A study of the active site of influenza virus sialidase: an approach to the rational design of novel anti-influenza drugs

Dual-Action Heteromultivalent Glycopolymers Stringently Block and Arrest Influenza A Virus Infection In Vitro and Ex Vivo

Here, we demonstrate the concerted inhibition of different influenza A virus (IAV) strains using a low-molecular-weight dual-action linear polymer. The 6'-sialyllactose and zanamivir conjugates of linear polyglycerol are optimized for simultaneous targeting of hemagglutinin and neuraminidase on the IAV surface. Independent of IAV subtypes, hemagglutination inhibition data suggest better adsorption of the heteromultivalent polymer than homomultivalent analogs onto the virus surface. Cryo-TEM images imply heteromultivalent compound-mediated virus aggregation. The optimized polymeric nanomaterial inhibits >99.9% propagation of various IAV strains 24 h postinfection in vitro at low nM concentrations and is up to 10000× more effective than the commercial zanamivir drug. In a human lung ex vivo multicyclic infection setup, the heteromultivalent polymer outperforms the commercial drug zanamivir and homomultivalent analogs or their physical mixtures. This study authenticates the translational potential of the dual-action targeting approach using small polymers for broad and high antiviral efficacy.

Influenza Viruses: Harnessing the Crucial Role of the M2 Ion-Channel and Neuraminidase toward Inhibitor Design

As a member of the Orthomyxoviridae family of viruses, influenza viruses (IVs) are known causative agents of respiratory infection in vertebrates. They remain a major global threat responsible for the most virulent diseases and global pandemics in humans. The virulence of IVs and the consequential high morbidity and mortality of IV infections are primarily attributed to the high mutation rates in the IVs' genome coupled with the numerous genomic segments, which give rise to antiviral resistant and vaccine evading strains. Current therapeutic options include vaccines and small molecule inhibitors, which therapeutically target various catalytic processes in IVs. However, the periodic emergence of new IV strains necessitates the continuous development of novel anti-influenza therapeutic options. The crux of this review highlights the recent studies on the biology of influenza viruses, focusing on the structure, function, and mechanism of action of the M2 channel and neuraminidase as therapeutic targets. We further provide an update on the development of new M2 channel and neuraminidase inhibitors as an alternative to existing anti-influenza therapy. We conclude by highlighting therapeutic strategies that could be explored further towards the design of novel anti-influenza inhibitors with the ability to inhibit resistant strains.

Guanidinothiosialoside-Human Serum Albumin Conjugate Mimics mucin Barrier to Restrict Influenza Infection

A guanidinothiosialoside-human serum albumin conjugate as mucin mimic was prepared via a copper-free click reaction. Matrix-Assisted Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (MALDI-TOF-MS) indicated that three sialoside groups were grafted onto the protein backbone. The synthetic glycoconjugate exhibited strong influenza virion capture and trapping capability. Further mechanistic studies showed that this neomucin bound tightly to neuraminidase on the surface of influenza virus with a dissociation constant (K_D) in the nanomolar range and had potent antiviral activity against a broad spectrum of virus strains. Most notably, the glycoconjugate acted as a biobarrier was able to protect Madin-Darby canine kidney (MDCK) cells from influenza viral infection with 50% effective concentrations (EC₅₀) in the nanomolar range and showed no cytotoxicity towards Human Umbilical Vein Endothelial Cells (HUVEC) at high concentrations. This research establishes an attractive strategy for the development of new multivalent antiviral agents based on mucin structure. Moreover, the method for the functionalization of the natural biological macromolecular scaffold with bioactive small molecules also lays the experimental foundation for potential biomedical and biomaterial applications.

Molecular Characterization of Hemorrhagic Enteritis Virus (HEV) Obtained from Clinical Samples in Western Canada 2017-2018

Hemorrhagic enteritis virus (HEV) is an immunosuppressive adenovirus that causes an acute clinical disease characterized by hemorrhagic gastroenteritis in 4-week-old turkeys and older. Recurrent incidence of secondary infections (e.g., systemic bacterial infections, cellulitis, and elevated mortality), may be associated with the presence of field-type HEV in Canadian turkey farms. We speculate that field-type HEV and vaccine/vaccine-like strains can be differentiated through analysis of the viral genomes, hexon genes, and the specific virulence factors (e.g., ORF1, E3, and fib knob domain). Nine out of sixteen spleens obtained from cases suspected of immunosuppression by HEV were analyzed. The limited data obtained showed that: (1) field-type HEV circulates in many non-vaccinated western Canadian flocks; (2) field-type HEV circulates in vaccinated flocks with increased recurrent bacterial infections; and (3) the existence of novel point mutations in hexon, ORF1, E3, and specially fib knob domains. This is the first publication showing the circulation of wild-type HEV in HEV-vaccinated flocks in Western Canada, and the usefulness of a novel procedure that allows whole genome sequencing of HEV directly from spleens, without passaging in cell culture or passaging in vivo. Further studies focusing more samples are required to confirm our observations and investigate possible vaccination failure.

The Symmetry of Viral Sialic Acid Binding Sites-Implications for Antiviral Strategies

Virus infections are initiated by the attachment of the viral particle to protein or carbohydrate receptors on the host cell. Sialic acid-bearing glycan structures are prominently displayed at the cell surface, and, consequently, these structures can function as receptors for a large number of diverse viruses. Structural biology research has helped to establish the molecular bases for many virus–sialic acid interactions. Due to the icosahedral 532 point group symmetry that underlies many viral capsids, the receptor binding sites are frequently arranged in a highly symmetric fashion and linked by five-fold, three-fold, or two-fold rotation axes. For the inhibition of viral attachment, one emerging strategy is based on developing multivalent sialic acid-based inhibitors that can simultaneously engage several of these binding sites, thus binding viral capsids with high avidity. In this review, we will evaluate the structures of non-enveloped virus capsid proteins bound to sialylated glycan receptors and discuss the potential of these structures for the development of potent antiviral attachment inhibitors.

Exploring the chemical space of influenza neuraminidase inhibitors

The fight against the emergence of mutant influenza strains has led to the screening of an increasing number of compounds for inhibitory activity against influenza neuraminidase. This study explores the chemical space of neuraminidase inhibitors (NAIs), which provides an opportunity to obtain further molecular insights regarding the underlying basis of their bioactivity. In particular, a large set of 347 and 175 NAIs against influenza A and B, respectively, was compiled from the literature. Molecular and quantum chemical descriptors were obtained from low-energy conformational structures geometrically optimized at the PM6 level. The bioactivities of NAIs were classified as active or inactive according to their half maximum inhibitory concentration (IC₅₀) value in which IC₅₀ < 1µM and ≥ 10µM were defined as active and inactive compounds, respectively. Interpretable decision rules were derived from a quantitative structure–activity relationship (QSAR) model established using a set of substructure descriptors via decision tree analysis. Univariate analysis, feature importance analysis from decision tree modeling and molecular scaffold analysis were performed on both data sets for discriminating important structural features amongst active and inactive NAIs. Good predictive performance was achieved as deduced from accuracy and Matthews correlation coefficient values in excess of 81% and 0.58, respectively, for both influenza A and B NAIs. Furthermore, molecular docking was employed to investigate the binding modes and their moiety preferences of active NAIs against both influenza A and B neuraminidases. Moreover, novel NAIs with robust binding fitness towards influenza A and B neuraminidase were generated via combinatorial library enumeration and their binding fitness was on par or better than FDA-approved drugs. The results from this study are anticipated to be beneficial for guiding the rational drug design of novel NAIs for treating influenza infections.

Selective modification of the 3''-amino group of kanamycin prevents significant loss of activity in resistant bacterial strains

Aminoglycosides are highly potent, wide-spectrum bactericidals. N-1 modification of aminoglycosides has thus far been the best approach to regain bactericidal efficiency of this class of antibiotics against resistant bacterial strains. In the present study we have evaluated the effect that both, the number of modifications and their distribution on the aminoglycoside amino groups (N-1, N-3, N-6' and N-3''), have on the antibiotic activity. The modification of N-3'' in the antibiotic kanamycin A is the key towards the design of new aminoglycoside antibiotics. This derivative maintains the antibiotic activity against aminoglycoside acetyl-transferase- and nucleotidyl-transferase-expressing strains, which are two of the most prevalent modifying enzymes found in aminoglycoside resistant bacteria.

Computational solvent mapping in structure-based drug design

Over the past two decades, solvent mapping has emerged as a useful tool for identifying hot spots within binding sites on proteins for drug-like molecules and suggesting properties of potential binders. While the experimental technique requires solving multiple crystal structures of a protein in different solvents, computational solvent mapping allows for fast analysis of a protein for potential binding sites and their druggability. Recent advances in genomics, systems biology and interactomics provide a multitude of potential targets for drug development and solvent mapping can provide useful information to help prioritize targets for drug discovery projects. Here, we review various approaches to computational solvent mapping, highlight some key advances and provide our opinion on future directions in the field.

Therapeutics against influenza

Despite 75 years of research into prevention and treatment of influenza, the viruses that cause this disease continue to rank as some of the most important pathogens afflicting humans today. Progress in development of therapeutics for influenza has been slow for much of that time, but has accelerated in pace over the last two decades. Two classes of antiviral medications are used in humans at present, but each has limitations in scope and effectiveness of use. New strategies involving these licensed agents, including alternate forms of delivery and combination therapy with other drugs, are currently being explored. In addition, several novel antiviral compounds are in various clinical phases of development. Together with strategies designed to target the virus itself, new approaches to interrupt host–pathogen interactions or modulate detrimental aspects of the immune response have been proposed. Therapy for influenza will likely undergo substantial changes in the decades to come, evolving with our knowledge of pathogenesis as new approaches become viable and are validated clinically.

Organism-adapted specificity of the allosteric regulation of pyruvate kinase in lactic acid bacteria

Pyruvate kinase (PYK) is a critical allosterically regulated enzyme that links glycolysis, the primary energy metabolism, to cellular metabolism. Lactic acid bacteria rely almost exclusively on glycolysis for their energy production under anaerobic conditions, which reinforces the key role of PYK in their metabolism. These organisms are closely related, but have adapted to a huge variety of native environments. They include food-fermenting organisms, important symbionts in the human gut, and antibiotic-resistant pathogens. In contrast to the rather conserved inhibition of PYK by inorganic phosphate, the activation of PYK shows high variability in the type of activating compound between different lactic acid bacteria. System-wide comparative studies of the metabolism of lactic acid bacteria are required to understand the reasons for the diversity of these closely related microorganisms. These require knowledge of the identities of the enzyme modifiers. Here, we predict potential allosteric activators of PYKs from three lactic acid bacteria which are adapted to different native environments. We used protein structure-based molecular modeling and enzyme kinetic modeling to predict and validate potential activators of PYK. Specifically, we compared the electrostatic potential and the binding of phosphate moieties at the allosteric binding sites, and predicted potential allosteric activators by docking. We then made a kinetic model of Lactococcus lactis PYK to relate the activator predictions to the intracellular sugar-phosphate conditions in lactic acid bacteria. This strategy enabled us to predict fructose 1,6-bisphosphate as the sole activator of the Enterococcus faecalis PYK, and to predict that the PYKs from Streptococcus pyogenes and Lactobacillus plantarum show weaker specificity for their allosteric activators, while still having fructose 1,6-bisphosphate play the main activator role in vivo. These differences in the specificity of allosteric activation may reflect adaptation to different environments with different concentrations of activating compounds. The combined computational approach employed can readily be applied to other enzymes.

Photodegradation and inhibition of drug-resistant influenza virus neuraminidase using anthraquinone-sialic acid hybrids

The anthraquinone-sialic acid hybrids designed effectively degraded not only non-drug-resistant neuraminidase but also drug-resistant neuraminidase, which is an important target of anti-influenza therapy. Degradation was achieved using long-wavelength UV radiation in the absence of any additives and under neutral conditions. Moreover, the hybrids efficiently inhibited neuraminidase activities upon photo-irradiation.

Therapeutics for filovirus infection: traditional approaches and progress towards in silico drug design

INTRODUCTION

Ebolaviruses and marburgviruses cause severe and often lethal human hemorrhagic fevers. As no FDA-approved therapeutics are available for these infections, efforts to discover new therapeutics are important, especially because these pathogens are considered biothreats and emerging infectious diseases. All methods for discovering new therapeutics should be considered, including compound library screening in vitro against virus and in silico structure-based drug design, where possible, if sufficient biochemical and structural information is available.

AREAS COVERED

This review covers the structure and function of filovirus proteins, as they have been reported to date, as well as some of the current antiviral screening approaches. The authors discuss key studies mapping small-molecule modulators that were found through library and in silico screens to potential sites on viral proteins or host proteins involved in virus trafficking and pathogenesis. A description of ebolavirus and marburgvirus diseases and available animal models is also presented.

EXPERT OPINION

To discover novel therapeutics with potent efficacy using sophisticated computational methods, more high-resolution crystal structures of filovirus proteins and more details about the protein functions and host interaction will be required. Current compound screening efforts are finding active antiviral compounds, but an emphasis on discovery research to investigate protein structures and functions enabling in silico drug design would provide another avenue for finding antiviral molecules. Additionally, targeting of protein-protein interactions may be a future avenue for drug discovery since disrupting catalytic sites may not be possible for all proteins.

A practical synthesis of zanamivir phosphonate congeners with potent anti-influenza activity

Two phosphonate compounds 1a (4-amino-1-phosphono-DANA) and 1b (phosphono-zanamivir) are synthesized and shown more potent than zanamivir against the neuraminidases of avian and human influenza viruses, including the oseltamivir-resistant strains. For the first time, the practical synthesis of these phosphonate compounds is realized by conversion of sialic acid to peracetylated phosphono-DANA diethyl ester (5) as a key intermediate in three steps by a novel approach. In comparison with zanamivir, the high affinity of 1a and 1b can be partly attributable to the strong electrostatic interactions of their phosphonate groups with the three arginine residues (Arg118, Arg292, and Arg371) in the active site of neuraminidases. These phosphonates are nontoxic to the human 293T cells; they protect cells from influenza virus infection with EC(50) values in low-nanomolar range, including the wild-type WSN (H1N1), the 2009 pandemic (H1N1), the oseltamivir-resistant H274Y (H1N1), RG14 (H5N1), and Udorn (H3N2) influenza strains.

Fragment-based approaches and computer-aided drug discovery

Fragment-based design has significantly modified drug discovery strategies and paradigms in the last decade. Besides technological advances and novel therapeutic avenues, one of the most significant changes brought by this new discipline has occurred in the minds of drug designers. Fragment-based approaches have markedly impacted rational computer-aided design both in method development and in applications. The present review illustrates the importance of molecular fragments in many aspects of rational ligand design, and discusses how thinking in "fragment space" has boosted computational biology and chemistry.

Evaluation of a Set of C9 N-acyl Neu5Ac2en Mimetics as Viral Sialidase Selective Inhibitors

Identification of selective influenza viral sialidase inhibitors is highly desirable in order to minimize or avoid the adverse effects due to the possible inhibition of endogenous human sialidases. We recently reported the evaluation of C9 N-acyl Neu5Ac2en mimetics as probes for human sialidases. Herein, we describe the in vitro activity of the same set of C9 N-acyl Neu5Ac2en mimetics against sialidases expressed by influenza virus A/PR/8/34 (H1N1), A/Memphis/1/72 (H3N2), and A/Duck/313/78 (H5N3) strains. Compound 8 is identified as a promising starting point for the development of viral sialidase selective inhibitors. Multiple sequence alignment and molecular docking techniques are also performed to explore the plausible interaction of compound 8 with viral sialidases.

Synergistic effect of zanamivir-porphyrin conjugates on inhibition of neuraminidase and inactivation of influenza virus

New anti-influenza agents of tetravalent zanamivir on a porphyrin scaffold were synthesized. These compounds are 10 to 100 times more potent in inhibiting influenza replications even though they are somewhat less potent in neuraminidase inhibition than the monomeric zanamivir. The enhanced anti-influenza activity is probably attributable to the additional viral inactivation by singlet oxygen due to sensitization of the porphyrin moiety, which is brought in close proximity of virus by the conjugated zanamivir in a manner resembling the "magic bullet" mechanism.

Molecular modeling of swine influenza A/H1N1, Spanish H1N1, and avian H5N1 flu N1 neuraminidases bound to Tamiflu and Relenza

A molecular model of the swine influenza A/H1N1 ( also called H1N1pdm) type-I neuraminidase was built using the pathogenic avian H5N1 type-I neuraminidase as a basis, due to the higher sequence identity between A/H1N1 and H5N1 (91.47%) compared to Spanish H1N1 (88.37%) neuraminidase. All-atom molecular dynamics (MD) simulations of all three neuraminidases were performed, either as apo-structures or with commercial antiviral drugs Tamiflu or Relenza separately bound; the simulations allowed for the identification of both conserved and unique drug-protein interactions across all three proteins. Specifically, conserved networks of hydrogen bonds stabilizing the drugs in the sialic acid binding site of the simulated neuraminidases are analyzed, providing insight into how disruption due to mutations may lead to increased drug resistance. In addition, a possible mechanism through which the residue 294 mutation acquires drug resistance is proposed by mapping the mutation site onto an electrostatic pathway which may play a role in controlling drug access to the binding pocket of neuraminidase, establishing a starting point for further investigations of neuraminidase drug resistance.

Combining crystallographic information and an aspherical-atom data bank in the evaluation of the electrostatic interaction energy in an enzyme-substrate complex: influenza neuraminidase inhibition

Although electrostatic interactions contribute only a part of the interaction energies between macromolecules, unlike dispersion forces they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In the reported study, a wide range of complexes of influenza neuraminidases with inhibitor molecules (sialic acid derivatives and others) have been analyzed using charge densities from a transferable aspherical-atom data bank. The strongest interactions of the residues are with the acidic group at the C2 position of the inhibitor ( approximately -300 kJ mol(-1) for -COO(-) in non-aromatic inhibitors, approximately -120-210 kJ mol(-1) for -COO(-) in aromatic inhibitors and approximately -450 kJ mol(-1) for -PO(3)(2-)) and with the amino and guanidine groups at C4 ( approximately -250 kJ mol(-1)). Other groups contribute less than approximately 100 kJ mol(-1). Residues Glu119, Asp151, Glu227, Glu276 and Arg371 show the largest variation in electrostatic energies of interaction with different groups of inhibitors, which points to their important role in the inhibitor recognition. The Arg292-->Lys mutation reduces the electrostatic interactions of the enzyme with the acidic group at C2 for all inhibitors that have been studied (SIA, DAN, 4AM, ZMR, G20, G28, G39 and BCZ), but enhances the interactions with the glycerol group at C6 for inhibitors that contain it. This is in agreement with the lower level of resistance of the mutated virus to glycerol-containing inhibitors compared with the more hydrophobic derivatives.

Anti-influenza drugs: the development of sialidase inhibitors

Viruses, particularly those that are harmful to humans, are the 'silent terrorists' of the twenty-first century. Well over four million humans die per annum as a result of viral infections alone. The scourge of influenza virus has plagued mankind throughout the ages. The fact that new viral strains emerge on a regular basis, particularly out of Asia, establishes a continual socio-economic threat to mankind. The arrival of the highly pathogenic avian influenza H5N1 heightened the threat of a potential human pandemic to the point where many countries have put in place 'preparedness plans' to defend against such an outcome. The discovery of the first designer influenza virus sialidase inhibitor and anti-influenza drug Relenza, and subsequently Tamiflu, has now inspired a number of continuing efforts towards the discovery of next generation anti-influenza drugs. Such drugs may act as 'first-line-of-defence' against the spread of influenza infection and buy time for necessary vaccine development particularly in a human pandemic setting. Furthermore, the fact that influenza virus can develop resistance to therapeutics makes these continuing efforts extremely important. An overview of the role of the virus-associated glycoprotein sialidase (neuraminidase) and some of the most recent developments towards the discovery of anti-influenza drugs based on the inhibition of influenza virus sialidase is provided in this chapter.

Pyrosequencing as a tool to detect molecular markers of resistance to neuraminidase inhibitors in seasonal influenza A viruses

Pyrosequencing has been successfully used to monitor resistance in influenza A viruses to the first class of anti-influenza drugs, M2 blockers (adamantanes). In contrast to M2 blockers, resistance to neuraminidase (NA) inhibitors (NAIs) is subtype- and drug-specific. Here, we designed a pyrosequencing assay for detection of the most commonly reported mutations associated with resistance to NAIs, a newer class of anti-influenza drugs. These common mutations occur at residues: H274 (N1), E119 (N2), R292 (N2), and N294 (N2) in seasonal influenza A viruses. Additionally, we designed primers to detect substitutions at D151 in NAs of N1 and N2 subtypes. This assay allows detection of mutations associated with resistance not only in grown viruses but also in clinical specimens, thus reducing the time needed for testing and providing an advantage for disease outbreak investigation and management. The pyrosequencing approach also allows the detection of mixed populations of virus variants at positions of interest. Analysis of viruses in the original clinical specimens reduces the potential for introducing genetic variance in the virus population due to selection by cell culture. Our results showed that, in at least one instance, a D151E change seen in N1NA after virus propagation in cell culture was not detected in the original clinical specimen. Although the pyrosequencing assay allows high throughput screening for established genetic markers of antiviral resistance, it is not a replacement for the NA inhibition assays due to insufficient knowledge of the molecular mechanisms of the NAI-resistance.

Design of ligand binding to an engineered protein cavity using virtual screening and thermal up-shift evaluation

Proteins could be used to carry and deliver small compounds. As a tool for designing ligand binding sites in protein cores, a three-step virtual screening method is presented that has been optimised using existing data on T4 lysozyme complexes and tested in a newly engineered cavity in flavodoxin. The method can pinpoint, in large databases, ligands of specific protein cavities. In the first step, physico-chemical filters are used to screen the library and discard a majority of compounds. In the second step, a flexible, fast docking procedure is used to score and select a smaller number of compounds as potential binders. In the third step, a finer method is used to dock promising molecules of the hit list into the protein cavity, and an optimised free energy function allows discarding the few false positives by calculating the affinity of the modelled complexes. To demonstrate the portability of the method, several cavities have been designed and engineered in the flavodoxin from Anabaena PCC 7119, and the W66F/L44A double mutant has been selected as a suitable host protein. The NCI database has then been screened for potential binders, and the binding to the engineered cavity of five promising compounds and three tentative non-binders has been experimentally tested by thermal up-shift assays and spectroscopic titrations. The five tentative binders (some apolar and some polar), unlike the three tentative non-binders, are shown to bind to the host mutant and, importantly, not to bind to the wild type protein. The three-step virtual screening method developed can thus be used to identify ligands of buried protein cavities. We anticipate that the method could also be used, in a reverse manner, to identify natural or engineerable protein cavities for the hosting of ligands of interest.

The war against influenza: discovery and development of sialidase inhibitors

The threat of a major human influenza pandemic, in particular from highly aggressive strains such as avian H5N1, has emphasized the need for therapeutic strategies to combat these pathogens. At present, two inhibitors of sialidase (also known as neuraminidase), a viral enzyme that has a key role in the life cycle of influenza viruses, would be the mainstay of pharmacological strategies in the event of such a pandemic. This article provides a historical perspective on the discovery and development of these drugs--zanamivir and oseltamivir--and highlights the value of structure-based drug design in this process.

Molecular dynamics and free energy analysis of neuraminidase-ligand interactions

We report molecular dynamics calculations of neuraminidase in complex with an inhibitor, 4-amino-2-deoxy-2,3-didehydro-N-acetylneuraminic acid (N-DANA), with subsequent free energy analysis of binding by using a combined molecular mechanics/continuum solvent model approach. A dynamical model of the complex containing an ionized Glu119 amino acid residue is found to be consistent with experimental data. Computational analysis indicates a major van der Waals component to the inhibitor-neuraminidase binding free energy. Based on the N-DANA/neuraminidase molecular dynamics trajectory, a perturbation methodology was used to predict the binding affinity of related neuraminidase inhibitors by using a force field/Poisson-Boltzmann potential. This approach, incorporating conformational search/local minimization schemes with distance-dependent dielectric or generalized Born solvent models, correctly identifies the most potent neuraminidase inhibitor. Mutation of the key ligand four-substituent to a hydrogen atom indicates no favorable binding free energy contribution of a hydroxyl group; conversely, cationic substituents form favorable electrostatic interactions with neuraminidase. Prospects for further development of the method as an analysis and rational design tool are discussed.

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.

Mechanism by which mutations at his274 alter sensitivity of influenza a virus n1 neuraminidase to oseltamivir carboxylate and zanamivir

Oseltamivir carboxylate is a potent and specific inhibitor of influenza neuraminidase (NA). An influenza A/H1N1 variant selected in vitro with reduced susceptibility to oseltamivir carboxylate contains a His274Tyr mutation. To understand the mechanism by which a His274Tyr mutation gives rise to drug resistance, we studied a series of NA variant proteins containing various substitutions at position 274. Replacement of His274 with larger side chain residues (Tyr or Phe) reduced the NA sensitivity to oseltamivir carboxylate. In contrast, replacement of His274 with smaller side chain residues (Gly, Asn, Ser, and Gln) resulted in enhanced or unchanged sensitivity to oseltamivir carboxylate. Previous studies have suggested that the slow-binding inhibition of NA by oseltamivir carboxylate is a result of the reorientation of Glu276. Loss of this slow-binding inhibition in the His274Tyr and His274Phe mutant NA but not in His274Asn, His274Gly, His274Ser, or His274Gln supports the conclusion that the conformational change of Glu276 is restricted in the His274Tyr and His274Phe mutant NA upon oseltamivir carboxylate binding. Interestingly, His274Asn, as well as His274Gly, His274Ser, and His274Gln, also displayed reduced sensitivity to zanamivir and its analogue, 4-amino-Neu5Ac2en. Substitution of His274 with Tyr in influenza A/Tokyo/3/67 (H3N2) recombinant NA did not affect the susceptibility to oseltamivir carboxylate. These data indicate that the volume occupied by the amino acid side chain at position 274 can influence the sensitivities of influenza N1 NA but not of N2 NA to both oseltamivir carboxylate and zanamivir.

Modelling studies of the active site of human sorbitol dehydrogenase: an approach to structure-based inhibitor design of the enzyme

The program GRID was used to design novel potential inhibitors of human sorbitol dehydrogenase based on a model of the holoenzyme in complex with the inhibitor WAY135 706. Replacement of the methyl hydroxyl group of the inhibitor with methyl phosphate and methyl carboxylate functional groups increased the net binding energy of the complex by 2.0- and 1.7-fold, respectively. This study may be useful in the development of potent and more specific inhibitors of the enzyme.

Functional group placement in protein binding sites: a comparison of GRID and MCSS

One approach to combinatorial ligand design begins by determining optimal locations (i.e., local potential energy minima) for functional groups in the binding site of a target macromolecule. MCSS and GRID are two methods, based on significantly different algorithms, which are used for this purpose. A comparison of the two methods for the same functional groups is reported. Calculations were performed for nonpolar and polar functional groups in the internal hydrophobic pocket of the poliovirus capsid protein, and on the binding surface of the src SH3 domain. The two approaches are shown to agree qualitatively; i.e., the global characteristics of the functional group maps generated by MCSS and GRID are similar. However, there are significant differences in the relative interaction energies of the two sets of minima, a consequence of the different functional form used to evaluate polar interactions (electrostatics and hydrogen bonding) in the two methods. The single sphere representation used by GRID affords only positional information, supplemented by the identification of hydrogen bonding interactions. By contrast, the multi-atom representation of most MCSS groups yields in both positional and orientational information. The two methods are most similar for small functional groups, while for larger functional groups MCSS yields results consistent with GRID but superior in detail. These results are in accord with the somewhat different purposes for which the two methods were developed. GRID has been used mainly to introduce functionalities at specific positions in lead compounds, in which case the orientation is predetermined by the structure of the latter. The orientational information provided by MCSS is important for its use in the de novo design of large, multi-functional ligands, as well as for improving lead compounds.

Comparative binding energy (COMBINE) analysis of influenza neuraminidase-inhibitor complexes

Neuraminidase is a surface glycoprotein of influenza viruses that cleaves terminal sialic acids from carbohydrates. It is critical for viral release from infected cells and facilitates viral spread in the respiratory tract. The catalytic active site of neuraminidase is highly conserved in all type A and B influenza viruses, making it an excellent target for antiinfluenza drug design. Indeed, neuraminidase inhibitors have recently become available in the clinic for the treatment of influenza. Here, we describe the use of 3D structures of neuraminidase-inhibitor complexes to derive quantitative structure-activity relationships (QSARs) to aid understanding of the mechanism of inhibition and the discovery of new inhibitors. Crystal structures of neuraminidase-inhibitor complexes were used alongside modeled complexes to derive QSAR models by COMparative BINding Energy (COMBINE) analysis (Ortiz, A. R.; Pisabarro, M. T.; Gago, F.; Wade, R. C. J. Med. Chem. 1995, 38, 2681-2691). The neuraminidase proteins studied include type A subtypes N2 and N9 (which have ca. 50% sequence identity) and an active site mutant of the N9 subtype. The inhibitors include sialic acid and benzoic acid analogues with diverse frameworks and substitution groups. By considering the contributions of the protein residues and a key water molecule to the electrostatic and van der Waals intermolecular interaction energies, a predictive and robust QSAR model for binding to type A neuraminidase was obtained. In this QSAR model, 12 protein residues and 1 bound water molecule are highlighted as particularly important for inhibitory activity. This QSAR model provides guidelines for structural modification of current inhibitors and the design of novel inhibitors in order to optimize inhibitory activity.

Design of inhibitors of Ras--Raf interaction using a computational combinatorial algorithm

Drugs that inhibit important protein-protein interactions are hard to find either by screening or rational design, at least so far. Most drugs on the market that target proteins today are therefore aimed at well-defined binding pockets in proteins. While computer-aided design is widely used to facilitate the drug discovery process for binding pockets, its application to the design of inhibitors that target the protein surface initially seems to be limited because of the increased complexity of the task. Previously, we had started to develop a computational combinatorial design approach based on the well-known 'multiple copy simultaneous search' (MCSS) procedure to tackle this problem. In order to identify sequence patterns of potential inhibitor peptides, a three-step procedure is employed: first, using MCSS, the locations of specific functional groups on the protein surface are identified; second, after constructing the peptide main chain based on the location of favorite locations of N-methylacetamide groups, functional groups corresponding to amino acid side chains are selected and connected to the main chain C(alpha) atoms; finally, the peptides generated in the second step are aligned and probabilities of amino acids at each position are calculated from the alignment scheme. Sequence patterns of potential inhibitors are determined based on the propensities of amino acids at each C(alpha) position. Here we report the optimization of inhibitor peptides using the sequence patterns determined by our method. Several short peptides derived from our prediction inhibit the Ras--Raf association in vitro in ELISA competition assays, radioassays and biosensor-based assays, demonstrating the feasibility of our approach. Consequently, our method provides an important step towards the development of novel anti-Ras agents and the structure-based design of inhibitors of protein--protein interactions.