Progress in structure-based drug design against influenza A virus

Introduction: The 2009-H1N1 influenza pandemic has prompted new global efforts to develop new drugs and drug design techniques to combat influenza viruses. While there have been a number of attempts to provide drugs to treat influenza, drug resistance has been a major problem with only four drugs currently approved by the FDA for its treatment.

Areas covered: In this review, the drug-resistant problem of influenza A viruses is discussed and summarized. The article also introduces the experimental and computational structures of drug targeting proteins, neuraminidases, and of the M2 proton channel. Furthermore, the article illustrates the latest drug candidates and techniques of computer-aided drug design with examples of their application, including virtual in silico screening and scoring, AutoDock and evolutionary technique AutoGrow.

Expert opinion: Structure-based drug design is the inventive process for finding new drugs based on the structural knowledge of the biological target. Computer-aided drug design strategies and techniques will make drug discovery more effective and economical. It is anticipated that the recent advances in structure-based drug design techniques will greatly help scientists to develop more powerful and specific drugs to fight the next generation of influenza viruses.     

Progress in structure-based drug design against influenza A virus

Introduction: The 2009-H1N1 influenza pandemic has prompted new global efforts to develop new drugs and drug design techniques to combat influenza viruses. While there have been a number of attempts to provide drugs to treat influenza, drug resistance has been a major problem with only four drugs currently approved by the FDA for its treatment. Areas covered: In this review, the drug-resistant problem of influenza A viruses is discussed and summarized. The article also introduces the experimental and computational structures of drug targeting proteins, neuraminidases, and of the M2 proton channel. Furthermore, the article illustrates the latest drug candidates and techniques of computer-aided drug design with examples of their application, including virtual in silico screening and scoring, AutoDock and evolutionary technique AutoGrow. Expert opinion: Structure-based drug design is the inventive process for finding new drugs based on the structural knowledge of the biological target. Computer-aided drug design strategies and techniques will make drug discovery more effective and economical. It is anticipated that the recent advances in structure-based drug design techniques will greatly help scientists to develop more powerful and specific drugs to fight the next generation of influenza viruses.     

Targeting the Plasmodium falciparum plasmepsin V by ligand‐based virtual screening

Malaria is a devastating disease depending only on chemotherapy as treatment. However, medication is losing efficacy, and therefore, there is an urgent need for the discovery of novel pharmaceutics. Recently, plasmepsin V, an aspartic protease anchored in the endoplasmaic reticulum, was demonstrated as responsible for the trafficking of parasite‐derived proteins to the erythrocytic surface and further validated as a drug target. In this sense, ligand‐based virtual screening has been applied to design inhibitors that target plasmepsin V of P. falciparum (PMV). After screening 5.5 million compounds, four novel plasmepsin inhibitors have been identified which were subsequently analyzed for the potency at the cellular level. Since PMV is membrane‐anchored, the verification in vivo by using transgenic PMV overexpressing P. falciparum cells has been performed in order to evaluate drug efficacy. Two lead compounds, revealing IC₅₀ values were 44.2 and 19.1 μm , have been identified targeting plasmepsin V in vivo and do not significantly affect the cell viability of human cells up to 300 μm . We herein report the use of the consensus of individual virtual screening as a new technique to design new ligands, and we propose two new lead compounds as novel protease inhibitors to target malaria.     

In search of novel protein drug targets for treatment of Enterococcus faecalis infections

Enterococcus faecalis (Ef) is one of the major pathogens involved in hospital‐acquired infections. It can cause nosocomial bacteremia, surgical wound infection, and urinary tract infection. It is important to mention here that Ef is developing resistance against many commonly occurring antibiotics. The occurrence of multidrug resistance (MDR) and extensive‐drug resistance (XDR) is now posing a major challenge to the medical community. In this regard, to combat the infections caused by Ef, we have to look for an alternative. Rational structure‐based drug design exploits the three‐dimensional structure of the target protein, which can be unraveled by various techniques such as X‐ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. In this review, we have discussed the complete picture of Ef infections, the possible treatment available at present, and the alternative treatment options to be explored. This study will help in better understanding of novel biological targets against Ef and the compounds, which are likely to bind with these targets. Using these detailed structural informations, rational structure‐based drug design is achievable and tight inhibitors against Ef can be prepared.     

Analysis of c‐Met Kinase Domain Complexes: A New Specific Catalytic Site Receptor Model for Defining Binding Modes of ATP‐Competitive Ligands

The receptor tyrosine kinase c‐Met have multiple roles during cancer development and is currently considered as an important target for molecularly targeted therapies. Structural knowledge of how compounds interact on c‐Met catalytic site could guide structure‐based drug design strategies towards more effective and selective anticancer drug candidates. However, although 17 crystal structures of c‐Met complexed with adenosine triphosphate (ATP)‐competitive kinase inhibitors are publicly available (August 2009), there are still open questions regarding the prediction of ligand binding modes. We have applied molecular modeling and molecular mechanics to analyze the distribution of ligands interaction energy on c‐Met residues, and deduced a new model of the active site allowing for an unambiguous identification of ligand binding modes. We demonstrate that the binding of known ligands on the c‐Met catalytic site involves seven identified structurally‐distinct areas. Five of these match the generic kinase ATP binding site model built by Novartis scientists in the 1990s, while the two others are distinct allosteric regions that can be exploited by second generation kinase inhibitors such as Gleevec. We show here that c‐Met can accept both such kinds of allosteric inhibitors, a very unusual feature in the kinase family that opens new grounds for highly specific drug design.     

The importance of employing computational resources for the automation of drug discovery

Introduction: The application of computational tools to drug discovery helps researchers to design and evaluate new drugs swiftly with a reduce economic resources. To discover new potential drugs, computational chemistry incorporates automatization for obtaining biological data such as adsorption, distribution, metabolism, excretion and toxicity (ADMET), as well as drug mechanisms of action.

Areas covered: This editorial looks at examples of these computational tools, including docking, molecular dynamics simulation, virtual screening, quantum chemistry, quantitative structural activity relationship, principal component analysis and drug screening workflow systems. The authors then provide their perspectives on the importance of these techniques for drug discovery.

Expert opinion: Computational tools help researchers to design and discover new drugs for the treatment of several human diseases without side effects, thus allowing for the evaluation of millions of compounds with a reduced cost in both time and economic resources. The problem is that operating each program is difficult; one is required to use several programs and understand each of the properties being tested. In the future, it is possible that a single computer and software program will be capable of evaluating the complete properties (mechanisms of action and ADMET properties) of ligands. It is also possible that after submitting one target, this computer–software will be capable of suggesting potential compounds along with ways to synthesize them, and presenting biological models for testing.     

Discovery of potential Toxoplasma gondii CDPK1 inhibitors with new scaffolds based on the combination of QSAR and scaffold‐hopping method with in vitro validation

To discover drugs for toxoplasmosis with less side‐effects and less probability to get drug resistance is eagerly appealed for pregnant women, infant or immunocompromised patients. In this work, using TgCDPK1 as drug target, we design a method to discover new inhibitors for CDPK1 as potential drug lead for toxoplasmosis with novel scaffolds based on the combination of 2D/3D‐QSAR and scaffold‐hopping methods. All the binding sites of the potential inhibitors were checked by docking method, and only the ones that docked to the most conserved sites of TgCDPK1, which make them have less probability to get drug resistance, were remained. As a result, 10 potential inhibitors within two new scaffolds were discovered for TgCDPK1 with experimentally verified inhibitory activities in micromole level. The discovery of these inhibitors may contribute to the drug development for toxoplasmosis. Besides, the pipeline which is composed in this work as the combination of QSAR and scaffold‐hopping is simple, easy to repeat for researchers without need of in‐depth knowledge of pharmacology to get inhibitors with novel scaffolds, which will accelerate the procedure of drug discovery and contribute to the drug repurposing study.     

De novo design: balancing novelty and confined chemical space

Importance of the field: De novo drug design serves as a tool for the discovery of new ligands for macromolecular targets as well as optimization of known ligands. Recently developed tools aim to address the multi-objective nature of drug design in an unprecedented manner.

Areas covered in this review: This article discusses recent advances in de novo drug design programs and accessory programs used to evaluate compounds post-generation.

What the reader will gain: The reader is introduced to the challenges inherent in de novo drug design and will become familiar with current trends in de novo design. Furthermore, the reader will be better prepared to assess the value of a tool, and be equipped to design more elegant tools in the future.

Take home message: De novo drug design can assist in the efficient discovery of new compounds with a high affinity for a given target. The inclusion of existing chemoinformatic methods with current structure-based de novo design tools provides a means of enhancing the therapeutic value of these generated compounds.     

Insights into the Interaction Mechanism of Ligands with Aβ42 Based on Molecular Dynamics Simulations and Mechanics: Implications of Role of Common Binding Site in Drug Design for Alzheimer's Disease

Aggregation of β‐amyloid (Aβ) into oligomers and further into fibrils is hypothesized to be a key factor in pathology of Alzheimer's disease (AD). In this study, mapping and docking were used to study the binding of ligands to protofibrils. It was followed by molecular simulations to understand the differences in interactions of known therapeutic agents such as curcumin, fluorescence‐based amyloid staining agents such as thioflavin T, and diagnostic agents such as florbetapir (AV45), with Aβ protofibrils. We show that therapeutic agents bind to and distort the protofibrils, thus causing destabilization or prevention of oligomerization, in contrast to diagnostic agents which bind to but do not distort such structures. This has implications in the rational design of ligands, both for diagnostics and therapeutics of AD.     

A high‐quality homology model for the human dopamine transporter validated for drug design purposes

The human dopamine transporter (hDAT) plays many vital functions within the central nervous system and is thus targeted by many pharmaceutical agents. Dopamine‐related therapies are in current development for individuals with dopamine‐related disorders including depression, Parkinson's disease, and psychostimulant addictions such as cocaine abuse. Yet, most efforts to develop new dopamine therapies are within costly structure–activity relationship studies. Through structure‐based drug design techniques, the binding site of hDAT can be utilized to develop novel selective and potent dopamine therapies at reduced costs. However, no structural models of hDAT specifically validated for rational drug design purposes currently exist. Here, using the Drosophila dopamine transporter as a template, a homology model for the hDAT was developed and validated. The model was able to reproduce experimental binding modes with great accuracy, was able to rank inhibitors in the correct order of increasing potency with an R² value of 0.81 for the test set, and it also outperformed other published hDAT models. Thus, the model can be used reliably in structure‐based drug design projects.     

Development of highly potent and ective dynorphin A analogues as new medicines

Abstract: Dynorphin A (Dyn A), a 17 amino acid peptide H‐Tyr‐Gly‐Gly‐Phe‐Leu‐Arg‐Arg‐Ile‐Arg‐Pro‐Lys‐Leu‐Lys‐Trp‐Asp‐Asn‐Gln‐OH, is a potent opioid peptide which interacts preferentially with κ‐opioid receptors. Research in the development of selective and potent opioid peptide ligands for the κ‐receptor is important in mediating analgesia. Several cyclic disulphide bridge‐containing peptide analogues of Dyn A, which were conformationally constrained in the putative message or address segment of the opioid ligand, were designed, synthesized and assayed. To further investigate the conformational and topographical requirements for the residues in positions 5 and 11 of these analogues, a systematic series of Dyn A_1?11‐NH₂ cyclic analogues incorporating the sulphydryl‐containing amino acids l ‐ and d ‐Cys and l ‐ and d ‐Pen in positions 5 and 11 were synthesized and assayed. Cyclic lactam peptide analogues were also synthesized and assayed. Several of these cyclic analogues, retained the same affinity and selectivity (vs. the μ‐ and δ‐receptors) as the parent Dyn A_1?11‐NH₂ peptide in the guinea‐pig brain (GPB), but exhibited a much lower activity in the guinea‐pig ileum (GPI), thus leading to centrally vs. peripherally selective peptides. Studies of the structure–activity relationship of Dyn A peptide provide new insights into the importance of each amino acid residue (and their configurations) in Dyn A analogues for high potency and good selectivity at κ‐opioid receptors. We report herein the progress towards the development of Dyn A peptide ligands, which can act as agonists or antagonists at cell surface receptors that modulate cell function and animal behaviour using various approaches to rational peptide ligand‐based drug design.     

Documenting and harnessing the biological potential of molecules in Distributed Drug Discovery (D3) virtual catalogs

Virtual molecular catalogs have limited utility if member compounds are (i) difficult to synthesize or (ii) unlikely to have biological activity. The Distributed Drug Discovery (D3) program addresses the synthesis challenge by providing scientists with a free virtual D3 catalog of 73,024 easy‐to‐synthesize N‐acyl unnatural α‐amino acids, their methyl esters, and primary amides. The remaining challenge is to document and exploit the bioactivity potential of these compounds. In the current work, a search process is described that retrospectively identifies all virtual D3 compounds classified as bioactive hits in PubChem‐cataloged experimental assays. The results provide insight into the broad range of drug‐target classes amenable to inhibition and/or agonism by D3‐accessible molecules. To encourage computer‐aided drug discovery centered on these compounds, a publicly available virtual database of D3 molecules prepared for use with popular computer docking programs is also presented.     

Testing of Insulin Hexamer-Stabilizing Ligands Using Theoretical Binding,Microcalorimetry, and Nuclear Magnetic Resonance (NMR) Line Broadening Techniques

In a study aimed at the development of a long-acting insulin preparation, Manallack and co-workers (5) reported on the design of small organic molecules which have the potential to bind to insulin and stabilize its hexameric aggregate. Two of the molecules that were designed with their computer graphics program were thought to be particularly promising as ligands: benzene-p-disulfonate and benzene-p-diphosphonate. In the present work, the insulin binding abilities of these molecules have been thoroughly tested. A theoretical binding program, GRID, was used to calculate the binding energetics of the molecules and to predict the most probable site of their binding. Microcalorimetry and NMR line broadening techniques were used to measure the actual binding reactions of the ligands. For both compounds, no evidence of binding to insulin was ever observed in either the microcalorimetry or the NMR studies. In contrast, a series of phenolic ligands commonly used as preservatives for insulin showed evidence of substantial binding using either method. An explanation has been proposed for this apparent discrepancy between computer predictions and actual experimental data: The theoretical programs do not take solvation effects of the aqueous medium into account. Solvation effects would tend to inhibit binding of the ionized ligand molecules due to charge delocalization and steric crowding.     

Design and Synthesis of Nicotinic Acetylcholine Receptor Antagonists and their Effect on Cognitive Impairment

Structure modification of a lead compound (NSC13378) was accomplished in the present work by an in silico target‐based design aimed at ligands acting on the nicotinic acetylcholine receptor (nAChR) for neurodegenerative diseases. A 187‐compound focused library derived from the scaffold of the lead compound was screened against acetylcholine‐binding proteins (AChBPs). Six compounds were identified and synthesized for binding and biological evaluations. Five compounds were found to bind with AChBPs. Among these compounds, QN 1 and BZ 1 showed the highest affinity binding with AChBP, with K_d values of 260 and 10 nm , respectively. Functional assays on isolated cell lines containing ligand‐gated ion channels revealed that QN 1 and BZ 1 are α 4 β 2‐nAChR antagonists. QN 1 and BZ 1 significantly alleviated the memory impairment caused by the muscarinic cholinergic antagonist scopolamine (p < 0.05) in mice. Our findings demonstrate the potential of nAChR antagonists in drug development for cognitive impairments.     

Towards the development of novel Trypanosoma brucei RNA editing ligase 1 inhibitors

Background

Trypanosoma brucei (T. brucei) is an infectious agent for which drug development has been largely neglected. We here use a recently developed computer program called AutoGrow to add interacting molecular fragments to S5, a known inhibitor of the validated T. brucei drug target RNA editing ligase 1, in order to improve its predicted binding affinity.

Results

The proposed binding modes of the resulting compounds mimic that of ATP, the native substrate, and provide insights into novel protein-ligand interactions that may be exploited in future drug-discovery projects.

Conclusions

We are hopeful that these new predicted inhibitors will aid medicinal chemists in developing novel therapeutics to fight human African trypanosomiasis.     

In vivo saturation binding of GABA‐A receptor ligands to estimate receptor occupancy using liquid chromatography/tandem mass spectrometry

Typically, the dose‐occupancy curves for GABA‐A receptor ligands are determined using in vivo binding of [³H]flumazenil. This study describes in vivo binding experiments without the use of tracer ligands. Bound and free fractions were measured directly using a highly sensitive LC/MS/MS detection method after in vivo administration of the GABA‐A ligands zolpidem, (RS)‐zopiclone, L‐838417 and flumazenil, to demonstrate affinity and saturation of the filter‐retained, membrane‐bound fraction. The in vivo binding of flumazenil and L‐838417 both saturated around 200 nm , at a similar level to the specific binding of (S)‐zopiclone after doses of the racemic zopiclone, using (R)‐zopiclone to estimate non‐specific binding. This saturable component represented an estimate of benzodiazepine binding sites available on GABA‐A receptors in vivo (200 nm ). Dose‐occupancy curves were constructed to estimate the dose required to achieve 50% occupancy and matched estimates obtained with tracer methods. In contrast to tracer methods, this method is uniquely suitable to the demonstration of stereoselective binding of the (S)‐isomer in vivo after doses of racemic zopiclone. These results demonstrate that the LC/MS/MS measurements of total drug concentrations typically used in early drug development can be adapted to provide information about receptor occupancy in vivo. Copyright © 2009 John Wiley & Sons, Ltd.     

Predicting molecular interactions in silico: I. A guide to pharmacophore identification and its applications to drug design

A major goal in contemporary drug design is to develop new ligands with high affinity of binding toward a given protein receptor. Pharmacophore, which is the three-dimensional arrangement of essential features that enable a molecule to exert a particular biological effect, is a very useful model for achieving this goal. If the three dimensional structure of the receptor is known, pharmacophore is a complementary tool to standard techniques, such as docking. However, frequently the structure of the receptor protein is unknown and only a set of ligands together with their measured binding affinities towards the receptor is available. In such a case, a pharmacophore based strategy is one of the few applicable tools. Here we present a broad, yet concise guide to pharmacophore identification and review a sample of applications for drug design. In particular, we present the framework of the algorithms, classify their modules and point out their advantages and challenges.     

Insight into the binding mode for cyclopentapeptide antagonists of the CXCR4 receptor

The finding that the chemokine receptor CXCR4 is involved in T‐cell HIV entry has encouraged the development of antiretroviral drugs targeting this receptor. Additional evidence that CXCR4 plays a crucial role in both angiogenesis and metastasis provides further motivation for the development of a CXCR4 inhibitor for therapeutic applications in oncology. To facilitate the design of such ligands, we have investigated the possible binding modes for cyclopentapeptide CXCR4 antagonists by docking 11 high/medium affinity cyclopentapeptides to a developed three‐dimensional model of the CXCR4 G‐protein‐coupled receptor's transmembrane region. These ligands, expected to bind in the same mode to the receptor, were docked in the previously deduced receptor‐bound conformation [Våbenøet al., in press; doi 10.1002/bip.20508]. Ligand–receptor complexes were generated using an automated docking procedure that allowed ligand flexibility. By comparing the resulting ligand poses, only two binding modes common for all 11 compounds were identified. Inspection of these two ligand–receptor complexes identified several CXCR4 contact residues shown by mutation to be interaction sites for ligands and important for HIV gp120 binding. Thus, the results provide further insight into the mechanism by which these cyclopentapeptides block HIV entry as well as a basis for rational design of CXCR4 mutants to map potential contacts with small peptide ligands.     

Evidence‐based policy or policy‐based evidence? The role of evidence in the development and implementation of the Illicit Drug Diversion Initiative

Issues . Evidence‐based policy is promoted as the ideal in drug policy, yet public policy theorists suggest that policy‐based evidence may be a more fitting analogy, where evidence is used selectively to support a predetermined policy direction. Approach . The following paper assesses the resonance of this notion to the development of the Illicit Drug Diversion Initiative (IDDI), an apparently pragmatic reform adopted in Australia in 1999 through the Federal Coalition ‘Tough on Drugs’ strategy. It utilises interviews with key informants from the Australian drug policy arena conducted in 2005 to assess the role of evidence in the design and implementation of the IDDI. Key Findings . The current paper shows that while policy‐makers were generally supportive of the IDDI and viewed drug diversion as a more pragmatic response to drug users, they contend that implementation has suffered through a selective and variable emphasis upon evidence. Most notably, the IDDI is not premised upon best‐practice objectives of reducing harm from drug use, but instead on ‘Tough on Drugs’ objectives of reducing drug use and crime. Implications . This paper contends that policy‐based evidence may facilitate the adoption of pragmatic reforms, but reduce the capacity for effective reform. It therefore has both functional and dysfunctional elements. Conclusion . The paper concludes that greater attention is needed to understanding how to mesh political and pragmatic objectives, and hence to maximise the benefits from policy‐based evidence. [Hughes CE. Evidence‐based policy or policy‐based evidence? The role of evidence in the development and implementation of the Illicit Drug Diversion Initiative. Drug Alcohol Rev 2007;26:363–368]