Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity

Inhibition of DEF-p65 Interactions as a Potential Avenue to Suppress Tumor Growth in Pancreatic Cancer

The limited success of current targeted therapies for pancreatic cancer underscores an urgent demand for novel treatment modalities. The challenge in mitigating this malignancy can be attributed to the digestive organ expansion factor (DEF), a pivotal yet underexplored factor in pancreatic tumorigenesis. The study uses a blend of in vitro and in vivo approaches, complemented by the theoretical analyses, to propose DEF as a promising anti-tumor target. Analysis of clinical samples reveals that high expression of DEF is correlated with diminished survival in pancreatic cancer patients. Crucially, the depletion of DEF significantly impedes tumor growth. The study further discovers that DEF binds to p65, shielding it from degradation mediated by the ubiquitin-proteasome pathway in cancer cells. Based on these findings and computational approaches, the study formulates a DEF-mimicking peptide, peptide-031, designed to disrupt the DEF-p65 interaction. The effectiveness of peptide-031 in inhibiting tumor proliferation has been demonstrated both in vitro and in vivo. This study unveils the oncogenic role of DEF while highlighting its prognostic value and therapeutic potential in pancreatic cancer. In addition, peptide-031 is a promising therapeutic agent with potent anti-tumor effects.

The Deinococcus protease PprI senses DNA damage by directly interacting with single-stranded DNA

Bacteria have evolved various response systems to adapt to environmental stress. A protease-based derepression mechanism in response to DNA damage was characterized in Deinococcus, which is controlled by the specific cleavage of repressor DdrO by metallopeptidase PprI (also called IrrE). Despite the efforts to document the biochemical, physiological, and downstream regulation of PprI-DdrO, the upstream regulatory signal activating this system remains unclear. Here, we show that single-stranded DNA physically interacts with PprI protease, which enhances the PprI-DdrO interactions as well as the DdrO cleavage in a length-dependent manner both in vivo and in vitro. Structures of PprI, in its apo and complexed forms with single-stranded DNA, reveal two DNA-binding interfaces shaping the cleavage site. Moreover, we show that the dynamic monomer-dimer equilibrium of PprI is also important for its cleavage activity. Our data provide evidence that single-stranded DNA could serve as the signal for DNA damage sensing in the metalloprotease/repressor system in bacteria. These results also shed light on the survival and acquired drug resistance of certain bacteria under antimicrobial stress through a SOS-independent pathway.

The rigidity of a structural bridge on HLA-I binding groove explains its differential outcome in cancer immune response

The tremendous success of immune checkpoint blockade (ICB) therapy has raised the great demand for the development of predictive biomarkers. A recent cancer genomic study suggested that human leukocyte antigen (HLA)-B*44:02 and HLA-B*15:01 alleles may act as potential biomarkers for ICB therapies, however, the underlying molecular mechanisms remain largely elusive. Here, we investigated the molecular origins of differential responses to ICB therapies for four representative HLA alleles: HLA-B*44:02, HLA-B*15:01, HLA-B*07:02, and HLA-B*53:01, using extensive all-atom molecular dynamics simulations. We first demonstrated that the relatively more rigid peptide-binding groove of HLA-B*15:01, than those in the other three HLA alleles, may result in challenges in its recognition with T-cell receptors. Specifically, the "bridge" structure in HLA-B*15:01 is stabilized through both intramolecular electrostatic interactions between the HLA residues and intermolecular interactions between the HLA and the antigenic peptide. These observations were further confirmed by in silico mutagenesis studies, as well as simulations of several other HLA-B*15:01-peptide complexes. By contrast, the "bridge" structure is either completely absent in HLA-B*44:02 or easily perturbed in HLA-B*07:02 and HLA-B*53:01. Our findings provide detailed structural and mechanistic insights into how HLA genotype influences ICB responses and may have important implications for developing immune markers.

Identifying and Overcoming the Sampling Challenges in Relative Binding Free Energy Calculations of a Model Protein:Protein Complex

Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on protein:protein binding affinities, but these calculations can involve sampling challenges due to the complex networks of protein and water interactions frequently present in protein:protein interfaces. We investigate these challenges by extending a graphics processing unit (GPU)-accelerated open-source relative free energy calculation package (Perses) to predict the impact of amino acid mutations on protein:protein binding. Using the well-characterized model system barnase:barstar, we describe analyses for identifying and characterizing sampling problems in protein:protein relative free energy calculations. We find that mutations with sampling problems often involve charge-changes, and inadequate sampling can be attributed to slow degrees of freedom that are mutation-specific. We also explore the accuracy and efficiency of current state-of-the-art approaches─alchemical replica exchange and alchemical replica exchange with solute tempering─for overcoming relevant sampling problems. By employing sufficiently long simulations, we achieve accurate predictions (RMSE 1.61, 95% CI: [1.12, 2.11] kcal/mol), with 86% of estimates within 1 kcal/mol of the experimentally determined relative binding free energies and 100% of predictions correctly classifying the sign of the changes in binding free energies. Ultimately, we provide a model workflow for applying protein mutation free energy calculations to protein:protein complexes, and importantly, catalog the sampling challenges associated with these types of alchemical transformations. Our free open-source package (Perses) is based on OpenMM and is available at https://github.com/choderalab/perses.

Mutagenesis and structural studies reveal the basis for the specific binding of SARS-CoV-2 SL3 RNA element with human TIA1 protein

Viral RNA-host protein interactions are indispensable during RNA virus transcription and replication, but their detailed structural and dynamical features remain largely elusive. Here, we characterize the binding interface for the SARS-CoV-2 stem-loop 3 (SL3) cis-acting element to human TIA1 protein with a combined theoretical and experimental approaches. The highly structured SARS-CoV-2 SL3 has a high binding affinity to TIA1 protein, in which the aromatic stacking, hydrogen bonds, and hydrophobic interactions collectively direct this specific binding. Further mutagenesis studies validate our proposed 3D binding model and reveal two SL3 variants have enhanced binding affinities to TIA1. And disruptions of the identified RNA-protein interactions with designed antisense oligonucleotides dramatically reduce SARS-CoV-2 infection in cells. Finally, TIA1 protein could interact with conserved SL3 RNA elements within other betacoronavirus lineages. These findings open an avenue to explore the viral RNA-host protein interactions and provide a pioneering structural basis for RNA-targeting antiviral drug design.

N1 neuraminidase of H5N1 avian influenza A virus complexed with sialic acid and zanamivir - A study by molecular docking and molecular dynamics simulation

Development of antiviral drugs is an urgent need to control and prevent the presently circulating H5N1 avian influenza virus which is affects the human respiratory tract. The complex crystal structure of N1-N-acetylneuranamic acid (sialic acid, SIA) is not available as complex and hence SIA and zanamivir (ZMR) are docked into the binding site of N1 neuraminidase. Based on the analysis, the initial complex structures have been simulated for 120 ns to get insight into the binding modes and interaction between protein-ligand complex systems. NAMD pair interaction energy and MM-PBSA binding free energy are calculated and show that there are two possible binding modes (BM1 and BM2) for N1-SIA and a single binding mode (BM1) for and N1-ZMR complex structures respectively. BM1 of N1-SIA is the most preferred binding mode. On contrary to the currently available drugs in which the chair conformation is distorted, in both the binding modes of N1-SIA, the binding pocket of N1 neuraminidase is able to accommodate SIA in ²C₅ chair conformation which is the preferred conformation of SIA in solution state. In N1-ZMR complex, ZMR is bind in a distorted chair conformation. The neuraminidase binding pocket is also able to accommodate galactose of SIAα(2→3)GAL and SIAα(2→6)GAL. RMSD, RMSF and hydrogen bonding analyses have been carried out to identify the conformational flexibility and structural stability of each complex system. All the analyses show that SIA can be used as an inhibitor for N1 neuraminidase of H5N1 influenza viral infection. Communicated by Ramaswamy H. Sarma.

Characterizing Receptor Flexibility to Predict Mutations That Lead to Human Adaptation of Influenza Hemagglutinin

A key step in the emergence of human pandemic influenza strains has been a switch in binding preference of the viral glycoprotein hemagglutinin (HA) from avian to human sialic acid (SA) receptors. The conformation of the bound SA varies substantially with HA sequence, and crystallographic evidence suggests that the bound SA is flexible, making it difficult to predict which mutations are responsible for changing HA-binding preference. We performed molecular dynamics (MD) simulations of SA analogues binding to various HAs and observed a dynamic equilibrium among structurally diverse receptor conformations, including conformations that have not been experimentally observed. Using one such novel conformation, we predicted—and experimentally confirmed—a set of mutations that substantially increased an HA’s affinity for a human SA analogue. This prediction could not have been inferred from the existing crystal structures, suggesting that MD-generated HA–SA conformational ensembles could help researchers predict human-adaptive mutations, aiding surveillance of emerging pandemic threats.

Binding Affinity Calculations of Gluten Peptides to HLA Risk Modifiers: DQ2.5 versus DQ7.5

Free energy perturbation (FEP) calculations can predict relative binding affinities of an antigen and its point mutants to the same human leukocyte antigen (HLA) with high accuracy (e.g., within 1.0 kcal/mol to experiment); however, a more challenging task is to compare binding affinities of wholly different antigens binding to completely different HLAs using FEP. Researchers have used a variety of different FEP schemes to compute and compare absolute binding affinities, with varied success. Here, we propose and assess a unifying scheme to compute the relative binding affinities of different antigens binding to completely different HLAs using absolute binding affinity FEP calculations. We apply our affinity calculation technique to HLA-antigen-T-cell receptor (TCR) systems relevant to celiac disease (CeD) by investigating binding affinity differences between HLA-DQ2.5 (enhanced CeD risk) and HLA-DQ7.5 (CeD protective) in the binary (HLA-gliadin) and ternary (HLA-gliadin-TCR) binding complexes for three gliadin derived epitopes: glia-α1, glia-α2, and glia-ω1. Based on FEP calculations with our carefully designed thermodynamic cycles, we demonstrate that HLA-DQ2.5 has higher binding affinity than HLA-DQ7.5 for gliadin and enhanced binding affinity with a common TCR, agreeing with known results that the HLA-DQ2.5 serotype exhibits increased risk for CeD. Our findings reveal that our proposed absolute binding affinity FEP method is appropriate for predicting HLA binding for disparate antigens with different genotypes. We also discuss atomic-level details of HLA genotypes interacting with gluten peptides and TCRs in regard to the pathogenesis of CeD.

Molecular mechanism of secreted amyloid-β precursor protein in binding and modulating GABABR1a

A recent phenomenal study discovered that the extension domain of secreted amyloid-β precursor protein (sAPP) can bind to the intrinsically disordered sushi 1 domain of the γ-aminobutyric acid type B receptor subunit 1a (GABA_BR1a) and modulate its synaptic transmission. The work provided an important structural foundation for the modulation of GABA_BR1a; however, the detailed molecular interaction mechanism, crucial for future drug design, remains elusive. Here, we further investigated the dynamical interactions between sAPP peptides and the natively unstructured sushi 1 domain using all-atom molecular dynamics simulations, for both the 17-residue sAPP peptide (APP 17-mer) and its minimally active 9 residue segment (APP 9-mer). We then explored mutations of the APP 9-mer with rigorous free energy perturbation (FEP) calculations. Our in silico mutagenesis studies revealed key residues (D4, W6, and W7) responsible for the binding with the sushi 1 domain. More importantly, one double mutation based on different vertebrate APP sequences from evolution exhibited a stronger binding (ΔΔG = −1.91 ± 0.66 kcal mol⁻¹), indicating a potentially enhanced GABA_BR1a modulator. These large-scale simulations may provide new insights into the binding mechanism between sAPP and the sushi 1 domain, which could open new avenues in the development of future GABA_BR1a-specific therapeutics.

A recent phenomenal study discovered that the extension domain of secreted amyloid-β precursor protein (sAPP) can bind to the intrinsically disordered sushi 1 domain of the γ-aminobutyric acid type B receptor subunit 1a (GABA_BR1a) and modulate its synaptic transmission.

Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase

Starting from late 2019, the coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures, and supporting apparatuses. Recently, because of its positive results in clinical trials, remdesivir was approved by the Food and Drug Administration to treat COVID-19 through Emergency Use Authorization. Here, we used molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). We first constructed the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identity of 95.8%). We then built a putative preinsertion binding structure by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp without the RNA template. The putative binding structure was further optimized with molecular dynamics simulations. The resulting stable preinsertion state of remdesivir appeared to form hydrogen bonds with the RNA template when aligned with the newly solved cryo-EM structure of SARS-CoV-2 RdRp. The relative binding free energy between remdesivir and ATP was calculated to be -2.80 ± 0.84 kcal/mol, where remdesivir bound much stronger to SARS-CoV-2 RdRp than the natural substrate ATP. The ∼100-fold improvement in the K_d from remdesivir over ATP indicates an effective replacement of ATP in blocking of the RdRp preinsertion site. Key residues D618, S549, and R555 are found to be the contributors to the binding affinity of remdesivir. These findings suggest that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA replication, with key residues also identified for future lead optimization and/or drug resistance studies.

Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase

Starting from late 2019, the coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures, and supporting apparatuses. Recently, because of its positive results in clinical trials, remdesivir was approved by the Food and Drug Administration to treat COVID-19 through Emergency Use Authorization. Here, we used molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). We first constructed the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identity of 95.8%). We then built a putative preinsertion binding structure by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp without the RNA template. The putative binding structure was further optimized with molecular dynamics simulations. The resulting stable preinsertion state of remdesivir appeared to form hydrogen bonds with the RNA template when aligned with the newly solved cryo-EM structure of SARS-CoV-2 RdRp. The relative binding free energy between remdesivir and ATP was calculated to be -2.80 ± 0.84 kcal/mol, where remdesivir bound much stronger to SARS-CoV-2 RdRp than the natural substrate ATP. The ∼100-fold improvement in the Kd from remdesivir over ATP indicates an effective replacement of ATP in blocking of the RdRp preinsertion site. Key residues D618, S549, and R555 are found to be the contributors to the binding affinity of remdesivir. These findings suggest that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA replication, with key residues also identified for future lead optimization and/or drug resistance studies.

Length-Dependent Structural Transformations of Huntingtin PolyQ Domain Upon Binding to 2D-Nanomaterials

There is a strong negative correlation between the polyglutamine (polyQ) domain length (Q-length) in the intrinsically disordered Huntingtin protein (Htt) exon-1 and the age of onset of Huntington's disease (HD). PolyQ of Q-length longer than 40 has the propensity of forming very compact aggregate structures, leading to HD at full penetrance. Recent advances in nanobiotechnology provided a new platform for the development of novel diagnosis and therapeutics. Here, we explore the possibility of utilizing 2D-nanomaterials to inhibit the formation of supercompact polyQ structures through the so-called “folding-upon-binding” where the protein structure is dependent on the binding substrate. Using molecular dynamics simulations, we characterize two polyQ peptides with Q-length of 22 (Q22, normal length) and 46 (Q46, typical length causing HD) binding to both graphene and molybdenum disulfide (MoS₂) nanosheets, which have been applied as antibacterial or anticancer agents. Upon binding, Q22 unfolds and elongates on both grapheme and MoS₂ surfaces, regardless of its initial conformation, with graphene showing slightly stronger effect. In contrast, initially collapsed Q46 remains mostly collapsed within our simulation time on both nanosheets even though they do provide some “stretching” to Q46 as well. Further analyses indicate that the hydrophobic nature of graphene/MoS₂ promotes the stretching of polyQ on nanosheets. However, there is strong competition with the intra-polyQ interactions (mainly internal hydrogen bonds) leading to the disparate folding/binding behaviors of Q22 and Q46. Our results present distinct Q-length specific behavior of the polyQ domain upon binding to two types of 2D-nanomaterials which holds clinical relevance for Huntington's disease.

Directional extraction and penetration of phosphorene nanosheets to cell membranes

Recently, phosphorene, a novel two-dimensional nanomaterial with a puckered surface morphology, was shown to exhibit cytotoxicity, but its underlying molecular mechanisms remain unknown. Herein, using large scale molecular dynamics simulations, we show that phosphorene nanosheets can penetrate into and extract large amounts of phospholipids from the cell membranes due to the strong dispersion interaction between phosphorene and lipid molecules, which would reduce cell viability. The extracted phospholipid molecules are aligned along the wrinkle direction of the phosphorene nanosheet because of its unique puckered structure. Our results also reveal that small phosphorene nanosheets penetrate into the cell membrane in a specific direction which is determined by the size and surface topography of phosphorene and the thickness of the membrane. These findings might shed light on understanding phosphorene's cytotoxicity and would be helpful for the future potential biomedical applications of phosphorene, such as biosensors and antibacterial agents.

Defect-assisted protein HP35 denaturation on graphene

Structural defects in nanomaterials can alter their physical and chemical properties including magnetization, electronic and thermal conductivities, light absorption, and emission capabilities. Here, we investigated the potential impact of these defects on their biological effects through molecular dynamics simulations. By modeling the interaction between a graphene nanosheet and a widely used model protein, the chicken villin headpiece subdomain (HP35), we observed severe protein denaturation upon contact with defective graphene, while the protein remained intact on ideal graphene. The enhanced toxicity of defective graphene was due to the stronger attraction of the surface residues of HP35 from the defect edges (represented by carboxyl groups in our simulations) than from the ideal graphene. Upon binding to defective graphene, the contacting residues were restrained near the defective sites, which acted as "anchors" for the adsorbed protein. The "anchors" subsequently caused the protein to expose its aromatic and hydrophobic core residues to the graphene surface, via strong π-π stacking and hydrophobic interactions, thus leading to the unfolding of the protein. These findings not only highlight the importance of defects in nanomaterials' impact on biological systems, but also provide insights into fine-tuning the potential biological properties of nanomaterials through defect engineering.

Exploring the binding mechanism between human profilin (PFN1) and polyproline-10 through binding mode screening

The large magnitude of protein-protein interaction (PPI) pairs within the human interactome necessitates the development of predictive models and screening tools to better understand this fundamental molecular communication. However, despite enormous efforts from various groups to develop predictive techniques in the last decade, PPI complex structures are in general still very challenging to predict due to the large number of degrees of freedom. In this study, we use the binding complex of human profilin (PFN1) and polyproline-10 (P10) as a model system to examine various approaches, with the aim of going beyond normal protein docking for PPI prediction and evaluation. The potential of mean force (PMF) was first obtained from the time-consuming umbrella sampling, which confirmed that the most stable binding structure identified by the maximal PMF difference is indeed the crystallographic binding structure. Moreover, crucial residues previously identified in experimental studies, W3, H133, and S137 of PFN1, were found to form favorable hydrogen bonds with P10, suggesting a zipping process during the binding between PFN1 and P10. We then explored both regular molecular dynamics (MD) and steered molecular dynamics (SMD) simulations, seeking for better criteria of ranking the PPI prediction. Despite valuable information obtained from conventional MD simulations, neither the commonly used interaction energy between the two binding parties nor the long-term root mean square displacement correlates well with the PMF results. On the other hand, with a sizable collection of trajectories, we demonstrated that the average and minimal rupture works calculated from SMD simulations correlate fairly well with the PMFs (R ² = 0.67), making this a promising PPI screening method.

Exploration of HIV-1 fusion peptide–antibody VRC34.01 binding reveals fundamental neutralization sites

VRC34.01 antibody binding to a vulnerable site of HIV envelope glycoprotein (Env), the gp41 fusion peptide, renders robust HIV neutralization, but several critical mutations decrease binding affinity and result in unbinding.

All-atom virus simulations

The constant threat of viral disease can be combated by the development of novel vaccines and therapeutics designed to disrupt key features of virus structure or infection cycle processes. Such development relies on high-resolution characterization of viruses and their dynamical behaviors, which are often challenging to obtain solely by experiment. In response, all-atom molecular dynamics simulations are widely leveraged to study the structural components of viruses, leading to some of the largest simulation endeavors undertaken to date. The present work reviews exemplary all-atom simulation work on viruses, as well as progress toward simulating entire virions.

Mechanism by which DHA inhibits the aggregation of KLVFFA peptides: A molecular dynamics study

Docosahexaenoic acid (DHA) is one of the omega-3 polyunsaturated fatty acids, which has shown promising applications in lowering Aβ peptide neurotoxicity in vitro by preventing aggregation of Aβ peptides and relieving accumulation of Aβ fibrils. Unfortunately, the underlying molecular mechanisms of how DHA interferes with the aggregation of Aβ peptides remain largely enigmatic. Herein, aggregation behaviors of amyloid-β(Aβ)_16-21 peptides (KLVFFA) with or without the presence of a DHA molecule were comparatively studied using extensive all-atom molecular dynamics simulations. We found that DHA could effectively suppress the aggregation of KLVFFA peptides by redirecting peptides to unstructured oligomers. The highly hydrophobic and flexible nature of DHA made it randomly but tightly entangled with Leu-17, Phe-19, and Phe-20 residues to form unstructured but stable complexes. These lower-ordered unstructured oligomers could eventually pass through energy barriers to form ordered β-sheet structures through large conformational fluctuations. This study depicts a microscopic picture for understanding the role and mechanism of DHA in inhibition of aggregation of Aβ peptides, which is generally believed as one of the important pathogenic mechanisms of Alzheimer's disease.

Differential Pd-nanocrystal facets demonstrate distinct antibacterial activity against Gram-positive and Gram-negative bacteria

Noble metal-based nanomaterials have shown promise as potential enzyme mimetics, but the facet effect and underlying molecular mechanisms are largely unknown. Herein, with a combined experimental and theoretical approach, we unveil that palladium (Pd) nanocrystals exhibit facet-dependent oxidase and peroxidase-like activities that endow them with excellent antibacterial properties via generation of reactive oxygen species. The antibacterial efficiency of Pd nanocrystals against Gram-positive bacteria is consistent with the extent of their enzyme-like activity, that is {100}-faceted Pd cubes with higher activities kill bacteria more effectively than {111}-faceted Pd octahedrons. Surprisingly, a reverse trend of antibacterial activity is observed against Gram-negative bacteria, with Pd octahedrons displaying stronger penetration into bacterial membranes than Pd nanocubes, thereby exerting higher antibacterial activity than the latter. Our findings provide a deeper understanding of facet-dependent enzyme-like activities and might advance the development of noble metal-based nanomaterials with both enhanced and targeted antibacterial activities.

Metal–organic framework as an efficient filter for the removal of heavy metal cations in water

Efficient removal of heavy metal cations by a zirconium phosphonate based metal–organic framework (MOF) filter.

Overcoming the crystallization and designability issues in the ultrastable zirconium phosphonate framework system

Metal-organic frameworks (MOFs) based on zirconium phosphonates exhibit superior chemical stability suitable for applications under harsh conditions. These compounds mostly exist as poorly crystallized precipitates, and precise structural information has therefore remained elusive. Furthermore, a zero-dimensional zirconium phosphonate cluster acting as secondary building unit has been lacking, leading to poor designability in this system. Herein, we overcome these challenges and obtain single crystals of three zirconium phosphonates that are suitable for structural analysis. These compounds are built by previously unknown isolated zirconium phosphonate clusters and exhibit combined high porosity and ultrastability even in fuming acids. SZ-2 possesses the largest void volume recorded in zirconium phosphonates and SZ-3 represents the most porous crystalline zirconium phosphonate and the only porous MOF material reported to survive in aqua regia. SZ-2 and SZ-3 can effectively remove uranyl ions from aqueous solutions over a wide pH range, and we have elucidated the removal mechanism.

Zirconium phosphonate based metal-organic frameworks often exhibit superior chemical stabilities, but typically exist as poorly crystalline or amorphous materials. Here the authors exploit an ionothermal method to obtain highly porous and remarkably stable single crystalline zirconium phosphonate frameworks that can efficiently remove uranyl ions from aqueous solutions.

Graphene-Induced Pore Formation on Cell Membranes

Examining interactions between nanomaterials and cell membranes can expose underlying mechanisms of nanomaterial cytotoxicity and guide the design of safer nanomedical technologies. Recently, graphene has been shown to exhibit potential toxicity to cells; however, the molecular processes driving its lethal properties have yet to be fully characterized. We here demonstrate that graphene nanosheets (both pristine and oxidized) can produce holes (pores) in the membranes of A549 and Raw264.7 cells, substantially reducing cell viability. Electron micrographs offer clear evidence of pores created on cell membranes. Our molecular dynamics simulations reveal that multiple graphene nanosheets can cooperate to extract large numbers of phospholipids from the membrane bilayer. Strong dispersion interactions between graphene and lipid-tail carbons result in greatly depleted lipid density within confined regions of the membrane, ultimately leading to the formation of water-permeable pores. This cooperative lipid extraction mechanism for membrane perforation represents another distinct process that contributes to the molecular basis of graphene cytotoxicity.

Membrane destruction-mediated antibacterial activity of tungsten disulfide (WS2)

Tungsten disulfide (WS₂) demonstrates clear antibacterial activity through inducing mechanical damage to the bacteria membrane integrity.

Structural influence of proteins upon adsorption to MoS2 nanomaterials: comparison of MoS2 force field parameters

Molybdenum disulfide (MoS₂) has recently emerged as a promising nanomaterial in a wide range of applications due to its unique and impressive properties.

Graphene Oxide Nanosheets Retard Cellular Migration via Disruption of Actin Cytoskeleton

Graphene and graphene-based nanomaterials are broadly used for various biomedical applications due to their unique physiochemical properties. However, how graphene-based nanomaterials interact with biological systems has not been thoroughly studied. This study shows that graphene oxide (GO) nanosheets retard A549 lung carcinoma cell migration through nanosheet-mediated disruption of intracellular actin filaments. After GO nanosheets treatment, A549 cells display slower migration and the structure of the intracellular actin filaments is dramatically changed. It is found that GO nanosheets are capable of absorbing large amount of actin and changing the secondary structures of actin monomers. Large-scale all-atom molecular dynamics simulations further reveal the interactions between GO nanosheets and actin filaments at molecular details. GO nanosheets can insert into the interstrand gap of actin tetramer (helical repeating unit of actin filament) and cause the separation of the tetramer which eventually leads to the disruption of actin filaments. These findings offer a novel mechanism of GO nanosheet induced biophysical responses and provide more insights into their potential for biomedical applications.

Robust Denaturation of Villin Headpiece by MoS2 Nanosheet: Potential Molecular Origin of the Nanotoxicity

MoS₂ nanosheet, a new two-dimensional transition metal dichalcogenides nanomaterial, has attracted significant attentions lately due to many potential promising biomedical applications. Meanwhile, there is also a growing concern on its biocompatibility, with little known on its interactions with various biomolecules such as proteins. In this study, we use all-atom molecular dynamics simulations to investigate the interaction of a MoS₂ nanosheet with Villin Headpiece (HP35), a model protein widely used in protein folding studies. We find that MoS₂ exhibits robust denaturing capability to HP35, with its secondary structures severely destroyed within hundreds of nanosecond simulations. Both aromatic and basic residues are critical for the protein anchoring onto MoS₂ surface, which then triggers the successive protein unfolding process. The main driving force behind the adsorption process is the dispersion interaction between protein and MoS₂ monolayer. Moreover, water molecules at the interface between some key hydrophobic residues (e.g. Trp-64) and MoS₂ surface also help to accelerate the process driven by nanoscale drying, which provides a strong hydrophobic force. These findings might have shed new light on the potential nanotoxicity of MoS₂ to proteins with atomic details, which should be helpful in guiding future biomedical applications of MoS₂ with its nanotoxicity mitigated.

DNA translocation through single-layer boron nitride nanopores

Ultra-thin nanopores have become promising biological sensors because of their outstanding signal-to-noise ratio and spatial resolution. Here, we show that boron nitride (BN), which is a new two-dimensional (2D) material similar to graphene, could be utilized for making a nanopore with an atomic thickness. Using an all-atom molecular dynamics simulation, we investigated the dynamics of DNA translocation through the BN nanopore. The results of our simulations demonstrated that it is possible to detect different double-stranded DNA (dsDNA) sequences from the recording of ionic currents through the pore during the DNA translocation. Surprisingly, opposite to results for a graphene nanopore, we found the calculated blockage current for poly(A-T)40 in a BN nanopore to be less than that for poly(G-C)40. Also in contrast with the case of graphene nanopores, dsDNA models moved smoothly and in an unimpeded manner through the BN nanopores in the simulations, suggesting a potential advantage for using BN nanopores to design stall-free sequencing devices. BN nanopores, which display several properties (such as being hydrophilic and non-metallic) that are superior to those of graphene, are thus expected to find applications in the next generation of high-speed and low-cost biological sensors.

Accurate Estimates of Free Energy Changes in Charge Mutations

The ability to determine the effect of charge changes on the free energy is necessary for fundamental studies of the electrostatic contribution to protein binding and stability. Currently, calculations of differences in free energy for charge mutations carried out in systems with periodic boundary conditions must include an approximate self-energy correction that can be on the same order of magnitude as the calculated free energy change. Here, a new method for accurately calculating the free energy change associated with any alchemical mutation, regardless of charge, is presented. In this method, paired mutations of opposite charge exactly cancel the self-energy term because of its quadratic charge dependence. Since the self-energy term implicitly cancels within the method, a correction never needs to be applied, and the statistical uncertainty associated is thereby removed. An implementation procedure is described and applied to the free energy of ionic hydration and a charged amino acid mutation.

Protein corona mitigates the cytotoxicity of graphene oxide by reducing its physical interaction with cell membrane

Many recent studies have shown that the way nanoparticles interact with cells and biological molecules can vary greatly in the serum-containing or serum-free culture medium. However, the underlying molecular mechanisms of how the so-called "protein corona" formed in serum medium affects nanoparticles' biological responses are still largely unresolved. Thus, it is critical to understand how absorbed proteins on the surfaces of nanoparticles alter their biological effects. In this work, we have demonstrated with both experimental and theoretical approaches that protein BSA coating can mitigate the cytotoxicity of graphene oxide (GO) by reducing its cell membrane penetration. Our cell viability and cellular uptake experiments showed that protein corona decreased cellular uptake of GO, thus significantly mitigating the potential cytotoxicity of GO. The electron microscopy images also confirmed that protein corona reduced the cellular morphological damage by limiting GO penetration into the cell membrane. Further molecular dynamics (MD) simulations validated the experimental results and revealed that the adsorbed BSA in effect weakened the interaction between the phospholipids and graphene surface due to a reduction of the available surface area plus an unfavorable steric effect, thus significantly reducing the graphene penetration and lipid bilayer damaging. These findings provide new insights into the underlying molecular mechanism of this important graphene protein corona interaction with cell membranes, and should have implications in future development of graphene-based biomedical applications.

The role of basic residues in the adsorption of blood proteins onto the graphene surface

With its many unique properties, graphene has shown great potential in various biomedical applications, while its biocompatibility has also attracted growing concerns. Previous studies have shown that the formation of protein-graphene corona could effectively reduce its cytotoxicity; however, the underlying molecular mechanism remains not well-understood. Herein, we use extensive molecular dynamics simulations to demonstrate that blood proteins such as bovine fibrinogen (BFG) can absorb onto the graphene surface quickly and tightly to form a corona complex. Aromatic residues contributed significantly during this adsorption process due to the strong π−π stacking interactions between their aromatic rings and the graphene sp²-carbons. Somewhat surprisingly, basic residues like arginine, also played an equally or even stronger role during this process. The strong dispersion interactions between the sidechains of these solvent-exposed basic residues and the graphene surface provide the driving force for a tight binding of these basic residues. To the best of our knowledge, this is the first study with blood proteins to show that, in addition to the aromatic residues, the basic residues also play an important role in the formation of protein-graphene corona complexes.

Bio-mimicking of proline-rich motif applied to carbon nanotube reveals unexpected subtleties underlying nanoparticle functionalization

Here, we report computational studies of the SH3 protein domain interacting with various single-walled carbon nanotubes (SWCNT) either bare or functionalized by mimicking the proline-rich motif (PRM) ligand (PPPVPPRR) and compare it to the SH3-PRM complex binding. With prolines or a single arginine attached, the SWCNT gained slightly on specificity when compared with the bare control, whereas with multi-arginine systems the specificity dropped dramatically to our surprise. Although the electrostatic interaction provided by arginines is crucial in the recognition between PRM and SH3 domain, our results suggest that attaching multiple arginines to the SWCNT has a detrimental effect on the binding affinity. Detailed analysis of the MD trajectories found two main factors that modulate the specificity of the binding: the existence of competing acidic patches at the surface of SH3 that leads to "trapping and clamping" by the arginines, and the rigidity of the SWCNT introducing entropic penalties in the proper binding. Further investigation revealed that the same "clamping" phenomenon exits in the PRM-SH3 system, which has not been reported in previous literature. The competing effects between nanoparticle and its functionalization components revealed by our model system should be of value to current and future nanomedicine designs.

Molecular recognition of metabotropic glutamate receptor type 1 (mGluR1): synergistic understanding with free energy perturbation and linear response modeling

Metabotropic glutamate receptors (mGluRs) constitute an important family of the G-protein coupled receptors. Due to their widespread distribution in the central nervous system (CNS), these receptors are attractive candidates for understanding the molecular basis of various cognitive processes as well as for designing inhibitors for relevant psychiatric and neurological disorders. Despite many studies on drugs targeting the mGluR receptors to date, the molecular level details on the ligand binding dynamics still remain unclear. In this study, we performed in silico experiments for mGluR1 with 29 different ligands including known synthetic agonists and antagonists as well as natural amino acids. The ligand-receptor binding affinities were estimated by the use of atomistic simulations combined with the mathematically rigorous, Free Energy Perturbation (FEP) method, which successfully recognized the native agonist l-glutamate among the highly favorable binders, and also accurately distinguished antagonists from agonists. Comparative contact analysis also revealed the binding mode differences between natural and non-natural amino acid-based ligands. Several factors potentially affecting the ligand binding affinity and specificity were identified including net charges, dipole moments, and the presence of aromatic rings. On the basis of these findings, linear response models (LRMs) were built for different sets of ligands that showed high correlations (R(2) > 0.95) to the corresponding FEP binding affinities. These results identify some key factors that determine ligand-mGluR1 binding and could be used for future inhibitor designs and support a role for in silico modeling for understanding receptor ligand interactions.

The complex and specific pMHC interactions with diverse HIV-1 TCR clonotypes reveal a structural basis for alterations in CTL function

Immune control of viral infections is modulated by diverse T cell receptor (TCR) clonotypes engaging peptide-MHC class I complexes on infected cells, but the relationship between TCR structure and antiviral function is unclear. Here we apply in silico molecular modeling with in vivo mutagenesis studies to investigate TCR-pMHC interactions from multiple CTL clonotypes specific for a well-defined HIV-1 epitope. Our molecular dynamics simulations of viral peptide-HLA-TCR complexes, based on two independent co-crystal structure templates, reveal that effective and ineffective clonotypes bind to the terminal portions of the peptide-MHC through similar salt bridges, but their hydrophobic side-chain packings can be very different, which accounts for the major part of the differences among these clonotypes. Non-specific hydrogen bonding to viral peptide also accommodates greater epitope variants. Furthermore, free energy perturbation calculations for point mutations on the viral peptide KK10 show excellent agreement with in vivo mutagenesis assays, with new predictions confirmed by additional experiments. These findings indicate a direct structural basis for heterogeneous CTL antiviral function.

Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study

A major current challenge for drug design efforts focused on protein kinases is the development of drug resistance caused by spontaneous mutations in the kinase catalytic domain. The ubiquity of this problem means that it would be advantageous to develop fast, effective computational methods that could be used to determine the effects of potential resistance-causing mutations before they arise in a clinical setting. With this long-term goal in mind, we have conducted a combined experimental and computational study of the thermodynamic effects of active-site mutations on a well-characterized and high-affinity interaction between a protein kinase and a small-molecule inhibitor. Specifically, we developed a fluorescence-based assay to measure the binding free energy of the small-molecule inhibitor, SB203580, to the p38α MAP kinase and used it measure the inhibitor's affinity for five different kinase mutants involving two residues (Val38 and Ala51) that contact the inhibitor in the crystal structure of the inhibitor-kinase complex. We then conducted long, explicit-solvent thermodynamic integration (TI) simulations in an attempt to reproduce the experimental relative binding affinities of the inhibitor for the five mutants; in total, a combined simulation time of 18.5 μs was obtained. Two widely used force fields - OPLS-AA/L and Amber ff99SB-ILDN - were tested in the TI simulations. Both force fields produced excellent agreement with experiment for three of the five mutants; simulations performed with the OPLS-AA/L force field, however, produced qualitatively incorrect results for the constructs that contained an A51V mutation. Interestingly, the discrepancies with the OPLS-AA/L force field could be rectified by the imposition of position restraints on the atoms of the protein backbone and the inhibitor without destroying the agreement for other mutations; the ability to reproduce experiment depended, however, upon the strength of the restraints' force constant. Imposition of position restraints in corresponding simulations that used the Amber ff99SB-ILDN force field had little effect on their ability to match experiment. Overall, the study shows that both force fields can work well for predicting the effects of active-site mutations on small molecule binding affinities and demonstrates how a direct combination of experiment and computation can be a powerful strategy for developing an understanding of protein-inhibitor interactions.

Engineering tocopherol selectivity in α-TTP: a combined in vitro/in silico study

We present a combined in vitro/in silico study to determine the molecular origin of the selectivity of [Formula: see text]-tocopherol transfer protein ([Formula: see text]-TTP) towards [Formula: see text]-tocopherol. Molecular dynamics simulations combined to free energy perturbation calculations predict a binding free energy for [Formula: see text]-tocopherol to [Formula: see text]-TTP 8.26[Formula: see text]2.13 kcal mol[Formula: see text] lower than that of [Formula: see text]-tocopherol. Our calculations show that [Formula: see text]-tocopherol binds to [Formula: see text]-TTP in a significantly distorted geometry as compared to that of the natural ligand. Variations in the hydration of the binding pocket and in the protein structure are found as well. We propose a mutation, A156L, which significantly modifies the selectivity properties of [Formula: see text]-TTP towards the two tocopherols. In particular, our simulations predict that A156L binds preferentially to [Formula: see text]-tocopherol, with striking structural similarities to the wild-type-[Formula: see text]-tocopherol complex. The affinity properties are confirmed by differential scanning fluorimetry as well as in vitro competitive binding assays. Our data indicate that residue A156 is at a critical position for determination of the selectivity of [Formula: see text]-TTP. The engineering of TTP mutants with modulating binding properties can have potential impact at industrial level for easier purification of single tocopherols from vitamin E mixtures coming from natural oils or synthetic processes. Moreover, the identification of a [Formula: see text]-tocopherol selective TTP offers the possibility to challenge the hypotheses for the evolutionary development of a mechanism for [Formula: see text]-tocopherol selection in omnivorous animals.

An induced pocket for the binding of potent fusion inhibitor CL-385319 with H5N1 influenza virus hemagglutinin

The influenza glycoprotein hemagglutinin (HA) plays crucial roles in the early stage of virus infection, including receptor binding and membrane fusion. Therefore, HA is a potential target for developing anti-influenza drugs. Recently, we characterized a novel inhibitor of highly pathogenic H5N1 influenza virus, CL-385319, which specifically inhibits HA-mediated viral entry. Studies presented here identified the critical binding residues for CL-385319, which clustered in the stem region of the HA trimer by site-directed mutagenesis. Extensive computational simulations, including molecular docking, molecular dynamics simulations, molecular mechanics generalized Born surface area (MM_GBSA) calculations, charge density and Laplacian calculations, have been carried out to uncover the detailed molecular mechanism that underlies the binding of CL-385319 to H5N1 influenza virus HA. It was found that the recognition and binding of CL-385319 to HA proceeds by a process of “induced fit” whereby the binding pocket is formed during their interaction. Occupation of this pocket by CL-385319 stabilizes the neutral pH structure of hemagglutinin, thus inhibiting the conformational rearrangements required for membrane fusion. This “induced fit” pocket may be a target for structure-based design of more potent influenza fusion inhibitors.

Understanding the molecular mechanism of the broad and potent neutralization of HIV-1 by antibody VRC01 from the perspective of molecular dynamics simulation and binding free energy calculations

VRC01 is one of the most broadly and potently neutralizing HIV-1 antibodies known-it has been shown to neutralize 91 % of the tested primary isolate Env pseudoviruses by recognizing the viral envelope glycoprotein gp120. To explore the mechanism of HIV-1 neutralization by VRC01 and thus obtain valuable information for vaccine design, we performed molecular dynamics simulations and binding free energy calculations for apo-VRC01, apo-gp120, and the gp120-VRC01 complex. For gp120, residue energy decomposition analysis showed that the hotspot residues Asn280, Lys282, Asp368, Ile371, and Asp457 are located in three primary loops, including the CD4-binding loop, loop D, and loop V5. For VRC01, the hotspot residues Trp47, Trp50, Asn58, Arg61, Gln64, Trp100, and Tyr91 mainly come from CDR2 of the heavy chain. By decomposing the binding free energy into different components, intermolecular van der Waals interactions and nonpolar solvation were found to dominate the binding process. Principal component analysis of loops D and V5, which are related to neutralization resistance, indicated that these two areas have a larger conformational space in apo-gp120 compared to bound gp120. A comparison of three representative structures from the cluster analysis of loops D and V5 indicated that changes primarily occur at the tip of loop V5, and are caused by fluctuations in the terminal Glu1 residue of the antibody. This information can be used to guide the design of vaccines and small molecule inhibitors.

Free-energy simulations reveal that both hydrophobic and polar interactions are important for influenza hemagglutinin antibody binding

Antibodies binding to conserved epitopes can provide a broad range of neutralization to existing influenza subtypes and may also prevent the propagation of potential pandemic viruses by fighting against emerging strands. Here we propose a computational framework to study structural binding patterns and detailed molecular mechanisms of viral surface glycoprotein hemagglutinin (HA) binding with a broad spectrum of neutralizing monoclonal antibody fragments (Fab). We used rigorous free-energy perturbation (FEP) methods to calculate the antigen-antibody binding affinities, with an aggregate underlying molecular-dynamics simulation time of several microseconds (∼2 μs) using all-atom, explicit-solvent models. We achieved a high accuracy in the validation of our FEP protocol against a series of known binding affinities for this complex system, with <0.5 kcal/mol errors on average. We then introduced what to our knowledge are novel mutations into the interfacial region to further study the binding mechanism. We found that the stacking interaction between Trp-21 in HA2 and Phe-55 in the CDR-H2 of Fab is crucial to the antibody-antigen association. A single mutation of either W21A or F55A can cause a binding affinity decrease of ΔΔG > 4.0 kcal/mol (equivalent to an ∼1000-fold increase in the dissociation constant K(d)). Moreover, for group 1 HA subtypes (which include both the H1N1 swine flu and the H5N1 bird flu), the relative binding affinities change only slightly (< ±1 kcal/mol) when nonpolar residues at the αA helix of HA mutate to conservative amino acids of similar size, which explains the broad neutralization capability of antibodies such as F10 and CR6261. Finally, we found that the hydrogen-bonding network between His-38 (in HA1) and Ser-30/Gln-64 (in Fab) is important for preserving the strong binding of Fab against group 1 HAs, whereas the lack of such hydrogen bonds with Asn-38 in most group 2 HAs may be responsible for the escape of antibody neutralization. These large-scale simulations may provide new insight into the antigen-antibody binding mechanism at the atomic level, which could be essential for designing more-effective vaccines for influenza.

Mechanism of drug resistance of hemagglutinin of influenza virus and potent scaffolds inhibiting its function

Highly pathogenic influenza viruses have become a global threat to humans. It is important to select an effective therapeutic option suitable for the subtypes in an epidemic or pandemic. To increase the options, the development of novel antiviral agents acting on targets different from those of the currently approved drugs is required. In this study, we performed molecular dynamics simulations on a spike protein on the viral envelop, hemagglutinin, for the wild-type and three kinds of mutants using a model system consisting of a trimeric hemagglutinin complex, viral lipid membrane, solvation waters, and ions. A natural product, stachyflin, which shows a high level of antiviral activity specific to some subtypes of influenza viruses, was examined on binding to the wild-type hemagglutinin by docking simulation. The compound potency of stachyflin is, however, easily lost due to resistant mutations. From a comparison of simulation results between the wild-type and the resistant mutants, the reason for the drug resistance of hemagglutinin was clarified. Next, 8 compounds were selected from a chemical database by in silico screening, considering the findings from the simulations. Inhibitory activities to suppress the proliferation of influenza virus were measured by cell-based antiviral assays, and two chemical scaffolds were found to be potent for an inhibitor. More than 30 derivatives bearing either of these two chemical scaffolds were synthesized, and cell culture assays were carried out to evaluate the compound potency. Several derivatives displayed a high compound potency, and 50% effective concentrations of two synthesized compounds were below 1 μM.

Receptor binding by influenza virus: using computational techniques to extend structural data

Influenza attaches to host cells via hemagglutinin binding of cell-surface glycans. These relatively low-affinity interactions involving flexible ligands are critical in determining tissue and host specificity, but their dynamic nature complicates structural characterization of hemagglutinin-receptor complexes. Molecular simulation can assist in analyzing glycan and protein flexibility in crystallized complexes, assessing how binding might change under mutation or altered glycosylation patterns, and evaluating how soluble ligands may relate to physiological presentation on the plasma membrane. Molecular dynamics simulation also has the potential to help integrate structural and dynamic data sources. Here we review recent progress from analysis of molecular dynamics simulation and outline challenges for the future.

Acquisition of human-type receptor binding specificity by new H5N1 influenza virus sublineages during their emergence in birds in Egypt

Highly pathogenic avian influenza A virus subtype H5N1 is currently widespread in Asia, Europe, and Africa, with 60% mortality in humans. In particular, since 2009 Egypt has unexpectedly had the highest number of human cases of H5N1 virus infection, with more than 50% of the cases worldwide, but the basis for this high incidence has not been elucidated. A change in receptor binding affinity of the viral hemagglutinin (HA) from α2,3- to α2,6-linked sialic acid (SA) is thought to be necessary for H5N1 virus to become pandemic. In this study, we conducted a phylogenetic analysis of H5N1 viruses isolated between 2006 and 2009 in Egypt. The phylogenetic results showed that recent human isolates clustered disproportionally into several new H5 sublineages suggesting that their HAs have changed their receptor specificity. Using reverse genetics, we found that these H5 sublineages have acquired an enhanced binding affinity for α2,6 SA in combination with residual affinity for α2,3 SA, and identified the amino acid mutations that produced this new receptor specificity. Recombinant H5N1 viruses with a single mutation at HA residue 192 or a double mutation at HA residues 129 and 151 had increased attachment to and infectivity in the human lower respiratory tract but not in the larynx. These findings correlated with enhanced virulence of the mutant viruses in mice. Interestingly, these H5 viruses, with increased affinity to α2,6 SA, emerged during viral diversification in bird populations and subsequently spread to humans. Our findings suggested that emergence of new H5 sublineages with α2,6 SA specificity caused a subsequent increase in human H5N1 influenza virus infections in Egypt, and provided data for understanding the virus's pandemic potential.

Rapid estimation of binding activity of influenza virus hemagglutinin to human and avian receptors

A critical step for avian influenza viruses to infect human hosts and cause epidemics or pandemics is acquisition of the ability of the viral hemagglutinin (HA) to bind to human receptors. However, current global influenza surveillance does not monitor HA binding specificity due to a lack of rapid and reliable assays. Here we report a computational method that uses an effective scoring function to quantify HA-receptor binding activities with high accuracy and speed. Application of this method reveals receptor specificity changes and its temporal relationship with antigenicity changes during the evolution of human H3N2 viruses. The method predicts that two amino acid differences at 222 and 225 between HAs of A/Fujian/411/02 and A/Panama/2007/99 viruses account for their differences in binding to both avian and human receptors; this prediction was verified experimentally. The new computational method could provide an urgently needed tool for rapid and large-scale analysis of HA receptor specificities for global influenza surveillance.