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4-(Pyrimidin-4-yl)morpholines are privileged pharmacophores for PI3K and PIKKs inhibition by virtue of the morpholine oxygen, both forming the key hydrogen bonding interaction and conveying selectivity over the broader kinome. Key to the morpholine utility as a kinase hinge binder is its ability to adopt a coplanar conformation with an adjacent aromatic core favored by the morpholine nitrogen nonbonding pair of electrons interacting with the electron deficient pyrimidine π-system. Few selective morpholine replacements have been identified to date. Herein we describe the discovery of a potent non-nitrogen containing morpholine isostere with the ability to mimic this conformation and its application in a potent selective dual inhibitor of mTORC1 and mTORC2 ( 29b ).

Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.

We report the identification of a novel biaryl template for H(+)/K(+) ATPase inhibition. Evaluation of critical SAR features within the biaryl imidazole framework and the use of pharmacophore modelling against known imidazopyridine and azaindole templates suggested that the geometry of the molecule is key to achieving activity. Herein we present our work optimising the potency of the molecule through modifications and substitutions to each of the ring systems. In particular sub-micromolar potency is achieved with (4b) presumably through a proposed intramolecular hydrogen bond that ensures the required imidazole basic centre is appropriately located., (Copyright (c) 2009 Elsevier Ltd. All rights reserved.)

A systematic analysis of data generated in key in vitro assays within GSK has been undertaken to identify what impact a range of common substituents have on a range of ADMET parameters. These include; P450 1A2, 2C9, 2C19, 2D6 and 3A4 inhibition, hERG inhibition, phosphate buffer solubility and artificial membrane permeability. We do this by identifying all matched molecular pairs, differing by the replacement of a hydrogen atom with a list of predefined substituents. For each substituent we calculate the mean difference in the ADMET parameter for all the matched molecular pairs identified, making a statistical assessment of the difference, as well as assessing the diversity for each example to ensure that the results can be generalized. We also relate the change in activity observed for each substituent to differences in their molecular properties in an effort to identify any structural alerts.

Three field-based similarity methods are compared in retrospective virtual screening experiments. The methods are the CatShape module of CATALYST, ROCS, and an in-house program developed at the University of Sheffield called FBSS. The programs are used in both rigid and flexible searches carried out in the MDL Drug Data Report. UNITY 2D fingerprints are also used to provide a comparison with a more traditional approach to similarity searching, and similarity based on simple whole-molecule properties is used to provide a baseline for the more sophisticated searches. Overall, UNITY 2D fingerprints and ROCS with the chemical force field option gave comparable performance and were superior to the shape-only 3D methods. When the flexible methods were compared with the rigid methods, it was generally found that the flexible methods gave slightly better results than their respective rigid methods; however, the increased performance did not justify the additional computational cost required.

Optimization of a pyrrolidine-based template using structure-based design and physicochemical considerations has provided a development candidate 20b (3082) with submicromolar potency in the HCV replicon and good pharmacokinetic properties.

A growing body of evidence suggests that creatine (Cr) might exert protective effects in a variety of pathologies where oxidative stress plays a concausal etiologic role; furthermore, it has been recently reported that Cr displays direct antioxidant activity in a cell-free setting. However, at present, no research has been specifically aimed to directly test the antioxidant potential of Cr on oxidatively injured cultured cells. Here, the effects of Cr were studied using cultured human promonocytic (U937) and endothelial (HUVEC) cells, and murine myoblasts (C2C12) exposed to H(2)O(2), tert-butylhydroperoxide (tB-OOH) and, in the case of U937 cells, peroxynitrite. Cr (0.1-10 mM) attenuated the cytotoxic effects caused by the oxidants in all the cell lines; under our conditions, cytoprotection was invariably associated with elevation of the intracellular fraction of Cr but it seemed to be unrelated to the levels of Cr phosphate (CrP); Cr did not affect the activity of catalase (CAT) and glutathione peroxidase (GpX), but it prevented H(2)O(2)- or tB-OOH-induced consumption of the nonprotein sulfhydryl (NPSH) pool in U937 and HUVEC cells; mass spectrometry experiments showed that a 136 MW molecule, which is likely to represent an oxidation by-product of Cr, formed in reaction buffers containing Cr and H(2)O(2) as well as in cellular extracts from H(2)O(2)- or tB-OOH- treated Cr-preloaded U937 cells; finally, Cr cytoprotection appeared to be unrelated to chelation of Fe(2+). In conclusion, it is suggested that Cr exerts a mild, although significant, antioxidant activity in living cells, via a mechanism depending on direct scavenging of reactive oxygen (in particular hydroxyl radical) and nitrogen species.

Three commercially available pharmacophore generation programs, Catalyst/HipHop, DISCO and GASP, were compared on their ability to generate known pharmacophores deduced from protein-ligand complexes extracted from the Protein Data Bank. Five different protein families were included Thrombin, Cyclin Dependent Kinase 2, Dihydrofolate Reductase, HIV Reverse Transcriptase and Thermolysin. Target pharmacophores were defined through visual analysis of the data sets. The pharmacophore models produced were evaluated qualitatively through visual inspection and according to their ability to generate the target pharmacophores. Our results show that GASP and Catalyst outperformed DISCO at reproducing the five target pharmacophores.

The interaction of competitive type inhibitors with the active site of cytochrome P450 (CYP) 2C9 has been predicted using three- and four-dimensional quantitative structure activity relationship (3D-/4D-QSAR) models constructed using previously unreported and literature-derived data. 3D-QSAR pharmacophore models of the common structural features of CYP2C9 inhibitors were built using the program Catalyst and compared with 3D- and 4D-QSAR partial least-squares models, which use molecular surface-weighted holistic invariant molecular descriptors of the size and shape of inhibitors. The Catalyst models generated from multiple conformers of competitive inhibitors of CYP2C9 activities contained at least one hydrophobic and two hydrogen bond acceptor/donor regions. Catalyst model 1 was constructed with Ki(apparent) values for inhibitors of tolbutamide and diclofenac 4'-hydroxylation (n = 9). Catalyst model 2 was generated from literature Ki(apparent) values for (S)-warfarin 7-hydroxylation (n = 29), and Catalyst model 3 from literature IC50 values for tolbutamide 4-hydroxylation (n = 13). These three models illustrated correlation values of observed and predicted inhibition for CYP2C9 of r = 0.91, 0.89, and 0.71, respectively. Catalyst pharmacophores generated with Ki(apparent) values were validated by predicting the Ki(apparent) value of a test set of CYP2C9 inhibitors also derived from the literature (n = 14). Twelve of fourteen of these Ki(apparent) values were predicted to be within 1 log residual of the observed value using Catalyst model 1, whereas Catalyst model 2 predicted 10 of 14 Ki(apparent) values. The corresponding partial least-squares molecular surface-weighted holistic invariant molecular 3D- and 4D-QSAR models for all CYP2C9 data sets yielded predictable models as assessed using cross-validation. These 3D- and 4D-QSAR models of CYP inhibition will aid in future prediction of drug-drug interactions.

The recently proposed MS-WHIM indices, a set of theoretical descriptors containing information about size, shape and electrostatic distribution of a molecule, have been further investigated. The main objectives of this work were: (i) to confirm the descriptive power of MS-WHIM in modelling specific biological interactions, (ii) to analyse the dependence of MS-WHIM on the type of atomic charges used for computing electrostatic potential and (iii) to compare the performances of MS-WHIM with those provided by other global 3D molecular descriptors. The spatial autocorrelation of atomic and molecular surface properties were selected for comparison purposes. WHIM-based and autocorrelation-based vectors were calculated for two molecular sets from the literature, namely a series of 18 HIV-1 reverse transcriptase inhibitors and a set of 36 sulphonamide endothelin inhibitors. PLS was adopted to derive statistical predictive models that were validated by means of cross-validation. The reported results confirmed that MS-WHIM indices are able to provide meaningful statistical correlations with biological activity. MS-WHIM descriptors are sensitive to the type of partial atomic charges applied and improved models were obtained using more accurate charges. Moreover for both the datasets, MS-WHIM results, in terms of fitting and predictive power of PLS models, were superior to those from autocorrelation. Finally, the strengths/weaknesses of global 3D-QSAR descriptors over local CoMFA-like methods, as well as the main differences between WHIM-based and autocorrelation-based vectors, are discussed.

To gain a better understanding of the active site of cytochrome P-450 (CYP) 3A4, a three-dimensional-quantitative structure activity relationship model was constructed using the structures and K(m (apparent)) values of 38 substrates of human liver microsomal CYP3A4. This pharmacophore was built using the program Catalyst and consisted of four features: two hydrogen bond acceptors, one hydrogen bond donor, and one hydrophobic region. The pharmacophore demonstrated a fit value (r) of observed and expected K(m(apparent)) value of 0.67. The validity of the CYP3A4 substrate model was tested by twice permuting (randomizing) the activity values and substrate structures. The results of this validation procedure indicated that the original model was a significant representation of the features required of CYP3A4 substrates. The second validation method used the Catalyst model to predict the K(m(apparent)) values of a test set of structurally diverse substrates for CYP3A4 not included in the 38 molecules used to build the model. Two fitting algorithms included in this software were examined: fast fit and best fit. The fast fitting method resulted in predictions for all 12 substrates that were within 1 log unit for the residual [i.e., the difference between predicted and observed K(m(apparent))]. In contrast, the best fit algorithm poorly predicted the K(m (apparent)) values (i.e., residual >1 log unit) of 4 of 12 substrates. These poor fits with the best fit function suggest that the fast fit method within Catalyst is more representative of the observed K(m(apparent)) values for CYP3A4 substrates and enables good in silico prediction of this activity. A Catalyst common features pharmacophore was also constructed from three molecules known to activate their own metabolism included in the 38 molecules of the initial CYP3A4 model. This demonstrated that activators of CYP3A4 possess multiple hydrophobic regions that might correspond with a region in the active site away from the metabolic site.

Three- and four-dimensional quantitative structure activity relationship (3D/4D-QSAR) pharmacophore models of competitive inhibitors of CYP2D6 were constructed using data from our laboratory or the literature. The 3D-QSAR pharmacophore models of the common structural features of CYP2D6 inhibitors were built using the program Catalyst (Molecular Simulations, San Diego, CA, USA). These 3D-QSAR models were compared with 3D and 4D-QSAR partial least squares (PLS) models which were constructed using molecular surface-weighted holistic invariant molecular (MS-WHIM) descriptors of size and shape of inhibitors. The first Catalyst model was generated from multiple conformers of competitive inhibitors (n = 20) of CYP2D6 mediated bufurolol 1'-hydroxylation. This model demonstrated a correlation of observed and predicted Ki (apparent) values of r = 0.75. A second Catalyst model was constructed from literature derived Ki (apparent) values (n = 31) for the inhibition of CYP2D6. This model provided a correlation of observed and predicted inhibition for CYP2D6 of r = 0.91. Both Catalyst Ki pharmacophores were then validated by predicting the Ki (apparent) of a test set of known CYP2D6 inhibitors (n = 15). Ten out of 15 of these Ki (apparent) values were predicted to be within one log residual of the observed value using our CYP2D6 inhibitor model, while the literature model predicted nine out of 15 values. Similarly, 3D- and 4D-QSARs derived from PLS MS-WHIM for our dataset yielded predictable models as assessed using cross-validation. The corresponding cross-validated PLS MS-WHIM model for the literature dataset yielded a comparable 3D-QSAR and improved 4D-QSAR value. Such computational models will aid in future prediction of drug-drug interactions.

The program Catalyst was used to build three-dimensional quantitative structure activity relationship (3D-QSAR) pharmacophore models of the structural features common to competitive-type inhibitors of cytochrome P-450 (CYP) 3A4. These were compared with 3D- and four-dimensional (4D)-QSAR partial least-squares (PLS) models built using molecular surface-weighted holistic invariant molecular (MS-WHIM) descriptors for size and shape of the inhibitor. The Catalyst pharmacophore model generated from multiple conformers of competitive inhibitors of CYP3A4-mediated midazolam 1'-hydroxylation (n = 14) yielded a high correlation of observed and predicted Ki values of r = 0.91. Similarly, PLS MS-WHIM was used to produce 3D- and 4D-QSARs for this data set and produced models that were statistically predictable after cross-validation. Two additional Catalyst pharmacophores were constructed from literature Ki values (n = 32) derived from the inhibition of CYP3A-mediated cyclosporin A metabolism and IC50 data (n = 22) from the inhibition of CYP3A4-mediated quinine 3-hydroxylation. These Catalyst pharmacophores illustrated correlations of observed and predicted inhibition for CYP3A4 of r = 0.77 and 0.92, respectively. The corresponding 4D-QSARs generated by PLS MS-WHIM for these data sets were of comparable quality as judged by cross-validation. Both Ki pharmacophores generated with Catalyst were also validated by predicting the Ki(apparent) values of a test set of eight CYP3A4 inhibitors not included in either model. In seven of eight cases, the residuals of the predicted Ki(apparent) values were within 1 log unit of the observed values. The 3D- and 4D-QSAR models produced in this study suggest the utility of future in silico prediction of CYP3A4-mediated drug-drug interactions.

To begin to build an understanding of the interactions of CYP2B6 with substrates, two different 3-dimensional quantitative structure activity relationship (3D-QSAR) models were constructed using 16 substrates of B-lymphoblastoid expressed CYP2B6. A pharmacophore model was built using the program Catalyst, which was compared with a partial least-squares (PLS) model using molecular surface-weighted holistic invariant molecular (MS-WHIM) descriptors. The Catalyst model yielded a 3-dimensional model of the common structural features of CYP2B6 substrates, whereas PLS MS-WHIM generated a model based on statistical analyses of molecular descriptors for size and shape of the substrate. The pharmacophore model obtained with Catalyst consisted of three hydrophobes and one hydrogen bond acceptor region. The cross-validated PLS MS-WHIM model gave a good q2 value of 0.607. Size, positive electrostatic potential, hydrogen bonding acceptor capacity, and hydrophobicity were found to be the most relevant descriptors for the model. These models were then used to predict the Km (apparent) values of a test set of structurally diverse substrates for CYP2B6 not included in the model building, specifically lidocaine, amitriptyline, bupropion, arteether, and verapamil. Overall, both 3D-QSAR methods yielded satisfactory Km (apparent) value predictions for the majority of the molecules in the test set. However, PLS MS-WHIM was unable to reliably predict the Km (apparent) value for verapamil, whereas Catalyst did not predict the Km (apparent) value for lidocaine. In both of these cases the residual of the Km (apparent) value was greater than one log unit. The strengths and limitations of both of these 3D-QSAR approaches are discussed.

A series of non-peptide angiotensin II receptor antagonists was investigated with the aim of developing a 3D QSAR model using comparative molecular field analysis descriptors and approaches. The main goals of the study were dictated by an interest in methodologies and an understanding of the binding requirements to the AT1 receptor. Consistency with the previously derived activity models was always checked to contemporarily test the validity of the various hypotheses. The specific conformations chosen for the study, the procedures invoked to superimpose all structures, the conditions employed to generate steric and electrostatic field values and the various PCA/PLS runs are discussed in detail. The effect of experimental design techniques to select objects (molecules) and variables (descriptors) with respect to the predictive power of the QSAR models derived was especially analysed.

A computer model of dianthin 30, a type 1 ribosome-inactivating protein (RIP), is constructed by homology modeling using two known X-ray structures; a type 1 RIP, pokeweed antiviral protein (PAP), and chain A of a type 2 RIP, ricin. The 3D structure is refined by molecular dynamics and its binding site compared with those of PAP and ricin using molecular electrostatic potential mapping. The differences in the maps obtained clearly show how, despite the similarity of the topology of the binding site, differences in electrostatic potential can account for the experimentally observed differences in substrate recognition and binding. This demonstrates the potential of these techniques for guiding further experimental analyses.

With the aim of explaining the influence of the structural changes on the biphenylic moiety on the activity, a series of N-[(heterobiaryl)methyl]imidazoles (I), constructed on the model of DuPont compounds by replacing either the central or terminal phenyl ring with a heteroaromatic one, such as furan, thiophene, thiazole, and pyridine, was synthesized. Compared to the reference DuPont compound (EXP-7711), all the heterobiaryl derivatives showed a reduced potency both in receptor binding (rat adrenal capsular membranes) and in the functional assay (angiotensin II-induced contraction of rabbit aorta strips). The lower activity was justified by the extensive molecular modeling studies, which took into consideration the conformational and electrostatic features of several heterobiaryl derivatives. On the basis of the results obtained, it was hypothesized that the central aromatic ring of the biarylic portion works as a spacer, orienting in the right way the terminal phenyl ring, whose electronic distribution is, instead, crucial to its fitting well with a lipophilic pocket at the receptor site.

A 3D QSAR methodology based on the combined use of conformational analysis and chemometrics was applied to perform a comparative analysis of the 3D conformational features of 13 nonpeptide angiotensin II receptor antagonists showing different levels of binding affinity. Conformational analysis by using a molecular mechanics MM2 method was carried out for each of these structures to obtain conformational minima. These minima were described by ten interatomic distances which define the relative spatial disposition of five significant atoms belonging to relevant functional groups present in all the 13 molecules. The structure-activity relationship between the interatomic distances and the biological activity was then assessed by using chemometric methods (cluster analysis, principal component analysis, classification methods). With our indirect approach based on the search for geometrical similarity it was possible, even though structural information on the receptor active site was lacking, to identify the 3D geometrical requirements for the binding affinity of nonpeptide angiotensin II receptor inhibitors.