2D conformationally sampled pharmacophore: a ligand-based pharmacophore to differentiate delta opioid agonists from antagonists

Bifunctional opioid receptor ligands as novel analgesics

Prolonged treatment of chronic severe pain with opioid analgesics is frought with problematic adverse effects including tolerance, dependence, and life-threatening respiratory depression. Though these effects are mediated predominately through preferential activation of μ opioid peptide (μOP) receptors, there is an emerging appreciation that actions at κOP and δOP receptors contribute to the observed pharmacologic and behavioral profile of μOP receptor agonists and may be targeted simultaneously to afford improved analgesic effects. Recent developments have also identified the related nociceptin opioid peptide (NOP) receptor as a key modulator of the effects of μOP receptor signaling. We review here the available literature describing OP neurotransmitter systems and highlight recent drug and probe design strategies.

Force Fields for Small Molecules

Molecular dynamics (MD) simulations have been widely applied to computer-aided drug design (CADD). While MD has been used in a variety of applications such as free energy perturbation and long-time simulations, the accuracy of the results from those methods depends strongly on the force field used. Force fields for small molecules are crucial, as they not only serve as building blocks for developing force fields for larger biomolecules but also act as model compounds that will be transferred to ligands used in CADD. Currently, a wide range of small molecule force fields based on additive or nonpolarizable models have been developed. While these nonpolarizable force fields can produce reasonable estimations of physical properties and have shown success in a variety of systems, there is still room for improvements due to inherent limitations in these models including the lack of an electronic polarization response. For this reason, incorporating polarization effects into the energy function underlying a force field is believed to be an important step forward, giving rise to the development of polarizable force fields. Recent simulations of biological systems have indicated that polarizable force fields are able to provide a better physical representation of intermolecular interactions and, in many cases, better agreement with experimental properties than nonpolarizable, additive force fields. Therefore, this chapter focuses on the development of small molecule force fields with emphasis on polarizable models. It begins with a brief introduction on the importance of small molecule force fields and their evolution from additive to polarizable force fields. Emphasis is placed on the additive CHARMM General Force Field and the polarizable force field based on the classical Drude oscillator. The theory for the Drude polarizable force field and results for small molecules are presented showing their improvements over the additive model. The potential importance of polarization for their application in a wide range of biological systems including CADD is then discussed.

Computer-Aided Drug Design Methods

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Conformational Heterogeneity of Intracellular Loop 3 of the μ-opioid G-protein Coupled Receptor

G-protein coupled receptors (GPCRs), including the μ-opioid receptor, interact with G-proteins and other proteins via their intracellular face as required for signal transduction. However, characterization of the structure of the intracellular face of GPCRs is complicated by the experimental methods used for structural characterization. In the present study we undertook a series of long-time molecular dynamics (MD) simulations, ranging from 1 to 5 μs, on the μ-opioid receptor in both the dimeric and monomeric states. Results show intracellular loop 2 (ICL2) to sample an equilibrium between coiled and helical states. Intracellular loop 3 (ICL3) samples a wider range of conformations. Previously unobserved β-sheet structures were primarily sampled in the simulations initiated from the inactive dimer conformation. In contrast, helical structures were sampled in simulations initiated from the active, monomer conformation. Notably, in the dimeric form of the receptor, both intramolecular and intermolecular β-sheet structures were sampled, with the latter occurring between the two monomers. These results indicate that the sampling of β-sheet structures can maintain the ICL3 in an inactive conformation that contributes to stabilization of the dimeric form of the receptor via interchain β-sheet structures.

Towards understanding the unbound state of drug compounds: Implications for the intramolecular reorganization energy upon binding

There has been an explosion of structural information for pharmaceutical compounds bound to biological targets, but the conformations and dynamics of compounds free in solution are poorly characterized, if at all. Yet, knowledge of the unbound state is essential to understand the fundamentals of molecular recognition, including the much debated conformational intramolecular reorganization energy of a compound upon binding (ΔEReorg). Also, dependable observation of the unbound compounds is important for ligand-based drug discovery, e.g. with pharmacophore modelling. Here, these questions are addressed with long (⩾0.5μs) state-of-the-art molecular dynamics (MD) simulations of 26 compounds (including 7 approved drugs) unbound in explicit solvent. These compounds were selected to be chemically diverse, with a range of flexibility, and good quality bioactive X-ray structures. The MD-simulated free compounds are compared to their bioactive structure and conformers generated with ad hoc sampling in vacuo or with implicit generalized Born (GB) aqueous solvation models. The GB conformational models clearly depart from those obtained in explicit solvent, and suffer from conformational collapse almost as severe as in vacuo. Thus, the global energy minima in vacuo or with GB are not suitable representations of the unbound state, which can instead be extensively sampled by MD simulations. Many, but not all, MD-simulated compounds displayed some structural similarity to their bioactive structure, supporting the notion of conformational pre-organization for binding. The ligand-protein complexes were also simulated in explicit solvent, to estimate ΔEReorg as an enthalpic difference ΔHReorg between the intramolecular energies in the bound and unbound states. This fresh approach yielded ΔHReorg values⩽6kcal/mol for 18 out of 26 compounds. For three particularly polar compounds 15⩽ΔHReorg⩽20kcal/mol, supporting the notion that ΔHReorg can be substantial. Those large ΔHReorg values correspond to a redistribution of electrostatic interactions upon binding. Overall, the study illustrates how MD simulations offer a promising avenue to characterize the unbound state of medicinal compounds.

Desmethyl Macrolides: Synthesis and Evaluation of 4,8,10-Tridesmethyl Cethromycin

Antibiotic-resistant bacteria are emerging at an alarming rate in both hospital and community settings. Motivated by this issue, we have prepared desmethyl (i.e., replacing methyl groups with hydrogens) analogues of third-generation macrolide drugs telithromycin (TEL, 2) and cethromycin (CET, 6), both of which are semi-synthetic derivatives of flagship macrolide antibiotic erythromycin (1). Herein, we report the total synthesis, molecular modeling, and biological evaluation of 4,8,10-tridesmethyl cethromycin (7). In MIC assays, CET analogue 7 was found to be equipotent with TEL (2) against a wild-type E. coli strain, more potent than previously disclosed desmethyl TEL congeners 3, 4, and 5, but fourfold less potent than TEL (2) against a mutant E. coli A2058G strain.

Force Field for Peptides and Proteins based on the Classical Drude Oscillator

Presented is a polarizable force field based on a classical Drude oscillator framework, currently implemented in the programs CHARMM and NAMD, for modeling and molecular dynamics (MD) simulation studies of peptides and proteins. Building upon parameters for model compounds representative of the functional groups in proteins, the development of the force field focused on the optimization of the parameters for the polypeptide backbone and the connectivity between the backbone and side chains. Optimization of the backbone electrostatic parameters targeted quantum mechanical conformational energies, interactions with water, molecular dipole moments and polarizabilities and experimental condensed phase data for short polypeptides such as (Ala)₅. Additional optimization of the backbone φ, ψ conformational preferences included adjustments of the tabulated two-dimensional spline function through the CMAP term. Validation of the model included simulations of a collection of peptides and proteins. This 1^st generation polarizable model is shown to maintain the folded state of the studied systems on the 100 ns timescale in explicit solvent MD simulations. The Drude model typically yields larger RMS differences as compared to the additive CHARMM36 force field (C36) and shows additional flexibility as compared to the additive model. Comparison with NMR chemical shift data shows a small degradation of the polarizable model with respect to the additive, though the level of agreement may be considered satisfactory, while for residues shown to have significantly underestimated S² order parameters in the additive model, improvements are calculated with the polarizable model. Analysis of dipole moments associated with the peptide backbone and tryptophan side chains show the Drude model to have significantly larger values than those present in C36, with the dipole moments of the peptide backbone enhanced to a greater extent in sheets versus helices and the dipoles of individual moieties observed to undergo significant variations during the MD simulations. Although there are still some limitations, the presented model, termed Drude-2013, is anticipated to yield a molecular picture of peptide and protein structure and function that will be of increased physical validity and internal consistency in a computationally accessible fashion.

Synthesis, modeling, and pharmacological evaluation of UMB 425, a mixed μ agonist/δ antagonist opioid analgesic with reduced tolerance liabilities

Opioid narcotics are used for the treatment of moderate-to-severe pain and primarily exert their analgesic effects through μ receptors. Although traditional μ agonists can cause undesired side effects, including tolerance, addition of δ antagonists can attenuate said side effects. Herein, we report 4a,9-dihydroxy-7a-(hydroxymethyl)-3-methyl-2,3,4,4a,5,6-hexahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7(7aH)-one (UMB 425) a 5,14-bridged morphinan-based orvinol precursor synthesized from thebaine. Although UMB 425 lacks δ-specific motifs, conformationally sampled pharmacophore models for μ and δ receptors predict it to have efficacy similar to morphine at μ receptors and similar to naltrexone at δ receptors, due to the compound sampling conformations in which the hydroxyl moiety interacts with the receptors similar to orvinols. As predicted, UMB 425 exhibits a mixed μ agonist/δ antagonist profile as determined in receptor binding and [(35)S]GTPγS functional assays in CHO cells. In vivo studies in mice show that UMB 425 displays potent antinociception in the hot plate and tail-flick assays. The antinociceptive effects of UMB 425 are blocked by naloxone, but not by the κ-selective antagonist norbinaltorphimine. During a 6-day tolerance paradigm, UMB 425 maintains significantly greater antinociception compared to morphine. These studies thus indicate that, even in the absence of δ-specific motifs fused to the C-ring, UMB 425 has mixed μ agonist/δ antagonist properties in vitro that translate to reduced tolerance liabilities in vivo.

Exploring binding properties of agonists interacting with a δ-opioid receptor

Ligand-receptor interactions are at the basis of the mediation of our physiological responses to a large variety of ligands, such as hormones, neurotransmitters and environmental stimulants, and their tuning represents the goal of a large variety of therapies. Several molecular details of these interactions are still largely unknown. In an effort to shed some light on this important issue, we performed a computational study on the interaction of two related compounds differing by a single methyl group (clozapine and desmethylclozapine) with a -opioid receptor. According to experiments, desmethylclozapine is more active than clozapine, providing a system well suited for a comparative study. We investigated stable configurations of the two drugs inside the receptor by simulating their escape routes by molecular dynamics simulations. Our results point out that the action of the compounds might be related to the spatial and temporal distribution of the affinity sites they visit during their permanency. Moreover, no particularly pronounced structural perturbations of the receptor were detected during the simulations, reinforcing the idea of a strong dynamical character of the interaction process, with an important role played by the solvent in addition.

Desmethyl Macrolides: Synthesis and Evaluation of 4,8-Didesmethyl Telithromycin

There is an urgent need for novel sources of antibiotics to address the incessant and inevitable onset of bacterial resistance. To this end, we have initiated a structure-based drug design program that features a desmethylation strategy (i.e., replacing methyl groups with hydrogens). Herein we report the total synthesis, molecular modeling and biological evaluation of 4,8-didesmethyl telithromycin (5), a novel desmethyl analogue of the third-generation ketolide antibiotic telithromycin (2), which is an FDA-approved semisynthetic derivative of erythromycin (1). We found 4,8-didesmethyl telithromycin (5) to be eight times more active than previously prepared 4,8,10-tridesmethyl congener (3) and two times more active than 4,10-didesmethyl regioisomer (4) in MIC assays. While less potent than telithromycin (2) and paralleling the observations made in the previous study of 4,10-didesmethyl analogue (4), the inclusion of a single methyl group improves biological activity thus supporting its role in antibiotic activity.

Spatial relationships between the pharmacophores of endomorphin-2: a comparative study of stereoisomers

The spatial relationships between the pharmacophore elements were investigated in the case of four different stereoisomeric forms of opioid tetrapeptide, endomorphin-2, taking into account the L-D and cis-trans isomerisms. On the basis of distances and angles measured between the pharmacophoric points, a comparative analysis of conformational distributions was performed, applying a variety of distance-angle maps. The results obtained by this theoretical study indicated that the stereoisomers of endomorphin-2 could be distinguished from one another, based on the comparative analysis of distance-angle maps. Nevertheless, it could be concluded that this method proved to be suitable to examine the effects of L-D and cis-trans isomerisms on the spatial relationships of the pharmacophores of tetrapeptide.

Deconstructing 14-phenylpropyloxymetopon: minimal requirements for binding to mu opioid receptors

A series of phenylpropyloxyethylamines and cinnamyloxyethylamines were synthesized as deconstructed analogs of 14-phenylpropyloxymetopon and analyzed for opioid receptor binding affinity. Using the Conformationally Sampled Pharmacophore modeling approach, we discovered a series of compounds lacking a tyrosine mimetic, historically considered essential for μ opioid binding. Based on the binding studies, we have identified the optimal analogs to be N-methyl-N-phenylpropyl-2-(3-phenylpropoxy)ethanamine, with 1520 nM, and 2-(cinnamyloxy)-N-methyl-N-phenethylethanamine with 1680 nM affinity for the μ opioid receptor. These partial opioid structure analogs will serve as the novel lead compounds for future optimization studies.

Desmethyl Macrolides: Synthesis and Evaluation of 4,10-Didesmethyl Telithromycin

Novel sources of antibiotics are required to keep pace with the inevitable onset of bacterial resistance. Continuing with our macrolide desmethylation strategy as a source of new antibiotics, we report the total synthesis, molecular modeling and biological evaluation of 4,10-didesmethyl telithromycin (4), a novel desmethyl analogue of the 3rd-generation drug telithromycin (2). Telithromycin is an FDA-approved ketolide antibiotic derived from erythromycin (1). We found 4,10-didesmethyl telithromycin (4) to be four times more active than previously prepared 4,8,10-tridesmethyl congener (3) in MIC assays. While less potent than telithromycin (2), the inclusion of the C-8 methyl group has improved biological activity suggesting it plays an important role in antibiotic function.

Recent Developments and Applications of the CHARMM force fields

Empirical force fields commonly used to describe the condensed phase properties of complex systems such as biological macromolecules are continuously being updated. Improvements in quantum mechanical (QM) methods used to generate target data, availability of new experimental target data, incorporation of new classes of compounds and new theoretical developments (eg. polarizable methods) make force-field development a dynamic domain of research. Accordingly, a number of improvements and extensions of the CHARMM force fields have occurred over the years. The objective of the present review is to provide an up-to-date overview of the CHARMM force fields. A limited presentation on the historical aspects of force fields will be given, including underlying methodologies and principles, along with a brief description of the strategies used for parameter development. This is followed by information on the CHARMM additive and polarizable force fields, including examples of recent applications of those force fields.

Consensus 3D model of μ-opioid receptor ligand efficacy based on a quantitative Conformationally Sampled Pharmacophore

Despite being studied for over 30 years, a consensus structure-activity relationship (SAR) that encompasses the full range peptidic and nonpeptidic μ-opioid receptor ligands is still not available. To achieve a consensus SAR the Conformationally Sampled Pharmacophore (CSP) method was applied to develop a predictive model of the efficacy of μ-opioid receptor ligands. Emphasis was placed on predicting the efficacy of a wide range of agonists, partial agonists, and antagonists as well as understanding their mode of interaction with the receptor. Inclusion of all accessible conformations of each ligand, a central feature of the CSP method, enabled structural features between diverse μ-opioid receptor ligands that dictate efficacy to be identified. The models were validated against a diverse collection of peptidic and nonpeptidic ligands, including benzomorphans, fentanyl (4-anilinopiperidine), methadone (3,3-diphenylpropylamines), etonitazene (benzimidazole derivatives), funaltrexamine (C6-substituted 4,5-epoxymorphinan), and herkinorin. The model predicts (1) that interactions of ligands with the B site, as with the 19-alkyl substituents of oripavines, modulate the extent of agonism; (2) that agonists with long N-substituents, as with fentanyl and N-phenethylnormorphine, can bind in an orientation such that the N substitutent interacts with the B site that also allows the basic N-receptor Asp interaction essential for agonism; and (3) that the μ agonist herkinorin, that lacks a basic nitrogen, binds to the receptor in a manner similar to the traditional opioids via interactions mediated by water or a ion. Importantly, the proposed CSP model can be reconciled with previously published SAR models for the μ receptor.

Computational ligand-based rational design: Role of conformational sampling and force fields in model development

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

Desmethyl Macrolide Analogues to Address Antibiotic Resistance: Total Synthesis and Biological Evaluation of 4,8,10-Tridesmethyl Telithromycin

There is an urgent need to discover new drugs to address the pressing problem of antibiotic-resistance. Macrolide antibiotics such as erythromycin (1) are safe, broad-spectrum antibiotics used in the clinic since 1954. Herein we report the synthesis and evaluation of 4,8,10-tridesmethyl telithromycin (3), a novel desmethyl analogue of the 3rd-generation drug telithromycin (2), which is a semisynthetic derivative of 1. Analogue 3 was found to possess antibiotic activity and was superior to telithromycin (2) when tested against resistant strains of S. aureus possessing an A→T mutation at position 2058 (E. coli numbering).

Structural determinants for transport across the intestinal bile acid transporter using C-24 bile acid conjugates

The human apical sodium dependent bile acid transporter (hASBT) reabsorbs gram quantities of bile acid daily and is a potential prodrug target to increase oral drug absorption. In the absence of a high resolution hASBT crystal structure, 3D-QSAR modeling may prove beneficial in designing prodrug targets to hASBT. The objective was to derive a conformationally sampled pharmacophore 3D-QSAR (CSP-SAR) model for the uptake of bile acid conjugates by hASBT. A series of bile acid conjugates of glutamyl chenodeoxycholate were evaluated in terms of K(m) and normalized V(max) (normV(max)) using hASBT-MDCK cells. All monoanionic conjugates were potent substrates. Dianions, cations and zwitterions, which bound with a high affinity, were not substrates. CSP-SAR models were derived using structural and physicochemical descriptors, and evaluated via cross validation. The best CSP-SAR model for K(m) included two structural and two physiochemical descriptors, where substrate hydrophobicity enhanced affinity. A best CSP-SAR model for K(m)/normV(max) employed one structural and three physicochemical descriptors, also indicating hydrophobicity enhanced efficiency. Overall, the bile acid C-24 region accommodated a range of substituted anilines, provided a single negative charge was present near C-24. In comparing uptake findings to prior inhibition results, increased hydrophobicity enhanced activity, with dianions and zwitterions hindering activity.

Molecular switch controlling the binding of anionic bile acid conjugates to human apical sodium-dependent bile acid transporter

The human apical sodium-dependent bile acid transporter (hASBT) may serve as a prodrug target for oral drug absorption. Synthetic, biological, NMR, and computational approaches identified the structure-activity relationships of mono- and dianionic bile acid conjugates for hASBT binding. Experimental data combined with a conformationally sampled pharmacophore/QSAR modeling approach (CSP-SAR) predicted that dianionic substituents with intramolecular hydrogen bonding between hydroxyls on the cholane skeleton and the acid group on the conjugate's aromatic ring increased conjugate hydrophobicity and improved binding affinity. Notably, the model predicted the presence of a conformational molecular switch, where shifting the carboxylate substituent on an aromatic ring by a single position controlled binding affinity. Model validation was performed by effectively shifting the spatial location of the carboxylate by inserting a methylene adjacent to the aromatic ring, resulting in the predicted alteration in binding affinity. This work illustrates conformation as a determinant of ligand physiochemical properties and ligand binding affinity to a biological transporter.

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like molecules is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chemical groups present in biomolecules and drug-like molecules, including a large number of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. Statistics related to the quality of the parametrization with a focus on experimental validation are presented. Additionally, the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethylpyrrolidine will allow users to readily extend the force field to chemical groups that are not explicitly covered in the force field as well as add functional groups to and link together molecules already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems.

Utilizing nature as a source of new probes for opioid pharmacology

Background: Traditional and current opioid pharmacology is fundamentally based on interactions between opioid receptors and compounds isolated from natural sources. Adverse effects associated with opioids have led to the search for compounds with diminished side effects. Discussion: Recent discoveries of non-nitrogenous and structurally diverse alkaloids as novel opioid ligands have led to renewed interest in the development of novel chemotypes for opioid receptors. Conclusion: The strong history of natural products as opioid receptor ligands suggests that nature is one of the most promising for the identification of novel opioids. This review highlights the vast potential of investigating natural products as novel probes of opioid receptors.

Inhibition requirements of the human apical sodium-dependent bile acid transporter (hASBT) using aminopiperidine conjugates of glutamyl-bile acids

PURPOSE

Synthesize aminopiperidine conjugates of glutamyl-bile acids (glu-BAs) and develop a hASBT inhibition model using the conformationally sampled pharmacophore (CSP) approach.

METHODS

glu-BAs aminopiperidine conjugates were synthesized. hASBT inhibition was measured as K(i). A CSP-SAR model was built using structural and physico-chemical descriptors and evaluated via cross-validation.

RESULTS

Twenty-nine aminopiperidine conjugates were synthesized. All inhibited hASBT, with K(i) ranging from 0.95 to 31.8 muM. Amidation of the piperidine nitrogen slightly decreased activity, while replacement by a carbon increased potency. Esterification of the glutamic acid linker had a minor impact, suggesting that a negative charge around C-24 is not required for binding. Three quantitative CSP-SAR models were developed. The best model (r (2) = 0.813, Q (2) = 0.726) included two descriptors: angle between 7-OH, alpha-substituent and centroid of rings B and C, and electrostatic contribution to the solvation free-energy. The model successfully distinguished between compounds with K(i) < 16muM and K(i) > 16muM. Models indicated that hydrophobicity, alpha substituent orientation, and partially compacted side chain conformation promote inhibitory potency. Qualitative CSP-SAR analysis indicated that the presence of an internal salt bridge, resulting in a locked conformation of the side chain, yielded weaker inhibitors.

CONCLUSIONS

Aminopiperidine conjugates of glu-BAs were potent hASBT inhibitors. A predictive and robust CSP-SAR model was developed.

Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor

Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule-specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 31, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of the corresponding rigid-body (or "planes") parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.

QUASI: A Novel Method for Simultaneous Superposition of Multiple Flexible Ligands and Virtual Screening Using Partial Similarity

The structure of many receptors is unknown, and only information about diverse ligands binding to them is available. A new method is presented for the superposition of such ligands, derivation of putative receptor site models and utilization of the models for screening of compound databases. In order to generate a receptor model, the similarity of all ligands is optimized simultaneously taking into account conformational flexibility and also the possibility that the ligands can bind to different regions of the site and only partially overlap. Ligand similarity is defined with respect to a receptor site model serving as a common reference frame. The receptor model is dynamic and coevolves with the ligand alignment until an optimal self-consistent superposition is achieved. When ligand conformational flexibility is permitted, different superposition models are possible and consistent with the data. Clustering of the superposition solutions is used to obtain diverse models. When the models are used to screen a database of compounds, high enrichments are obtained, comparable to those obtained in docking studies.

Quantitative conformationally sampled pharmacophore for delta opioid ligands: reevaluation of hydrophobic moieties essential for biological activity

Recent studies have indicated several therapeutic applications for delta opioid agonists and antagonists. To exploit the therapeutic potential of delta opioids developing a structural basis for the activity of ligands at the delta opioid receptor is essential. The conformationally sampled pharmacophore (CSP) method (Bernard et al. J. Am. Chem. Soc. 2003, 125, 3103-3107) is extended here to obtain quantitative models of delta opioid ligand efficacy and affinity. Quantification is performed via overlap integrals of the conformational space sampled by ligands with respect to a reference compound. Iterative refinement of the CSP model identified hydrophobic groups other than the traditional phenylalanine residues as important for efficacy and affinity in DSLET and ICI 174 864. The obtained models for a structurally diverse set of peptidic and nonpeptidic delta opioid ligands offer good predictions with R2 values>0.9, and the predicted efficacy for a set of test compounds was consistent with the experimental values.

DAT/SERT selectivity of flexible GBR 12909 analogs modeled using 3D-QSAR methods

The dopamine reuptake inhibitor GBR 12909 (1-{2-[bis(4-fluorophenyl)methoxy]ethyl}-4-(3-phenylpropyl)piperazine, 1) and its analogs have been developed as tools to test the hypothesis that selective dopamine transporter (DAT) inhibitors will be useful therapeutics for cocaine addiction. This 3D-QSAR study focuses on the effect of substitutions in the phenylpropyl region of 1. CoMFA and CoMSIA techniques were used to determine a predictive and stable model for the DAT/serotonin transporter (SERT) selectivity (represented by pK(i) (DAT/SERT)) of a set of flexible analogs of 1, most of which have eight rotatable bonds. In the absence of a rigid analog to use as a 3D-QSAR template, six conformational families of analogs were constructed from six pairs of piperazine and piperidine template conformers identified by hierarchical clustering as representative molecular conformations. Three models stable to y-value scrambling were identified after a comprehensive CoMFA and CoMSIA survey with Region Focusing. Test set correlation validation led to an acceptable model, with q(2)=0.508, standard error of prediction=0.601, two components, r(2)=0.685, standard error of estimate=0.481, F value=39, percent steric contribution=65, and percent electrostatic contribution=35. A CoMFA contour map identified areas of the molecule that affect pK(i) (DAT/SERT). This work outlines a protocol for deriving a stable and predictive model of the biological activity of a set of very flexible molecules.

Hierarchical clustering analysis of flexible GBR 12909 dialkyl piperazine and piperidine analogs

Pharmacophore modeling of large, drug-like molecules, such as the dopamine reuptake inhibitor GBR 12909, is complicated by their flexibility. A comprehensive hierarchical clustering study of two GBR 12909 analogs was performed to identify representative conformers for input to three-dimensional quantitative structure-activity relationship studies of closely-related analogs. Two data sets of more than 700 conformers each produced by random search conformational analysis of a piperazine and a piperidine GBR 12909 analog were studied. Several clustering studies were carried out based on different feature sets that include the important pharmacophore elements. The distance maps, the plot of the effective number of clusters versus actual number of clusters, and the novel derived clustering statistic, percentage change in the effective number of clusters, were shown to be useful in determining the appropriate clustering level. Six clusters were chosen for each analog, each representing a different region of the torsional angle space that determines the relative orientation of the pharmacophore elements. Conformers of each cluster that are representative of these regions were identified and compared for each analog. This study illustrates the utility of using hierarchical clustering for the classification of conformers of highly flexible molecules in terms of the three-dimensional spatial orientation of key pharmacophore elements.

The Novel, Orally Active, Delta Opioid RWJ-394674 Is Biotransformed to the Potent Mu Opioid RWJ-413216

Although the mu opioid receptor is the primary target of marketed opioid analgesics, several studies suggest the advantageous effect of combinations of mu and delta opioids. The novel compound RWJ-394674 [N,N-diethyl-4-[(8-phenethyl-8-azabicyclo]3.2.1]oct-3-ylidene)-phenylmethyl]-benzamide]; bound with high affinity to the delta opioid receptor (0.2 nM) and with weaker affinity to the mu opioid receptor (72 nM). 5'-O-(3-[(35)S]-thio)triphosphate binding assay demonstrated its delta agonist function. Surprisingly given this pharmacologic profile, RWJ-394674 exhibited potent oral antinociception (ED(50) = 10.5 micromol/kg or 5 mg/kg) in the mouse hot-plate (48 degrees C) test and produced a moderate Straub tail. Antagonist studies in the more stringent 55 degrees C hot-plate test demonstrated the antinociception produced by RWJ-394674 to be sensitive to the nonselective opioid antagonist naloxone as well as to the delta- and mu-selective antagonists, naltrindole and beta-funaltrexamine, respectively. In vitro studies demonstrated that RWJ-394674 was metabolized by hepatic microsomes to its N-desethyl analog, RWJ-413216 [N-ethyl-4-[(8-phenethyl-8-azabicyclo[3.2.1]oct-3-ylidene)-phenylmethyl]-benzamide], which, in contrast to RWJ-394674, had a high affinity for the mu rather than the delta opioid receptor and was an agonist at both. Pharmacokinetic studies in the rat revealed that oral administration of RWJ-394674 rapidly gave rise to detectable plasma levels of RWJ-413216, which reached levels equivalent to those of RWJ-394674 by 1 h. RWJ-413216 itself demonstrated a potent oral antinociceptive effect. Thus, RWJ-394674 is a delta opioid receptor agonist that appears to augment its antinociceptive effect through biotransformation to a novel mu opioid receptor-selective agonist.

Singular value decomposition of torsional angles of analogs of the dopamine reuptake inhibitor GBR 12909

Analysis of large, flexible molecules, such as the dopamine reuptake inhibitor GBR 12909 (1), is complicated by the fact that they can take on a wide range of closely related conformations. The first step in the analysis is to classify the conformers into groups. Here, Singular Value Decomposition (SVD) was used to group conformations of GBR 12909 analogs by the similarity of their nonring torsional angles. The significance of the present work, the first application of SVD to the analysis of very flexible molecules, lies in the development of a novel scaling technique for circular data and in the grouping of molecular conformations using a technique that is independent of molecular alignment. Over 700 conformers each of a piperazine (2) and piperidine (3) analog of 1 were studied. Analysis of the score and loading plots showed that the conformers of 2 separate into three large groups due to torsional angles on the naphthalene side of the molecule, whereas those of 3 separate into nine groups due to torsional angles on the bisphenyl side of the molecule. These differences are due to nitrogen inversion at the unprotonated piperazinyl nitrogen of 2, which results in a different ensemble of conformers than those of 3, where no inversion is possible at the corresponding piperidinyl carbon.

Molecular recognition of opioid receptor ligands

The cloning of the opioid receptors and subsequent use of recombinant DNA technology have led to many new insights into ligand binding. Instead of focusing on the structural features that lead to increased affinity and selectivity, researchers are now able to focus on why these features are important. Site-directed mutagenesis and chimeric data have often been at the forefront in answering these questions. Herein, we survey pharmacophores of several opioid ligands in an effort to understand the structural requirements for ligand binding and selectivity. Models are presented and compared to illustrate key sites of recognition for both opiate and nonopiate ligands. The results indicate that different ligand classes may recognize different sites within the receptor, suggesting that multiple epitopes may exist for ligand binding and selectivity.

Conformationally sampled pharmacophore for peptidic delta opioid ligands

Opioids represent the frontline treatment for acute pain, despite their side effects, motivating efforts toward developing novel opioid analgesics. To facilitate these efforts, a novel modeling approach, the conformationally sampled pharmacophore (CSP), has been developed that increases the probability of including the receptor bound form in the model. This method, originally used for developing a nonpeptidic delta opioid efficacy pharmacophore, is extended to peptidic ligands using replica exchange molecular dynamics simulation for conformational sampling. The developed 2D CSP indicates that the spatial relationship of the basic nitrogen and the hydrophobic moiety in the delta opioid ligands differentiates activity. In addition, results indicate that both peptidic and nonpeptidic ligands have the same binding mode with the receptor. Thus, the CSP approach distinguishes both peptidic and nonpeptidic delta opioid agonists and antagonists and is anticipated to be of general utility for the development of pharmacophores for species with multiple rotatable bonds.

Development of a quasi-dynamic pharmacophore model for anti-complement peptide analogues

Three quasi-dynamic pharmacophore models have been constructed for the complement inhibitor peptide compstatin, using first principles. Uniform sampling along 5-ns molecular dynamics trajectories provided dynamic conformers that are thought to represent the entire conformational space for nine training set molecules, compstatin, four active analogues, and four inactive analogues. The pharmacophore models were built using mixed physicochemical and structural properties of residues indispensable for structural stability and activity. Owing to the size and flexibility of compstatin, one-dimensional probability distributions of intrapharmacophore point distances, angles, and dihedral angles of different analogues spread over wide and overlapping ranges. More robust two-dimensional distance-angle probability distributions for two pharmacophore models discriminated individual analogues in terms of specific distance-angle pairs, but overall failed to identify the active and the inactive analogues as two distinct groups. Two-dimensional distance-dihedral angle probability distributions in a third pharmacophore model allowed discrimination of the groups of active and inactive analogues more effectively, with the highest-activity analogue having distinct behavior. The present study indicates that more stringent structural constraints should be used for a set of structurally similar but flexible peptides, as opposed to organic molecules, to convert dynamic conformers into pharmacophore models. Flexibility is a general aspect of the structure and function of peptides and should be taken into account in ligand-based pharmacophore design. However, the discrimination of activity using multidimensional probability surfaces depends on the peptide system, the selection of the training set, the molecular dynamics protocol, and the selection of the type and number of pharmacophore points.

Computational approaches to modeling drug transporters

Computational modeling has advanced our understanding of drug absorption, tissue distribution, excretion and toxicity profiles by providing both direct and indirect knowledge of drug-transporter interactions that would otherwise be unavailable using experimental methods. Currently, two complementary approaches are available in modeling transporters: substrate-based and transporter-based methods. The transporter-based approach directly predicts the transporter's three-dimensional structure to assist in understanding the drug transport process, whereas substrate-based models infer such information by studying a group of substrates or inhibitors with measured activities. In this review, the available strategies in both transporter-based and substrate-based approaches are explained and illustrated with applications and case studies. With increasing computational power and continuously improving modeling algorithms, computational techniques can assist in further understanding transporter-substrate interactions as well as, the optimization of transporter-directed drug design.

Novel feature extraction technique for fuzzy relational clustering of a flexible dopamine reuptake inhibitor

This paper describes a novel clustering methodology for classifying over 700 conformations of a flexible analogue of GBR 12909, a dopamine reuptake inhibitor that has completed phase I clinical trials as a treatment for cocaine abuse. The major aspect of the clustering methodology includes an efficient data-conditioning scheme where a systematic feature extraction procedure based on the structural properties of the molecule was used to reduce the associated feature space. This allowed region-specific clustering that focused on individual pharmacophore elements of the molecule. For clustering of the reduced feature set, the fuzzy clustering partitional method was utilized. Due to the relational nature of the feature data, fuzzy relational clustering was employed, and it successfully detected natural groups defined by rotational minima around N(sp(3))-C(sp(3)), O(sp(3))-C(sp(3)), and C(sp(3))-C(sp(2)) bonds. The proposed clustering methodology also employed several cluster validity measures, which corroborated the partitions produced by the clustering technique and agreed with the results of hierarchical clustering using the XCluster program. Representative structures which exhibited a reasonable spread of energies and showed good spatial coverage of the conformational space were identified for use as putative bioactive conformations in a future Comparative Molecular Field Analysis of GBR 12909 analogues. The clustering methodology developed here is capable of handling other computational chemistry problems, and the feature extraction technique can be easily generalized to other molecules.

Homology modeling of opioid receptor-ligand complexes using experimental constraints

Opioid receptors interact with a variety of ligands, including endogenous peptides, opiates, and thousands of synthetic compounds with different structural scaffolds. In the absence of experimental structures of opioid receptors, theoretical modeling remains an important tool for structure-function analysis. The combination of experimental studies and modeling approaches allows development of realistic models of ligand-receptor complexes helpful for elucidation of the molecular determinants of ligand affinity and selectivity and for understanding mechanisms of functional agonism or antagonism. In this review we provide a brief critical assessment of the status of such theoretical modeling and describe some common problems and their possible solutions. Currently, there are no reliable theoretical methods to generate the models in a completely automatic fashion. Models of higher accuracy can be produced if homology modeling, based on the rhodopsin X-ray template, is supplemented by experimental structural constraints appropriate for the active or inactive receptor conformations, together with receptor-specific and ligand-specific interactions. The experimental constraints can be derived from mutagenesis and cross-linking studies, correlative replacements of ligand and receptor groups, and incorporation of metal binding sites between residues of receptors or receptors and ligands. This review focuses on the analysis of similarity and differences of the refined homology models of mu, delta, and kappa-opioid receptors in active and inactive states, emphasizing the molecular details of interaction of the receptors with some representative peptide and nonpeptide ligands, underlying the multiple modes of binding of small opiates, and the differences in binding modes of agonists and antagonists, and of peptides and alkaloids.

GPCR-tailored pharmacophore pattern recognition of small molecular ligands

The goal of our work was to differentiate between patterns, which are responsible for the activity of small molecular ligands binding to G-protein coupled receptors (GPCRs) and molecules, which are pharmacologically active on other target classes. Second the aim was to go one step further and analyze the chemical space occupied by GPCR active ligands itself, to distinguish between the actives of different subclasses or even cluster ligands for single receptors. To achieve these objectives, we have built a database of small, organic molecules, which bind to GPCRs. Once this crucial foundation for pattern recognition has been laid, we needed to find a descriptor, which is able to detect the compulsory features responsible for activity within a molecule. In this matter we found that the well accepted pharmacophore descriptor served us well. Finally we needed to find a method to display the clustering or separation of the specific ligands. We found that self-organizing maps (SOMs) perform excellently in this task. We herein present the analysis of the chemical space of active compounds, depending on their biological target, the GPCRs. We will also discuss the techniques used to create the chemical spaces. The findings can be applied and have an impact at various stages of the drug discovery process.

Conformational analysis of methylphenidate: comparison of molecular orbital and molecular mechanics methods

Methylphenidate (MP) binds to the cocaine binding site on the dopamine transporter and inhibits reuptake of dopamine, but does not appear to have the same abuse potential as cocaine. This study, part of a comprehensive effort to identify a drug treatment for cocaine abuse, investigates the effect of choice of calculation technique and of solvent model on the conformational potential energy surface (PES) of MP and a rigid methylphenidate (RMP) analogue which exhibits the same dopamine transporter binding affinity as MP. Conformational analysis was carried out by the AM1 and AM1/SM5.4 semiempirical molecular orbital methods, a molecular mechanics method (Tripos force field with the dielectric set equal to that of vacuum or water) and the HF/6-31G* molecular orbital method in vacuum phase. Although all three methods differ somewhat in the local details of the PES, the general trends are the same for neutral and protonated MP. In vacuum phase, protonation has a distinctive effect in decreasing the regions of space available to the local conformational minima. Solvent has little effect on the PES of the neutral molecule and tends to stabilize the protonated species. The random search (RS) conformational analysis technique using the Tripos force field was found to be capable of locating the minima found by the molecular orbital methods using systematic grid search. This suggests that the RS/Tripos force field/vacuum phase protocol is a reasonable choice for locating the local minima of MP. However, the Tripos force field gave significantly larger phenyl ring rotational barriers than the molecular orbital methods for MP and RMP. For both the neutral and protonated cases, all three methods found the phenyl ring rotational barriers for the RMP conformers/invertamers (denoted as cte, tte, and cta) to be: cte, tte > MP > cta. Solvation has negligible effect on the phenyl ring rotational barrier of RMP. The B3LYP/6-31G* density functional method was used to calculate the phenyl ring rotational barrier for neutral MP and gave results very similar to those of the HF/6-31G* method.

Kinetics of ?-funaltrexamine binding to wild-type and mutant ?-opioid receptors expressed in Chinese hamster ovary cells

The two-stage reaction whereby the antagonist beta-funaltrexamine (beta-FNA) binds covalently to micro opioid receptors makes it a highly discriminating probe into the tertiary structure of the receptor's recognition pocket. To obtain a quantitative measure of how well this pocket is preserved in a mutated form of the receptor, in which His-297 is substituted with glutamine, we employed [3H]-beta-FNA to evaluate the kinetic rate constants for both the reversible as well as the irreversible stages of its binding to wild-type and mutant H297Q micro receptors stably expressed in Chinese hamster ovary cells. The expression levels of the wild-type and mutant H297Q receptors were matched by exploiting the variation in receptor density as a function of plating day and by raising the expression level by pretreatment with naloxone. We found that all of the kinetic rate constants for [3H]-beta-FNA were diminished by about one-half at the mutant H297Q micro receptors with respect to wild-type receptors. By comparison, the association rate constant of [3H]-naloxone likewise decreased by one-half; however, the dissociation rate constant increased 5-fold at the mutant H297Q receptor. We conclude that the mutation has had only minor influence on the recognition site and that the function of position 297 is more likely as a link in the transduction chain.