On homology modeling of the M2 muscarinic acetylcholine receptor subtype

Twelve homology models of the human M₂ muscarinic receptor using different sets of templates have been designed using the Prime program or the modeller program and compared to crystallographic structure (PDB:3UON). The best models were obtained using single template of the closest published structure, the M₃ muscarinic receptor (PDB:4DAJ). Adding more (structurally distant) templates led to worse models. Data document a key role of the template in homology modeling. The models differ substantially. The quality checks built into the programs do not correlate with the RMSDs to the crystallographic structure and cannot be used to select the best model. Re-docking of the antagonists present in crystallographic structure and relative binding energy estimation by calculating MM/GBSA in Prime and the binding energy function in YASARA suggested it could be possible to evaluate the quality of the orthosteric binding site based on the prediction of relative binding energies. Although estimation of relative binding energies distinguishes between relatively good and bad models it does not indicate the best one. On the other hand, visual inspection of the models for known features and knowledge-based analysis of the intramolecular interactions allows an experimenter to select overall best models manually.     

Comparative pharmacophore modeling of human adenosine receptor A1 and A3 antagonists

Adenosine receptors are promising therapeutic targets in drug discovery. In this study, three-dimensional pharmacophore models of human adenosine receptor A1 and A3 antagonists were developed based on 26 and 23 diverse compounds, respectively. The best A1 pharmacophore model (A 1 _Hopy1) consists of four features: one hydrogen bond donor, one hydrophobic point and two ring aromatics, while the best A 3 pharmacophore model (A3 _Hopy1) also has four features: one hydrogen bond acceptor, one hydrophobic point and two ring aromatics. The correlation coefficients were 0.840 for A 1 test set with 146 diverse compounds and 0.827 for A3 test set with 238 diverse compounds. In the simulated virtual screening experiments, high enrichment factors of 6.51 and 6.90 were obtained for A 1 _Hopy1 and A3 _Hopy1 models, respectively. Moreover, two models also showed high subtype-selectivity in the simulated virtual screening experiments. These results could be helpful for the discovery of novel potent and selective A 1 and A3 antagonists.     

Semi-empirical correlation of solid solute solubility in supercritical carbon dioxide: Comparative study and proposition of a novel density-based model

A comprehensive data set on experimental solubility of 210 solid solutes in supercritical CO₂ counting 5550 data points has been used for comparison of the correlation performance of 21 empirical models. On the basis of the comparison results a new eight-parameter density-based model has been proposed. The comparison shows that the three-parameter models are the least accurate. The results also show that models that relate the logarithm of the solubility to the logarithm of solvent density and temperature are more accurate than models that include the pressure. When comparing the overall correlating performance in terms of average absolute relative deviation the proposed model is by far the best with an average absolute relative deviation lying in the range 0.17–81.99% and an average value of 8.88%.     

An Improved Force Field for O2, CO and CN Binding to Metalloporphyrins

Parametrization of a molecular-mechanics program to include terms specific for five- and six-coordinate transition metal complexes is applied to heme complexes. The principal new feature peculiar to five and six coordination is a term that represents the effect of electron-pair repulsion modified by the ligand electronegativity and takes into account the different possible structures of complexes. The model system takes into account the structural differences of the fixing centre in the haemoglobin subunits. The customary proximal histidine is added. The macrocycle heme IX is wholly considered in our model. The calculations show clearly that certain conformations of heme IX–histidine models are much more favourable than others for fixing O₂. From the O₂ binding in haemoglobin and myoglobin and in simple Fe porphyrin models it is concluded that the bent O₂ ligand is best viewed as bound superoxide, O₂ ^?. Rotation of axial ligands are practically free. A small modification of the model in both crystal and protein matrix affects the orientation of the ligands in experimental systems.     

Comparison of three models for permeation of CO2/CH4 mixtures in poly(phenylene oxide)

Two models for the permeability of pure gases have been extended to include binary gas mixtures. The first is an extension of a pure gas permeability model, proposed by Petropoulos, which is based on gradients of chemical potential. This model predicts the permeability of components in a gas mixture solely on the basis of competition for sorption sites within the polymer matrix. The second mixed gas model follows an earlier analysis by Barrer for pure gases which includes the effects of saturation of Langmuir sites on the diffusion as well as the sorption processes responsible for permeation. This generalized “competitive sorption/diffusion” model includes the effect of each gas component on the sorption and diffusion of the other component in the mixture. The flux equations from these two models have been solved numerically to predict the permeability of gas mixtures on the basis of pure gas sorption and transport parameters. Both the mixed gas Petropoulos and competitive sorption/diffusion model predictions are compared with predictions from the earlier simple competitive sorption model based on gradients of concentration. An analysis of all three models is presented for the case of CO₂/CH₄ permeability in poly(phenylene oxide) (PPO). As expected, the competitive sorption/diffusion model predicts lower permeability than either of the models which consider only competitive sorption effects. The permeability depression of both CO₂ and CH₄ predicted by the competitive sorption/diffusion model is roughly twice that predicted by the competitive sorption model, whereas the mixed gas Petropoulos model predictions for both gases lie between the other two model predictions. For the PPO/CO₂/CH₄ system, the methane permeability data lie above the predictions of all three models, whereas CO₂ data lie below the predictions of all models. Consequently, the competitive sorption/diffusion model gives the most accurate prediction for CO₂, while the simple competitive sorption model is best for methane. The effects of mixed gas sorption, fugacity, and CO₂-induced dilation were considered and do not explain the inaccuracies of any of the models. The relatively small errors in mixed gas permeability predictions using either of the three models are likely to be related to “transport plasticization” of PPO owing to high levels of CO₂ sorption and its effect on polymer segmental motions and gas diffusivity.     

The kinetics of gasification of char derived from sewage sludge

Gasification of char derived from sewage sludge was studied under different oxidizing atmospheres containing CO₂, O₂ or H₂O. The gasification tests were carried out in thermobalance at different temperatures and oxidizing reagent concentrations. The most efficient were the gaseous mixtures containing oxygen. The reaction took place at temperature 400–500 °C, whilst in the case of CO₂ and steam much higher temperatures (700–900 °C) were necessary to complete the conversion. Two rate models for gas–solid reaction were applied to describe the effect of char conversion on reaction rate. The shrinking core model for reaction-controlled regime was found to be the best for predicting the rate of char gasification in CO₂ and O₂ atmosphere. The experimental data for steam gasification of the char were fitted best by the first-order kinetics. The kinetic parameters estimated from the experimental data are in accordance with the literature for lignocellulosic char gasification and are the first published for sewage sludge char gasification.     

Predictive modeling and computational machine learning simulation of adsorption separation using advanced nanocomposite materials

Adsorption process was simulated in this study for removal of Hg and Ni from water using nanocomposite materials. The used nanostructured material for the adsorption study was a combined MOF and layered double hydroxide, which is considered as MOF-LDH in this work. The data were obtained from resources and different machine learning models were trained. We selected three different regression models, including elastic net, decision tree, and Gradient boosting, to make regression on the small data set with two inputs and two outputs. Inputs are Ion type (Hg or Ni) and initial ion concentration in the feed solution (C₀), and outputs are equilibrium concentration (Ce) and equilibrium capacity of the adsorbent (Qe) in this dataset. After tuning their hyper-parameters, final models were implemented and assessed using different metrics. In terms of the R2-score metric, all models have more than 0.97 for Ce and more than 0.88 for Qe. The Gradient Boosting has an R2-score of 0.994 for Qe. Also, considering RMSE and MAE, Gradient Boosting shows acceptable errors and best models. Finally, the optimal values with the GB model are identical to dataset optimal: (Ion = Ni, C₀ = 250, Ce = 206.0). However, for Qe, it is different and is equal to (Ion = Hg, C0 = 121.12, Ce = 606.15). The results revealed that the developed methods of simulation are of high capacity in prediction of adsorption for removal of heavy metals using nanostructure materials.     

Modeling of isospecific Ti sites in MgCl2 supported heterogeneous Ziegler-Natta catalysts

New models for the steric environment of Ti isospecific polymerization sites for poly(propylene) on MgCl₂ microcrystals are proposed. They directly involve a donor molecule in order to obtain isospecific activable Ti atoms otherwise belonging to isolated adsorbed TiCl₄ molecules or Ti₂Cl₈ dimers which are lacking of the required chirality for stereocontrol. The donor molecules able to attain at best this effect keep to some peculiar conformational rules settled by the authors in a previous theoretical-correlative study on highly active Lewis bases. The new 1,3-dimethoxypropane series suggested by the authors and recently patented by Montell has been examined in detail. Essentially three different types of closeness between Ti atoms and donor molecules can take place, in which different moieties of the diether compound help to build the ‘right’ steric environment in the site's neighbouring. In the three proposed models S1, S2, S3 the stereocontrol is attained through, respectively, one of the methoxy moieties, one of the methyls, and one of the central carbon atom substituents. New hypotheses on the role of Lewis bases in the preparation of isospecific heterogeneous Ziegler-Natta catalysts are discussed.     

The Effect of Functional Groups on the Phase Behavior of Carbon Dioxide Binaries and Their Role in CCS

In recent years we have focused our efforts on investigating various binary mixtures containing carbon dioxide to find the best candidate for CO₂ capture and, therefore, for applications in the field of CCS and CCUS technologies. Continuing this project, the present study investigates the phase behavior of three binary systems containing carbon dioxide and different oxygenated compounds. Two thermodynamic models are examined for their ability to predict the phase behavior of these systems. The selected models are the well-known Peng–Robinson (PR) equation of state and the General Equation of State (GEOS), which is a generalization for all cubic equations of state with two, three, and four parameters, coupled with classical van der Waals mixing rules (two-parameter conventional mixing rule, 2PCMR). The carbon dioxide + ethyl acetate, carbon dioxide + 1,4-dioxane, and carbon dioxide + 1,2-dimethoxyethane binary systems were analyzed based on GEOS and PR equation of state models. The modeling approach is entirely predictive. Previously, it was proved that this approach was successful for members of the same homologous series. Unique sets of binary interaction parameters for each equation of state, determined for the carbon dioxide + 2-butanol binary model system, based on k₁₂–l₁₂ method, were used to examine the three systems. It was shown that the models predict that CO₂ solubility in the three substances increases globally in the order 1,4-dioxane, 1,2-dimethoxyethane, and ethyl acetate. CO₂ solubility in 1,2-dimethoxyethane, 1.4-dioxane, and ethyl acetate reduces with increasing temperature for the same pressure, and increases with lowering temperature for the same pressure, indicating a physical dissolving process of CO₂ in all three substances. However, CO₂ solubility for the carbon dioxide + ether systems (1,4-dioxane, 1,2-dimethoxyethane) is better at low temperatures and pressures, and decreases with increasing pressures, leading to higher critical points for the mixtures. By contrast, the solubility of ethyl acetate in carbon dioxide is less dependent on temperatures and pressures, and the mixture has lower pressures critical points. In other words, the ethers offer better solubilization at low pressures; however, the ester has better overall miscibility in terms of lower critical pressures. Among the binary systems investigated, the 1,2-dimethoxyethane is the best solvent for CO₂ absorption.     

An evaluation of thermodynamic models for the prediction of drug and drug-like molecule solubility in organic solvents

Prediction of solubility of active pharmaceutical ingredients (API) in different solvents is one of the main issue for crystallization process design. Experimental determination is not always possible because of the small amount of product available in the early stages of a drug development. Thus, one interesting perspective is the use of thermodynamic models, which are usually employed for predicting the activity coefficients in case of Vapour-Liquid equilibria or Liquid-Liquid equilibria (VLE or LLE). The choice of the best thermodynamic model for Solid-Liquid equilibria (SLE) is not an easy task as most of them are not meant particularly for this. In this paper, several models are tested for the solubility prediction of five drugs or drug-like molecules: Ibuprofen, Acetaminophen, Benzoic acid, Salicylic acid and 4-aminobenzoic acid, and another molecule, anthracene, a rather simple molecule. The performance of predictive (UNIFAC, UNIFAC mod., COSMO-SAC) and semi-predictive (NRTL-SAC) models are compared and discussed according to the functional groups of the molecules and the selected solvents. Moreover, the model errors caused by solid state property uncertainties are taken into account. These errors are indeed not negligible when accurate quantitative predictions want to be performed. It was found that UNIFAC models give the best results and could be an useful method for rapid solubility estimations of an API in various solvents. This model achieves the order of magnitude of the experimental solubility and can predict in which solvents the drug will be very soluble, soluble or not soluble. In addition, predictions obtained with NRTL-SAC model are also in good agreement with the experiments, but in that case the relevance of the results is strongly dependent on the model parameters regressed from solubility data in single and mixed solvents. However, this is a very interesting model for quick estimations like UNIFAC models. Finally, COSMO-SAC needs more developments to increase its accuracy especially when hydrogen bonding is involved. In that case, the predicted solubility is always overestimated from two to three orders of magnitude. Considering the use of the most accurate equilibrium equation involving the ΔC_p term, no benefits were found for drug predictions as the models are still too inaccurate. However, in function of the molecules and their solid thermodynamic properties, the ΔC_p term can be neglected and will not have a great impact on the results.