Multivariate Analysis of Solubility Parameters for Drug-Polymer Miscibility Assessment in Preparing Raloxifene Hydrochloride Amorphous Solid Dispersions.

The success of obtaining solid dispersions for solubility improvement invariably depends on the miscibility of the drug and polymeric carriers. This study aimed to categorize and select polymeric carriers via the classical group contribution method using the multivariate analysis of the calculated solubility parameter of RX-HCl. The total, partial, and derivate parameters for RX-HCl were calculated. The data were compared with the results of excipients (N = 36), and a hierarchical clustering analysis was further performed. Solid dispersions of selected polymers in different drug loads were produced using solvent casting and characterized via X-ray diffraction, infrared spectroscopy and scanning electron microscopy. RX-HCl presented a Hansen solubility parameter (HSP) of 23.52 MPa1/2. The exploratory analysis of HSP and relative energy difference (RED) elicited a classification for miscible (n = 11), partially miscible (n = 15), and immiscible (n = 10) combinations. The experimental validation followed by a principal component regression exhibited a significant correlation between the crystallinity reduction and calculated parameters, whereas the spectroscopic evaluation highlighted the hydrogen-bonding contribution towards amorphization. The systematic approach presented a high discrimination ability, contributing to optimal excipient selection for the obtention of solid solutions of RX-HCl.

Assessment on malvidin-3-glucoside interaction with TLR4 via multi-spectroscopic analysis and molecular docking.

As one innate immune pattern recognition receptor, Toll-like receptor 4 (TLR4) recently has been considered as a critical player in glucolipid metabolism. Blueberries contain high level of anthocyanins, especially malvidin-3-glucoside (Mv-3-glc), which contribute the anti-inflammatory, hypoglycemic, and hypolipidemic effects. It is speculated that Mv-3-glc is able to possess these functions by binding to TLR4. Here, the noncovalent interactions of Mv-3-glc and TLR4 was explored through multi-techniques including fluorescence and ultraviolet-visible (UV-Vis) absorption spectroscopy, as well as molecular docking. The results demonstrated that Mv-3-glc was able to quench TLR4 intrinsic fluorescence effectively. A stable complex was formed spontaneously and the reaction was exothermic. The degree of binding of Mv-3-glc to TLR4 showed a strong dependence on the chemical concentration, temperature, and pH values. The negative signs for enthalpy (ΔH = -69.1 ± 10.8 kJ/mol) and entropy (ΔS = -105.0 ± 12.3 J/mol/K) from the interaction of the Mv-3-glc and TLR4 shows that the major driving forces are the hydrogen bonding and van der Waals' force, which is consistent with the molecular docking results. In addition, molecular docking predicted that the active center with specific amino acid residues, Phe126, Ser127, Leu54, Ile153, and Tyr131 was responsible for the site of Mv-3-glc binding to TLR4/myeloid differentiation protein-2 (MD-2). These findings confirmed that Mv-3-glc could bind to TLR4, which would be beneficial to understand the target therapeutic effects of blueberry anthocyanins on TLR4 in regulating glucolipid metabolism.

An Assessment of Dispersion-Corrected DFT Methods for Modeling Nonbonded Interactions in Protein Kinase Inhibitor Complexes.

Accurate modeling of nonbonded interactions between protein kinases and their small molecule inhibitors is essential for structure-based drug design. Quantum chemical methods such as density functional theory (DFT) hold significant promise for quantifying the strengths of these key protein-ligand interactions. However, the accuracy of DFT methods can vary substantially depending on the choice of exchange-correlation functionals and associated basis sets. In this study, a comprehensive benchmarking of nine widely used DFT methods was carried out to identify an optimal approach for quantitative modeling of nonbonded interactions, balancing both accuracy and computational efficiency. From a database of 2139 kinase-inhibitor crystal structures, a diverse library of 49 nonbonded interaction motifs was extracted, encompassing CH-π, π-π stacking, cation-π, hydrogen bonding, and salt bridge interactions. The strengths of nonbonded interaction energies for all 49 motifs were calculated at the advanced CCSD(T)/CBS level of theory, which serve as references for a systematic benchmarking of BLYP, TPSS, B97, ωB97X, B3LYP, M062X, PW6B95, B2PLYP, and PWPB95 functionals with D3BJ dispersion correction alongside def2-SVP, def2-TZVP, and def2-QZVP basis sets. The RI, RIJK, and RIJCOSX approximations were used for selected functionals. It was found that the B3LYP/def2-TZVP and RIJK RI-B2PLYP/def2-QZVP methods delivered the best combination of accuracy and computational efficiency, making them well-suited for efficient modeling of nonbonded interactions responsible for molecular recognition of protein kinase inhibitors in their targets.

Assessment of Halogen Off-Center Point-Charge Models Using Explicit Solvent Simulations.

Compounds containing halogens can form halogen bonds (XBs) with biological targets such as proteins and membranes due to their anisotropic electrostatic potential. To accurately describe this anisotropy, off-center point-charge (EP) models are commonly used in force field methods, allowing the description of XBs at the molecular mechanics and molecular dynamics level. Various EP implementations have been documented in the literature, and despite being efficient in reproducing protein-ligand geometries and sampling of XBs, it is unclear how well these EP models predict experimental properties such as hydration free energies (ΔGhyd), which are often used to validate force field performance. In this work, we report the first assessment of three EP models using alchemical free energy calculations to predict ΔGhyd values. We show that describing the halogen anisotropy using some EP models can lead to a slight improvement in the prediction of the ΔGhyd when compared with the models without EP, especially for the chlorinated compounds; however, this improvement is not related to the establishment of XBs but is most likely due to the improvement of the sampling of hydrogen bonds. We also highlight the importance of the choice of the EP model, especially for the iodinated molecules, since a slight tendency to improve the prediction is observed for compounds with a larger σ-hole but significantly worse results were obtained for compounds that are weaker XB donors.

Overall protein structure quality assessment using hydrogen-bonding parameters.

Atomic model refinement at low resolution is often a challenging task. This is mostly because the experimental data are not sufficiently detailed to be described by atomic models. To make refinement practical and ensure that a refined atomic model is geometrically meaningful, additional information needs to be used such as restraints on Ramachandran plot distributions or residue side-chain rotameric states. However, using Ramachandran plots or rotameric states as refinement targets diminishes the validating power of these tools. Therefore, finding additional model-validation criteria that are not used or are difficult to use as refinement goals is desirable. Hydrogen bonds are one of the important noncovalent interactions that shape and maintain protein structure. These interactions can be characterized by a specific geometry of hydrogen donor and acceptor atoms. Systematic analysis of these geometries performed for quality-filtered high-resolution models of proteins from the Protein Data Bank shows that they have a distinct and a conserved distribution. Here, it is demonstrated how this information can be used for atomic model validation.

Characterization of a novel recombinant calcium-binding protein from Arca subcrenata and its anti-hepatoma activities in vitro and in vivo.

Previous studies demonstrated that ASP-3 was a novel calcium-binding protein from Arca subcrenata that effectively inhibited the proliferation of HepG2 cells. To further study the antitumor activity and mechanism of ASP-3, the cytotoxic effects of recombinant ASP-3 were evaluated in HepG2 cells. The results demonstrated that ASP-3 inhibited the proliferation of HepG2 cells by competitively binding to the EGF binding pocket of EGFR and inhibiting the JAK-STAT, RAS-RAF-MEK-ERK, and PI3K-Akt-mTOR signaling pathways mediated by EGFR. ASP-3 significantly inhibited tumor growth in a HepG2 cell subcutaneous xenograft nude mouse model, and its (25 mg/kg and 75 mg/kg) tumor inhibition rates were 46.92 % and 60.28 %, respectively. Furthermore, the crystal structure of ASP-3 was resolved at 1.4 Å. ASP-3 formed as a stable dimer and folded as an EF-Hand structure. ASP-3 stably bound to domain I and domain III of the EGFR extracellular region by using molecular docking and molecular dynamics simulation analysis. Compared with the endogenous ligand EGF, ASP-3 displayed a stronger interaction with EGFR. These experimental results indicated that recombinant ASP-3 possessed an effective anti-hepatoma effect. So, it might be a potential molecule for liver cancer therapy.

A quantitative assessment of deformation energy in intermolecular interactions: How important is it?

Dimer interaction energies have been well studied in computational chemistry, but they can offer an incomplete understanding of molecular binding depending on the system. In the current study, we present a dataset of focal-point coupled-cluster interaction and deformation energies (summing to binding energies, De) of 28 organic molecular dimers. We use these highly accurate energies to evaluate ten density functional approximations for their accuracy. The best performing method (with a double-ζ basis set), B97M-D3BJ, is then used to calculate the binding energies of 104 organic dimers, and we analyze the influence of the nature and strength of interaction on deformation energies. Deformation energies can be as large as 50% of the dimer interaction energy, especially when hydrogen bonding is present. In most cases, two or more hydrogen bonds present in a dimer correspond to an interaction energy of -10 to -25 kcal mol-1, allowing a deformation energy above 1 kcal mol-1 (and up to 9.5 kcal mol-1). A lack of hydrogen bonding usually restricts the deformation energy to below 1 kcal mol-1 due to the weaker interaction energy.

Quantum Mechanical Assessment of Protein-Ligand Hydrogen Bond Strength Patterns: Insights from Semiempirical Tight-Binding and Local Vibrational Mode Theory.

Hydrogen bonds (HB)s are the most abundant motifs in biological systems. They play a key role in determining protein-ligand binding affinity and selectivity. We designed two pharmaceutically beneficial HB databases, database A including ca. 12,000 protein-ligand complexes with ca. 22,000 HBs and their geometries, and database B including ca. 400 protein-ligand complexes with ca. 2200 HBs, their geometries, and bond strengths determined via our local vibrational mode analysis. We identified seven major HB patterns, which can be utilized as a de novo QSAR model to predict the binding affinity for a specific protein-ligand complex. Glycine was reported as the most abundant amino acid residue in both donor and acceptor profiles, and N-H⋯O was the most frequent HB type found in database A. HBs were preferred to be in the linear range, and linear HBs were identified as the strongest. HBs with HB angles in the range of 100-110°, typically forming intramolecular five-membered ring structures, showed good hydrophobic properties and membrane permeability. Utilizing database B, we found a generalized Badger's relationship for more than 2200 protein-ligand HBs. In addition, the strength and occurrence maps between each amino acid residue and ligand functional groups open an attractive possibility for a novel drug-design approach and for determining drug selectivity and affinity, and they can also serve as an important tool for the hit-to-lead process.

Hydrogen Bonding Parameters by Rapid Colorimetric Assessment: Evaluation of Structural Components Found in Biological Ligands and Organocatalysts.

Hydrogen bonding is a key molecular interaction in biological processes, drug delivery, and catalysis. This report describes a high throughput UV-Vis spectroscopic method to measure hydrogen bonding capacity using a pyrazinone sensor. This colormetric sensor reversibly binds to a hydrogen bond donor, resulting in a blue shift as additional equivalents of donor are added. Titration with excess equivalents of donor is used to determine the binding coefficient, ln(Keq ). Over 100 titrations were performed for a variety of biologically relevant compounds. This data enabled development a multiple linear regression model that is capable of predicting 95 % of ln(Keq ) values within 1 unit, allowing for the estimation of hydrogen bonding affinity from a single measurement. To show the effectiveness of the single point measurements, hydrogen bond strengths were obtained for a set of carboxylic acid bioisosteres. The values from the single point measurements were validated with full titrations.

Markov state models elucidate the stability of DNA influenced by the chiral 5S-Tg base.

The static and dynamic structures of DNA duplexes affected by 5S-Tg (Tg, Thymine glycol) epimers were studied using MD simulations and Markov State Models (MSMs) analysis. The results show that the 5S,6S-Tg base caused little perturbation to the helix, and the base-flipping barrier was determined to be 4.4 kcal mol-1 through the use of enhanced sampling meta-eABF calculations, comparable to 5.4 kcal mol-1 of the corresponding thymine flipping. Two conformations with the different hydrogen bond structures between 5S,6R-Tg and A19 were identified in several independent MD trajectories. The 5S,6R-Tg:O6HO6•••N1:A19 hydrogen bond is present in the high-energy conformation displaying a clear helical distortion, and near barrier-free Tg base flipping. The low-energy conformation always maintains Watson-Crick base pairing between 5S,6R-Tg and A19, and 5S-Tg base flipping is accompanied by a small barrier of ca. 2.0 KBT (T = 298 K). The same conformations are observed in the MSMs analysis. Moreover, the transition path and metastable structures of the damaged base flipping are for the first time verified through MSMs analysis. The data clearly show that the epimers have completely different influence on the stability of the DNA duplex, thus implying different enzymatic mechanisms for DNA repair.

Monte Carlo molecular simulation of solution and surface-bound DNA hybridization of short oligomers at varying surface densities.

DNA microarrays utilize surface bound sequences to probe for target sequences in samples of interest, and density of surface coverage plays an important role in any duplex formation and subsequent detection. Here, Monte Carlo molecular simulations utilize a modified coarse-grained DNA model to calculate the impact of binding density and arrangement as well as temperature on duplex structure and hydrogen bonding patterns for two different undecamer sequences. Results indicate a modest, sequence-dependent increase in dissociation related to the proximity of neighboring duplexes but little impact on duplex structure or hydrogen bonding pattern.

Deciphering the Effect of Lysine Acetylation on the Misfolding and Aggregation of Human Tau Fragment 171IPAKTPPAPK180 Using Molecular Dynamic Simulation and the Markov State Model.

The formation of neurofibrillary tangles (NFT) with ß-sheet-rich structure caused by abnormal aggregation of misfolded microtubule-associated protein Tau is a hallmark of tauopathies, including Alzheimer's Disease. It has been reported that acetylation, especially K174 located in the proline-rich region, can largely promote Tau aggregation. So far, the mechanism of the abnormal acetylation of Tau that affects its misfolding and aggregation is still unclear. Therefore, revealing the effect of acetylation on Tau aggregation could help elucidate the pathogenic mechanism of tauopathies. In this study, molecular dynamics simulation combined with multiple computational analytical methods were performed to reveal the effect of K174 acetylation on the spontaneous aggregation of Tau peptide 171IPAKTPPAPK180, and the dimerization mechanism as an early stage of the spontaneous aggregation was further specifically analyzed by Markov state model (MSM) analysis. The results showed that both the actual acetylation and the mutation mimicking the acetylated state at K174 induced the aggregation of the studied Tau fragment; however, the effect of actual acetylation on the aggregation was more pronounced. In addition, acetylated K174 plays a major contributing role in forming and stabilizing the antiparallel ß-sheet dimer by forming several hydrogen bonds and side chain van der Waals interactions with residues I171, P172, A173 and T175 of the corresponding chain. In brief, this study uncovered the underlying mechanism of Tau peptide aggregation in response to the lysine K174 acetylation, which can deepen our understanding on the pathogenesis of tauopathies.

Comprehensive Basis-Set Testing of Extended Symmetry-Adapted Perturbation Theory and Assessment of Mixed-Basis Combinations to Reduce Cost.

Hybrid or "extended" symmetry-adapted perturbation theory (XSAPT) replaces traditional SAPT's treatment of dispersion with better performing alternatives while at the same time extending two-body (dimer) SAPT to a many-body treatment of polarization using a self-consistent charge embedding procedure. The present work presents a systematic study of how XSAPT interaction energies and energy components converge with respect to the choice of Gaussian basis set. Errors can be reduced in a systematic way using correlation-consistent basis sets, with aug-cc-pVTZ results converged within <0.1 kcal/mol. Similar (if slightly less systematic) behavior is obtained using Karlsruhe basis sets at much lower cost, and we introduce new versions with limited augmentation that are even more efficient. Pople-style basis sets, which are more efficient still, often afford good results if a large number of polarization functions are included. The dispersion models used in XSAPT afford much faster basis-set convergence as compared to the perturbative description of dispersion in conventional SAPT, meaning that "compromise" basis sets (such as jun-cc-pVDZ) are no longer required and benchmark-quality results can be obtained using triple-ζ basis sets. The use of diffuse functions proves to be essential, especially for the description of hydrogen bonds. The "δ(Hartree-Fock)" correction for high-order induction can be performed in double-ζ basis sets without significant loss of accuracy, leading to a mixed-basis approach that offers 4× speedup over the existing (cubic scaling) XSAPT approach.

The protective effect of natural phenolic compound on the functional and structural responses of inhibited catalase by a common azo food dye.

In this research retrieval effects of natural yellow (NY) on the performance of carmoisine (CAR) inhibited bovine liver catalase (BLC) was studied using multispectral and theoretical methods. Kinetic studies showed that CAR inhibited BLC through competitive inhibition (IC50 value of 2.24 × 10-6 M) while the addition of NY recover the activity of CAR-BLC up to 82% in comparison with the control enzyme. Circular dichroism data revealed that NY can repair the structural changes of BLC, affected by CAR. Furthermore, an equilibrium dialysis study indicated that NY could reduce the stability of the CAR-catalase complex. The surface plasmon resonance (SPR) data analysis indicated a high affinity of NY to BLC compared to CAR and the binding of NY led to a decrease in the affinity of the enzyme to the inhibitor. On the other hand, fluorescence and molecular docking studies showed that the quenching mechanism of BLC by CAR occurs through a static quenching process, and van der Waals forces and hydrogen bonding play a crucial role in the binding of CAR to BLC. MLSD data demonstrated that NY could increase the binding energy of CAR-BLC complex from -7.72 kJ mol-1 to -5.9 kJ mol-1, leading to complex instability and catalase activity salvage.

Preparation and physicochemical assessment of bioactive films based on chitosan and starchy powder of white turmeric rhizomes (Curcuma Zedoaria) for green packaging applications.

In the current study, the bioactive films of chitosan/white turmeric (CH/WT) were prepared by employing solvent casting technique and analyzed their physicochemical and biological properties for active packaging applications. The successful inclusion of white turmeric into the chitosan matrix is confirmed by Fourier Transform Infrared Spectroscopy. Due to the presence of hydrogen bonding interaction, the active films exhibited good tensile properties, smooth surface morphology, miscibility, water resistance and UV barrier properties. The incorporation of white turmeric reduced the water vapour transmission rate and oxygen permeability (p < 0.05) in contrast with pristine film. The prepared blend films revealed soil degradation rate more than 60% within 15 days. Furthermore, the blend films exhibited lesser water solubility, moisture content and swelling index after addition of white turmeric to chitosan (p < 0.05). The prepared films revealed extensive antimicrobial activity against gram positive and gram negative bacteria. The antioxidant activity and total phenolic content were improved upon the incorporation of white turmeric. Moreover, the oil absorption rate of the blend films was decreased by 46% in comparison with pristine film. Overall, white turmeric incorporated chitosan films were employed as a green packaging material to extend the shelf life of the foodstuff.

The synergistic mechanisms of apo-ferritin structural transitions and Au(iii) ion transportation: molecular dynamics simulations with the Markov state model.

Due to its unique structure, recent years have witnessed the use of apo-ferritin to accumulate various non-natural metal ions as a scaffold for nanomaterial synthesis. However, the transport mechanism of metal ions into the cavity of apo-ferritin is still unclear, limiting the rational design and controllable preparation of nanomaterials. Here, we conducted all-atom classical molecular dynamics (MD) simulations combined with Markov state models (MSMs) to explore the transportation behavior of Au(iii) ions. We exhibited the complete transportation paths of Au(iii) from solution into the apo-ferritin cage at the atomic level. We also revealed that the transportation of Au(iii) ions is accompanied by coupled protein structural changes. It is shown that the 3-fold axis channel serves as the only entrance with the longest residence time of Au(iii) ions. Besides, there are eight binding clusters and five 3-fold structural metastable states, which are important during Au(iii) transportation. The conformational changes of His118, Asp127, and Glu130, acting as doors, were observed to highly correlate with the Au(iii) ion's position. The MSM analysis and Potential Mean Force (PMF) calculation suggest a remarkable energy barrier near Glu130, making it the rate-limiting step of the whole process. The dominant transportation pathway is from cluster 3 in the 3-fold channel to the inner cavity to cluster 5 on the inner surface, and then to cluster 6. These findings provide inspiration and theoretical guidance for the further rational design and preparation of new nanomaterials using apo-ferritin.

Interactions between large molecules pose a puzzle for reference quantum mechanical methods.

Quantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol-1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.

Date pits based nanomaterials for thermal insulation applications-Towards energy efficient buildings in Qatar.

Air-conditioning systems make the most significant part of energy consumption in the residential sector. There is no denying that it is essential to produce a comfortable indoor thermal environment for residents in a building. The actual goal is to achieve thermal comfort level without putting too much cost on the ecological system by trying to conserve the amount of energy consumed. An effective way to help achieve such a goal is by incorporating thermal insulation in buildings. Thermal insulations help reduce thermal energy gained during the implementation of a desired thermal comfort level. This study aims to use an environmentally friendly nanoparticle of date pits to create thermal insulations that can be used in buildings. Different ratios of the nanoparticle of the date pits and sand composite were investigated. Fourier transform infrared spectroscopy and scanning electron microscopy were used to characterize the new materials. The material with nanoparticles of date pits and 50% by-volume epoxy provided good thermal insulation with thermal conductivity of 0.26 W/mK that could be used in the existing buildings. This has the potential to reduce the overall energy consumption by 4,494 kWh and thereby reduce CO2 emissions of a 570 m2 house by 1.8 tons annually. In conclusion, the future of using nanoparticles of date pits in construction is bright and promising due to their promising results.

Implications of an Improved Model of the TSH Receptor Transmembrane Domain (TSHR-TMD-TRIO).

The thyroid-stimulating hormone receptor (TSHR) is a G-protein-coupled receptor group A family member with 7 transmembrane helices. We generated 3 new models of its entire transmembrane region using a 600 ns molecular simulation. The simulation started from our previously published model, which we have now revised by also modeling the intracellular loops and the C-terminal tail, adding internal waters and embedding it into a lipid bilayer with a water layer and with ions added to complete the system. We have named this model TSHR-TMD-TRIO since 3 representative dominant structures were then extracted from the simulation trajectory and compared with the original model. These structures each showed small but significant changes in the relative positions of the helices. The 3 models were also used as targets to dock a set of small molecules that are known active compounds including a new TSHR antagonist (BT362), which confirmed the appropriateness of the model with some small molecules showing significant preference for one or other of the structures.

Assessment of O-H⋯O and O-H⋯S intramolecular hydrogen bond energies in some substituted pyrimidines using quantum chemistry methods.

Resonance-assisted hydrogen bond (RAHB) theory was studied in some substituted pyrimidines in which encompass O-H⋯Y unit (Y= O and S). Alteration of substituents (R 1, R2, R3 = H, C2H, C2F) on pyrimidine ring changes properties of electron charge density at this ring and influences indirectly on strength of intramolecular hydrogen bond (IHB) interactions in the mentioned structures. Then, IHB energies were estimated using cis-trans method (CTM), related rotamers method (RRM), Espinosa' method (EM), and a viewpoint based on properties of electron charge densities at ring critical point (RCP) of RAHB ring. Moreover, the estimated IHB energies with these methods were compared with those obtained using modified Espinosa' method (MEM), Iogansen's relationship, and chemical shift-based method to find more consistent method with the proposed viewpoint based on RCP characteristics. The linear correlations between the all estimated IHB energies and some hydrogen bonding descriptors such as geometrical, spectroscopic, topological, and molecular orbital factors were examined. Results indicated that the IHB energies that obtained by way of MEM and Iogansen's relationship have better correlations with hydrogen bonding descriptors. Also, there are good consistencies between results of these two methods with viewpoint based on properties of RCPs. Therefore, IHB energies can suitably estimate using properties of RCPs in heterocyclic molecular systems especially in cases that rotation around C-C/CC bonds makes additional interactions in isomers and influences on accuracy of calculated IHB energies using approaches such as CTM and RRM.