Macromolecules In Solvent Research Articles

Formulation and Development of herbal Gel containing Cannabis sativa and Azadirachta indica leaves extract for Anti-inflammatory and Anti-bacterial activity

Bacteria are everywhere and play a crucial part in the maintenance of germs that cause illness and disease. Skin infections are anticipated to occur at a rate of 24.6 per 1000 people yearly. The treatment of any skin infections primarily consists of any necessary surgical debridement; nevertheless, injecting an antibiotic directly into a wound has several potential benefits. Topical antibiotic treatment and wound care are recommended. The administration of a therapy may allow treatment with medicines that are not yet available (or safe) for systemic therapy. Gels are semi-solid systems having qualities intermediate between solids and liquids, in which the movement of the dispersing medium is constrained by an interlacing three-dimensional network of particles or solvated macromolecules of the dispersed phase. This study aimed to explore the potential of Cannabis sativa, Azadirachta indica leaves extract as anti-inflammatory and antibacterial agents. The formulation has been developed by solvent casting method. The experiment was conducted using various techniques to measure the effectiveness of each substance individually and in combination. Results showed that Cannabis sativa and Azadirachta indica leaves extract both had strong anti-inflammatory properties, while glycerol demonstrated significant antibacterial activity. When combined, these substances exhibited enhanced anti-inflammatory and antibacterial effects, indicating potential for their use in pharmaceutical and medical applications. Overall, this study highlights the importance of exploring natural products for their therapeutic potential and provides insight into the potential of these substances as novel anti-inflammatory and antibacterial agents.

Docking Ligands into Flexible and Solvated Macromolecules. 8. Forming New Bonds─Challenges and Opportunities.

Over the years, structure-based design programs and specifically docking small molecules to proteins have become prominent in drug discovery. However, many of these computational tools have been developed to primarily dock enzyme inhibitors (and ligands to other protein classes) relying heavily on hydrogen bonds and electrostatic and hydrophobic interactions. In reality, many drug targets either feature metal ions, can be targeted covalently, or are simply not even proteins (e.g., nucleic acids). Herein, we describe several new features that we have implemented into Fitted to broaden its applicability to a wide range of covalent enzyme inhibitors and to metalloenzymes, where metal coordination is essential for drug binding. This updated version of our docking program was tested for its ability to predict the correct binding mode of drug-sized molecules in a large variety of proteins. We also report new datasets that were essential to demonstrate areas of success and those where additional efforts are required. This resource could be used by other program developers to assess their own software.

Approaches to Understanding the Solution-State Organization of Spray-Dried Dispersion Feed Solutions and Its Translation to the Solid State

It is well established that polymers adopt a range of conformations and solution-state organization in response to varying solution environments, although very little work has been done to understand how these effects might impact the physical stability and bioavailability of spray-dried amorphous dispersions (SDDs). Potentially relevant solution-state polymer-solvent/cosolute interactions include preferential solvation, hydrodynamic size (i.e., polymer swelling or collapse), and solvent quality effects (i.e., attractive or repulsive self-interactions). Of particular interest is the investigation of preferential solvation, defined as the relative attraction or rejection of a cosolvent and/or cosolute from the local environment of a solvated macromolecule, which often occurs in multicomponent macromolecular solutions. As spray drying and other solvent-based dispersion processing necessitates the use of complex media consisting of at least three or more components (drug, polymer, solvent(s), and other possible excipients), the prevalence of this phenomenon is likely. This work characterizes largely unexplored solution-state properties in model spray-dried dispersion feed solutions using light scattering and viscometric techniques to add greater context and guidance in studying these information-rich materials. These systems are found to exhibit complex non-intuitive behavior, which serves to highlight the potential utility of preferential solvation in spray-dried dispersion processing and stability. It is hypothesized that solution-state organization of the liquid feed can be engineered and translated to the solid-state for the optimization of SDD properties.

An implicit boundary integral method for computing electric potential of macromolecules in solvent

A numerical method using implicit surface representations is proposed to solve the linearized Poisson–Boltzmann equation that arises in mathematical models for the electrostatics of molecules in solvent. The proposed method uses an implicit boundary integral formulation to derive a linear system defined on Cartesian nodes in a narrowband surrounding the closed surface that separates the molecule and the solvent. The needed implicit surface is constructed from the given atomic description of the molecules, by a sequence of standard level set algorithms. A fast multipole method is applied to accelerate the solution of the linear system. A few numerical studies involving some standard test cases are presented and compared to other existing results.

A framework of finite element procedures for the analysis of proteins

Large-scale, functional collective motions of proteins and their supra-molecular assemblies occur in a physiological solvent environment at finite temperatures. The solution of these motions with standard molecular dynamics algorithms is computationally hardly possible when considering macromolecules. Much research has focused on alternative approaches that use coarse-graining to model proteins, but mostly in vacuum. In this paper, we incorporate realistically the physical effects of solvent damping into the finite element model of proteins. The proposed framework is based on Brownian dynamics and shown to be effective. An important advantage of the approach is that the computational cost is not dependent on the molecular size, which makes the long-time simulation of macromolecules possible. Using the proposed procedure, we demonstrate the analysis of a macromolecule in solvent—an analysis that has not been achieved before and could not be performed with a molecular dynamics algorithm.

Morphological switching of unimolecular micelles of ternary graft copolymers in different solvents

ABSTRACTA series of ternary graft copolymers with poly(3‐azido‐2‐hydroxypropyl methacrylate) (P(GMA‐N3)) as the main chain, end‐functionalized poly(ethylene glycol) methyl ether (MPEG), poly(t‐butyl acrylate) (PtBA), and poly(2‐cinnamoyloxyethyl methacrylate) (PCEMA) as the side‐chains, was synthesized via the combination of atom transfer radical polymerization (ATRP) and click chemistry. The formation of well‐defined ternary graft copolymers was confirmed by both size exclusion chromatography (SEC) and 1H NMR spectroscopy The loose and worm‐like morphology of the ternary graft copolymer in a common solvent (N,N‐dimethylformamide) for both the backbone and the grafts was directly visualized via atomic force microscopy (AFM). The average height, width, and length of these solvated macromolecules were about 1.5, 17, and 45 nm, respectively. The ternary graft copolymers underwent self‐assembly in different selective solvents (dichloromethane, methanol, and water) and thus yielded unimolecular micelles (UMs) with different morphologies. The morphological transitions in response to variations in the selective solvents was investigated by AFM as well as/or transmission electron microscopy (TEM). Experimental results showed that the micellar morphology of the ternary graft copolymer changed from a pearl‐necklace to a worm‐like structure and then to a spherical structure when the selective solvent was respectively changed from CH2Cl2 to CH3OH and then to H2O. SEC characterization revealed that the compact globules formed in H2O with PCEMA/PtBA as the hydrophobic core arose due to intramolecular folding. Thus, multicompartment UMs were generated. The volume ratio of the multicompartment UMs formed in H2O was in close agreement with their molecular weight ratio. The hydrodynamic diameters (Dh) of the acquired multicompartment UMs and their polydispersity indices were characterized by dynamic light scattering. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017, 55, 1021–1030

Adaptive Resolution Simulations with Self-Adjusting High-Resolution Regions.

In adaptive resolution simulations, different regions of a simulation box are modeled with different levels of detail. Particles change their resolution on-the-fly when traveling from one subregion to the other. This method is particularly useful for studying multiscale systems in which effects on a broad range of length and time scales play a role. Until now, the geometry of the high-resolution region has been limited to simple geometries of spherical, cuboid, or cylindrical form, whose shape does not change during the simulation. However, many phenomena involve changes in size and shape of system components, for example, protein folding, polymer collapse, nucleation, and crystallization. In this work, we develop a scheme that uses a series of overlapping spheres to allow for an arbitrary division of space into domains of different levels of resolution. Furthermore, the geometry is automatically adjusted on-the-fly during the simulation according to changes in size and shape of, for example, a solvated macromolecule within the high-resolution region. The proposed approach is validated on liquid water. We then simulate the folding of an atomistically detailed polypeptide solvated in a shell of atomistic water that changes shape as the peptide conformation changes. We demonstrate that the peptide folding process is unperturbed by the use of our methodology.

In-situ temperature-controllable shear flow device for neutron scattering measurement--an example of aligned bicellar mixtures.

We have designed and constructed a temperature-controllable shear flow cell for in-situ study on flow alignable systems. The device has been tested in the neutron diffraction and has the potential to be applied in the small angle neutron scattering configuration to characterize the nanostructures of the materials under flow. The required sample amount is as small as 1 ml. The shear rate on the sample is controlled by the flow rate produced by an external pump and can potentially vary from 0.11 to 3.8 × 10(5) s(-1). Both unidirectional and oscillational flows are achievable by the setting of the pump. The instrument is validated by using a lipid bicellar mixture, which yields non-alignable nanodisc-like bicelles at low T and shear-alignable membranes at high T. Using the shear cell, the bicellar membranes can be aligned at 31 °C under the flow with a shear rate of 11.11 s(-1). Multiple high-order Bragg peaks are observed and the full width at half maximum of the "rocking curve" around the Bragg's condition is found to be 3.5°-4.1°. It is noteworthy that a portion of the membranes remains aligned even after the flow stops. Detailed and comprehensive intensity correction for the rocking curve has been derived based on the finite rectangular sample geometry and the absorption of the neutrons as a function of sample angle [See supplementary material at http://dx.doi.org/10.1063/1.4908165 for the detailed derivation of the absorption correction]. The device offers a new capability to study the conformational or orientational anisotropy of the solvated macromolecules or aggregates induced by the hydrodynamic interaction in a flow field.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

Temperature-triggered fast-disintegrating polyNIPAM particles via semicontinuous heterophase polymerisation

Crosslinker-free poly(n-isopropylacrylamide) (polyNIPAM) particles produced by conventional emulsifier-free heterophase polymerisations contain gels and do not easily and completely disintegrate in water, if at all. These particles, when cooled below lower critical solution temperature (LCST) swell first and then gradually shrink, due to their slow rate of disintegration. We first show that only particles formed using very low monomer concentration, which have a low molecular weight, are fully soluble in water. Then, we describe a seeded semicontinuous route which was designed in order to be able to maintain a low monomer concentration in water in the course of reaction and control the length and location of growing chains. Nanoparticles produced via semicontinuous approach not only disintegrated in water very quickly but also dissolved in water completely as soon as LCST was reached. This finding may also find applications in technologically important processes for dissolution of macromolecules in solvents.

Docking Ligands into Flexible and Solvated Macromolecules. 6. Development and Application to the Docking of HDACs and other Zinc Metalloenzymes Inhibitors

Metalloenzymes are ubiquitous proteins which feature one or more metal ions either directly involved in the enzymatic activity and/or structural properties (i.e., zinc fingers). Several members of this class take advantage of the Lewis acidic properties of zinc ions to carry out their various catalytic transformations including isomerization or amide cleavage. These enzymes have been validated as drug targets for a number of diseases including cancer; however, despite their pharmaceutical relevance and the availability of crystal structures, structure-based drug design methods have been poorly and indirectly parametrized for these classes of enzymes. More specifically, the metal coordination component and proton transfers of the process of drugs binding to metalloenzymes have been inadequately modeled by current docking programs, if at all. In addition, several known issues, such as coordination geometry, atomic charge variability, and a potential proton transfer from small molecules to a neighboring basic residue, have often been ignored. We report herein the development of specific functions and parameters to account for zinc-drug coordination focusing on the above-listed phenomena and their impact on docking to zinc metalloenzymes. These atom-type-dependent but atomic charge-independent functions implemented into Fitted 3.1 enable the simulation of drug binding to metalloenzymes, considering an acid-base reaction with a neighboring residue when necessary with good accuracy.

Solvent Boundary Potentials for Hybrid QM/MM Computations Using Classical Drude Oscillators: A Fully Polarizable Model.

Accurate quantum mechanical/molecular mechanical (QM/MM) treatments should account for MM polarization and properly include long-range electrostatic interactions. We report on a development that covers both these aspects. Our approach combines the classical Drude oscillator (DO) model for the electronic polarizability of the MM atoms with the generalized solvent boundary Potential (GSBP) and the solvated macromolecule boundary potential (SMBP). These boundary potentials (BP) are designed to capture the long-range effects of the outer region of a large system on its interior. They employ a finite difference approximation to the Poisson-Boltzmann equation for computing electrostatic interactions and take into account outer-region bulk solvent through a polarizable dielectric continuum (PDC). This approach thus leads to fully polarizable three-layer QM/MM-DO/BP methods. As the mutual responses of each of the subsystems have to be taken into account, we propose efficient schemes to converge the polarization of each layer simultaneously. For molecular dynamics (MD) simulations using GSBP, this is achieved by considering the MM polarizable model as a dynamical degree of freedom, and hence contributions from the boundary potential can be evaluated for a frozen state of polarization at every time step. For geometry optimizations using SMBP, we propose a dual self-consistent field approach for relaxing the Drude oscillators to their ideal positions and converging the QM wave function with the proper boundary potential. The chosen coupling schemes are evaluated with a test system consisting of a glycine molecule in a water ball. Both boundary potentials are capable of properly reproducing the gradients at the inner-region atoms and the Drude oscillators. We show that the effect of the Drude oscillators must be included in all terms of the boundary potentials to obtain accurate results and that the use of a high dielectric constant for the PDC does not lead to a polarization catastrophe of the DO models. Optimum values for some key parameters are discussed. We also address the efficiency of these approaches compared to standard QM/MM-DO calculations without BP. In the SMBP case, computation times can be reduced by around 40% for each step of a geometry optimization, with some variation depending on the chosen QM method. In the GSBP case, the computational advantages of using the boundary potential increase with system size and with the number of MD steps.

Single-cell adhesion probed in-situ using optical tweezers: A case study with Saccharomyces cerevisiae

A facile method of using optical trapping to measure cell adhesion forces is presented and applied to the adhesion of Saccharomyces cerevisiae on glass, in contact with solutions of different compositions. Trapping yeast cells with optical tweezers (OT) is not perturbed by cell wall deformation or cell deviation from a spherical shape. The trapping force calibration requires correction not only for the hydrodynamic effect of the neighboring wall but also for spherical aberrations affecting the focal volume and the trap stiffness. Yeast cells trapped for up to 5 h were still able to undergo budding but showed an increase of doubling time. The proportion of adhering cells showed the expected variation according to the solution composition. The detachment force varied in the same way. This observation and the fact that the detachment stress was exerted parallel to the substrate surface point to the role of interactions involving solvated macromolecules. Both the proportion of adhering cells and the removal force showed a distribution which, in our experimental conditions, must be attributed to a heterogeneity of surface properties at the cell level or at the subcellular scale. As compared with magnetic tweezers, atomic force microscopy, and more conventional ways of studying cell adhesion (shear-flow cells), OT present several advantages that are emphasized in this paper.

Long-Range Electrostatic Effects in QM/MM Studies of Enzymatic Reactions: Application of the Solvated Macromolecule Boundary Potential.

Long-range electrostatic interactions are important in simulations of enzymatic reactions. They can be divided into the effects due to bulk solvent and those due to the electrostatic potential of the outer macromolecule. We study and quantify the importance of these two effects for two test systems by application of the solvated macromolecule boundary potential (SMBP) [J. Chem. Theory Comput. 2009, 5, 3114-3128]. We validate the accuracy of the SMBP for these test systems and present a transferable protocol for determination of optimal SMBP parameters as well as recommended default values for these parameters. Two enzymatic reactions with different characteristics are studied: the intramolecular Claisen rearrangement in chorismate mutase that is associated with little charge transfer and the hydroxylation reaction in p-hydroxybenzoate hydroxylase that corresponds to a formal "OH(+)" transfer and thus involves significant charge transfer. It is found that the effects of the electrostatic potential of the outer macromolecule and of bulk solvent are only important in the latter case, where their neglect causes deviations in the computed barriers on the order of 1-2 kcal/mol, respectively. Even larger deviations on the order of several kilocalories per mole are observed for the reaction energies in p-hydroxybenzoate hydroxylase if the electrostatic potential of the outer macromolecule is neglected.

Solution behavior of methyl cellulose mixtures with poly(N-vinylformamide) in water and dimethyl sulfoxide

The rheological properties of diluted and moderately concentrated solutions of methyl cellulose mixtures with poly(N-vinylformamide) in water and dimethyl sulfoxide are investigated. Negative deviations of the viscosities of these solutions from the additive values are observed and explained by different mechanisms of solvation of macromolecules with water and dimethyl sulfoxide. Incompatibility of the polymers in a common solvent is discovered. This circumstance leads to the formation of a new system of hydrogen bonds and rearrangement of the structural organization of solutions.

The electronic-structure theory of a large-molecular system in solution: Application to the intercalation of proflavine with solvated DNA

A new approach for investigating solvent effects on the electronic structure of solvated macromolecules is proposed. The method is constructed by combining the quantum and molecular mechanics (QM/MM) methods with the reference interaction site model (RISM) theory. The system treated with the method is divided into three regions, quantum and molecular mechanical regions of solute, and the solvent region. The two solute regions are treated by the ordinary QM/MM method, while the solvent region is handled with the RISM theory. The method is applied to investigate the intercalation of proflavine to two types of decameric B-DNA, namely [deca(dG-dC)] 2 and [deca(dA-dT)] 2. Our results indicate that the affinity of intercalation of proflavine to the dG-dC base sequence is higher than that of the dA-dT DNA base sequence, which is consistent with the experimental results. The drastic change of solvation structure due to the intercalation makes large positive change in the solvation free energy which is attributed to the dehydration penalty of PR, the screening of electrostatic interaction between PR and DNA, and the hydrophobic interaction of elongated DNA chain.

Docking Ligands into Flexible and Solvated Macromolecules. 5. Force-Field-Based Prediction of Binding Affinities of Ligands to Proteins

We report herein our efforts in the development of three empirical scoring functions with application in protein-ligand docking. A first scoring function was developed from 209 crystal structures of protein-ligand complexes and a second one from 946 cross-docked complexes. Tuning of the coefficients for the different terms making up these functions was performed by an iterative approach to optimize the correlations between observed activities and calculated scores. A third scoring function was developed from libraries of known actives and decoys docked to six different protein conformational ensembles. In the latter case, the tuning of the coefficients was performed so as to optimize the area under the curve of a receiver operating characteristic (ROC) for the discrimination of actives and inactives. The newly developed scoring functions were next assessed on independent sets of protein-ligand complexes for their ability to predict binding affinities and to discriminate actives from inactives. In the first validation the first function, which was trained on active compounds only, performed as well as other commonly used ones. On a high-throughput virtual screening validation on five protein conformational ensembles, the third scoring function that included data from inactive compounds performed significantly better. This validation showed that the inclusion of data from inactive compounds is critical for performance in virtual high-throughput screening applications.

A General Boundary Potential for Hybrid QM/MM Simulations of Solvated Biomolecular Systems

We present a general boundary potential for the efficient and accurate evaluation of electrostatic interactions in hybrid quantum mechanical/molecular mechanical (QM/MM) approaches called solvated macromolecule boundary potential (SMBP), which is designed for QM/MM calculations with any kind of QM method. The SMBP targets QM/MM single-point energy calculations and geometry optimizations. In the SMBP scheme, the outer solvent and macromolecule region is described by a boundary potential obtained with the use of Poisson-Boltzmann calculations (treating the bulk solvent as a dielectric continuum). In the QM calculations, the SMBP is represented by virtual point charges on a surface enclosing the explicitly treated inner region. These charges and their interactions with the QM density are determined through a self-consistent reaction field procedure. The accuracy of the SMBP is evaluated on three diverse test systems: the intramolecular proton transfer of glycine in water, the hydroxylation reaction in p-hydroxybenzoate hydroxylase, and the spin state energy splittings in the pentacoordinated ferric complex of cytochrome P450cam. In the case of solvated glycine, application of the SMBP turns out to be problematic since analogous QM/MM/SMBP and full QM/MM geometry optimizations lead to different close-lying local minima. In both enzymes, the SMBP performs very well and closely reproduces the results from full QM/MM optimizations of these more rigid test systems. Starting from optimized QM/MM/SMBP structures along a reaction path, one can apply the previously implemented generalized solvent boundary potential (GSBP) to sample over MM phase space in QM/MM free energy calculations within the framework of free energy perturbation theory. This reduces the overall computational costs of sampling by 1 order of magnitude while maintaining good accuracy. The combined use of SMBP and GSBP thus allows for efficient QM/MM free energy studies of enzymes.

Docking Ligands into Flexible and Solvated Macromolecules. 4. Are Popular Scoring Functions Accurate for this Class of Proteins?

In our previous report, we investigated the impact of protein flexibility and the presence of water molecules on the pose-prediction accuracy of major docking programs. To complete these investigations, we report herein a study of the impact of these two aspects on the accuracy of scoring functions. To this effect, we developed two sets of protein/ligand complexes made up of ligands cross-docked or cocrystallized with a large variety of proteins, featuring bridging water molecules and demonstrating protein flexibility. Efforts were made to reduce the correlation between the molecular weights of the selected ligands and their binding affinities, a major bias in some previously reported benchmark sets. Using these sets, 18 available scoring functions have been assessed for their accuracy to predict binding affinities and to rank-order compounds by their affinity to cocrystallized proteins. This study confirmed the good and similar accuracy of Xscore, GlideScore, DrugScore(CSD), GoldScore, PLP1, ChemScore, RankScore, and the eHiTS scoring function. Our next investigations demonstrated that most of the assessed scoring functions were much less accurate when the correct protein conformation was not provided. This study also revealed that considering the water molecules for scoring does not greatly affect the accuracy. Finally, this work sheds light on the high correlation between scoring functions and the poor increase in accuracy one can expect from consensus scoring.

Docking Ligands into Flexible and Solvated Macromolecules. 3. Impact of Input Ligand Conformation, Protein Flexibility, and Water Molecules on the Accuracy of Docking Programs

Several modifications and additions to Fitted1.5 led to the development of Fitted2.6. Among the novel implementations are a matching algorithm-enhanced genetic algorithm and a ring conformational search algorithm. With these various optimizations, we also hoped to remove the biases and to develop a docking program that would provide results (i.e., poses) as independent as possible to the input ligand and protein conformations and used parameters, although keeping the options to provide additional experimental information. These biases were investigated within Fitted2.6 along with FlexX, GOLD, Glide, and Surflex. The input ligand conformation was found to have a major impact on the program accuracy as drops as large as 10-50% were observed with all the programs but Fitted. This comparative study also demonstrates that the accuracy of Fitted is similar to that of other widely used programs. We have also demonstrated that protein flexibility, displaceable water molecules, and ring conformational search algorithms, three of the main Fitted features, significantly increased its accuracy. Finally, we also proposed potential modifications to the available programs to further improve their accuracy in binding mode prediction.