Equilibrium landscape of ingress/egress channels and gating residues of the Cytochrome P450 3A4.

The Cytochrome P450 (CYP) enzymes metabolize a variety of drugs, which may potentially lead to toxicity or reduced efficacy when drugs are co-administered. These drug-drug interactions are often manifested by CYP3A4, the most prevalent of all CYP isozymes. We carried out multiple MD simulations employing CAVER to quantify the channels, and Hidden Markov Models (HMM) to characterize the behavior of the gating residues. We discuss channel properties, bottleneck residues with respect to their likelihood to deem the respective channel ingress or egress, gating residues regarding their open or closed states, and channel location relative to the membrane. Channels do not display coordinated motion and randomly transition between different conformations. Gateway residues also behave in a random fashion. Our findings shed light on the equilibrium behavior of the gating residues and channels in the apo state.

Development of a Simple and Effective Lipid-A Antagonist Based on Computational Prediction.

Sepsis is a serious medical condition characterized by bacterial infection and a subsequent massive systemic inflammatory response. In an effort to identify compounds that block lipopolysaccharide (LPS)-induced inflammation reported herein is the development of simple Lipid-A analogues that lack a disaccharide core yet still possess potent antagonistic activity against LPS. The structure of the new lead compound was developed based on predictive computational experiments. LPS antagonism by the lead compound was not straightforward, and a biphasic effect was observed suggesting a possibility of more than one binding site. An IC50 value of 13 nM for the new compound was determined for the possible high affinity site. The combination of computational, synthetic, and biological studies revealed new structural determinants of these simplified analogues. It is expected that the acquired information will aid future design of LPS targeting glycopharmaceuticals.

RSK1 vs. RSK2 Inhibitory Activity of the Marine ß-Carboline Alkaloid Manzamine A: A Biochemical, Cervical Cancer Protein Expression, and Computational Study.

Manzamines are complex polycyclic marine-derived ß-carboline alkaloids with reported anticancer, immunostimulatory, anti-inflammatory, antibacterial, antiviral, antimalarial, neuritogenic, hyperlipidemia, and atherosclerosis suppression bioactivities, putatively associated with inhibition of glycogen synthase kinase-3, cyclin-dependent kinase 5, SIX1, and vacuolar ATPases. We hypothesized that additional, yet undiscovered molecular targets might be associated with Manzamine A's (MZA) reported pharmacological properties. We report here, for the first time, that MZA selectively inhibited a 90 kDa ribosomal protein kinase S6 (RSK1) when screened against a panel of 30 protein kinases, while in vitro RSK kinase assays demonstrated a 10-fold selectivity in the potency of MZA against RSK1 versus RSK2. The effect of MZA on inhibiting cellular RSK1 and RSK2 protein expression was validated in SiHa and CaSki human cervical carcinoma cell lines. MZA's differential binding and selectivity toward the two isoforms was also supported by computational docking experiments. Specifically, the RSK1-MZA (N- and C-termini) complexes appear to have stronger interactions and preferable energetics contrary to the RSK2-MZA ones. In addition, our computational strategy suggests that MZA binds to the N-terminal kinase domain of RSK1 rather than the C-terminal domain. RSK is a vertebrate family of cytosolic serine-threonine kinases that act downstream of the ras-ERK1/2 (extracellular-signal-regulated kinase 1/2) pathway, which phosphorylates substrates shown to regulate several cellular processes, including growth, survival, and proliferation. Consequently, our findings have led us to hypothesize that MZA and the currently known manzamine-type alkaloids isolated from several sponge genera may have novel pharmacological properties with unique molecular targets, and MZA provides a new tool for chemical-biology studies involving RSK1.

Synthesis and structure-activity relationships of 3,4,5-trisubstituted-1,2,4-triazoles: high affinity and selective somatostatin receptor-4 agonists for Alzheimer's disease treatment.

Somatostatin receptor-4 (SST4) is highly expressed in brain regions affiliated with learning and memory. SST4 agonist treatment may act to mitigate Alzheimer's disease (AD) pathology. An integrated approach to SST4 agonist lead optimization is presented herein. High affinity and selective agonists with biological efficacy were identified through iterative cycles of a structure-based design strategy encompassing computational methods, chemistry, and preclinical pharmacology. 1,2,4-Triazole derivatives of our previously reported hit (4) showed enhanced SST4 binding affinity, activity, and selectivity. Thirty-five compounds showed low nanomolar range SST4 binding affinity, 12 having a K i < 1 nM. These compounds showed >500-fold affinity for SST4 as compared to SST2A. SST4 activities were consistent with the respective SST4 binding affinities (EC50 < 10 nM for 34 compounds). Compound 208 (SST4 K i = 0.7 nM; EC50 = 2.5 nM; >600-fold selectivity over SST2A) display a favorable physiochemical profile, and was advanced to learning and memory behavior evaluations in the senescence accelerated mouse-prone 8 model of AD-related cognitive decline. Chronic administration enhanced learning with i.p. dosing (1 mg kg-1) compared to vehicle. Chronic administration enhanced memory with both i.p. (0.01, 0.1, 1 mg kg-1) and oral (0.01, 10 mg kg-1) dosing compared to vehicle. This study identified a novel series of SST4 agonists with high affinity, selectivity, and biological activity that may be useful in the treatment of AD.

Decoding Protein-protein Interactions: An Overview.

Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

The compromise of virtual screening and its impact on drug discovery.

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Toward Computational Understanding of Molecular Recognition in the Human Metabolizing Cytochrome P450s.

Cytochrome P450s are enzymes capable of metabolizing a wide variety of drugs. Their significant impact in drug discovery has led to extensive research, computationally and experimentally, in order to explore how a chemical entity responds to metabolizing enzymes. We present an overview of ligand-based and structure-based methodologies, along with pertinent information on the structures, biology, and relevance of these enzymes.

Discovery of a 3,4,5-trisubstituted-1,2,4-triazole agonist with high affinity and selectivity at the somatostatin subtype-4 (sst4) receptor.

A series of compounds containing a 1,2,4-triazole moiety were synthesized, targeting the somatostatin receptor subtype-4 (sst4). Compounds were developed in which the Phe6/Phe7/Phe11, Trp8, and Lys9 mimetic groups were interchanged at positions 3, 4, and 5 of the 1,2,4-triazole ring. The 1,2,4-triazoles containing an 2-(imidazol-4-yl)ethyl substituent at position-3 demonstrated moderate binding affinity at sst4. 1,2,4-Triazoles containing an (indol-3-yl)methyl substituent at position-5 lacked affinity at sst4. The 1,2,4-triazoles containing an aminopropyl group at position-4 showed enhanced binding affinity compared to the 3-position. One compound with an 3-(imidazol-4-yl)propyl group at position-4 (compound 44) imparted high affinity and selectivity at sst4 (sst2A = >10 000 nM; sst4 = 19 nM), acting as an agonist (EC50 = 6.8 nM). Docking 44 into a model-built structure of sst4 pointed to differences in its binding versus the other low-affinity compounds and was also in line with one of the two previously reported binding modes. A virtual screening (VS) experiment, employing two separate docking algorithms, was able to score 44 among the top-ranked poses. In summary, compound 44 represents a novel and promising lead structure towards the development of a clinically viable sst4 agonist for the treatment of conditions ranging from Alzheimer's disease to chronic pain.

Docking and Virtual Screening in Drug Discovery.

Stages in a typical drug discovery organization include target selection, hit identification, lead optimization, preclinical and clinical studies. Hit identification and lead optimization are very much intertwined with computational modeling. Structure-based virtual screening (VS) has been a staple for more than a decade now in drug discovery with its underlying computational technique, docking, extensively studied. Depending on the objective, the parameters for VS may change, but the overall protocol is very straightforward. The idea behind VS is that a library of small compounds are docked into the binding pocket of a protein (e.g., receptor, enzyme), a number of solutions per molecule, among the top-ranked, are being returned, and a choice is made on the fraction of compounds to be moved forward for testing toward hit identification. The underlying principle of VS is that it differentiates between active and inactive compounds, thus reducing the number of molecules moving forward and possibly offering a complementary tool to high-throughput screening (HTS). Best practices in library selection, target preparation and refinement, criteria in selecting the most appropriate docking/scoring scheme, and a step-wise approach in performing Glide VS are discussed.

G Protein Coupled Receptors And Structure-Based Advances.

G protein coupled receptors (GPCRs) are membrane proteins coupled with G proteins through which they transmit signals to the cytoplasm. Approximately 30% of pharmaceuticals target these receptors, even though crystal structures were scarce at the time. Furthermore, an additional 15% of GPCRs have yet to be exploited for therapeutic intervention. An overview of structural information is presented, with emphasis on rearrangements occurring during activation,in light of recently resolved activated state crystal structures. Computational efforts over recent years are also highlighted.

Identification of key residues involved in the activation and signaling properties of dopamine D3 receptor.

The dopamine D3 receptor exhibits agonist-dependent tolerance and slow response termination (SRT) signaling properties that distinguish it from the closely-related D2 receptors. While amino acid residues important for D3 receptor ligand binding have been identified, the residues involved in activation of D3 receptor signaling and induction of signaling properties have not been determined. In this paper, we used cis and trans isomers of a novel D3 receptor agonist, 8-OH-PBZI, and site-directed mutagenesis to identify key residues involved in D3 receptor signaling function. Our results show that trans-8-OH-PBZI, but not cis-8-OH-PBZI, elicit the D3 receptor tolerance and SRT properties. We show that while both agonists require a subset of residues in the orthosteric binding site of D3 receptors for activation of the receptor, the ability of the two isomers to differentially induce tolerance and SRT is mediated by interactions with specific residues in the sixth transmembrane helix and third extracellular loop of the D3 receptor. We also show that unlike cis-8-OH-PBZI, which is a partial agonist at the dopamine D2S receptor and full agonist at dopamine D2L receptor, trans-8-OH-PBZI is a full agonist at both D2S and D2L receptors. The different effect of the two isomers on D3 receptor signaling properties and D2S receptor activation correlated with differential effects of the isomers on agonist-induced mouse locomotor activity. The two isomers of 8-OH-PBZI represent novel pharmacological tools for in silico D3 and D2 receptor homology modeling and for determining the role of D3 receptor tolerance and SRT properties in signaling and behavior.

Elucidating substrate promiscuity in the human cytochrome 3A4.

The human cytochrome P450 enzymes (CYPs) are heme-protein monooxygenases, which catalyze oxidative reactions of a broad spectrum of substrates. Consequently, they play a critical role in the metabolism of xenobiotics, such as drugs and carcinogens, and the catabolism of endogenous lipophilic factors. Bioavailability and toxicity, both of which can be related to CYPs, continue to pose problems in the development of new drugs. The isoform which metabolizes over one-third of drugs, CYP 3A4, was investigated employing ensemble-docking experiments of a 195-substrate library with induced fit and GOLD docking algorithms and a number of scoring functions. Enzyme conformations included three currently available CYP 3A4 crystal structures. All docking experiments were performed in duplicates with and without inclusion of crystallographic waters. Resultant poses were assessed based on accuracy of site of metabolism prediction. Analyses of the docked solutions pertaining to ranking efficacy, ligand molecular properties, stabilizing residues in the ligand-enzyme complexes, and metabolic reactions are discussed. Our analyses suggest that certain residues make favorable interactions with the bound substrates. Employing multiple receptor conformations enhances the accuracy of catalytic prediction, while ligand size and flexibility impact docking performance. The presence of waters observed in crystal complexes does not necessarily lead to improved performance.

Identification of novel Interleukin-2 inhibitors through computational approaches.

Interleukin-2 (IL-2), is a 15.5-kDa cytokine that is now emerging as a target in drug discovery for novel therapeutic approaches in several autoimmune disorders. In an attempt to identify new inhibitors for the IL-2/IL-2R interaction, virtual screening (VS) was performed. Four different docking programs (GOLD, FlexX, Glide, and LigandFit) in combination with several scoring functions were used to identify novel IL-2/IL-2R interaction inhibitors.VSof a database of 6,000compounds resulted in the identification of three novel and moderately active hits with IC50 values ranging from 6.6 to 44.3 µM. Furthermore, the effect of these three compounds on the expression of IL-2Rα was assessed. The three active hits showed dose-dependent inhibitory effects on the expression of IL-2Rα with an IC50 range of 5.8 to 140µM. The cytotoxicity of these active hits was assessed using three normal cell-lines: bovine kidney cell-line (MDBK), mouse fibroblast cell-line (3T3), and rat hepatocytes cell-line (CC-1).Thecompoundswere found to have negligible cytotoxicity compared to their IC50 as IL-2/IL-2R interaction inhibitors. These results demonstrate that our VS protocol can identify novel inhibitors for IL-2/IL-2R interaction that effectively suppress IL-2 production, as well as the expression of IL-2Rα. Optimization of these molecules could lead to improved and effective anti-inflammatory therapeutics.

Functional prediction of binding pockets.

Putative function for targets with no known ligands has typically been determined from liganded homologous proteins using sequence and structure comparisons. However, it is debatable what percentage of sequence identity implies similar function, whereas structural similarity is focused on global folds and could miss divergent structures and novel global folds. The present study describes an approach to classify a diverse set of proteins and predict their function. Descriptors corresponding to structural, physicochemical, and geometric properties of the ligand-binding cavities of a collection of 434 complexes (17 protein families) were calculated and analyzed by statistical methods. The best model using discriminant function analysis (DFA) consisted of 371 proteins (15 families) and had correct classification rates of 90% and cross-validation 86%. DFA with one protein and a random sample of the remaining proteins led to 100% correct prediction of putative protein function for 10 of the 15 protein families.

A structure-based approach to understanding somatostatin receptor-4 agonism (sst4).

It has been reported that somatostatin receptor subtypes 4 and 5 would be high-impact templates for homology modeling if their 3D structures became available. We have generated a homology model of the somatostatin receptor subtype 4 (sst4), using the newest active state ß(2) adrenoreceptor crystal structure, and subsequently docked a variety of agonists into the model-built receptor to elucidate the binding modes of reported agonists. Using experimental restraints, we were able to explain observed activity profiles. We propose two binding modes that can consistently explain findings for high-affinity agonists and reason why certain structures display low affinities for the receptor.

Theoretical and practical considerations in virtual screening: a beaten field?

In this review, several aspects of virtual screening are presented. Although, docking and scoring have been the most widely employed techniques, ligand-based virtual screening has also gained momentum in recent years. We have classified the docking programs into four categories, based on their underline theories, and accordingly describe the most up-to-date algorithms and newest versions. Similarly, three categories of scoring functions are presented, while their weighting schemes on particular binding terms are discussed. The latter is important, since knowledge of the function can be used to select the ones that could be more appropriate for targets of similar nature. Challenging aspects, such as protein flexibility and practices to select the most appropriate docking/scoring schemes, are also discussed. Finally, a real-life example is presented where a pharmacophore-driven approach combined with a docking exercise were undertaken in an iterative manner to successfully enhance the virtual screening hit rates. In the end, we present our own perspective for best practices in the field based on our experiences.

Design and synthesis of novel N-sulfonyl-2-indole carboxamides as potent PPAR-gamma binding agents with potential application to the treatment of osteoporosis.

The synthesis and structure-activity relationships of a novel series of N-sulfonyl-2-indole carboxamides that bind to peroxisome proliferator-activated receptor gamma (PPAR-gamma) are reported. Chemical optimization of the series led to the identification of 4q (IC(50)=50 nM) as a potent binding agent of PPAR-gamma. Also reported is preliminary cell based data suggesting the use of these compounds in the treatment of osteoporosis.

Evaluation of library ranking efficacy in virtual screening.

We present the results of a comprehensive study in which we explored how the docking procedure affects the performance of a virtual screening approach. We used four docking engines and applied 10 scoring functions to the top-ranked docking solutions of seeded databases against six target proteins. The scores of the experimental poses were placed within the total set to assess whether the scoring function required an accurate pose to provide the appropriate rank for the seeded compounds. This method allows a direct comparison of library ranking efficacy. Our results indicate that the LigandFit/Ligscore1 and LigandFit/GOLD docking/scoring combinations, and to a lesser degree FlexX/FlexX, Glide/Ligscore1, DOCK/PMF (Tripos implementation), LigandFit1/Ligscore2 and LigandFit/PMF (Tripos implementation) were able to retrieve the highest number of actives at a 10% fraction of the database when all targets were looked upon collectively. We also show that the scoring functions rank the observed binding modes higher than the inaccurate poses provided that the experimental poses are available. This finding stresses the discriminatory ability of the scoring algorithms, when better poses are available, and suggests that the number of false positives can be lowered with conformers closer to bioactive ones.

Ab Initio and DFT Conformational Studies of Propanal, 2-Butanone, and Analogous Imines and Enamines.

The potential energy surfaces (PES) of 2-butanone, 2-butanimine, 1-butenamine, propanal, and propanimine have been explored with ab initio and DFT calculations at the RHF/6-311G**, MP2/6-311G**, and B3LYP/6-311G** levels of theory. In agreement with previous experimental and computational results, the PES provides two minima for each of the above molecules with the exception of 2-butanone, which clearly shows three distinct minima. Factors influencing the conformational preferences are also elaborated. Our calculations suggest that for 2-butanone and propanal, the steric and the bond dipole interactions are primarily responsible for the conformational preferences of these compounds. Additional charge-charge interactions might also play an important role in determining the imine conformations. For enamines, however, steric interactions play a critical role, with bond dipole interactions exerting some influence. Our results also suggest that for imine formation from butanone and/or propanal, the imine is the predominant product, not the enamine, which is consistent with experimental observations. Therefore, these calculations should provide a better understanding of the ketone/aldehyde to imine and enamine transformations. This transformation may introduce an important imine moiety for the analogues of trans-N-methyl-4-(1-naphthylvinyl)pyridine (NVP), a choline acetyltransferase (ChAT) inhibitor.