Development of neuraminidase inhibitors as anti-influenza virus drugs

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

Latest trends in structure based drug design with protein targets

Structure based drug designing is an important endeavor in the field of structural bioinformatics. Previously the entire process was dependent on the wet-lab experiments to build libraries of ligand molecules. And the molecules used to be tested to determine their binding efficacies with protein target. However, the entire process is very lengthy and above all highly expensive. With the advent of supercomputers and increasing computational powers, the search process for finding suitable ligand molecules against target proteins have become more streamlined and cost-effective. Now the entire ligand search process is performed in-silico with the help of the techniques of virtual screening, molecular docking simulations and molecular dynamics studies. In the present chapter, a brief overview of the computational techniques involved in structure based drug designing is presented with a special emphasis on the thermodynamic principles behind the molecular interactions.

Epidemics and Peptide Vaccine Response: A Brief Review

We briefly review the situations arising out of epidemics that erupt rather suddenly, threatening life and livelihoods of humans. Ebola, Zika and the Nipah virus outbreaks are recent examples where the viral epidemics have led to considerably high degree of fatalities or debilitating consequences. The problems are accentuated by a lack of drugs or vaccines effective against the new and emergent viruses, and the inordinate amount of temporal and financial resources that are required to combat the novel pathogens. Progress in computational, biological and informational sciences have made it possible to consider design of synthetic vaccines that can be rapidly developed and deployed to help stem the damages. In this review, we consider the pros and cons of this new paradigm and suggest a new system where the manufacturing process can be decentralized to provide more targeted vaccines to meet the urgent needs of protection in case of a rampaging epidemic.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the "golden age for GPCR structural biology." Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand- and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

Evaluation of the potential defensive strategy against Influenza A in cell line models

Background: Influenza virus can cause both seasonal infections and unpredictable pandemics. Rapidly evolving avian H5N1 and  H7N9 viruses have a potential pandemic threat for humans. Since avian Influenza can be transmitted by domestic birds, serving as a key link between wild birds and humans, an effective measure to control the influenza transmission would be eradication of the infection in poultry. It is known that the virus penetrates into the cell through binding with the terminal oligosaccharides - sialic acids (SA) - on the cell surfaces. Removal of SA might be a potential antiviral strategy. An approach to developing chicken lines that are resistant to influenza viruses could be the creation of genetically modified birds. Thus it is necessary to select a gene that provides defense to influenza. Here we have expressed in cells a range of exogenous sialidases and estimated their activity and specificity towards SA residues. Methods: Several bacterial, viral and human sialidases were tested. We adopted bacterial sialidases from Salmonella and Actinomyces for expression on the cell surface by fusing catalytic domains with transmembrane domains. We also selected Influenza A/PuertoRico/8/34/H1N1 neuraminidase and human membrane sialidase ( hNeu3) genes. Lectin binding assay was used for estimation of a α (2,3)-sialylation level by fluorescent microscopy and FACS.   Results: We compared sialidases from bacteria, Influenza virus and human. Sialidases from Salmonella and Influenza A neuraminidase effectively cleaved α (2-3)-SA receptors. Viral neuraminidase demonstrated a higher activity. Sialidases from Actinomyces and hNeu3 did not show any activity against α (2-3) SA under physiological conditions. Conclusion: Our results demonstrated that sialidases with different specificity and activity can be selected as genes providing antiviral defence. Combining chosen sialidases with different activity together with tissue-specific promoters would provide an optimal level of desialylation. Tissue specific expression of the sialidases could protect domestic birds from infection.

Evaluation of defense strategy against Influenza A in cell line models

Background: Influenza virus can cause both seasonal infections and unpredictable pandemics. Rapidly evolving avian H5N1 virus is getting increasingly infective for humans. Since avian Influenza can be transmitted by domestic birds, serving as a key link between wild aquatic birds and humans, an effective measure to control the influenza transmission would be eradication of the infection in poultry. It is known that the virus penetrates into the cell through binding with the terminal oligosaccharides - sialic acids (SA) - on the cell surfaces. Removal of SA might be a potential antiviral strategy. An approach to developing chicken lines that are resistant to influenza viruses could be the creation of genetically modified birds. Thus it is necessary to select a gene that provides defense to influenza. Here we have expressed in cells a range of exogenous sialidases and estimated their activity and specificity towards SA residues. Methods: Several bacterial, viral and human sialidases were tested. We adopted bacterial sialidases from Salmonella and Actinomyces for expression on the cell surface by fusing catalytic domains with transmembrane domains. We also selected Influenza A/PuertoRico/8/34/H1N1 neuraminidase and human membrane sialidase ( hNeu3) genes. Lectin binding assay was used for estimation of a α (2,3)-sialylation level by fluorescent microscopy and FACS.   Results: We compared sialidases from bacteria, Influenza virus and human. Sialidases from Salmonella and Influenza A neuraminidase effectively cleaved α (2-3)-SA receptors. Viral neuraminidase demonstrated a higher activity. Sialidases from Actinomyces and hNeu3 did not show any activity against α (2-3) SA under physiological conditions. Conclusion: Our results demonstrated that sialidases with different specificity and activity can be selected as genes providing antiviral defence. Combining chosen sialidases with different activity together with tissue-specific promoters would provide an optimal level of desialilation to prevent infection. Tissue specific expression of the sialidases could protect domestic birds from infection.

Trends in GPCR drug discovery: new agents, targets and indications

G protein-coupled receptors (GPCRs) are the most intensively studied drug targets, mostly due to their substantial involvement in human pathophysiology and their pharmacological tractability. Here, we report an up-to-date analysis of all GPCR drugs and agents in clinical trials, which reveals current trends across molecule types, drug targets and therapeutic indications, including showing that 475 drugs (~34% of all drugs approved by the US Food and Drug Administration (FDA)) act at 108 unique GPCRs. Approximately 321 agents are currently in clinical trials, of which ~20% target 66 potentially novel GPCR targets without an approved drug, and the number of biological drugs, allosteric modulators and biased agonists has increased. The major disease indications for GPCR modulators show a shift towards diabetes, obesity and Alzheimer disease, although several central nervous system disorders are also highly represented. The 224 (56%) non-olfactory GPCRs that have not yet been explored in clinical trials have broad untapped therapeutic potential, particularly in genetic and immune system disorders. Finally, we provide an interactive online resource to analyse and infer trends in GPCR drug discovery.

Mix-and-diffuse serial synchrotron crystallography

Unravelling the interaction of biological macromolecules with ligands and substrates at high spatial and temporal resolution remains a major challenge in structural biology. The development of serial crystallography methods at X-ray free-electron lasers and subsequently at synchrotron light sources allows new approaches to tackle this challenge. Here, a new polyimide tape drive designed for mix-and-diffuse serial crystallography experiments is reported. The structure of lysozyme bound by the competitive inhibitor chitotriose was determined using this device in combination with microfluidic mixers. The electron densities obtained from mixing times of 2 and 50 s show clear binding of chitotriose to the enzyme at a high level of detail. The success of this approach shows the potential for high-throughput drug screening and even structural enzymology on short timescales at bright synchrotron light sources.

Molecular Basis for Differential Patterns of Drug Resistance in Influenza N1 and N2 Neuraminidase

Neuraminidase (NA) inhibitors are used for the prevention and treatment of influenza A virus infections. Two subtypes of NA, N1 and N2, predominate in viruses that infect humans, but differential patterns of drug resistance have emerged in each subtype despite highly homologous active sites. To understand the molecular basis for the selection of these drug resistance mutations, structural and dynamic analyses on complexes of N1 and N2 NA with substrates and inhibitors were performed. Comparison of dynamic substrate and inhibitor envelopes and interactions at the active site revealed how differential patterns of drug resistance have emerged for specific drug resistance mutations, at residues I222, S246, and H274 in N1 and E119 in N2. Our results show that the differences in intermolecular interactions, especially van der Waals contacts, of the inhibitors versus substrates at the NA active site effectively explain the selection of resistance mutations in the two subtypes. Avoiding such contacts that render inhibitors vulnerable to resistance by better mimicking the dynamics and intermolecular interactions of substrates can lead to the development of novel inhibitors that avoid drug resistance in both subtypes.

Structural biology in antiviral drug discovery

Structural biology has emerged during the last thirty years as a powerful tool for rational drug discovery. Crystal structures of biological targets alone and in complex with ligands and inhibitors provide essential insights into the mechanisms of actions of enzymes, their conformational changes upon ligand binding, the architectures and interactions of binding pockets. Structure-based methods such as crystallographic fragment screening represent nowadays invaluable instruments for the identification of new biologically active compounds. In this context, three-dimensional protein structures have played essential roles for the understanding of the activity and for the design of novel antiviral agents against several different viruses. In this review, the evolution in the resolution of viral structures is analysed, along with the role of crystal structures in the discovery and optimisation of new antivirals.

A Brief Review of Computer-Assisted Approaches to Rational Design of Peptide Vaccines

The growing incidences of new viral diseases and increasingly frequent viral epidemics have strained therapeutic and preventive measures; the high mutability of viral genes puts additional strains on developmental efforts. Given the high cost and time requirements for new drugs development, vaccines remain as a viable alternative, but there too traditional techniques of live-attenuated or inactivated vaccines have the danger of allergenic reactions and others. Peptide vaccines have, over the last several years, begun to be looked on as more appropriate alternatives, which are economically affordable, require less time for development and hold the promise of multi-valent dosages. The developments in bioinformatics, proteomics, immunogenomics, structural biology and other sciences have spurred the growth of vaccinomics where computer assisted approaches serve to identify suitable peptide targets for eventual development of vaccines. In this mini-review we give a brief overview of some of the recent trends in computer assisted vaccine development with emphasis on the primary selection procedures of probable peptide candidates for vaccine development.

Inhibitors of the human neuraminidase enzymes

A review of known small molecule inhibitors and substrates of the human neuraminidase enzymes.

Current Challenges and Trends in the Discovery of Agrochemicals

Crop protection chemistry has come a long way from its “alchemic” beginnings in the late 19th century to a high-tech science that supports the sustainable production of food, feed, and fiber for a rapidly growing population. Cutting-edge developments in the design and synthesis of agrochemicals help to tackle today’s challenges of weed and pest resistance, higher regulatory safety margins, and higher cost of goods with the invention of selective, environmentally benign, low use rate, and cost-effective active ingredients.

Immobilized sialyloligo-macroligand and its protein binding specificity

We report a chemoenzymatic synthesis of chain-end functionalized sialyllactose-containing glycopolymers with different linkages and their oriented immobilization for glycoarray and SPR-based glyco-biosensor applications. Specifically, O-cyanate chain-end functionalized sialyllactose-containing glycopolymers were synthesized by enzymatic α2,3- and α2,6-sialylation of a lactose-containing glycopolymer that was synthesized by cyanoxyl-mediated free radical polymerization. (1)H NMR showed almost quantitative α2,3- and α2,6-sialylation. The O-cyanate chain-end functionalized sialyllactose-containing glycopolymers were printed onto amine-functionalized glass slides via isourea bond formation for glycoarray formation. Specific protein binding activity of the arrays was confirmed with α2,3- and α2,6-sialyl specific binding lectins together with inhibition assays. Further, immobilizing O-cyanate chain-end functionalized sialyllactose-containing glycopolymers onto amine-modified SPR chip via isourea bond formation afforded SPR-based glyco-biosensor, which showed specific binding activity for lectins and influenza viral hemagglutinins (HA). These sialyloligo-macroligand derived glycoarray and SPR-based glyco-biosensor are closely to mimic 3D nature presentation of sialyloligosaccharides and will provide important high-throughput tools for virus diagnosis and potential antiviral drug candidates screening applications.

Different inhibitory potency of febuxostat towards mammalian and bacterial xanthine oxidoreductases: insight from molecular dynamics

Febuxostat, a drug recently approved in the US, European Union and Japan for treatment of gout, inhibits xanthine oxidoreductase (XOR)-mediated generation of uric acid during purine catabolism. It inhibits bovine milk XOR with a K_i in the picomolar-order, but we found that it is a much weaker inhibitor of Rhodobacter capsulatus XOR, even though the substrate-binding pockets of mammalian and bacterial XOR are well-conserved as regards to catalytically important residues and three-dimensional structure, and both permit the inhibitor to be accommodated in the active site, as indicated by computational docking studies. To clarify the reason for the difference of inhibitory potency towards the two XORs, we performed molecular dynamics simulations. The results indicate that differences in mobility of hydrophobic residues that do not directly interact with the substrate account for the difference in inhibitory potency.

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing

BACKGROUND

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.

METHODOLOGY

In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.

CONCLUSIONS

The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

An overview on GPCRs and drug discovery: structure-based drug design and structural biology on GPCRs

G protein-coupled receptors (GPCRs) represent 50-60% of the current drug targets. There is no doubt that this family of membrane proteins plays a crucial role in drug discovery today. Classically, a number of drugs based on GPCRs have been developed for such different indications as cardiovascular, metabolic, neurodegenerative, psychiatric, and oncologic diseases. Owing to the restricted structural information on GPCRs, only limited exploration of structure-based drug design has been possible. Much effort has been dedicated to structural biology on GPCRs and very recently an X-ray structure of the beta2-adrenergic receptor was obtained. This breakthrough will certainly increase the efforts in structural biology on GPCRs and furthermore speed up and facilitate the drug discovery process.

Genomic-scale prioritization of drug targets: the TDR Targets database

The increasing availability of genomic data for pathogens that cause tropical diseases has created new opportunities for drug discovery and development. However, if the potential of such data is to be fully exploited, the data must be effectively integrated and be easy to interrogate. Here, we discuss the development of the TDR Targets database (http://tdrtargets.org), which encompasses extensive genetic, biochemical and pharmacological data related to tropical disease pathogens, as well as computationally predicted druggability for potential targets and compound desirability information. By allowing the integration and weighting of this information, this database aims to facilitate the identification and prioritization of candidate drug targets for pathogens.

Contribution of structural biology to clinically validated target proteins

We identified six groups of diseases expected to cause serious future health issues on the basis of a WHO report. Approved drugs for these diseases were associated with 409 target proteins; however, the percentage of selected proteins with full-length structural information deposited in the Protein Data Bank (PDB) was only 9.8%. The reason for the low percentage may be as a result of a disproportionate number of intractable proteins with multiple transmembrane regions and variable, or undefined glycosylation patterns, which impede protein preparation and crystallization, in such druggable proteins. We stress the importance of structural analysis of proteins, especially approved-drug target proteins, and the development of new methods to enable structural analyses of presently intractable proteins. In addition, we present an overview of large structural biology projects.

Structure of an IgNAR-AMA1 complex: targeting a conserved hydrophobic cleft broadens malarial strain recognition

Apical membrane antigen 1 (AMA1) is essential for invasion of erythrocytes and hepatocytes by Plasmodium parasites and is a leading malarial vaccine candidate. Although conventional antibodies to AMA1 can prevent such invasion, extensive polymorphisms within surface-exposed loops may limit the ability of these AMA1-induced antibodies to protect against all parasite genotypes. Using an AMA1-specific IgNAR single-variable-domain antibody, we performed targeted mutagenesis and selection against AMA1 from three P. falciparum strains. We present cocrystal structures of two antibody-AMA1 complexes which reveal extended IgNAR CDR3 loops penetrating deep into a hydrophobic cleft on the antigen surface and contacting residues conserved across parasite species. Comparison of a series of affinity-enhancing mutations allowed dissection of their relative contributions to binding kinetics and correlation with inhibition of erythrocyte invasion. These findings provide insights into mechanisms of single-domain antibody binding, and may enable design of reagents targeting otherwise cryptic epitopes in pathogen antigens.

Structural genomics and drug discovery

Structure determination has already proven useful for lead optimization and direct drug design. The number of high-resolution structures available in public databases today exceeds 30,000 and will definitely aid in structure-based drug design. Structural genomics approaches covering whole genomes, topologically similar proteins or gene families are great assets for further progress in the development of new drugs. However, membrane proteins representing 70% of current drug targets are poorly characterized structurally. The problems have been related to difficulties in obtaining large amount of recombinant membrane proteins as well as their purification and structure determination. Structural genomics has proven successful in developing new methods in areas from expression to structure determination by studying a large number of target proteins in parallel.

Structural Genomics

Drug discovery based on structural knowledge has proven useful as several structure-based medicines are already on the market. Structural genomics aims at studying a large number of gene products including whole genomes, topologically similar proteins, protein families and protein subtypes in parallel. Particularly, therapeutically relevant targets have been selected for structural genomics initiatives. In this context, integral membrane proteins, which represent 60–70% of the current drug targets, have been of major interest. Paradoxically, membrane proteins present the last frontier to conquer in structural biology as some 100 high resolution structures among the 30,000 entries in public structural databases are available. The modest success rate on membrane proteins relates to the difficulties in their expression, purification and crystallography. To facilitate technology development large networks providing expertise in molecular biology, protein biochemistry and structural biology have been established. The privately funded MePNet program has studied 100 G protein-coupled receptors, which resulted in high level expression of a large number of receptors at structural biology compatible levels. Currently, selected GPCRs have been purified and subjected to crystallization attempts

Structural biology and drug discovery

It has long been recognized that knowledge of the 3D structures of proteins has the potential to accelerate drug discovery, but recent developments in genome sequencing, robotics and bioinformatics have radically transformed the opportunities. Many new protein targets have been identified from genome analyses and studied by X-ray analysis or NMR spectroscopy. Structural biology has been instrumental in directing not only lead optimization and target identification, where it has well-established roles, but also lead discovery, now that high-throughput methods of structure determination can provide powerful approaches to screening.

Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery

Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding.

The process of structure-based drug design

The field of structure-based drug design is a rapidly growing area in which many successes have occurred in recent years. The explosion of genomic, proteomic, and structural information has provided hundreds of new targets and opportunities for future drug lead discovery. This review summarizes the process of structure-based drug design and includes, primarily, the choice of a target, the evaluation of a structure of that target, the pivotal questions to consider in choosing a method for drug lead discovery, and evaluation of the drug leads. Key principles in the field of structure-based drug design will be illustrated through a case study that explores drug design for AmpC beta-lactamase.

Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 2. Computational titration and pH effects in molecular models of neuraminidase-inhibitor complexes

One factor that can strongly influence predicted free energy of binding is the ionization state of functional groups on the ligands and at the binding site at which calculations are performed. This analysis is seldom performed except in very detailed computational simulations. In this work, we address the issues of (i) modeling the complexity resulting from the different ionization states of ligand and protein residues involved in binding, (ii) if, and how, computational methods can evaluate the pH dependence of ligand inhibition constants, and (iii) how to score the protonation-dependent models. We developed a new and fairly rapid protocol called "computational titration" that enables parallel modeling of multiple ionization ensembles for each distinct protonation level. Models for possible protonation combinations for site/ligand ionizable groups are built, and the free energy of interaction for each of them is quantified by the HINT (Hydropathic INTeractions) software. We applied this procedure to the evaluation of the binding affinity of nine inhibitors (six derived from 2,3-didehydro-2-deoxy-N-acetylneuraminic acid, DANA) of influenza virus neuraminidase (NA), a surface glycoprotein essential for virus replication and thus a pharmaceutically relevant target for the design of anti-influenza drugs. The three-dimensional structures of the NA enzyme-inhibitor complexes indicate considerable complexity as the ligand-protein recognition site contains several ionizable moieties. Each computational titration experiment reveals a peak HINT score as a function of added protons. This maximum HINT score indicates the optimum pH (or the optimum protonation state of each inhibitor-protein binding site) for binding. The pH at which inhibition is measured and/or crystals were grown and analyzed can vary from this optimum. A protonation model is proposed for each ligand that reconciles the experimental complex structure with measured inhibition and the free energy of binding. Computational titration methods allow us to analyze the effect of pH in silico and may be helpful in improving ligand binding free energy prediction when protonation or deprotonation of the residues or ligand functional groups at the binding site might be significant.

High-throughput crystallography to enhance drug discovery

Protein crystallography has traditionally been regarded as a resource-intensive, time-consuming technique that, with some notable exceptions, has not made a significant impact on drug discovery. However, inspired by successes in the genome-sequencing initiatives, recent years have seen major changes in X-ray crystallography methodologies and the concept of high-throughput crystallography has emerged. Advances have been made in all phases of the process, including improved molecular biology, protein expression, crystallization and structure determination. This transformation has allowed X-ray crystallography to impact more broadly in the drug-discovery process, extending its utility from structure-based lead optimisation to novel fragment-based lead generation approaches.

Chemoenzymatic synthesis of neuraminic acid containing C-glycoside polymers

[structure: see text] Two neuraminic acid-based, C-glycoside polymers were synthesized. Preliminary studies on one of these polymers showed potent neuraminidase inhibitory activity, suggesting potential utility as an antipathogenic surface coating for the preparation of antimicrobial biomaterials.

Synthesis of an influenza neuraminidase inhibitor intermediate via a highly diastereoselective coupling reaction

[reaction: see text]. A highly diastereoselective coupling reaction between TBSOP (3) and trityl sulfenimine 4 was developed which provided influenza neuraminidase inhibitor intermediate 7 in 80% yield and >99% de after crystallization. The reaction was shown to be reversible with the high diastereoselectivity resulting from a favorable H-bonding interaction in the major diastereomer.

High-throughput crystallography for lead discovery in drug design

Knowledge of the three-dimensional structures of protein targets now emerging from genomic data has the potential to accelerate drug discovery greatly. X-ray crystallography is the most widely used technique for protein structure determination, but technical challenges and time constraints have traditionally limited its use primarily to lead optimization. Here, we describe how significant advances in process automation and informatics have aided the development of high-throughput X-ray crystallography, and discuss the use of this technique for structure-based lead discovery.