Biochemical Characterization and Structural Modeling of Fused Glucose-6-Phosphate Dehydrogenase-Phosphogluconolactonase from Giardia lamblia.

Glucose-6-phosphate dehydrogenase (G6PD) is the first enzyme in the pentose phosphate pathway and is highly relevant in the metabolism of Giardialamblia. Previous reports suggested that the G6PD gene is fused with the 6-phosphogluconolactonase (6PGL) gene (6pgl). Therefore, in this work, we decided to characterize the fused G6PD-6PGL protein in Giardialamblia. First, the gene of g6pd fused with the 6pgl gene (6gpd::6pgl) was isolated from trophozoites of Giardialamblia and the corresponding G6PD::6PGL protein was overexpressed and purified in Escherichia coli. Then, we characterized the native oligomeric state of the G6PD::6PGL protein in solution and we found a catalytic dimer with an optimum pH of 8.75. Furthermore, we determined the steady-state kinetic parameters for the G6PD domain and measured the thermal stability of the protein in both the presence and absence of guanidine hydrochloride (Gdn-HCl) and observed that the G6PD::6PGL protein showed alterations in the stability, secondary structure, and tertiary structure in the presence of Gdn-HCl. Finally, computer modeling studies revealed unique structural and functional features, which clearly established the differences between G6PD::6PGL protein from G. lamblia and the human G6PD enzyme, proving that the model can be used for the design of new drugs with antigiardiasic activity. These results broaden the perspective for future studies of the function of the protein and its effect on the metabolism of this parasite as a potential pharmacological target.

Impact of Lipid Composition and Receptor Conformation on the Spatio-temporal Organization of µ-Opioid Receptors in a Multi-component Plasma Membrane Model.

The lipid composition of cell membranes has increasingly been recognized as playing an important role in the function of various membrane proteins, including G Protein-Coupled Receptors (GPCRs). For instance, experimental and computational evidence has pointed to lipids influencing receptor oligomerization directly, by physically interacting with the receptor, and/or indirectly, by altering the bulk properties of the membrane. While the exact role of oligomerization in the function of class A GPCRs such as the µ-opioid receptor (MOR) is still unclear, insight as to how these receptors oligomerize and the relevance of the lipid environment to this phenomenon is crucial to our understanding of receptor function. To examine the effect of lipids and different MOR conformations on receptor oligomerization we carried out extensive coarse-grained molecular dynamics simulations of crystal structures of inactive and/or activated MOR embedded in an idealized mammalian plasma membrane composed of 63 lipid types asymmetrically distributed across the two leaflets. The results of these simulations point, for the first time, to specific direct and indirect effects of the lipids, as well as the receptor conformation, on the spatio-temporal organization of MOR in the plasma membrane. While sphingomyelin-rich, high-order lipid regions near certain transmembrane (TM) helices of MOR induce an effective long-range attractive force on individual protomers, both long-range lipid order and interface formation are found to be conformation dependent, with a larger number of different interfaces formed by inactive MOR compared to active MOR.

Macro and nano scale modelling of water-water interactions at ambient and low temperature: relaxation and residence times.

The decay dynamics of ambient and low temperature liquid water has been investigated through all-atom molecular dynamics simulations, residence times calculations and time correlation functions from 300 K down to 243 K. Those simulations replicate the experimental value of the self-diffusion constant as a function of temperature by tuning the damping factor of the Langevin equation of motion. A stretched exponential function exp[-(t/τ)(ß)] has been found to properly describe the relaxation of residence times calculated at different temperatures for solvent molecules in a nanodrop of free water modelled as a sphere of nanometric dimensions. As the temperature goes down the decay time τ increases showing a divergence at Ts = 227 ± 3 K. The temperature independence of the dimensionless stretched exponent ß = 0.59 ± 0.01 suggests the presence of, not a characteristic relaxation time (since ß≠ 1), but a distribution of decay times that also holds at low temperature. An explanation for such heterogeneity can be found at the nanoscopic level. Moreover it can be concluded that the distribution of times already reported for the dynamics of water surrounding proteins (ß≤ 0.5) can not be exclusively due to the presence of the biomolecule itself since isolated water also exhibits such behaviour. The above reported Ts and ß values quantitatively reproduce experimental data.

A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks.

The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ.

Structure and dynamics of water in crowded environments slows down peptide conformational changes.

The concentration of macromolecules inside the cell is high with respect to conventional in vitro experiments or simulations. In an effort to characterize the effects of crowding on the thermodynamics and kinetics of disordered peptides, molecular dynamics simulations were run at different concentrations by varying the number of identical weakly interacting peptides inside the simulation box. We found that the presence of crowding does not influence very much the overall thermodynamics. On the other hand, peptide conformational dynamics was found to be strongly affected, resulting in a dramatic slowing down at larger concentrations. The observation of long lived water bridges between peptides at higher concentrations points to a nontrivial role of the solvent in the altered peptide kinetics. Our results reinforce the idea for an active role of water in molecular crowding, an effect that is expected to be relevant for problems influenced by large solvent exposure areas like in intrinsically disordered proteins.

The quest for self-consistency in hydrogen bond definitions.

In the last decades several hydrogen-bond definitions were proposed by classical computer simulations. Aiming at validating their self-consistency on a wide range of conditions, here we present a comparative study of six among the most common hydrogen-bond definitions for temperatures ranging from 220 K to 400 K and six classical water models. Our results show that, in the interval of temperatures investigated, a generally weak agreement among definitions is present. Moreover, cutoff choice for geometrically based definitions depends on both temperature and water model. As such, analysis of the same water model at different temperatures as well as different water models at the same temperature would require the development of specific cutoff values. Interestingly, large discrepancies were found between two hydrogen-bond definitions which were recently introduced to improve on more conventional methods. Our results reinforce the idea that a more universal way to characterize hydrogen bonds in classical molecular systems is needed.

Consensus for the Fip35 folding mechanism?

Recent advances in computational power and simulation programs finally delivered the first examples of reversible folding for small proteins with an all-atom description. But having at hand the atomistic details of the process did not lead to a straightforward interpretation of the mechanism. For the case of the Fip35 WW-domain where multiple long trajectories of 100 µs are available from D. E. Shaw Research, different interpretations emerged. Some of those are in clear contradiction with each other while others are in qualitative agreement. Here, we present a network-based analysis of the same data by looking at the local fluctuations of conventional order parameters for folding. We found that folding occurs through two major pathways, one almost four times more populated than the other. Each pathway involves the formation of an intermediate with one of the two hairpins in a native configuration. The quantitative agreement of our results with a state-of-the-art reaction coordinate optimization procedure as well as qualitative agreement with other Markov-state-models and different simulation schemes provides strong evidence for a multiple folding pathways scenario with the presence of intermediates.

Opitz GBBB syndrome with total anomalous pulmonary venous connection: A new MID1 gene variant.

BACKGROUND: Opitz GBBB syndrome (GBBB) is an X-linked disease characterized by midline defects, including congenital heart defects. We present our diagnostic approach to the identification of GBBB in a consanguineous family in which two males siblings were concordant for a total anomalous connection of pulmonary veins and minor facial dysmorphias. METHODS: Targeted exome sequencing analysis of a 380-gene panel associated with cardiovascular disease was performed on the propositus. Interpretative analysis of the exome results was conducted, and 3D models of the protein changes were generated. RESULTS: We identified a NM_000381.4:c.608G>A;p.(Arg203Gln) change in MID1, affecting the conformation of the B-box 2 domain of the protein, with a zinc finger structure and associated protein interactions. This clinical phenotype is consistent with GBBB; however, the type of congenital heart disease observed in this case has not been previously reported. CONCLUSION: A new likely pathogenic variant on MID1 c.608G>A was found to be associated with Opitz GBBB syndrome.

Accounting for the kinetics in order parameter analysis: lessons from theoretical models and a disordered peptide.

Molecular simulations as well as single molecule experiments have been widely analyzed in terms of order parameters, the latter representing candidate probes for the relevant degrees of freedom. Notwithstanding this approach is very intuitive, mounting evidence showed that such descriptions are inaccurate, leading to ambiguous definitions of states and wrong kinetics. To overcome these limitations a framework making use of order parameter fluctuations in conjunction with complex network analysis is investigated. Derived from recent advances in the analysis of single molecule time traces, this approach takes into account the fluctuations around each time point to distinguish between states that have similar values of the order parameter but different dynamics. Snapshots with similar fluctuations are used as nodes of a transition network, the clusterization of which into states provides accurate Markov-state-models of the system under study. Application of the methodology to theoretical models with a noisy order parameter as well as the dynamics of a disordered peptide illustrates the possibility to build accurate descriptions of molecular processes on the sole basis of order parameter time series without using any supplementary information.

Towards a microscopic description of the free-energy landscape of water.

Free-energy landscape theory is often used to describe complex molecular systems. Here, a microscopic description of water structure and dynamics based on configuration-space-networks and molecular dynamics simulations of the TIP4P/2005 model is applied to investigate the free-energy landscape of water. The latter is built on top of a large set of water microstates describing the kinetic stability of local hydrogen-bond arrangements up to the second solvation shell. In temperature space, the landscape displays three different regimes. At around ambient conditions, the free-energy surface is characterized by many short-lived basins of attraction which are structurally well-defined (inhomogeneous regime). At lower temperatures instead, the liquid rapidly becomes homogeneous. In this regime, the free energy is funneled-like, with fully coordinated water arrangements at the bottom of the funnel. Finally, a third regime develops below the temperature of maximal compressibility (Widom line) where the funnel becomes steeper with few interconversions between microstates other than the fully coordinated ones. Our results present a way to manage the complexity of water structure and dynamics, connecting microscopic properties to its ensemble behavior.

Exploring the druggability of the binding site of aurovertin, an exogenous allosteric inhibitor of FOF1-ATP synthase.

In addition to playing a central role in the mitochondria as the main producer of ATP, FOF1-ATP synthase performs diverse key regulatory functions in the cell membrane. Its malfunction has been linked to a growing number of human diseases, including hypertension, atherosclerosis, cancer, and some neurodegenerative, autoimmune, and aging diseases. Furthermore, inhibition of this enzyme jeopardizes the survival of several bacterial pathogens of public health concern. Therefore, FOF1-ATP synthase has emerged as a novel drug target both to treat human diseases and to combat antibiotic resistance. In this work, we carried out a computational characterization of the binding sites of the fungal antibiotic aurovertin in the bovine F1 subcomplex, which shares a large identity with the human enzyme. Molecular dynamics simulations showed that although the binding sites can be described as preformed, the inhibitor hinders inter-subunit communications and exerts long-range effects on the dynamics of the catalytic site residues. End-point binding free energy calculations revealed hot spot residues for aurovertin recognition. These residues were also relevant to stabilize solvent sites determined from mixed-solvent molecular dynamics, which mimic the interaction between aurovertin and the enzyme, and could be used as pharmacophore constraints in virtual screening campaigns. To explore the possibility of finding species-specific inhibitors targeting the aurovertin binding site, we performed free energy calculations for two bacterial enzymes with experimentally solved 3D structures. Finally, an analysis of bacterial sequences was carried out to determine conservation of the aurovertin binding site. Taken together, our results constitute a first step in paving the way for structure-based development of new allosteric drugs targeting FOF1-ATP synthase sites of exogenous inhibitors.

Exploring the free energy landscape: from dynamics to networks and back.

Knowledge of the Free Energy Landscape topology is the essential key to understanding many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers there are, what the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times and rate constants, or hierarchical relationships among basins, completes the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides.

Expanding the Structural Diversity of DNA Methyltransferase Inhibitors.

Inhibitors of DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug discovery. They are also chemical tools to understand the biochemistry of epigenetic processes. Herein, we report five distinct inhibitors of DNMT1 characterized in enzymatic inhibition assays that did not show activity with DNMT3B. It was concluded that the dietary component theaflavin is an inhibitor of DNMT1. Two additional novel inhibitors of DNMT1 are the approved drugs glyburide and panobinostat. The DNMT1 enzymatic inhibitory activity of panobinostat, a known pan inhibitor of histone deacetylases, agrees with experimental reports of its ability to reduce DNMT1 activity in liver cancer cell lines. Molecular docking of the active compounds with DNMT1, and re-scoring with the recently developed extended connectivity interaction features approach, led to an excellent agreement between the experimental IC50 values and docking scores.

Cell-Permeable Bak BH3 Peptide Induces Chemosensitization of Hematologic Malignant Cells.

Hematologic malignancies such as leukemias and lymphomas are among the leading causes of pediatric cancer death worldwide, and although survival rates have improved with conventional treatments, the development of drug-resistant cancer cells may lead to patient relapse and limited possibilities of a cure. Drug-resistant cancer cells in these hematologic neoplasms are induced by overexpression of the antiapoptotic B-cell lymphoma 2 (Bcl-2) protein families, such as Bcl-XL, Bcl-2, and Mcl-1. We have previously shown that peptides from the BH3 domain of the proapoptotic Bax protein that also belongs to the Bcl-2 family may antagonize the antiapoptotic activity of the Bcl-2 family proteins, restore apoptosis, and induce chemosensitization of tumor cells. Furthermore, cell-permeable Bax BH3 peptides also elicit antitumor activity and extend survival in a murine xenograft model of human B non-Hodgkin's lymphoma. However, the activity of the BH3 peptides of the proapoptotic Bak protein of the Bcl-2 family against these hematologic malignant cells requires further characterization. In this study, we report the ability of the cell-permeable Bak BH3 peptide to restore apoptosis and induce chemosensitization of acute lymphoblastic leukemia and non-Hodgkin's lymphoma cell lines, and this event is enhanced with the coadministration of cell-permeable Bax BH3 peptide and represents an attractive approach to improve the patient outcomes with relapsed or refractory hematological malignant cells.

Molecular dynamics of the histamine H3 membrane receptor reveals different mechanisms of GPCR signal transduction.

In this work, we studied the mechanisms of classical activation and inactivation of signal transduction by the histamine H3 receptor, a 7-helix transmembrane bundle G-Protein Coupled Receptor through long-time-scale atomistic molecular dynamics simulations of the receptor embedded in a hydrated double layer of dipalmitoyl phosphatidyl choline, a zwitterionic polysaturated ordered lipid. Three systems were prepared: the apo receptor, representing the constitutively active receptor; and two holo-receptors-the receptor coupled to the antagonist/inverse agonist ciproxifan, representing the inactive state of the receptor, and the receptor coupled to the endogenous agonist histamine and representing the active state of the receptor. An extensive analysis of the simulation showed that the three states of H3R present significant structural and dynamical differences as well as a complex behavior given that the measured properties interact in multiple and interdependent ways. In addition, the simulations described an unexpected escape of histamine from the orthosteric binding site, in agreement with the experimental modest affinities and rapid off-rates of agonists.

Live Attenuated Salmonella enterica Expressing and Releasing Cell-Permeable Bax BH3 Peptide Through the MisL Autotransporter System Elicits Antitumor Activity in a Murine Xenograft Model of Human B Non-hodgkin's Lymphoma.

The survival of patients with non-Hodgkin's lymphoma (NHL) has substantially improved with current treatments. Nevertheless, the appearance of drug-resistant cancer cells leads to patient relapse. It is therefore necessary to find new antitumor therapies that can completely eradicate transformed cells. Chemotherapy-resistant cancer cells are characterized by the overexpression of members of the anti-apoptotic B-cell lymphoma 2 (Bcl-2) protein family, such as Bcl-XL, Bcl-2, and Mcl-1. We have recently shown that peptides derived from the BH3 domain of the pro-apoptotic Bax protein may antagonize the anti-apoptotic activity of the Bcl-2 family proteins, restore apoptosis, and induce chemosensitization of tumor cells. In this study, we investigated the feasibility of releasing this peptide into the tumor microenvironment using live attenuated Salmonella enterica, which has proven to be an ally in cancer therapy due to its high affinity for tumor tissue, its ability to activate the innate and adaptive antitumor immune responses, and its potential use as a delivery system of heterologous molecules. Thus, we expressed and released the cell-permeable Bax BH3 peptide from the surface of Salmonella enterica serovar Typhimurium SL3261 through the MisL autotransporter system. We demonstrated that this recombinant bacterium significantly decreased the viability and increased the apoptosis of Ramos cells, a human B NHL cell line. Indeed, the intravenous administration of this recombinant Salmonella enterica elicited antitumor activity and extended survival in a xenograft NHL murine model. This antitumor activity was mediated by apoptosis and an inflammatory response. Our approach may represent an eventual alternative to treat relapsing or refractory NHL.

Molecular details of dimerization kinetics reveal negligible populations of transient µ-opioid receptor homodimers at physiological concentrations.

Various experimental and computational techniques have been employed over the past decade to provide structural and thermodynamic insights into G Protein-Coupled Receptor (GPCR) dimerization. Here, we use multiple microsecond-long, coarse-grained, biased and unbiased molecular dynamics simulations (a total of ~4 milliseconds) combined with multi-ensemble Markov state models to elucidate the kinetics of homodimerization of a prototypic GPCR, the µ-opioid receptor (MOR), embedded in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/cholesterol lipid bilayer. Analysis of these computations identifies kinetically distinct macrostates comprising several different short-lived dimeric configurations of either inactive or activated MOR. Calculated kinetic rates and fractions of dimers at different MOR concentrations suggest a negligible population of MOR homodimers at physiological concentrations, which is supported by acceptor photobleaching fluorescence resonance energy transfer (FRET) experiments. This study provides a rigorous, quantitative explanation for some conflicting experimental data on GPCR oligomerization.

Cloning and biochemical characterization of three glucose­6­phosphate dehydrogenase mutants presents in the Mexican population.

The deficiency of glucose­6­phosphate dehydrogenase (G6PD) is one of the most common inborn errors of metabolism worldwide. This congenital disorder generally results from mutations that are spread throughout the entire gene of G6PD. Three single-point mutations for G6PD have been reported in the Mexican population and named Veracruz (Arg365His), G6PD Seattle (Asp282His), and G6PD Mexico DF (Thr65Ala), whose biochemical characterization have not yet been studied. For this reason, in this work we analyzed the putative role of the three mutations to uncover the functional consequences on G6PD activity. To this end, was developed a method to clone, overexpress, and purify recombinant human G6PD. The results obtained from all variants showed a loss of catalysis by 80 to 97% and had a decrease in affinity for both physiological substrates with respect to the wild type (WT) G6PD. Our results also showed that the three mutations affected three-dimensional structure and protein stability, suggesting an unstable structure with low conformational stability that affected its G6PD functionality. Finally, based on the biochemical characterization of the unclassified G6PD Mexico DF, we suggest that this variant could be grouped as a Class I variant, because biochemical data are similar with other Class I G6PDs.

New perspectives on the computational characterization of the kinetics of binding-unbinding in drug design: implications for novel therapies.

The efficiency and the propensity of a drug to be bound to its target protein have been inseparable concepts for decades now. The correlation between the pharmacological activity and the binding affinity has been the first rule to design and optimize a new drug rationally. However, this argument does not prove to be infallible when the results of in vivo assays have to be confronted. Only recently, we understand that other magnitudes as the kinetic rates of binding and unbinding, or the mean residence time of the complex drug-protein, are equally relevant to draw a more accurate model of the mechanism of action of a drug. It is in this scenario where new computational techniques to simulate the all-atom dynamics of the biomolecular system find its valuable place on the challenge of designing new molecules for more effective and less toxic therapies.

Application of computational methods for anticancer drug discovery, design, and optimization.

Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.