Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus

Fitness Determinants of Influenza A Viruses

Influenza A (IAV) is a major human respiratory pathogen that causes illness, hospitalizations, and mortality annually worldwide. IAV is also a zoonotic pathogen with a multitude of hosts, allowing for interspecies transmission, reassortment events, and the emergence of novel pandemics, as was seen in 2009 with the emergence of a swine-origin H1N1 (pdmH1N1) virus into humans, causing the first influenza pandemic of the 21st century. While the 2009 pandemic was considered to have high morbidity and low mortality, studies have linked the pdmH1N1 virus and its gene segments to increased disease in humans and animal models. Genetic components of the pdmH1N1 virus currently circulate in the swine population, reassorting with endemic swine viruses that co-circulate and occasionally spillover into humans. This is evidenced by the regular detection of variant swine IAVs in humans associated with state fairs and other intersections of humans and swine. Defining genetic changes that support species adaptation, virulence, and cross-species transmission, as well as mutations that enhance or attenuate these features, will improve our understanding of influenza biology. It aids in surveillance and virus risk assessment and guides the establishment of counter measures for emerging viruses. Here, we review the current understanding of the determinants of specific IAV phenotypes, focusing on the fitness, transmission, and virulence determinants that have been identified in swine IAVs and/or in relation to the 2009 pdmH1N1 virus.

Identifying mutation positions in all segments of influenza genome enables better differentiation between pandemic and seasonal strains

Influenza has a negative sense, single-stranded, and segmented RNA. In the context of pandemic influenza research, most studies have focused on variations in the surface proteins (Hemagglutinin and Neuraminidase). However, new findings suggest that all internal and external proteins of influenza viruses can contribute in pandemic emergence, pathogenicity and increasing host range. The occurrence of the 2009 influenza pandemic and the availability of many external and internal segments of pandemic and non-pandemic sequences offer a unique opportunity to evaluate the performance of machine learning models in discrimination of pandemic from seasonal sequences using mutation positions in all segments. In this study, we hypothesized that identifying mutation positions in all segments (proteins) encoded by the influenza genome would enable pandemic and seasonal strains to be more reliably distinguished. In a large scale study, we applied a range of data mining techniques to all segments of influenza for rule discovery and discrimination of pandemic from seasonal strains. CBA (classification based on association rule mining), Ripper and Decision tree algorithms were utilized to extract association rules among mutations. CBA outperformed the other models. Our approach could discriminate pandemic sequences from seasonal ones with more than 95% accuracy for PA and NP, 99.33% accuracy for NA and 100% accuracy, precision, specificity and sensitivity (recall) for M1, M2, PB1, NS1, and NS2. The values of precision, specificity, and sensitivity were more than 90% for other segments except PB2. If sequences of all segments of one strain were available, the accuracy of discrimination of pandemic strains was 100%. General rules extracted by rule base classification approaches, such as M1-V147I, NP-N334H, NS1-V112I, and PB1-L364I, were able to detect pandemic sequences with high accuracy. We observed that mutations on internal proteins of influenza can contribute in distinguishing the pandemic viruses, similar to the external ones.

Docking study of flavonoid derivatives as potent inhibitors of influenza H1N1 virus neuraminidase

Influenza type A is considered as a severe public health concern. The mechanism of drugs applied for the control of this virus depends on two surface glycoproteins with antigenic properties, namely hemagglutinin (HA) and neuraminidase (NA). HA aids the virus to penetrate cells in the early stage of infection and NA is an enzyme with the ability to break glycoside bonds, which enables virion spread through the host cell membrane. Since NA contains a relatively preserved active site, it has been an important target in drug design. Oseltamivir is a common drug used for the treatment of influenza infections, for which cases of resistance have recently been reported, giving rise to health concerns. Flavonoids are natural polyphenolic compounds with potential blocking effects in the neuraminidase active site. Based on their antiviral effect, the flavonoids quercetin, catechin, naringenin, luteolin, hispidulin, vitexin, chrysin and kaempferol were selected in the present study and compared alongside oseltamivir on molecular docking, binding energy and active site structure, in order to provide insight on the potential of these compounds as targeted drugs for the control and treatment of influenza type A. The molecular characterization of flavonoids with binding affinity was performed using AutoDock Vina software. The results indicated that these compounds may effectively block the NA active site. Therefore, these natural compounds derived from fruits have the potential for development into drugs for controlling influenza, which may aid overcome the clinical challenge of the H1N1 strain epidemic.

Computational assay of Zanamivir binding affinity with original and mutant influenza neuraminidase 9 using molecular docking

Based upon molecular docking, this study aimed to find notable in silico neuraminidase 9 (NA9) point mutations of the avian influenza A H7N9 virus that possess a Zanamivir resistant property and to determine the lead compound capable of inhibiting these NA9 mutations. Seven amino acids (key residues) at the binding site of neuraminidase 9 responsible for Zanamivir-NA9 direct interactions were identified and 72 commonly occurring mutant NA9 versions were created using the Sybyl-X 2.0 software. The docking scores obtained after Zanamivir was bound to all mutant molecules of NA9 revealed 3 notable mutations R292W, R118P, and R292K that could greatly reduce the binding affinity of the medicine. These 3 mutant NA9 versions were then bound to each of 154 different molecules chosen from 5 groups of compounds to determine which molecule(s) might be capable of inhibiting mutant neuraminidase 9, leading to the discovery of the lead compound of potent mutant NA9 inhibitors. This compound, together with other mutations occurring to NA9 identified in the study, would be used as data for further research regarding neuraminidase inhibitors and synthesizing new viable medications used in the fight against the virus.

Insight into a molecular interaction force supporting peptide backbones and its implication to protein loops and folding

Although not being classified as the most fundamental protein structural elements like α-helices and β-strands, the loop segment may play considerable roles for protein stability, flexibility, and dynamic activity. Meanwhile, the protein loop is also quite elusive; i.e. its interactions with the other parts of protein as well as its own shape-maintaining forces have still remained as a puzzle or at least not quite clear yet. Here, we report a molecular force, the so-called polar hydrogen-π interaction (Hp-π), which may play an important role in supporting the backbones of protein loops. By conducting the potential energy surface scanning calculations on the quasi π-plane of peptide bond unit, we have observed the following intriguing phenomena: (1) when the polar hydrogen atom of a peptide unit is perpendicularly pointing to the π-plane of other peptide bond units, a remarkable Hp-π interaction occurs; (2) the interaction is distance and orientation dependent, acting in a broad space, and belonging to the 'point-to-plane' one. The molecular force reported here may provide useful interaction concepts and insights into better understanding the loop's unique stability and flexibility feature, as well as the driving force of the protein global folding.

A novel influenza virus neuraminidase inhibitor AV5027

A medium-sized focused library of novel Oseltamivir structural analogues with promising antiviral activity was successfully synthesized using a combinatorial approach. The synthesized compounds were then thoroughly evaluated in neuraminidase- and cell-based assays. As a result, (3R,4R,5S)-4-(2,2-difluoroacetylamino)-5-amino-3-(1-ethyl-propoxy)-cyclohex-1-enecarboxylic acid (AV5027) was identified as novel Hit-compound with picomolar potency. QSAR analysis was carried out based on the obtained biological data. Computational modeling was performed using a 3D-molecular docking approach and classical regression analysis. The developed integral model demonstrated a sufficient prediction accuracy and tolerance to evaluate compounds based on their potential activity against neuraminidase (NA) at least within the scaffold. Several compounds from the series can be reasonably regarded as promising anti-influenza drug-candidates.

Structural position correlation analysis (SPCA) for protein family

Background

The proteins in a family, which perform the similar biological functions, may have very different amino acid composition, but they must share the similar 3D structures, and keep a stable central region. In the conservative structure region similar biological functions are performed by two or three catalytic residues with the collaboration of several functional residues at key positions. Communication signals are conducted in a position network, adjusting the biological functions in the protein family.

Methodology

A computational approach, namely structural position correlation analysis (SPCA), is developed to analyze the correlation relationship between structural segments (or positions). The basic hypothesis of SPCA is that in a protein family the structural conservation is more important than the sequence conservation, and the local structural changes may contain information of biology functional evolution. A standard protein P⁽⁰⁾ is defined in a protein family, which consists of the most-frequent amino acids and takes the average structure of the protein family. The foundational variables of SPCA is the structural position displacements between the standard protein P⁽⁰⁾ and individual proteins P_i of the family. The structural positions are organized as segments, which are the stable units in structural displacements of the protein family. The biological function differences of protein members are determined by the position structural displacements of individual protein P_i to the standard protein P⁽⁰⁾. Correlation analysis is used to analyze the communication network among segments.

Conclusions

The structural position correlation analysis (SPCA) is able to find the correlation relationship among the structural segments (or positions) in a protein family, which cannot be detected by the amino acid sequence and frequency-based methods. The functional communication network among the structural segments (or positions) in protein family, revealed by SPCA approach, well illustrate the distantly allosteric interactions, and contains valuable information for protein engineering study.

Discovery of potential M2 channel inhibitors based on the amantadine scaffold via virtual screening and pharmacophore modeling

The M2 channel protein on the influenza A virus membrane has become the main target of the anti-flu drugs amantadine and rimantadine. The structure of the M2 channel proteins of the H3N2 (PDB code 2RLF) and 2009-H1N1 (Genbank accession number GQ385383) viruses may help researchers to solve the drug-resistant problem of these two adamantane-based drugs and develop more powerful new drugs against influenza A virus. In the present study, we searched for new M2 channel inhibitors through a combination of different computational methodologies, including virtual screening with docking and pharmacophore modeling. Virtual screening was performed to calculate the free energies of binding between receptor M2 channel proteins and 200 new designed ligands. After that, pharmacophore analysis was used to identify the important M2 protein-inhibitor interactions and common features of top binding compounds with M2 channel proteins. Finally, the two most potential compounds were determined as novel leads to inhibit M2 channel proteins in both H3N2 and 2009-H1N1 influenza A virus.

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.

Impact of calcium on N1 influenza neuraminidase dynamics and binding free energy

The highly pathogenic influenza strains H5N1 and H1N1 are currently treated with inhibitors of the viral surface protein neuraminidase (N1). Crystal structures of N1 indicate a conserved, high affinity calcium binding site located near the active site. The specific role of this calcium in the enzyme mechanism is unknown, though it has been shown to be important for enzymatic activity and thermostability. We report molecular dynamics (MD) simulations of calcium-bound and calcium-free N1 complexes with the inhibitor oseltamivir (marketed as the drug Tamiflu), independently using both the AMBER FF99SB and GROMOS96 force fields, to give structural insight into calcium stabilization of key framework residues. Y347, which demonstrates similar sampling patterns in the simulations of both force fields, is implicated as an important N1 residue that can “clamp” the ligand into a favorable binding pose. Free energy perturbation and thermodynamic integration calculations, using two different force fields, support the importance of Y347 and indicate a +3 to +5 kcal/mol change in the binding free energy of oseltamivir in the absence of calcium. With the important role of structure-based drug design for neuraminidase inhibitors and the growing literature on emerging strains and subtypes, inclusion of this calcium for active site stability is particularly crucial for computational efforts such as homology modeling, virtual screening, and free energy methods. Proteins 2010. © 2010 Wiley-Liss, Inc.