Insights from investigating the interactions of adamantane-based drugs with the M2 proton channel from the H1N1 swine virus

Small molecular floribundiquinone B derived from medicinal plants inhibits acetylcholinesterase activity

Being a neurodegenerative disorder, Alzheimer's disease (AD) is the one of the most terrible diseases. And acetylcholinesterase (AChE) is considered as an important target for treating AD. Acetylcholinesterase inhibitors (AChEI) are considered to be one of the effective drugs for the treatment of AD. The aim of this study is to find a novel potential AChEI as a drug for the treatment of AD. In this study, instead of using the synthetic compounds, we used those extracted from plants to investigate the interaction between floribundiquinone B (FB) and AChE by means of both the experimental approach such as fluorescence spectra, ultraviolet-visible (UV-vis) absorption spectrometry, circular dichroism (CD) and the theoretical approaches such as molecular docking. The findings reported here have provided many useful clues and hints for designing more effective and less toxic drugs against Alzheimer's disease.

Exploring the structure and conformational landscape of human leptin. A molecular dynamics approach

Leptin is a hormone that regulates energy homeostasis, inflammation, hematopoiesis and immune response, among other functions (Houseknecht et al., 1998; Zhang et al., 1995; Paz-Filho et al., 2010). To obtain its crystallographic structure, it was necessary to substitute a tryptophan for a glutamic acid at position 100, thus creating a mutant leptin that has been reported to have biological activity comparable to the activity of the wild type but that crystallizes more readily. Here, we report a comparative study of the conformational space of WT and W100E leptin using molecular dynamics simulations performed at 300, 400, and 500 K. We detected differences between the interactions of the two proteins with local and distal effects, resulting in changes in the conformation, accessible surface area, compactness, electrostatic potential and dynamic behavior. Additionally, the series of unfolding events that occur when leptin is subjected to high temperature differs for the two constructs. We observed that both proteins are mostly unstructured after 20 ns of MD simulation at 500 K. However, WT leptin maintains a significant amount of secondary structure in helix α2, while the most stable region of W100E leptin is helix α3. Furthermore, we found that the region between residues 25 and 42 might adopt interconverting secondary structures ranging from α-helices and random coils to β-strand structures. Thus, this region can be considered an intrinsically disordered region. This atomistic description supports our understanding of leptin signaling and consequently might facilitate the use of leptin in treatments for the pathophysiologies in which it is implicated.

A novel influenza virus neuraminidase inhibitor AV5027

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

Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection

Motivation: Owing to its importance in both basic research (such as molecular evolution and protein attribute prediction) and practical application (such as timely modeling the 3D structures of proteins targeted for drug development), protein remote homology detection has attracted a great deal of interest. It is intriguing to note that the profile-based approach is promising and holds high potential in this regard. To further improve protein remote homology detection, a key step is how to find an optimal means to extract the evolutionary information into the profiles.

Results: Here, we propose a novel approach, the so-called profile-based protein representation, to extract the evolutionary information via the frequency profiles. The latter can be calculated from the multiple sequence alignments generated by PSI-BLAST. Three top performing sequence-based kernels (SVM-Ngram, SVM-pairwise and SVM-LA) were combined with the profile-based protein representation. Various tests were conducted on a SCOP benchmark dataset that contains 54 families and 23 superfamilies. The results showed that the new approach is promising, and can obviously improve the performance of the three kernels. Furthermore, our approach can also provide useful insights for studying the features of proteins in various families. It has not escaped our notice that the current approach can be easily combined with the existing sequence-based methods so as to improve their performance as well.

Availability and implementation: For users’ convenience, the source code of generating the profile-based proteins and the multiple kernel learning was also provided at

http://bioinformatics.hitsz.edu.cn/main/∼binliu/remote/

Contact:bliu@insun.hit.edu.cn or bliu@gordonlifescience.org

Supplementary information:Supplementary data are available at Bioinformatics online.

Structure and dynamic properties of membrane proteins using NMR

Integral membrane proteins are one of the most challenging groups of macromolecules despite their apparent conformational simplicity. They manage and drive transport, circulate information, and participate in cellular movements via interactions with other proteins and through intricate conformational changes. Their structural and functional decoding is challenging and has imposed demanding experimental development. Solution nuclear magnetic resonance (NMR) spectroscopy is one of the techniques providing the capacity to make a significant difference in the deciphering of the membrane protein structure-function paradigm. The method has evolved dramatically during the last decade resulting in a plethora of new experiments leading to a significant increase in the scientific repertoire for studying membrane proteins. Besides solving the three-dimensional structures using state-of-the-art approaches, a large variety of developments of well-established techniques are available providing insight into membrane protein flexibility, dynamics, and interactions. Inspired by the speed of development in the application of new strategies, by invention of methods to measure solvent accessibility and describe low-populated states, this review seeks to introduce the vast possibilities solution NMR can offer to the study of membrane protein structure-function analyses with special focus on applicability.

Computational studies on the substrate interactions of influenza A virus PB2 subunit

Influenza virus, which spreads around the world in seasonal epidemics and leads to large numbers of deaths every year, has several ribonucleoproteins in the central core of the viral particle. These viral ribonucleoproteins can specifically bind the conserved 3' and 5' caps of the viral RNAs with responsibility for replication and transcription of the viral RNA in the nucleus of infected cells. A fundamental question of most importance is that how the cap-binding proteins in the influenza virus discriminates between capped RNAs and non-capped ones. To get an answer, we performed molecular dynamics simulations and free energy calculations on the influenza A virus PB2 subunit, an important component of the RNP complexes, with a cap analog m7GTP. Our calculations showed that some key residues in the active site, such as Arg355, His357, Glu361 as well as Gln406, could offer significant hydrogen bonding and hydrophobic interactions with the guanine ring of the cap analog m7GTP to form an aromatic sandwich mechanism for the cap recognition and positioning in the active site. Subsequently, we applied this idea to a virtual screening procedure and identified 5 potential candidates that might be inhibitors against the PB2 subunit. Interestingly, 2 candidates Cpd1 and Cpd2 have been already reported to have inhibitory activities to the influenza virus cap-binding proteins. Further calculation also showed that they had comparatively higher binding affinities to the PB2 subunit than that of m7GTP. We believed that our findings could give an atomic insight into the deeper understanding of the cap recognition and binding mechanism, providing useful information for searching or designing novel drugs against influenza viruses.

Insights into the mutation-induced HHH syndrome from modeling human mitochondrial ornithine transporter-1

Human mitochondrial ornithine transporter-1 is reported in coupling with the hyperornithinemia-hyperammonemia-homocitrullinuria (HHH) syndrome, which is a rare autosomal recessive disorder. For in-depth understanding of the molecular mechanism of the disease, it is crucially important to acquire the 3D structure of human mitochondrial ornithine transporter-1. Since no such structure is available in the current protein structure database, we have developed it via computational approaches based on the recent NMR structure of human mitochondrial uncoupling protein (Berardi MJ, Chou JJ, et al. Nature 2011, 476:109–113). Subsequently, we docked the ligand L-ornithine into the computational structure to search for the favorable binding mode. It was observed that the binding interaction for the most favorable binding mode is featured by six remarkable hydrogen bonds between the receptor and ligand, and that the most favorable binding mode shared the same ligand-binding site with most of the homologous mitochondrial carriers from different organisms, implying that the ligand-binding sites are quite conservative in the mitochondrial carriers family although their sequences similarity is very low with 20% or so. Moreover, according to our structural analysis, the relationship between the disease-causing mutations of human mitochondrial ornithine transporter-1 and the HHH syndrome can be classified into the following three categories: (i) the mutation occurs in the pseudo-repeat regions so as to change the region of the protein closer to the mitochondrial matrix; (ii) the mutation is directly affecting the substrate binding pocket so as to reduce the substrate binding affinity; (iii) the mutation is located in the structural region closer to the intermembrane space that can significantly break the salt bridge networks of the protein. These findings may provide useful insights for in-depth understanding of the molecular mechanism of the HHH syndrome and developing effective drugs against the disease.

Alignment free comparison: similarity distribution between the DNA primary sequences based on the shortest absent word

This work proposes an alignment free comparison model for the DNA primary sequences. In this paper, we treat the double strands of the DNA rather than single strand. We define the shortest absent word of the double strands between the DNA sequences and some properties are studied to speed up the algorithm for searching the shortest absent word. We present a novel model for comparison, in which the similarity distribution is introduced to describe the similarity between the sequences. A distance measure is deduced based on the Shannon entropy meanwhile is used in phylogenetic analysis. Some experiments show that our model performs well in the field of sequence analysis.

Exploration of conformational transition in the aryl-binding site of human FXa using molecular dynamics simulations

Human coagulation Factor X (FX), a member of the vitamin K-dependent serine protease family, is a crucial component of the human coagulation cascade. Activated FX (FXa) participates in forming the prothrombinase complex on activated platelets to convert prothrombin to thrombin in coagulation reactions. In the current study, 30-ns MD simulations were performed on both the open and closed states of human FXa. Root mean squares (RMS) fluctuations showed that structural fluctuations concentrated on the loop regions of FXa, and the presence of a ligand in the closed system resulted in larger fluctuations of the gating residues. The open system had a gating distance from 9.23 to 11.33 Å, i.e., significantly larger than that of the closed system (4.69-6.35 Å), which allows diversified substrates of variable size to enter. Although the solvent accessible surface areas (SASA) of FXa remained the same in both systems, the open system generally had a larger total SASA or hydrophobic SASA (or both) for residues surrounding the S4 pocket. Additionally, more hydrogen bonds were formed in the closed state than in the open state of FXa, which is believed to play a significant role in maintaining the closed confirmation of the aryl-binding site. Based on the results of MD simulations, we propose that an induced-fit mechanism governs the functioning of human coagulation FX, which helps provide a better understanding of the interactions between FXa and its substrate, and the mechanism of the conformational changes involved in human coagulation.

A negative cooperativity mechanism of human CYP2E1 inferred from molecular dynamics simulations and free energy calculations

Human cytochrome P450 2E1 (CYP2E1) participates in the metabolism of over 2% of all the oral drugs. A hallmark peculiar feature of this enzyme is that it exhibits a pronounced negative cooperativity in substrate binding. However the mechanism by which the negative cooperativity occurs is unclear. Here, we performed molecular dynamics simulations and free energy calculations on human CYP2E1 to examine the structural differences between the substrate-free and the enzymes with one and two aniline molecules bound. Our results indicate that although the effector substrate does not bind in the active site cavity, it still can directly interact with the active site residues of human CYP2E1. The interaction of the effector substrate with the active site leads to a reorientation of active site residues, which thereby weakens the interactions of the active substrate with this site. We also identify a conserved residue T303 that plays a crucial role in the negative cooperative binding on the short-range effects. This residue is a key factor in the positioning of substrates and in proton delivery to the active site. Additionally, a long-range effect of the effector substrate is identified in which F478 is proposed to play a key role. As located in the interface between the active and effector sites, this residue structurally links the active and effector sites and is found to play a significant role in affecting substrate access and ligand positioning within the active site. In the negative cooperative binding, this residue can decrease the interactions of the active substrate with the active site by π-π stacking which then lowers the hydroxylation activity for the active substrate. These findings are in agreement with previous experimental observations and thus provide detailed atomistic insight into the poorly understood mechanism of the negative cooperativity in human CYP2E1.

An allosteric mechanism inferred from molecular dynamics simulations on phospholamban pentamer in lipid membranes

Phospholamban functions as a regulator of Ca(2+) concentration of cardiac muscle cells by triggering the bioactivity of sarcoplasmic reticulum Ca(2+)-ATPase. In order to understand its dynamic mechanism in the environment of bilayer surroundings, we performed long time-scale molecular dynamic simulations based on the high-resolution NMR structure of phospholamban pentamer. It was observed from the molecular dynamics trajectory analyses that the conformational transitions between the "bellflower" and "pinwheel" modes were detected for phospholamban. Particularly, the two modes became quite similar to each other after phospholamban was phosphorylated at Ser16. Based on these findings, an allosteric mechanism was proposed to elucidate the dynamic process of phospholamban interacting with Ca(2+)-ATPase.

Insights from modeling the 3D structure of New Delhi metallo-β-lactamse and its binding interactions with antibiotic drugs

New Delhi metallo-beta-lactamase (NDM-1) is an enzyme that makes bacteria resistant to a broad range of beta-lactam antibiotic drugs. This is because it can inactivate most beta-lactam antibiotic drugs by hydrolyzing them. For in-depth understanding of the hydrolysis mechanism, the three-dimensional structure of NDM-1 was developed. With such a structural frame, two enzyme-ligand complexes were derived by respectively docking Imipenem and Meropenem (two typical beta-lactam antibiotic drugs) to the NDM-1 receptor. It was revealed from the NDM-1/Imipenem complex that the antibiotic drug was hydrolyzed while sitting in a binding pocket of NDM-1 formed by nine residues. And for the case of NDM-1/Meropenem complex, the antibiotic drug was hydrolyzed in a binding pocket formed by twelve residues. All these constituent residues of the two binding pockets were explicitly defined and graphically labeled. It is anticipated that the findings reported here may provide useful insights for developing new antibiotic drugs to overcome the resistance problem.

Structural and dynamic mechanisms for the function and inhibition of the M2 proton channel from influenza A virus

The M2 proton channel from influenza A virus, a prototype for a class of viral ion channels known as viroporins, conducts protons along a chain of water molecules and ionizable sidechains, including His37. Recent studies highlight a delicate interplay between protein folding, proton binding, and proton conduction through the channel. Drugs inhibit proton conduction by binding to an aqueous cavity adjacent to M2's proton-selective filter, thereby blocking access of proton to the filter, and altering the energetic landscape of the channel and the energetics of proton-binding to His37.

Molecular dynamics studies on T1 lipase: insight into a double-flap mechanism

T1 lipase is isolated from the palm Geobacillus zalihae strain T1 in Malaysia, functioning as a secreted protein responsible for the catalyzing hydrolysis of long-chain triglycerides into fatty acids and glycerol at high temperatures. In the current study, using 30 ns molecular dynamics simulations at different temperatures, an aqueous activation was detected for T1 lipase. This aqueous activation in T1 lipase was mainly caused by a double-flap movement mechanism. The double flaps were constituted by the hydrophobic helices 6 and 9. Helix 6 employed two major components with the hydrophilic part at the surface and the hydrophobic part inside. In the aqueous solution, the hydrophobic part could provide enough power for helix 6 to move away, driving the protein into an open configuration and exposing the catalytic triad. Our findings could provide structural evidence to support the double-flap movement, revealing the catalytic mechanism for T1 lipase.

Insights from studying the mutation-induced allostery in the M2 proton channel by molecular dynamics

As an essential component of the viral envelope, M2 proton channel plays a central role in the virus replications and has been a key target for drug design against the influenza A viruses. The adamantadine-based drugs, such as amantadine and rimantadine, were developed for blocking the channel so as to suppress the replication of viruses. However, patients, especially those infected by the H1N1 influenza A viruses, are increasingly suffering from the drug-resistance problem. According to the findings revealed recently by the high-resolution NMR studies, the drug-resistance problem is due to the structural allostery caused by some mutations, such as L26F, V27A and S31N, in the four-helix bundle of the channel. In this study, we are to address this problem from a dynamic point of view by conducting molecular dynamics (MD) simulations on both the open and the closed states of the wild-type (WT) and S31N mutant M2 channels in the presence of rimantadine. It was observed from the MD simulated structures that the mutant channel could still keep open even if binding with rimantadine, but the WT channel could not. This was because the mutation would destabilize the helix bundle and trigger it from a compact packing state to a loose one. It is anticipated that the findings may provide useful insights for in-depth understanding the action mechanism of the M2 channel and developing more-effective drugs against influenza A viruses.

Molecular modeling of BAD complex resided in a mitochondrion integrating glycolysis and apoptosis

BAD (Bcl-2 antagonist of cell death) and GK (glucokinase) reside in a mitochondrial complex together with PKA and PP1 catalytic units (PKAc and PP1c) and WAVE-1 that integrates glycolysis and apoptosis. Our research results reveal that BAD is phosphorylated and inactivated on Ser 75 in a BAD-Bcl-xL complex by PKA (targeted to mitochondria through association with WAVE1), resulting in the dissociation of BAD and its binding to GK. Moreover, GK can interact with PP1c and also distinguish WAVE1. On the other hand, BAD is dephosphorylated and activated on Ser75 by PP1c, leading to the separation of PKAc and its binding to the regulatory (R) subunit of PKA which by the dimerization domain of its R subunit connects with WAVE1 linked with GK of the complex. This may be the reason of the complex existing in liver mitochondria, regardless of phosphorylated and dephosphorylated BAD. Additionally, GK like PKA may also prevent Bcl-xL from rebinding to BAD by phosphorylating BAD at Ser 118. The BAD complex model reveals that BAD and GK play key roles because of BAD as a substrate for the PKA-PP1 pair and by BH3 domain directly interacting with GK. This is helpful for our development and research of the molecular mechanism of BAD integrating glycolysis and apoptosis.

Studies on the structural stability of rabbit prion probed by molecular dynamics simulations of its wild-type and mutants

Prion diseases are invariably fatal and highly infectious neurodegenerative diseases that affect humans and animals. Rabbits are the only mammalian species reported to be resistant to infection from prion diseases isolated from other species (Vorberg et al., 2003). Fortunately, the NMR structure of rabbit prion (124-228) (PDB entry 2FJ3), the NMR structure of rabbit prion protein mutation S173N (PDB entry 2JOH) and the NMR structure of rabbit prion protein mutation I214V (PDB entry 2JOM) were released recently. This paper studies these NMR structures by molecular dynamics simulations. Simulation results confirm the structural stability of wild-type rabbit prion, and show that the salt bridge between D177 and R163 greatly contributes to the structural stability of rabbit prion protein.

Predict potential drug targets from the ion channel proteins based on SVM

The identification of molecular targets is a critical step in the drug discovery and development process. Ion channel proteins represent highly attractive drug targets implicated in a diverse range of disorders, in particular in the cardiovascular and central nervous systems. Due to the limits of experimental technique and low-throughput nature of patch-clamp electrophysiology, they remain a target class waiting to be exploited. In our study, we combined three types of protein features, primary sequence, secondary structure and subcellular localization to predict potential drug targets from ion channel proteins applying classical support vector machine (SVM) method. In addition, our prediction comprised two stages. In stage 1, we predicted ion channel target proteins based on whole-genome target protein characteristics. Firstly, we performed feature selection by Mann-Whitney U test, then made predictions to identify potential ion channel targets by SVM and designed a new evaluating indicator Q to prioritize results. In stage 2, we made a prediction based on known ion channel target protein characteristics. Genetic algorithm was used to select features and SVM was used to predict ion channel targets. Then, we integrated results of two stages, and found that five ion channel proteins appeared in both prediction results including CGMP-gated cation channel beta subunit and Gamma-aminobutyric acid receptor subunit alpha-5, etc., and four of which were relative to some nerve diseases. It suggests that these five proteins are potential targets for drug discovery and our prediction strategies are effective.