtained was subsequently taken as basis for a comparative field analysis applying the GRID/GOLPE approach. Using GRID interaction fields and applying variable selection procedures, highly predictive models were obtained. It is expected that concepts from receptor-based 3D QSAR will be valuable tools for the analysis of high-throughput screening as well as virtual screening data     

3D-QSAR methods on the basis of ligand–receptor complexes. Application of COMBINE and GRID/GOLPE methodologies to a series of CYP1A2 ligands

Many heterocyclic amines (HCA) present in cooked food exert a genotoxic activity when they are metabolised (N-oxidated) by the human cytochrome P450 1A2 (CYP1A2h). In order to rationalize the observed differences in activity of this enzyme on a series of 12 HCA, 3D-QSAR methods were applied on the basis of models of HCA–CYP1A2h complexes. The CYP1A2h enzyme model has been previously reported and was built by homology modeling based on cytochrome P450 BM3. The complexes were automatically generated applying the AUTODOCK software and refined using AMBER. A COMBINE analysis on the complexes identified the most important enzyme–ligand interactions that account for the differences in activity within the series. A GRID/GOLPE analysis was then performed on just the ligands, in the conformations and orientations found in the modeled complexes. The results from both methods were concordant and confirmed the advantages of incorporating structural information from series of ligand–receptor complexes into 3D-QSAR methodologies.