Molecular dynamics simulations suggest that electrostatic funnel directs binding of Tamiflu to influenza N1 neuraminidases

Treatment of flexibility of protein backbone in simulations of protein-ligand interactions using steered molecular dynamics

To ensure that an external force can break the interaction between a protein and a ligand, the steered molecular dynamics simulation requires a harmonic restrained potential applied to the protein backbone. A usual practice is that all or a certain number of protein's heavy atoms or Cα atoms are fixed, being restrained by a small force. This present study reveals that while fixing both either all heavy atoms and or all Cα atoms is not a good approach, while fixing a too small number of few atoms sometimes cannot prevent the protein from rotating under the influence of the bulk water layer, and the pulled molecule may smack into the wall of the active site. We found that restraining the Cα atoms under certain conditions is more relevant. Thus, we would propose an alternative solution in which only the Cα atoms of the protein at a distance larger than 1.2 nm from the ligand are restrained. A more flexible, but not too flexible, protein will be expected to lead to a more natural release of the ligand.

An insight from computational approach to explore novel, high-affinity phosphodiesterase 10A inhibitors for neurological disorders

The enzyme Phosphodiesterase 10A (PDE10A) plays a regulatory role in the cAMP/protein kinase A (PKA) signaling pathway by means of hydrolyzing cAMP and cGMP. PDE10A emerges as a relevant pharmacological drug target for neurological conditions such as psychosis, schizophrenia, Parkinson's, Huntington's disease, and other memory-related disorders. In the current study, we subjected a set of 1,2,3-triazoles to be explored as PDE10A inhibitors using diverse computational approaches, including molecular docking, classical molecular dynamics (MD) simulations, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations, steered MD, and umbrella sampling simulations. Molecular docking of cocrystallized ligands papaverine and PFJ, along with a set of in-house synthesized molecules, suggested that molecule 3i haded the highest binding affinity, followed by 3h and 3j. Furthermore, the structural stability studies using MD and MM-PBSA indicated that the 3h and 3j formed stable complexes with PDE10A. The binding free energy of -240.642 kJ/mol and -201.406 kJ/mol was observed for 3h and 3j, respectively. However, the cocrystallized ligands papaverine and PFJ exhibited comparitively higher binding free energy values of -202.030 kJ/mol and -138.764 kJ/mol, respectively. Additionally, steered MD and umbrella sampling simulations provided conclusive evidence that the molecules 3h and 3j could be exploited as promising candidates to target PDE10A.Communicated by Ramaswamy H. Sarma.

Molecular docking used as an advanced tool to determine novel compounds on emerging infectious diseases: A systematic review

Emerging infectious diseases (EID) as well as reappearing irresistible infections are expanding worldwide. Utmost of similar cases, it was seen that the EIDs have long been perceived as a predominant conclusion of host-pathogen adaption. Here, one should get to analyze their host-pathogen interlink and their by needs to look ways, as an example, by exploitation process methodology particularly molecular docking and molecular dynamics simulation, have been utilized in recent time as the most outstanding tools. Hence, we have overviewed some of important factors that influences on EIDs especially HIV/AIDs, H1N1 and coronavirus. Moreover, here we specified the importance of molecular docking applications especially molecular dynamics simulations approach to determine novel compounds on the emerging infectious diseases. Additionally, in vivo and in vitro studies approach to determine novel compounds on the emerging infectious diseases that has implemented to evaluate the limiting affinities between small particles as well as macromolecule that can further, used as a target of HIV/AIDs, H1N1, and coronavirus were also discussed. These novel drug molecules approved in vivo and in vitro studies with reaffirm results and hence, it is clear that the computational methods (mainly molecular docking and molecular dynamics) are found to be more effective technique for drug discovery and medical practitioners.

Binding mechanism of oseltamivir and influenza neuraminidase suggests perspectives for the design of new anti-influenza drugs

Oseltamivir is a widely used influenza virus neuraminidase (NA) inhibitor that prevents the release of new virus particles from host cells. However, oseltamivir-resistant strains have emerged, but effective drugs against them have not yet been developed. Elucidating the binding mechanisms between NA and oseltamivir may provide valuable information for the design of new drugs against NA mutants resistant to oseltamivir. Here, we conducted large-scale (353.4 μs) free-binding molecular dynamics simulations, together with a Markov State Model and an importance-sampling algorithm, to reveal the binding process of oseltamivir and NA. Ten metastable states and five major binding pathways were identified that validated and complemented previously discovered binding pathways, including the hypothesis that oseltamivir can be transferred from the secondary sialic acid binding site to the catalytic site. The discovery of multiple new metastable states, especially the stable bound state containing a water-mediated hydrogen bond between Arg118 and oseltamivir, may provide new insights into the improvement of NA inhibitors. We anticipated the findings presented here will facilitate the development of drugs capable of combating NA mutations.

Influenza virus neuraminidase (NA), a viral membrane glycoprotein, plays an important role in the interactions with host cell surface receptors. The emergence and spread of influenza mutants resistant to neuraminidase inhibitors (NAIs), such as oseltamivir, has been of great concern. Despite many improvements to NAIs, no new first-line NAIs are currently in clinical use. Although there have been previous molecular dynamics simulation studies on the binding and dissociation process of oseltamivir-NA, we discovered new binding pathways and states of oseltamivir through larger-scale simulations and more systematic analysis, which may provide new ideas for the improvement of oseltamivir and even a series of NAIs. In our study, we strongly demonstrate that a detailed understanding of the drug−receptor association process is of fundamental importance for drug design and provide methodological references for the improvement of other drugs.

Critical Interactions Between the SARS-CoV-2 Spike Glycoprotein and the Human ACE2 Receptor

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human cells by binding its spike (S) glycoproteins to angiotensin-converting enzyme 2 (ACE2) receptors and causes the coronavirus disease 2019 (COVID-19). Therapeutic approaches to prevent SARS-CoV-2 infection are mostly focused on blocking S-ACE2 binding, but critical residues that stabilize this interaction are not well understood. By performing all-atom molecular dynamics (MD) simulations, we identified an extended network of salt bridges, hydrophobic and electrostatic interactions, and hydrogen bonds between the receptor-binding domain (RBD) of the S protein and ACE2. Mutagenesis of these residues on the RBD was not sufficient to destabilize binding but reduced the average work to unbind the S protein from ACE2. In particular, the hydrophobic end of RBD serves as the main anchor site and is the last to unbind from ACE2 under force. We propose that blocking the hydrophobic surface of RBD via neutralizing antibodies could prove to be an effective strategy to inhibit S-ACE2 interactions.

Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies

Local 3D-structural differences in homologous proteins contribute to functional diversity observed in a superfamily, but so far received little attention as bioinformatic analysis was usually carried out at the level of amino acid sequences. We have developed Zebra3D - the first-of-its-kind bioinformatic software for systematic analysis of 3D-alignments of protein families using machine learning. The new tool identifies subfamily-specific regions (SSRs) - patterns of local 3D-structure (i.e. single residues, loops, or secondary structure fragments) that are spatially equivalent within families/subfamilies, but are different among them, and thus can be associated with functional diversity and function-related conformational plasticity. Bioinformatic analysis of protein superfamilies by Zebra3D can be used to study 3D-determinants of catalytic activity and specific accommodation of ligands, help to prepare focused libraries for directed evolution or assist development of chimeric enzymes with novel properties by exchange of equivalent regions between homologs, and to characterize plasticity in binding sites. A companion Mustguseal web-server is available to automatically construct a 3D-alignment of functionally diverse proteins, thus reducing the minimal input required to operate Zebra3D to a single PDB code. The Zebra3D + Mustguseal combined approach provides the opportunity to systematically explore the value of SSRs in superfamilies and to use this information for protein design and drug discovery. The software is available open-access at https://biokinet.belozersky.msu.ru/Zebra3D.

Investigation on penetration of saffron components through lipid bilayer bound to spike protein of SARS-CoV-2 using steered molecular dynamics simulation

A coronavirus identified as COVID-19 is the reason for an infection outbreak which is started in December 2019. NO completely effective drugs and treatments are not recognized for this virus. Recently, saffron and its compounds were used to treat different viral diseases. Saffron extract and its major ingredients have shown antiviral effects. In this study, the steered molecular dynamics simulation was used for investigating the effect of four main components of saffron that include: crocin, crocetin, safranal, and picrocrocin as candidate for drug molecules, on COVID-19. The binding energies between drug molecules and spike protein and the main protease of the virus were evaluated. The obtained results based on Lennard-Jones and electrostatic potentials demonstrated that crocetin has a high affinity towards spike protein and also the main protease of the virus. Also, the quantum mechanics calculations elucidated that the crocetin could overcome energy barrier of lipid bilayer with strong dipole moment and polarizability. The pharmacokinetic and ADMET properties proved that crocetin could be a suitable drug candidate. So, crocetin could be a promising drug for treatment of COVID-19.

MovableType Software for Fast Free Energy-Based Virtual Screening: Protocol Development, Deployment, Validation, and Assessment

For decades, the complicated energy surfaces found in macromolecular protein:ligand structures, which require large amounts of computational time and resources for energy state sampling, have been an inherent obstacle to fast, routine free energy estimation in industrial drug discovery efforts. Beginning in 2013, the Merz research group addressed this cost with the introduction of a novel sampling methodology termed “Movable Type” (MT). Using numerical integration methods, the MT method reduces the computational expense for energy state sampling by independently calculating each atomic partition function from an initial molecular conformation in order to estimate the molecular free energy using ensembles of the atomic partition functions. In this work, we report a software package, the DivCon Discovery Suite with the MovableType module from QuantumBio Inc., that performs this MT free energy estimation protocol in a fast, fully encapsulated manner. We discuss the computational procedures and improvements to the original work, and we detail the corresponding settings for this software package. Finally, we introduce two validation benchmarks to evaluate the overall robustness of the method against a broad range of protein:ligand structural cases. With these publicly available benchmarks, we show that the method can use a variety of input types and parameters and exhibits comparable predictability whether the method is presented with “expensive” X-ray structures or “inexpensively docked” theoretical models. We also explore some next steps for the method. The MovableType software is available at http://www.quantumbioinc.com/

Plasticity of the 340-Loop in Influenza Neuraminidase Offers New Insight for Antiviral Drug Development

The recently discovered 340-cavity in influenza neuraminidase (NA) N6 and N7 subtypes has introduced new possibilities for rational structure-based drug design. However, the plasticity of the 340-loop (residues 342–347) and the role of the 340-loop in NA activity and substrate binding have not been deeply exploited. Here, we investigate the mechanism of 340-cavity formation and demonstrate for the first time that seven of nine NA subtypes are able to adopt an open 340-cavity over 1.8 μs total molecular dynamics simulation time. The finding that the 340-loop plays a role in the sialic acid binding pathway suggests that the 340-cavity can function as a druggable pocket. Comparing the open and closed conformations of the 340-loop, the side chain orientation of residue 344 was found to govern the formation of the 340-cavity. Additionally, the conserved calcium ion was found to substantially influence the stability of the 340-loop. Our study provides dynamical evidence supporting the 340-cavity as a druggable hotspot at the atomic level and offers new structural insight in designing antiviral drugs.

Deamidated Human Triosephosphate Isomerase is a Promising Druggable Target

Therapeutic strategies for the treatment of any severe disease are based on the discovery and validation of druggable targets. The human genome encodes only 600-1500 targets for small-molecule drugs, but posttranslational modifications lead to a considerably larger druggable proteome. The spontaneous conversion of asparagine (Asn) residues to aspartic acid or isoaspartic acid is a frequent modification in proteins as part of the process called deamidation. Triosephosphate isomerase (TIM) is a glycolytic enzyme whose deamidation has been thoroughly studied, but the prospects of exploiting this phenomenon for drug design remain poorly understood. The purpose of this study is to demonstrate the properties of deamidated human TIM (HsTIM) as a selective molecular target. Using in silico prediction, in vitro analyses, and a bacterial model lacking the tim gene, this study analyzed the structural and functional differences between deamidated and nondeamidated HsTIM, which account for the efficacy of this protein as a druggable target. The highly increased permeability and loss of noncovalent interactions of deamidated TIM were found to play a central role in the process of selective enzyme inactivation and methylglyoxal production. This study elucidates the properties of deamidated HsTIM regarding its selective inhibition by thiol-reactive drugs and how these drugs can contribute to the development of cell-specific therapeutic strategies for a variety of diseases, such as COVID-19 and cancer.

Mesoscale All-Atom Influenza Virus Simulations Suggest New Substrate Binding Mechanism

Influenza virus circulates in human, avian, and swine hosts, causing seasonal epidemic and occasional pandemic outbreaks. Influenza neuraminidase, a viral surface glycoprotein, has two sialic acid binding sites. The catalytic (primary) site, which also binds inhibitors such as oseltamivir carboxylate, is responsible for cleaving the sialic acid linkages that bind viral progeny to the host cell. In contrast, the functional annotation of the secondary site remains unclear. Here, we better characterize these two sites through the development of an all-atom, explicitly solvated, and experimentally based integrative model of the pandemic influenza A H1N1 2009 viral envelope, containing ∼160 million atoms and spanning ∼115 nm in diameter. Molecular dynamics simulations of this crowded subcellular environment, coupled with Markov state model theory, provide a novel framework for studying realistic molecular systems at the mesoscale and allow us to quantify the kinetics of the neuraminidase 150-loop transition between the open and closed states. An analysis of chloride ion occupancy along the neuraminidase surface implies a potential new role for the neuraminidase secondary site, wherein the terminal sialic acid residues of the linkages may bind before transfer to the primary site where enzymatic cleavage occurs. Altogether, our work breaks new ground for molecular simulation in terms of size, complexity, and methodological analyses of the components. It also provides fundamental insights into the understanding of substrate recognition processes for this vital influenza drug target, suggesting a new strategy for the development of anti-influenza therapeutics.

Impact of tetramerization on the ligand recognition of N1 influenza neuraminidase via MMGBSA approach

Influenza virus neuraminidase (NA) is a homotetrameric surface protein that, in contrast to other non-influenza NAs, requires a quaternary assembly to exhibit enzymatic activity, suggesting that the oligomeric state significantly impacts the active site of influenza NA. Nevertheless, most structure-based drug design studies have been reported by employing the monomeric state in the closed or open-loop due to the computational cost of employing the tetrameric NA. In this work, we present MD simulations coupled to the MMGBSA approach of avian N1 type NA in its monomeric and tetrameric closed and open-loop state both with and without the inhibitor oseltamivir and its natural substrate, sialic acid. Structural and energetic analyses revealed that the tetrameric state impacts flexibility as well as the map of interactions participating in stabilizing the protein-ligand complexes with respect to the monomeric state. It was observed that the tetrameric state exerts dissimilar effects in binding affinity, characteristic of positive and negative cooperativity for oseltamivir and sialic acid, respectively. Based on our results, to perform a confident structure-based drug design, as well as to evaluate the impact of key mutations through MD simulations, it is important to consider the tetrameric state closed-loop state.

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.

Kinetic, Thermodynamic, and Structural Analysis of Drug Resistance Mutations in Neuraminidase from the 2009 Pandemic Influenza Virus

Neuraminidase is the main target for current influenza drugs. Reduced susceptibility to oseltamivir, the most widely prescribed neuraminidase inhibitor, has been repeatedly reported. The resistance substitutions I223V and S247N, alone or in combination with the major oseltamivir-resistance mutation H275Y, have been observed in 2009 pandemic H1N1 viruses. We overexpressed and purified the ectodomain of wild-type neuraminidase from the A/California/07/2009 (H1N1) influenza virus, as well as variants containing H275Y, I223V, and S247N single mutations and H275Y/I223V and H275Y/S247N double mutations. We performed enzymological and thermodynamic analyses and structurally examined the resistance mechanism. Our results reveal that the I223V or S247N substitution alone confers only a moderate reduction in oseltamivir affinity. In contrast, the major oseltamivir resistance mutation H275Y causes a significant decrease in the enzyme’s ability to bind this drug. Combination of H275Y with an I223V or S247N mutation results in extreme impairment of oseltamivir’s inhibition potency. Our structural analyses revealed that the H275Y substitution has a major effect on the oseltamivir binding pose within the active site while the influence of other studied mutations is much less prominent. Our crystal structures also helped explain the augmenting effect on resistance of combining H275Y with both substitutions.

Thiamine and selected thiamine antivitamins - biological activity and methods of synthesis

Thiamine plays a very important coenzymatic and non-coenzymatic role in the regulation of basic metabolism. Thiamine diphosphate is a coenzyme of many enzymes, most of which occur in prokaryotes. Pyruvate dehydrogenase and 2-oxoglutarate dehydrogenase complexes as well as transketolase are the examples of thiamine-dependent enzymes present in eukaryotes, including human. Therefore, thiamine is considered as drug or diet supplement which can support the treatment of many pathologies including neurodegenerative and vascular system diseases. On the other hand, thiamine antivitamins, which can interact with thiamine-dependent enzymes impeding their native functions, thiamine transport into the cells or a thiamine diphosphate synthesis, are good propose to drug design. The development of organic chemistry in the last century allowed the synthesis of various thiamine antimetabolites such as amprolium, pyrithiamine, oxythiamine, or 3-deazathiamine. Results of biochemical and theoretical chemistry research show that affinity to thiamine diphosphate-dependent enzymes of these synthetic molecules exceeds the affinity of native coenzyme. Therefore, some of them have already been used in the treatment of coccidiosis (amprolium), other are extensively studied as cytostatics in the treatment of cancer or fungal infections (oxythiamine and pyrithiamine). This review summarizes the current knowledge concerning the synthesis and mechanisms of action of selected thiamine antivitamins and indicates the potential of their practical use.

Multiscale Simulation of Receptor-Drug Association Kinetics: Application to Neuraminidase Inhibitors

A detailed understanding of the drug-receptor association process is of fundamental importance for drug design. Due to the long time scales of typical binding kinetics, the atomistic simulation of the ligand traveling from bulk solution into the binding site is still computationally challenging. In this work, we apply a multiscale approach of combined Molecular Dynamics (MD) and Brownian Dynamics (BD) simulations to investigate association pathway ensembles for the two prominent H1N1 neuraminidase inhibitors oseltamivir and zanamivir. Including knowledge of the approximate binding site location allows for the selective confinement of detailed but expensive MD simulations and application of less demanding BD simulations for the diffusion controlled part of the association pathway. We evaluate a binding criterion based on the residence time of the inhibitor in the binding pocket and compare it to geometric criteria that require prior knowledge about the binding mechanism. The method ranks the association rates of both inhibitors in qualitative agreement with experiment and yields reasonable absolute values depending, however, on the reaction criteria. The simulated association pathway ensembles reveal that, first, ligands are oriented in the electrostatic field of the receptor. Subsequently, a salt bridge is formed between the inhibitor's carboxyl group and neuraminidase residue Arg368, followed by adopting the native binding mode. Unexpectedly, despite oseltamivir's higher overall association rate, the rate into the intermediate salt-bridge state was found to be higher for zanamivir. The present methodology is intrinsically parallelizable and, although computationally demanding, allows systematic binding rate calculation on selected sets of potential drug molecules.

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

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

Multilevel summation method for electrostatic force evaluation

The multilevel summation method (MSM) offers an efficient algorithm utilizing convolution for evaluating long-range forces arising in molecular dynamics simulations. Shifting the balance of computation and communication, MSM provides key advantages over the ubiquitous particle–mesh Ewald (PME) method, offering better scaling on parallel computers and permitting more modeling flexibility, with support for periodic systems as does PME but also for semiperiodic and nonperiodic systems. The version of MSM available in the simulation program NAMD is described, and its performance and accuracy are compared with the PME method. The accuracy feasible for MSM in practical applications reproduces PME results for water property calculations of density, diffusion constant, dielectric constant, surface tension, radial distribution function, and distance-dependent Kirkwood factor, even though the numerical accuracy of PME is higher than that of MSM. Excellent agreement between MSM and PME is found also for interface potentials of air–water and membrane–water interfaces, where long-range Coulombic interactions are crucial. Applications demonstrate also the suitability of MSM for systems with semiperiodic and nonperiodic boundaries. For this purpose, simulations have been performed with periodic boundaries along directions parallel to a membrane surface but not along the surface normal, yielding membrane pore formation induced by an imbalance of charge across the membrane. Using a similar semiperiodic boundary condition, ion conduction through a graphene nanopore driven by an ion gradient has been simulated. Furthermore, proteins have been simulated inside a single spherical water droplet. Finally, parallel scalability results show the ability of MSM to outperform PME when scaling a system of modest size (less than 100 K atoms) to over a thousand processors, demonstrating the suitability of MSM for large-scale parallel simulation.

High Performance Molecular Visualization: In-Situ and Parallel Rendering with EGL

Large scale molecular dynamics simulations produce terabytes of data that is impractical to transfer to remote facilities. It is therefore necessary to perform visualization tasks in-situ as the data are generated, or by running interactive remote visualization sessions and batch analyses co-located with direct access to high performance storage systems. A significant challenge for deploying visualization software within clouds, clusters, and supercomputers involves the operating system software required to initialize and manage graphics acceleration hardware. Recently, it has become possible for applications to use the Embedded-system Graphics Library (EGL) to eliminate the requirement for windowing system software on compute nodes, thereby eliminating a significant obstacle to broader use of high performance visualization applications. We outline the potential benefits of this approach in the context of visualization applications used in the cloud, on commodity clusters, and supercomputers. We discuss the implementation of EGL support in VMD, a widely used molecular visualization application, and we outline benefits of the approach for molecular visualization tasks on petascale computers, clouds, and remote visualization servers. We then provide a brief evaluation of the use of EGL in VMD, with tests using developmental graphics drivers on conventional workstations and on Amazon EC2 G2 GPU-accelerated cloud instance types. We expect that the techniques described here will be of broad benefit to many other visualization applications.

The significance of naturally occurring neuraminidase quasispecies of H5N1 avian influenza virus on resistance to oseltamivir: a point of concern

Viral adaptability and survival arise due to the presence of quasispecies populations that are able to escape the immune response or produce drug-resistant variants. However, the presence of H5N1 virus with natural mutations acquired without any drug selection pressure poses a great threat. Cloacal samples collected from the 2004-2005 epidemics in Thailand from Asian open-billed storks revealed one major and several minor quasispecies populations with mutations on the oseltamivir (OTV)-binding site of the neuraminidase gene (NA) without prior exposure to a drug. Therefore, this study investigated the binding between the NA-containing novel mutations and OTV drug using molecular dynamic simulations and plaque inhibition assay. The results revealed that the mutant populations, S236F mutant, S236F/C278Y mutant, A250V/V266A/P271H/G285S mutant and C278Y mutant, had a lower binding affinity with OTV as compared with the WT virus due to rearrangement of amino acid residues and increased flexibility in the 150-loop. This result was further emphasized through the IC50 values obtained for the major population and WT virus, 104.74 nM and 18.30 nM, respectively. Taken together, these data suggest that H5N1 viruses isolated from wild birds have already acquired OTV-resistant point mutations without any exposure to a drug.

Residue-based design of small molecule inhibitor for H1N1, H5N1 and H7N1 mutants

Point mutations H274Y and N294S can lead to resistance of influenza virus strains to some drug molecules. Recently, a large number of experiments has focused on the many frameworks and catalytic residues thought to prevent the efficacy of anti-flu drugs. In the past, most research has considered the role of drugs in rigid proteins rather than in flexible proteins. In this study, we used molecular dynamics simulation (MD) combined with structure- and ligand-based drug design (SBDD and LBDD) methods to study dynamic interaction and protein dynamics correlation statistics between compounds and both the framework and catalytic residues in influenza virus N1 strains. Drug candidates were screened using the IC50 of the docking result predicted by support vector machine, multiple linear regression, and genetic function approximation (P < 0.001). As shown by MD, saussureamine C and diiodotyrosine have a protein dynamics correlation similar to that of sialic acid, and both can participate in hydrogen bond formation with loop, framework, and catalytic residues. Our in silico findings suggest that saussureamine C can inhibit H274Y and N294S mutants, and that diiodotyrosine can also inhibit N294S mutants. Therefore, the drugs saussureamine C and diiodotyrosine have the potential to produce inhibitory effects on wild-type influenza virus and some N1 mutants.

Understanding the cross-resistance of oseltamivir to H1N1 and H5N1 influenza A neuraminidase mutations using multidimensional computational analyses

This study embarks on a comprehensive description of the conformational contributions to resistance of neuraminidase (N1) in H1N1 and H5N1 to oseltamivir, using comparative multiple molecular dynamic simulations. The available data with regard to elucidation of the mechanism of resistance as a result of mutations in H1N1 and H5N1 neuraminidases is not well established. Enhanced post-dynamic analysis, such as principal component analysis, solvent accessible surface area, free binding energy calculations, and radius of gyration were performed to gain a precise insight into the binding mode and origin of resistance of oseltamivir in H1N1 and H5N1 mutants. Three significant features reflecting resistance in the presence of mutations H274Y and I222K, of the protein complexed with the inhibitor are: reduced flexibility of the α-carbon backbone; an improved ΔE_ele of ~15 (kcal/mol) for H1N1 coupled with an increase in ΔG_sol (~13 kcal/mol) from wild-type to mutation; a low binding affinity in comparison with the wild-type of ~2 (kcal/mol) and ~7 (kcal/mol) with respect to each mutation for the H5N1 systems; and reduced hydrophobicity of the overall surface structure due to an impaired hydrogen bonding network. We believe the results of this study will ultimately provide a useful insight into the structural landscape of neuraminidase-associated binding of oseltamivir. Furthermore, the results can be used in the design and development of potent inhibitors of neuraminidases.

Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review

Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods.

Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase

Drug binding and unbinding are transient processes which are hardly observed by experiment and difficult to analyze by computational techniques. In this paper, we employed a cost-effective method called "pathway docking" in which molecular docking was used to screen ligand-receptor binding free energy surface to reveal possible paths of ligand approaching protein binding pocket. A case study was applied on oseltamivir, the key drug against influenza a virus. The equilibrium pathways identified by this method are found to be similar to those identified in prior studies using highly expensive computational approaches.

Molecular dynamics simulation in virus research

Virus replication in the host proceeds by chains of interactions between viral and host proteins. The interactions are deeply influenced by host immune molecules and anti-viral compounds, as well as by mutations in viral proteins. To understand how these interactions proceed mechanically and how they are influenced by mutations, one needs to know the structures and dynamics of the proteins. Molecular dynamics (MD) simulation is a powerful computational method for delineating motions of proteins at an atomic-scale via theoretical and empirical principles in physical chemistry. Recent advances in the hardware and software for biomolecular simulation have rapidly improved the precision and performance of this technique. Consequently, MD simulation is quickly extending the range of applications in biology, helping to reveal unique features of protein structures that would be hard to obtain by experimental methods alone. In this review, we summarize the recent advances in MD simulations in the study of virus–host interactions and evolution, and present future perspectives on this technique.

GPU/CPU Algorithm for Generalized Born/Solvent-Accessible Surface Area Implicit Solvent Calculations

Molecular dynamics methodologies comprise a vital research tool for structural biology. Molecular dynamics has benefited from technological advances in computing, such as multi-core CPUs and graphics processing units (GPUs), but harnessing the full power of hybrid GPU/CPU computers remains difficult. The generalized Born/solvent-accessible surface area implicit solvent model (GB/SA) stands to benefit from hybrid GPU/CPU computers, employing the GPU for the GB calculation and the CPU for the SA calculation. Here, we explore the computational challenges facing GB/SA calculations on hybrid GPU/CPU computers and demonstrate how NAMD, a parallel molecular dynamics program, is able to efficiently utilize GPUs and CPUs simultaneously for fast GB/SA simulations. The hybrid computation principles demonstrated here are generally applicable to parallel applications employing hybrid GPU/CPU calculations.

Long time scale GPU dynamics reveal the mechanism of drug resistance of the dual mutant I223R/H275Y neuraminidase from H1N1-2009 influenza virus

Multidrug resistance of the pandemic H1N1-2009 strain of influenza has been reported due to widespread treatment using the neuraminidase (NA) inhibitors, oseltamivir (Tamiflu), and zanamivir (Relenza). From clinical data, the single I223R (IR(1)) mutant of H1N1-2009 NA reduced efficacy of oseltamivir and zanamivir by 45 and 10 times, (1) respectively. More seriously, the efficacy of these two inhibitors against the double mutant I223R/H275Y (IRHY(2)) was significantly reduced by a factor of 12 374 and 21 times, respectively, compared to the wild-type.(2) This has led to the question of why the efficacy of the NA inhibitors is reduced by the occurrence of these mutations and, specifically, why the efficacy of oseltamivir against the double mutant IRHY was significantly reduced, to the point where oseltamivir has become an ineffective treatment. In this study, 1 μs of molecular dynamics (MD) simulations was performed to answer these questions. The simulations, run using graphical processors (GPUs), were used to investigate the effect of conformational change upon binding of the NA inhibitors oseltamivir and zanamivir in the wild-type and the IR and IRHY mutant strains. These long time scale dynamics simulations demonstrated that the mechanism of resistance of IRHY to oseltamivir was due to the loss of key hydrogen bonds between the inhibitor and residues in the 150-loop. This allowed NA to transition from a closed to an open conformation. Oseltamivir binds weakly with the open conformation of NA due to poor electrostatic interactions between the inhibitor and the active site. The results suggest that the efficacy of oseltamivir is reduced significantly because of conformational changes that lead to the open form of the 150-loop. This suggests that drug resistance could be overcome by increasing hydrogen bond interactions between NA inhibitors and residues in the 150-loop, with the aim of maintaining the closed conformation, or by designing inhibitors that can form a hydrogen bond to the mutant R223 residue, thereby preventing competition between R223 and R152.

A comparative analysis of protein targets of withdrawn cardiovascular drugs in human and mouse

Background

Mouse is widely used in animal testing of cardiovascular disease. However, a large number of cardiovascular drugs that have been experimentally proved to work well on mouse were withdrawn because they caused adverse side effects in human.

Methods

In this study, we investigate whether binding patterns of withdrawn cardiovascular drugs are conserved between mouse and human through computational dockings and molecular dynamic simulations. In addition, we also measured the level of conservation of gene expression patterns of the drug targets and their interacting partners by analyzing the microarray data.

Results

The results show that target proteins of withdrawn cardiovascular drugs are functionally conserved between human and mouse. However, all the binding patterns of withdrawn drugs we retrieved show striking difference due to sequence divergence in drug-binding pocket, mainly through loss or gain of hydrogen bond donors and distinct drug-binding pockets. The binding affinities of withdrawn drugs to their receptors tend to be reduced from mouse to human. In contrast, the FDA-approved and best-selling drugs are little affected.

Conclusions

Our analysis suggests that sequence divergence in drug-binding pocket may be a reasonable explanation for the discrepancy of drug effects between animal models and human.

Molecular-level simulation of pandemic influenza glycoproteins

Computational simulation of pandemic diseases provides important insight into many disease features that may benefit public health. This is especially true for the influenza virus, a continuing global pandemic threat. Molecular or atomic-level investigation of influenza has predominantly focused on the two major virus glycoproteins, neuraminidase (NA) and hemagglutinin (HA). In this chapter, we walk the readers through major considerations for studying pandemic influenza glycoproteins, from choosing the most useful choice of system(s) to avoiding common pitfalls in experimental design and execution. While a brief discussion of several potential simulation and docking techniques is presented, we emphasize molecular dynamics (MD) and Brownian dynamics (BD) simulation techniques and molecular docking, within the context of biologically outstanding questions in influenza research.

Two birds with one stone? Possible dual-targeting H1N1 inhibitors from traditional Chinese medicine

The H1N1 influenza pandemic of 2009 has claimed over 18,000 lives. During this pandemic, development of drug resistance further complicated efforts to control and treat the widespread illness. This research utilizes traditional Chinese medicine Database@Taiwan (TCM Database@Taiwan) to screen for compounds that simultaneously target H1 and N1 to overcome current difficulties with virus mutations. The top three candidates were de novo derivatives of xylopine and rosmaricine. Bioactivity of the de novo derivatives against N1 were validated by multiple machine learning prediction models. Ability of the de novo compounds to maintain CoMFA/CoMSIA contour and form key interactions implied bioactivity within H1 as well. Addition of a pyridinium fragment was critical to form stable interactions in H1 and N1 as supported by molecular dynamics (MD) simulation. Results from MD, hydrophobic interactions, and torsion angles are consistent and support the findings of docking. Multiple anchors and lack of binding to residues prone to mutation suggest that the TCM de novo derivatives may be resistant to drug resistance and are advantageous over conventional H1N1 treatments such as oseltamivir. These results suggest that the TCM de novo derivatives may be suitable candidates of dual-targeting drugs for influenza.

Multidrug-resistant pandemic (H1N1) 2009 infection in immunocompetent child

Recent case reports describe multidrug-resistant influenza A pandemic (H1N1) 2009 virus infection in immunocompromised patients exposed to neuraminidase inhibitors because of an I223R neuraminidase mutation. We report a case of multidrug-resistant pandemic (H1N1) 2009 bearing the I223R mutation in an ambulatory child with no previous exposure to neuraminidase inhibitors.

Effects of Biomolecular Flexibility on Alchemical Calculations of Absolute Binding Free Energies

The independent trajectory thermodynamic integration (IT-TI) approach (Lawrenz et. al J. Chem. Theory. Comput. 2009, 5:1106-1116(1)) for free energy calculations with distributed computing is employed to study two distinct cases of protein-ligand binding: first, the influenza surface protein N1 neuraminidase bound to the inhibitor oseltamivir, and second, the M. tuberculosis enzyme RmlC complexed with the molecule CID 77074. For both systems, finite molecular dynamics (MD) sampling and varied molecular flexibility give rise to IT-TI free energy distributions that are remarkably centered on the target experimental values, with a spread directly related to protein, ligand, and solvent dynamics. Using over 2 μs of total MD simulation, alternative protocols for the practical, general implementation of IT-TI are investigated, including the optimal use of distributed computing, the total number of alchemical intermediates, and the procedure to perturb electrostatics and van der Waals interactions. A protocol that maximizes predictive power and computational efficiency is proposed. IT-TI outperforms traditional TI predictions and allows a straightforward evaluation of the reliability of free energy estimates. Our study has broad implications for the use of distributed computing in free energy calculations of macromolecular systems.