Comparing pharmacophore models derived from crystallography and NMR ensembles

NMR and X-ray crystallography are the two most widely used methods for determining protein structures. Our previous study examining NMR versus X-Ray sources of protein conformations showed improved performance with NMR structures when used in our Multiple Protein Structures (MPS) method for receptor-based pharmacophores (Damm, Carlson, J Am Chem Soc 129:8225–8235, 2007). However, that work was based on a single test case, HIV-1 protease, because of the rich data available for that system. New data for more systems are available now, which calls for further examination of the effect of different sources of protein conformations. The MPS technique was applied to Growth factor receptor bound protein 2 (Grb2), Src SH2 homology domain (Src-SH2), FK506-binding protein 1A (FKBP12), and Peroxisome proliferator-activated receptor-γ (PPAR-γ). Pharmacophore models from both crystal and NMR ensembles were able to discriminate between high-affinity, low-affinity, and decoy molecules. As we found in our original study, NMR models showed optimal performance when all elements were used. The crystal models had more pharmacophore elements compared to their NMR counterparts. The crystal-based models exhibited optimum performance only when pharmacophore elements were dropped. This supports our assertion that the higher flexibility in NMR ensembles helps focus the models on the most essential interactions with the protein. Our studies suggest that the “extra” pharmacophore elements seen at the periphery in X-ray models arise as a result of decreased protein flexibility and make very little contribution to model performance.     

Use of catalyst pharmacophore models for screening of large combinatorial libraries

Using a data set comprised of literature compounds and structure-activity data for cyclin dependent kinase 2, several pharmacophore hypotheses were generated using Catalyst and evaluated using several criteria. The two best were used in retrospective searches of 10 three-dimensional databases containing over 1,000,000 proprietary compounds. The results were then analyzed for the efficiency with which the hypotheses performed in the areas of compound prioritization, library prioritization, and library design. First as a test of their compound prioritization capabilities, the pharmacophore models were used to search combinatorial libraries that were known to contain CDK active compounds to see if the pharmacophore models could selectively choose the active compounds over the inactive compounds. Second as a test of their utility in library design again the pharmacophore models were used to search the active combinatorial libraries to see if the key synthons were over represented in the hits from the pharmacophore searches. Finally as a test of their ability to prioritize combinatorial libraries, several inactive libraries were searched in addition to the active libraries in order to see if the active libraries produced significantly more hits than the inactive libraries. For this study the pharmacophore models showed potential in all three areas. For compound prioritization, one of the models selected active compounds at a rate nearly 11 times that of random compound selection though in other cases models missed the active compounds entirely. For library design, most of the key fragments were over represented in the hits from at least one of the searches though again some key fragments were missed. Finally, for library prioritization, the two active libraries both produced a significant number of hits with both pharmacophore models, whereas none of the eight inactive libraries produced a significant number of hits for both models.     

Antimitotic diterpenes from Erythropodium caribaeorum test pharmacophore models for microtubule stabilization

[structure: see text] Six new antimitotic diterpenes, 2-7, have been isolated from the Caribbean octocoral Erythropodium caribaeorum. Structural variations encountered in this group of natural products test recently proposed pharmacophore models for microtubule stabilizing compounds.     

Parallel screening and activity profiling with HIV protease inhibitor pharmacophore models

Parallel Screening has been introduced as an in silico method to predict the potential biological activities of compounds by screening them with a multitude of pharmacophore models. This study presents an early application example employing a Pipeline Pilot-based screening platform for automatic large-scale virtual activity profiling. An extensive set of HIV protease inhibitor pharmacophore models was used to screen a selection of active and inactive compounds. Furthermore, we aimed to address the usually critically eyed point, whether it is possible in a parallel screening system to differentiate between similar molecules/molecules acting on closely related proteins, and therefore we incorporated a collection of other protease inhibitors including aspartic protease inhibitors. The results of the screening experiments show a clear trend toward most extensive retrieval of known active ligands, followed by the general protease inhibitors and lowest recovery of inactive compounds.     

Surface-active substrates for Raman and luminescence analysis

This paper describes the development of active materials for optically enhanced Raman and fluorescence spectroscopy. The substrates for surface-enhanced Raman scattering investigated in this study involved silver-coated microspheres on glass plates. The effect of various experimental parameters, such as angle of incidence and excitation wavelength, were investigated. The substrate used for surface luminescence analysis consisted of a cellulose membrane coated with fumed silica microparticles, to enhance the sensitivity of analysis. Examples of analysis of benzo[a]pyrene and its derivatives are used to illustrate the efficacy of the analytical techniques.     

Influence of the conditions in pharmacophore generation, scoring, and 3D database search for chemical feature-based pharmacophore models: one application study of ETA- and ETB-selective antagonists

Using the commercial pharmacophore modeling suite Catalyst, we have studied the influence of the compare.scaledMultiBlobFeatureErrors . Catalyst parameter. The influence of this parameter has been studied in pharmacophore generation, hypothesis scoring, and database searching. This parameter, introduced in Catalyst 4.7, changed its default value in Catalyst 4.8, and it strongly influences the statistical quality of pharmacophore generation, scoring of the hypotheses, and database searching. Two different pharmacophore models have been constructed for the ETA and ETB receptor antagonists. Both models contain one positive ionizable, one negative ionizable, one hydrogen-bond acceptor, one hydrophobic aromatic, and one hydrophobic aliphatic feature. The models have been compared, and some differences in the position of the hydrogen-bond acceptor in the putative binding pocket have been highlighted.     

A virtual screening approach for thymidine monophosphate kinase inhibitors as antitubercular agents based on docking and pharmacophore models

Docking and pharmacophore screening tools were used to examine the binding of ligands in the active site of thymidine monophosphate kinase of Mycobacterium tuberculosis. Docking analysis of deoxythymidine monophosphate (dTMP) analogues suggests the role of hydrogen bonding and other weak interactions in enzyme selectivity. Water-mediated hydrogen-bond networks and a halogen-bond interaction seem to stabilize the molecular recognition. A pharmacophore model was developed using 20 dTMP analogues. The pharmacophoric features were complementary to the active site residues involved in the ligand recognition. On the basis of these studies, a composite screening model that combines the features from both the docking analysis and the pharmacophore model was developed. The composite model was validated by screening a database spiked with 47 known inhibitors. The model picked up 42 of these, giving an enrichment factor of 17. The validated model was used to successfully screen an in-house database of about 500,000 compounds. Subsequent screening with other filters gave 186 hit molecules.     

Predicting hiCE inhibitors based upon pharmacophore models derived from the receptor and its ligands

Human intestinal carboxyl esterase (hiCE) is a drug target for ameliorating irinotecan-induced diarrhea. By reducing irinotecan-induced diarrhea, hiCE inhibitors can improve the anti-cancer efficacy of irinotecan. To find effective hiCE inhibitors, a new virtual screening protocol that combines pharmacophore models derived from the hiCE structure and its ligands has been proposed. The hiCE structure has been constructed through homology techniques using hCES1’s crystal structure. The hiCE structure was optimized via molecular dynamics simulations with the most known active hiCE inhibitors docked into the structure. An optimized pharmacophore, derived from the receptor, was then generated. A ligand-based pharmacophore was also generated from a larger set of known hiCE inhibitors. The final hiCE inhibitor predictions were based upon the virtual screening hits from both ligand-based and receptor-based pharmacophore models. The hit rates from the ligand-based and receptor-based pharmacophore models are 88% and 86%, respectively. The final hit rate is 94%. The two models are highly consistent with one another (85%). This proves that both models are reliable.     

QSAR and pharmacophore analysis on amides against drug-resistant S. aureus

Considering the worth of developing new antibacterial agents against drug-resistant Stapylococcus aureus, the present study explores the structure-activity relationships analysis of N-(2-hydroxy-4(or 5)-nitro/aminophenyl)benzamide and phenylacetamide derivatives using classical QSAR and 3D-common-feature pharmacophore hypothese approaches. QSAR analysis revealed that the compounds possessing a methylene group between the phenyl and the carboxyamido moiety played a role for decreasing the activity. On the other side, substituent effects on position R1 was found important for the activity and holding a substituent possessing a minimum width property on this position like as alkyl groups enhanced the activity. Moreover, substituting position R3 with a group enhancing the electron-donor capability of the phenolic ring system increased the potency. 3D-common-feature pharmacophore approach considered that the conformational properties of the compounds were important for the activity against drug-resistant S. aureus and compounds possessing a benzamide moiety rather than phenylacetamide structure increased the activity. Furthermore, holding NO2 and OH groups on the phenyl ring attached to the benzamide moiety was important for improving the potency against drug-resistant S. aureus.     

Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation

We have developed a method that uses energetic analysis of structure-based fragment docking to elucidate key features for molecular recognition. This hybrid ligand- and structure-based methodology uses an atomic breakdown of the energy terms from the Glide XP scoring function to locate key pharmacophoric features from the docked fragments. First, we show that Glide accurately docks fragments, producing a root mean squared deviation (RMSD) of <1.0 Å for the top scoring pose to the native crystal structure. We then describe fragment-specific docking settings developed to generate poses that explore every pocket of a binding site while maintaining the docking accuracy of the top scoring pose. Next, we describe how the energy terms from the Glide XP scoring function are mapped onto pharmacophore sites from the docked fragments in order to rank their importance for binding. Using this energetic analysis we show that the most energetically favorable pharmacophore sites are consistent with features from known tight binding compounds. Finally, we describe a method to use the energetically selected sites from fragment docking to develop a pharmacophore hypothesis that can be used in virtual database screening to retrieve diverse compounds. We find that this method produces viable hypotheses that are consistent with known active compounds. In addition to retrieving diverse compounds that are not biased by the co-crystallized ligand, the method is able to recover known active compounds from a database screen, with an average enrichment of 8.1 in the top 1% of the database.     

Improved method for the diimide reduction of multiple bonds on solid-supported substrates

A mild and improved method for reducing multiple bonds on various resins with diimide is described. The simple procedure readily generates diimide from 2-nitrobenzenesulfonohydrazide and triethylamine at room temperature. A number of representative multiple bonds in various steric and electronic environments were examined, including polar double bonds such as carbonyl and azo, for ease and selectivity of reduction. A general trend of reactivity was identified which revealed, inter alia, that terminal olefins, 1,2-disubstituted olefins, electron-poor olefins, and terminal alkynes were the most easily reduced.     

The nicotinic pharmacophore: thermodynamics of the hydrogen-bonding complexation of nicotine, nornicotine, and models

The thermodynamics of the hydrogen-bonding complexation of the acetylcholine agonists nicotine and nornicotine and of model pyridines, pyrrolidines, and N-methylpyrrolidines has been measured in CCl(4) by FTIR spectrometry toward a reference hydrogen-bond donor, 4-fluorophenol. Various methods are devised for measuring separately the hydrogen-bond acceptor strength of each nitrogen of nicotine and nornicotine: variation of the stoichiometry of complexation; correlations with electrostatic potentials on nitrogens and with substituent constants in the series of 3-substituted pyridines, 2-substituted pyrrolidines, and 2-substituted N-methylpyrrolidines; and linear free energy relationships between 4-fluorophenol and hydrogen fluoride hydrogen-bonded complexes. It is consistently found that nicotine and nornicotine have two active hydrogen-bond acceptor sites, the pyridine and pyrrolidine nitrogens, and that ca. 90% (for nicotine) and 80% (for nornicotine) of the 1:1 hydrogen-bonded complexes are formed to the pyridine nitrogen, although the pyrrolidine nitrogen is the first protonation site of nicotine and nornicotine in water. The low hydrogen-bond basicity of the pyrrolidine nitrogen in nicotine is mainly explained by the inductive electron-withdrawing and steric effects of the 2-(3-pyridyl) substituent. The partition of the Gibbs energy of the isomerism of complexation (AH...Nsp(2) <==> AH...Nsp(3)) into enthalpic and entropic contributions shows that the selectivity in favor of the pyridine nitrogen is driven by entropy. It is important to recognize the bifunctionality of nicotine in hydrogen bonding for understanding its lipophilicity and molecular recognition in non protonic media. When monoprotonated on their sp(3) nitrogen, nicotine and nornicotine keep, through their sp(2) nitrogen, a significant hydrogen-bond basicity which is greater than that of the ester group of acetylcholine.     

Sampling and local models for multivariate image analysis

Local models are a very important concept for microscopic and macroscopic imaging. Different methods of sub-sampling a multivariate image are described both in general and for three examples. The need for sub-sampling and its influence on multivariate image analysis and visualization are studied. Examples from MRI (256 × 256), satellite imaging (7 × 512 × 512) and biofuel studies (6 × 512 × 512) are used to illustrate some of the principles involved.     

A genetic algorithm for flexible molecular overlay and pharmacophore elucidation

Summary A genetic algorithm (GA) has been developed for the superimposition of sets of flexible molecules. Molecules are represented by a chromosome that encodes angles of rotation about flexible bonds and mappings between hydrogen-bond donor proton, acceptor lone pair and ring centre features in pairs of molecules. The molecule with the smallest number of features in the data set is used as a template, onto which the remaining molecules are fitted with the objective of maximising structural equivalences. The fitness function of the GA is a weighted combination of: (i) the number and the similarity of the features that have been overlaid in this way; (ii) the volume integral of the overlay; and (iii) the van der Waals energy of the molecular conformations defined by the torsion angles encoded in the chromosomes. The algorithm has been applied to a number of pharmacophore elucidation problems, i.e., angiotensin II receptor antagonists, Leu-enkephalin and a hybrid morphine molecule, 5-HT_1D agonists, benzodiazepine receptor ligands, 5-HT₃ antagonists, dopamine D₂ antagonists, dopamine reuptake blockers and FKBP12 ligands. The resulting pharmacophores are generated rapidly and are in good agreement with those derived from alternative means.