Formation of Ligand Clusters on Multimodal Chromatographic Surfaces

Multimodal chromatography is a powerful tool which uses multiple modes of interaction, such as charge and hydrophobicity, to purify protein-based therapeutics. In this work, we performed molecular dynamics simulations of a series of multimodal cation-exchange ligands immobilized on a hydrophilic self-assembled monolayer surface at the commercially relevant surface density (1 ligand/nm²). We found that ligands that were flexible and terminated in a hydrophobic group had a propensity to aggregate on the surface, while less flexible ligands containing a hydrophobic group closer to the surface did not aggregate. For aggregating ligands, this resulted in the formation of a surface pattern that contained relatively large patches of hydrophobicity and charge whose sizes exceeded the length scale of the individual ligands. On the other hand, lowering the surface density to 1 ligand/3 nm² reduced or eliminated this aggregation behavior. In addition, the introduction of a flexible linker (corresponding to the commercially available ligand) enhanced cluster formation and allowed aggregation to occur at lower surface densities. Further, the use of flexible linkers enabled hydrophobic groups to collapse to the surface, reducing their accessibility. Finally, we developed an approach for quantifying differences in the observed surface patterns by calculating distributions of the patch size and patch length. This clustering phenomenon is likely to play a key role in governing protein-surface interactions in multimodal chromatography. This new understanding of multimodal surfaces has important implications for developing improved predictive models and designing new classes of multimodal separation materials.

Bulk and interfacial properties of decane in the presence of carbon dioxide, methane, and their mixture

Molecular dynamics simulations were performed to study the bulk and interfacial properties of methane + n-decane, carbon dioxide + n-decane, and methane + carbon dioxide + n-decane systems under geological conditions. In addition, theoretical calculations using the predictive Peng-Robinson equation of state and density gradient theory are carried out to compare with the simulation data. A key finding is the preferential dissolution in the decane-rich phase and adsorption at the interface for carbon dioxide from the methane/carbon dioxide mixture. In general, both the gas solubility and the swelling factor increase with increasing pressure and decreasing temperature. Interestingly, the methane solubility and the swelling of the methane + n-decane system are not strongly influenced by temperature. Our results also show that the presence of methane increases the interfacial tension (IFT) of the carbon dioxide + n-decane system. Typically, the IFT of the studied systems decreases with increasing pressure and temperature. The relatively higher surface excess of the carbon dioxide + n-decane system results in a steeper decrease in its IFT as a function of pressure. Such systematic investigations may help to understand the behavior of the carbon dioxide-oil system in the presence of impurities such as methane for the design and operation of carbon capture and storage and enhanced oil recovery processes.

Ranking near-native candidate protein structures via random forest classification

Background

In ab initio protein-structure predictions, a large set of structural decoys are often generated, with the requirement to select best five or three candidates from the decoys. The clustered central structures with the most number of neighbors are frequently regarded as the near-native protein structures with the lowest free energy; however, limitations in clustering methods and three-dimensional structural-distance assessments make identifying exact order of the best five or three near-native candidate structures difficult.

Results

To address this issue, we propose a method that re-ranks the candidate structures via random forest classification using intra- and inter-cluster features from the results of the clustering. Comparative analysis indicated that our method was better able to identify the order of the candidate structures as comparing with current methods SPICKR, Calibur, and Durandal. The results confirmed that the identification of the first model were closer to the native structure in 12 of 43 cases versus four for SPICKER, and the same as the native structure in up to 27 of 43 cases versus 14 for Calibur and up to eight of 43 cases versus two for Durandal.

Conclusions

In this study, we presented an improved method based on random forest classification to transform the problem of re-ranking the candidate structures by an binary classification. Our results indicate that this method is a powerful method for the problem and the effect of this method is better than other methods.

Inclusion Complexes of Naringenin in Dimethylated and Permethylated β-Cyclodextrins: Crystal Structures and Molecular Dynamics Studies

The crystal structures of the inclusion complexes of naringenin in dimethylated and permethylated β-cyclodextrin (DM-β-CD and TM-β-CD) were determined and extensively analyzed. Naringenin is found with its 4-hydroxyphenyl residue fully immersed in the DM-β-CD cavity and its chromone group protruding from the narrow rim of the open-cone shaped host. The naringenin/DM-β-CD complex units are packed in a ‘herring bone’ fashion. In the case of naringenin/TM-β-CD, the complex units are arranged in a cage-type mode, the guest naringenin is partially encapsulated in the cavity of the closed-cone shaped host, with its chromone group laying equatorially and its 4-hydroxyphenyl protruding extensively from the wide rim of the host. Furthermore, the crystallographically-determined coordinates of both complexes were employed for Molecular Dynaimics simulations in explicit water solvent and in the absence of crystal contacts. The trajectories showed that naringenin rapidly penetrates the open narrow rim of DM-β-CD but not the closed narrow rim of TM-β-CD. Thus, in the latter case, the chromone group of naringenin is accommodated shallowly in the wide rim of the host, tethered via hydrogen bonds to the secondary methoxy groups of the host. Finally, a significantly higher binding affinity for naringenin in DM-β-CD than TM-β-CD was estimated by Molecular Mechanics/Generalized Born Surface Area calculations.

Mechanistic study of the ATP hydrolysis reaction in dynein motor protein

Dynein, a large and complex motor protein, harnesses energy from adenosine triphosphate (ATP) hydrolysis to regulate essential cellular activities. The ATP hydrolysis mechanism for the dynein motor is still shrouded in mystery. Herein, molecular dynamics simulations of a dynein motor disclosed that two water molecules are present close to the γ-phosphate of ATP and Glu1742 at the AAA1 site of dynein. We have proposed three possible mechanisms for the ATP hydrolysis. We divulge by using a quantum mechanics/molecular mechanics (QM/MM) study that two water molecules and Glu1742 are crucial for facilitating the ATP hydrolysis reaction in dynein. Moreover, the ATP hydrolysis step is initiated by the activation of lytic water (W1) by Glu1742 through relay proton transfers with the help of auxiliary water (W2) yielding HPO₄^2- and ADP, as a product. In the next step, a proton is shifted back from Glu1742 to generate inorganic phosphate (H₂PO₄^-) via another relay proton transfer event. The overall activation barrier for the Glu1742 assisted ATP hydrolysis is found to be the most favourable pathway compared to other plausible pathways. We also unearthed that ATP hydrolysis in dynein follows a so-called associative-like pathway in its rate-limiting step. Our study ascertained the important indirect roles of the two amino acids (such as Arg2109, Asn1792) and Mg²⁺ ion in the ATP hydrolysis of dynein. Additionally, multiple sequence alignment of the different organisms of dynein motors has conveyed the evolutionary importance of the Glu1742, Asn1742, and Arg2109 residues, respectively. As similar mechanisms are also prevalent in other motors, and GTPase and ATPase enzymes, the present finding spells out the definitive requirement of a proton relay process through an extended water-chain as one of the key components in an enzymatic ATP hydrolysis reaction.

Highly Efficient Metal-Free Nitrogen-Doped Nanocarbons with Unexpected Active Sites for Aerobic Catalytic Reactions

Nitrogen (N)-doped nanocarbons (NDN) as metal-free catalysts have elicited considerable attention toward selective oxidation of alcohols with easily oxidizable groups to aldehydes in the past few years. However, finding a new NDN catalytic material that can meet the requirement of the feasibility on the aerobic catalytics for other complicated alcohols is a big challenge. The real active sites and the corresponding mechanisms on NDN are still unambiguous because of inevitable coexistence of diverse edge sites and N species based on recently reported doping methods. Here, four NDN catalysts with enriched pyridinic N species and without any graphitic N species are simply fabricated via a chemical-vapor-deposition-like method. The results of X-ray photoelectron spectroscopy and X-ray absorption near-edge structure spectra suggest that the dominating N species on NDN are pyridinic N. It is demonstrated that NDN catalysts perform impressive reactivity for aerobic oxidation of complicated alcohols at an atmospheric pressure. Eleven kinds of aromatic molecules with single N species and tunable π conjugation systems are used as model catalysts to experimentally identify the actual role of each N species at a real molecular level. It is suggested that pyridinic N species play an unexpected role in catalytic reactions. Neighboring carbon atoms in pyridinic N species are responsible for facilitating the rate-determining step process clarified by kinetic isotope effects, in situ nuclear magnetic resonance, in situ attenuated total reflectance infrared, and theoretical calculation. Moreover, NDN catalysts exhibit a good catalytic feasibility on the synthesis of important natural products (e.g., intermediates of vitamin E and K3) from phenol oxidation.

Interfacial Thermal Conductivity and Its Anisotropy

There is a significant effort in miniaturizing nanodevices, such as semi-conductors, currently underway. However, a major challenge that is a significant bottleneck is dissipating heat generated in these energy-intensive nanodevices. In addition to being a serious operational concern (high temperatures can interfere with their efficient operation), it is a serious safety concern, as has been documented in recent reports of explosions resulting from many such overheated devices. A significant barrier to heat dissipation is the interfacial films present in these nanodevices. These interfacial films generally are not an issue in macro-devices. The research presented in this paper was an attempt to understand these interfacial resistances at the molecular level, and present possibilities for enhancing the heat dissipation rates in interfaces. We demonstrated that the thermal resistances of these interfaces were strongly anisotropic; i.e., the resistance parallel to the interface was significantly smaller than the resistance perpendicular to the interface. While the latter is well-known—usually referred to as Kapitza resistance—the anisotropy and the parallel component have previously been investigated only for solid-solid interfaces. We used molecular dynamics simulations to investigate the density profiles at the interface as a function of temperature and temperature gradient, to reveal the underlying physics of the anisotropy of thermal conductivity at solid-liquid, liquid-liquid, and solid-solid interfaces.

Multilevel Quantum Mechanics and Molecular Mechanics Study of the Double-Inversion Mechanism at Nitrogen: F- + NH2Cl in Aqueous Solution

We employ a multilevel quantum mechanics and molecular mechanics method to investigate the double-inversion mechanism of the nucleophilic substitution reaction at the N center: the F^- + NH₂Cl reaction in aqueous solution. We find that the structures of the stationary points along the reaction path are quite different from the ones in the gas phase owing to the hydrogen-bond interactions between the solute and the surrounding water molecules. The atomic-level evolutions of the structures and charge transfer along the reaction path show that this double-inversion mechanism consists of an upside-down proton inversion process and a Walden-inversion process. The computed potential of mean force at the coupled-cluster singles and doubles with perturbative triples (CCSD(T))/molecular mechanics (MM) level of theory has the two-inversion barrier heights, and reaction free energy at 11.7, 29.6, and 12.6 kcal/mol, agreeing well with the predicted ones at 12.6, 32.5, and 12.2 kcal/mol obtained on the basis of the gas-phase reaction path and the solvation free energies of the stationary points.

Role of AAA3 Domain in Allosteric Communication of Dynein Motor Proteins

Cytoplasmic dynein, an AAA+ motif containing motor, generates force and movement along the microtubule to execute important biological functions including intracellular material transport and cell division by hydrolyzing ATP. Among the six AAA+ domains, AAA1 is the primary ATPase site where a single ATP hydrolysis generates a single step. Nucleotide states in AAA3 gate dynein's activity, suggesting that AAA3 acts as a regulatory switch. However, the comprehensive structural perspective of AAA3 in dynein's mechanochemical cycle remains unclear. Here, we explored the allosteric transition path of dynein involving AAA3 using a coarse-grained structure-based model. ATP binding to the AAA1 domain creates a cascade of conformational changes through the other domains of the ring, which leads to the pre-power stroke formation. The linker domain, which is the mechanical element of dynein, shifts from a straight to a bent conformation during this process. In our present study, we observe that AAA3 gates the allosteric communication from AAA1 to the microtubule binding domain (MTBD) through AAA4 and AAA5. The MTBD is linked to the AAA+ ring via a coiled-coil stalk and a buttress domain, which are extended from AAA4 and AAA5, respectively. Further analysis also uncovers the role of AAA3 in the linker movement. The free energy calculation shows that the linker prefers the straight conformation when AAA3 remains in the ATP-bound condition. As AAA3 restricts the motion of AAA4 and AAA5, the linker/AAA5 interactions get stabilized, and the linker cannot move to the pre-power stroke state that halts the complete structural transition required for the mechanochemical cycle. Therefore, we suggest that AAA3 governs dynein's mechanochemical cycle and motility by controlling the AAA4 and AAA5 domains that further regulate the linker movement and the power stroke formation.

Structural and Functional Analyses of Human ChaC2 in Glutathione Metabolism

Glutathione (GSH) degradation plays an essential role in GSH homeostasis, which regulates cell survival, especially in cancer cells. Among human GSH degradation enzymes, the ChaC2 enzyme acts on GSH to form 5-l-oxoproline and Cys-Gly specifically in the cytosol. Here, we report the crystal structures of ChaC2 in two different conformations and compare the structural features with other known γ-glutamylcyclotransferase enzymes. The unique flexible loop of ChaC2 seems to function as a gate to achieve specificity for GSH binding and regulate the constant GSH degradation rate. Structural and biochemical analyses of ChaC2 revealed that Glu74 and Glu83 play crucial roles in directing the conformation of the enzyme and in modulating the enzyme activity. Based on a docking study of GSH to ChaC2 and binding assays, we propose a substrate-binding mode and catalytic mechanism. We also found that overexpression of ChaC2, but not mutants that inhibit activity of ChaC2, significantly promoted breast cancer cell proliferation, suggesting that the GSH degradation by ChaC2 affects the growth of breast cancer cells. Our structural and functional analyses of ChaC2 will contribute to the development of inhibitors for the ChaC family, which could effectively regulate the progression of GSH degradation-related cancers.

Effect of Reaction Temperature on Shape Evolution of Palladium Nanoparticles and Their Cytotoxicity against A-549 Lung Cancer Cells

Palladium nanoparticles (Pd NPs) of different shapes and sizes have been synthesized by reducing potassium tetrachloropalladinate(II) by l-ascorbic acid (AA) in an aqueous solution phase in the presence of an amphiphilic nonionic surfactant poly ethylene glycol (PEG) via a sonochemical method. Materials have been characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray soectrscopy (EDX), Fourier transform infrared (FTIR), surface-enhanced Raman spectroscopy (SERS), particle distribution, and zeta potential studies. Truncated octahedron/fivefold twinned pentagonal rods are formed at room temperature (RT) (25 °C) while hexagonal/trigonal plates are formed at 65 °C. XRD results show evolution of anisotropically grown, phase-pure, and well crystalline face-centered cubic Pd NPs at both temperatures. FTIR and SERS studies revealed adsorption of ascorbic acid (AA) and PEG at NP's surface. Particle's size distribution graph indicates formation of particles having wide size distribution while the zeta potential particle surface is negatively charged and stable. The truncated octahedron/fivefold twinned pentagonal rod-shaped Pd NPs, formed at RT, while thermally stable and kinetically controlled hexagonal/trigonal plate-like Pd NPs, evolved at higher temperature 65 °C. The obtained Pd NPs have a high surface area and narrow pore size distribution. To predict protein reactivity of the Pd cluster, docking has been done with DNA and lung cancer-effective proteins. The cytotoxicity of the Pd NPs has been screened on human lung cancer cells A-549 at 37 °C. The biological adaptability exhibited by Pd NPs has opened a pathway in biochemical applications.

Predicting drug-target interactions from drug structure and protein sequence using novel convolutional neural networks

Background

Accurate identification of potential interactions between drugs and protein targets is a critical step to accelerate drug discovery. Despite many relative experimental researches have been done in the past decades, detecting drug-target interactions (DTIs) remains to be extremely resource-intensive and time-consuming. Therefore, many computational approaches have been developed for predicting drug-target associations on a large scale.

Results

In this paper, we proposed an deep learning-based method to predict DTIs only using the information of drug structures and protein sequences. The final results showed that our method can achieve good performance with the accuracies up to 92.0%, 90.0%, 92.0% and 90.7% for the target families of enzymes, ion channels, GPCRs and nuclear receptors of our created dataset, respectively. Another dataset derived from DrugBank was used to further assess the generalization of the model, which yielded an accuracy of 0.9015 and an AUC value of 0.9557.

Conclusion

It was elucidated that our model shows improved performance in comparison with other state-of-the-art computational methods on the common benchmark datasets. Experimental results demonstrated that our model successfully extracted more nuanced yet useful features, and therefore can be used as a practical tool to discover new drugs.

Availability

http://deeplearner.ahu.edu.cn/web/CnnDTI.htm.

Performance-Enhanced Non-Enzymatic Glucose Sensor Based on Graphene-Heterostructure

Non-enzymatic glucose sensing is a crucial field of study because of the current market demand. This study proposes a novel design of glucose sensor with enhanced selectivity and sensitivity by using graphene Schottky diodes, which is composed of graphene (G)/platinum oxide (PtO)/n-silicon (Si) heterostructure. The sensor was tested with different glucose concentrations and interfering solutions to investigate its sensitivity and selectivity. Different structures of the device were studied by adjusting the platinum oxide film thickness to investigate its catalytic activity. It was found that the film thickness plays a significant role in the efficiency of glucose oxidation and hence in overall device sensitivity. 0.8-2 μA output current was obtained in the case of 4-10 mM with a sensitivity of 0.2 A/mM.cm2. Besides, results have shown that 0.8 A and 15 A were obtained by testing 4 mM glucose on two different PtO thicknesses, 30 nm and 50 nm, respectively. The sensitivity of the device was enhanced by 150% (i.e., up to 30 A/mM.cm2) by increasing the PtO layer thickness. This was attributed to both the increase of the number of active sites for glucose oxidation as well as the increase in the graphene layer thickness, which leads to enhanced charge carriers concentration and mobility. Moreover, theoretical investigations were conducted using the density function theory (DFT) to understand the detection method and the origins of selectivity better. The working principle of the sensors puts it in a competitive position with other non-enzymatic glucose sensors. DFT calculations provided a qualitative explanation of the charge distribution across the graphene sheet within a system of a platinum substrate with D-glucose molecules above. The proposed G/PtO/n-Si heterostructure has proven to satisfy these factors, which opens the door for further developments of more reliable non-enzymatic glucometers for continuous glucose monitoring systems.

Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis-A Survey

This paper provides a starting point for researchers and practitioners from biology, medicine, physics and engineering who can benefit from an up-to-date literature survey on patient-specific bone fracture modelling, simulation and risk analysis. This survey hints at a framework for devising realistic patient-specific bone fracture simulations. This paper has 18 sections: Section 1 presents the main interested parties; Section 2 explains the organzation of the text; Section 3 motivates further work on patient-specific bone fracture simulation; Section 4 motivates this survey; Section 5 concerns the collection of bibliographical references; Section 6 motivates the physico-mathematical approach to bone fracture; Section 7 presents the modelling of bone as a continuum; Section 8 categorizes the surveyed literature into a continuum mechanics framework; Section 9 concerns the computational modelling of bone geometry; Section 10 concerns the estimation of bone mechanical properties; Section 11 concerns the selection of boundary conditions representative of bone trauma; Section 12 concerns bone fracture simulation; Section 13 presents the multiscale structure of bone; Section 14 concerns the multiscale mathematical modelling of bone; Section 15 concerns the experimental validation of bone fracture simulations; Section 16 concerns bone fracture risk assessment. Lastly, glossaries for symbols, acronyms, and physico-mathematical terms are provided.

Structural Control of Charge Storage Capacity to Achieve 100% Doping in Vapor Phase-Polymerized PEDOT/Tosylate

Vapor phase polymerization (VPP) is used to fabricate a series of tosylate-doped poly(3,4-ethylenedioxythiophene) (PEDOT) electrodes on carbon paper. The series of VPP PEDOT/tosylate coatings has varying levels of crystallinity and electrical conductivity because of the use (or not) of nonionic triblock copolymers in the oxidant solution during synthesis. As a result, the impact of the structure on charge storage capacity is investigated using tetra-n-butylammonium hexafluorophosphate (0.1 M in acetonitrile). The ability to insert anions, and hence store charge, of the VPP PEDOT/tosylate is inversely related to its electrical conductivity. In the case of no nonionic triblock copolymer employed, the VPP PEDOT/tosylate achieves electrochemical doping levels of 1.0 charge per monomer or greater (≥100% doping level). Such high doping levels are demonstrated to be plausible by molecular dynamics simulations and density functional theory calculations. Experiments show that this high doping level is attainable when the PEDOT structure is weakly crystalline with (relatively) large crystallite domains.

Electronic Structure with Rovibrational Calculations of the Magnesium Monohalides MgX and Their Cations MgX+ (X = Cl, Br, and I)

Alkaline-earth monohalides are popular compounds that are used in various applications. Little is known, however, in terms of electronic structure, about their cations and their low-lying electronic states. We present in this work electronic structure ab-initio calculations based on multireference configuration interaction plus Davidson correction of three magnesium monohalides and their cations (MgCl, MgBr, MgI, MgCl⁺, MgBr⁺, and MgI⁺). We determine the spectroscopic constants T _e, R _e, ω_e, B _e, and α_e and the dissociation energies D _e for their bound states. Additionally, we investigate their vibrational properties by calculating the vibrational eigenvalue E _v, the rotational constant B _v, and the centrifugal distortion constant D _v. We additionally study the electric charge distribution of several states by determining their permanent dipole moment and transition dipole moment curves. Finally, we calculate the Franck-Condon factors and the radiative lifetimes as precursors for laser cooling experiments.

A computational-experimental investigation on high ethylene selectivity in ethanol dehydration reaction found on WOx/ZrO2-activated carbon bi-support systems

The high ethylene selectivity exhibited on the zirconia-activated-carbon bi-support catalyst is investigated by experiment and density functional theory-based (DFT) analysis. This bi-support catalyst systems prepared by the physical mixing method for the tungsten catalyst show a significant increase in ethylene selectivity up to 90% compared to the zirconia single support system (~58%) during the ethanol dehydration reaction. Besides, the optimal percent weight ratio of zirconia to activated carbon, which results in the highest ethanol conversion is 50:50. The DFT-based analysis is used to investigate high ethylene selectivity in the bi-support system. It shows that the WO₅/zirconia is the most stable model for the zirconia single-support tungsten catalyst represented by the zirconia (101) facet of the tetrahedral phase. The carbon atoms were added to the WO₅/zirconia to model the tungsten catalyst on the bi-support system. The Bader charge analysis is carried out to determine the electron transfer in the catalyst. The bonding between ethylene and the WO₅ active site on the catalyst is weakened when the system is bi-support, where the added carbon atoms on the catalyst in the ZrO₂ region decrease the ethylene adsorption energy. Thus, the desorption and the selectivity of ethylene are promoted. The decrease in adsorption energy can be explained via the analysis of the projected density of states (PDOS) profiles of atom involving the adsorption. It was found that the added carbon in the ZrO₂ region induces the electron transfer from the ethylene molecule to the surface, especially to the ZrO₂ region. The depletion of the electron around the ethylene molecule weakens the bonds, thus, promote desorption. Hence, the advantages of using the bi-support system in the tungsten catalyst are that the catalyst exhibit (1) high conversion due to the zirconia support and (2) high ethylene selectivity due to the added carbon promoting the desorption of ethylene via the induction of electron from an ethylene molecule to surface.

Characterization of an Extensive Interface on Vitronectin for Binding to Plasminogen Activator Inhibitor-1: Adoption of Structure in an Intrinsically Disordered Region

Small-angle neutron scattering (SANS) measurements were pursued to study human vitronectin, a protein found in tissues and the circulation that regulates cell adhesion/migration and proteolytic cascades that govern hemostasis and pericellular proteolysis. Many of these functions occur via interactions with its binding partner, plasminogen activator inhibitor-1 (PAI-1), the chief inhibitor of proteases that lyse and activate plasminogen. We focused on a region of vitronectin that remains uncharacterized from previous X-ray scattering, nuclear magnetic resonance, and computational modeling approaches and which we propose is involved in binding to PAI-1. This region, which bridges the N-terminal somatomedin B (SMB) domain with a large central β-propeller domain of vitronectin, appears unstructured and has characteristics of an intrinsically disordered domain (IDD). The effect of osmolytes was evaluated using circular dichroism and SANS to explore the potential of the IDD to undergo a disorder-to-order transition. The results suggest that the IDD favors a more ordered structure under osmotic pressure; SANS shows a smaller radius of gyration (R_g) and a more compact fold of the IDD upon addition of osmolytes. To test whether PAI-1 binding is also coupled to folding within the IDD structure, a set of SANS experiments with contrast variation were performed on the complex of PAI-1 with a vitronectin fragment corresponding to the N-terminal 130 amino acids (denoted the SMB-IDD because it contains the SMB domain and IDD in linear sequence). Analysis of the SANS data using the Ensemble Optimization Method confirms that the SMB-IDD adopts a more compact configuration when bound to PAI-1. Calculated structures for the PAI-1:SMB-IDD complex suggest that the IDD provides an interaction surface outside of the primary PAI-1-binding site located within the SMB domain; this binding is proposed to lead to the assembly of higher-order structures of vitronectin and PAI-1 commonly found in tissues.

Berbamine Enhances the Efficacy of Gefitinib by Suppressing STAT3 Signaling in Pancreatic Cancer Cells

Background

Small molecular inhibitors such as gefitinib (Gefi), which target EGF receptor (EGFR), are considered to be a viable pathway for the selective inhibition of pancreatic cancer (PC) development. However, the large difference in Gefi response between PC patient individuals and PC cell lines severely limits the clinical efficacy of Gefi. Berbamine (BBM) is a well-known natural-derived antitumor agent. However, no study yet exists on whether BBM can enhance the sensitivity of PC cells to Gefi or its underlying mechanisms.

Methods

MTS assay and clonogenic assay were used to determine whether BBM could enhance the anti-PC activity of Gefi by. Flow cytometric analysis was performed to study the cell cycle progression and rate of apoptosis after combined treatment with BBM and Gefi. Surface plasmon resonance (SPR) and Western blot experiments were carried out to detect the STAT3 binding affinity and the STAT3 inhibitory effect of BBM. Molecular docking and Molecular dynamic simulation were used to predicting the dominant interaction between BBM and STAT3.

Results

This study found that BBM synergizes with Gefi to inhibit cell growth and induce cell cycle arrest and PC cell apoptosis. Mechanistically, our results showed that BBM and Gefi have synergistic inhibitory effects on STAT3 phosphorylation, but have little effect on other EGFR downstream pathways, suggesting that BBM may exert sensitization through the inhibition of STAT3. Besides, BBM has a high affinity for STAT3 and a good inhibitory effect on STAT3 activation, further indicating that BBM was a potent direct STAT3 inhibitor. Molecular modeling between STAT3 and BBM suggested that BBM formed several key hydrophilic interactions with STAT3.

Conclusion

Our findings suggest that the combination of BBM and Gefi could be further developed as a potential PC therapy.

Metallization and superconductivity in methane doped by beryllium at low pressure

As one of the simplest hydrocarbons, methane (CH₄) has great potential in the research of superconductors. However, the metallization of CH₄ has been an issue for a long time. Here, we report the structure, metallization, and superconductivity of CH₄ doped by Be at low pressures, based on first-principles calculations. The result shows that the thermodynamically stable BeCH₄ with P1[combining macron] space-group can transform into a metal at ambient pressure. This ternary hydride BeCH₄ exhibits a superconductivity of ∼6 K below 25.6 GPa. Interestingly, the superconducting critical temperature of BeCH₄ can reach ∼30 K at 80 GPa in the form of an a-P1 space-group phase. The charge transfer from Be to CH₄ molecules plays an important role in the superconductivity. Our results present a novel way to realize the metallization of methane at relative pressures and indicate that the doped methane is a potential candidate for seeking high temperature and low pressure superconductivity.

A van der Waals Heterostructure Based on Graphene-like Gallium Nitride and Boron Selenide: A High-Efficiency Photocatalyst for Water Splitting

Hydrogen generation by photocatalytic water splitting has attained more and more research interests in the recent years since the solar energy can be directly transferred and stored as hydrogen. However, the search for a high-efficiency photocatalyst for water splitting is a really challenge. In this paper, we designed a novel 2D material-based van der Waals heterostructure (vdWH) composed by g-GaN and BSe, which is thermally stable at room temperature. The g-GaN/BSe vdWH has suitable band-edge positions for the oxidation and reduction reactions of water splitting at pH 0 and 7. The carrier mobility of this heterostructure is high, indicating the effective occurrence of reactions for water splitting. The g-GaN/BSe vdWH also possesses a type-II band alignment, which can promote the separation of the photogenerated electron-hole pairs constantly. Moreover, a large built-in electric field can be established at the interface, which will further prevent the recombination of photogenerated charges. In addition, the g-GaN/BSe vdWH also exhibits outstanding sunlight-absorption ability, and the biaxial strain can further enhance this ability. Thus, we conclude that the g-GaN/BSe vdWH can act as a high-efficiency photocatalyst for water splitting.

The Effect of Calcium on the Cohesive Strength and Flexural Properties of Low-Methoxyl Pectin Biopolymers

Abstract: Pectin binds the mesothelial glycocalyx of visceral organs, suggesting its potential role as a mesothelial sealant. To assess the mechanical properties of pectin films, we compared pectin films with a less than 50% degree of methyl esterification (low-methoxyl pectin, LMP) to films with greater than 50% methyl esterification (high-methoxyl pectin, HMP). LMP and HMP polymers were prepared by step-wise dissolution and high-shear mixing. Both LMP and HMP films demonstrated a comparable clear appearance. Fracture mechanics demonstrated that the LMP films had a lower burst strength than HMP films at a variety of calcium concentrations and hydration states. The water content also influenced the extensibility of the LMP films with increased extensibility (probe distance) with an increasing water content. Similar to the burst strength, the extensibility of the LMP films was less than that of HMP films. Flexural properties, demonstrated with the 3-point bend test, showed that the force required to displace the LMP films increased with an increased calcium concentration (p < 0.01). Toughness, here reflecting deformability (ductility), was variable, but increased with an increased calcium concentration. Similarly, titrations of calcium concentrations demonstrated LMP films with a decreased cohesive strength and increased stiffness. We conclude that LMP films, particularly with the addition of calcium up to 10 mM concentrations, demonstrate lower strength and toughness than comparable HMP films. These physical properties suggest that HMP has superior physical properties to LMP for selected biomedical applications.

Ultrasensitive SERS-Based Plasmonic Sensor with Analyte Enrichment System Produced by Direct Laser Writing

We report an easy-to-implement device for surface-enhanced Raman scattering (SERS)-based detection of various analytes dissolved in water droplets at trace concentrations. The device combines an analyte-enrichment system and SERS-active sensor site, both produced via inexpensive and high-performance direct femtosecond (fs)-laser printing. Fabricated on a surface of water-repellent polytetrafluoroethylene substrate as an arrangement of micropillars, the analyte-enrichment system supports evaporating water droplet in the Cassie-Baxter superhydrophobic state, thus ensuring delivery of the dissolved analyte molecules towards the hydrophilic SERS-active site. The efficient pre-concentration of the analyte onto the sensor site based on densely arranged spiky plasmonic nanotextures results in its subsequent label-free identification by means of SERS spectroscopy. Using the proposed device, we demonstrate reliable SERS-based fingerprinting of various analytes, including common organic dyes and medical drugs at ppb concentrations. The proposed device is believed to find applications in various areas, including label-free environmental monitoring, medical diagnostics, and forensics.

The Staphylococcus aureus IsdH Receptor Forms a Dynamic Complex with Human Hemoglobin that Triggers Heme Release via Two Distinct Hot Spots

Iron is an essential nutrient that is actively acquired by bacterial pathogens during infections. Clinically important Staphylococcus aureus obtains iron by extracting heme from hemoglobin (Hb) using the closely related IsdB and IsdH surface receptors. In IsdH, extraction is mediated by a conserved tridomain unit that contains its second (N2) and third (N3) NEAT domains joined by a helical linker, called IsdH^N2N3. Leveraging the crystal structure of the IsdH^N2N3:Hb complex, we have probed the mechanism of heme capture using NMR, stopped-flow transfer kinetics measurements, and molecular dynamics (MD) simulations. NMR studies of the 220 kDa IsdH^N2N3:Hb complex reveal that it is dynamic, with persistent interdomain motions enabling the linker and N3 domains in the receptor to transiently engage Hb to remove its heme. An alanine mutagenesis analysis reveals that two receptor subsites positioned ~20 Å apart trigger heme release by contacting Hb's F-helix. These subsites are located within the N3 and linker domains and appear to play distinct roles in stabilizing the heme transfer transition state. Linker domain contacts primarily function to destabilize Hb-heme interactions, thereby lowering ΔH^‡, while contacts from the N3 subsite play a similar destabilizing role, but also form a bridge through which heme moves from Hb to the receptor. Interestingly, MD simulations suggest that within the transiently forming interface, both the F-helix and receptor bridge are in motion, dynamically sampling conformations that are suitable for heme transfer. Thus, IsdH triggers heme release from Hb via a flexible, low-affinity interface that forms fleetingly in solution.

Revealing the mechanism of protein-lipid interactions for a putative membrane curvature sensor in plant endoplasmic reticulum

Membrane curvature sensing via helical protein domains, such as those identified in Amphiphysin and ArfGAP1, have been linked to a diverse range of cellular processes. However, these regions can vary significantly between different protein families and thus remain challenging to identify from sequence alone. Greater insight into the protein-lipid interactions that drive this behavior could lead to production of therapeutics that specifically target highly curved membranes. Here we demonstrate the curvature-dependence of membrane binding for an amphipathic helix (APH) in a plant reticulon, namely RTNLB13 from A. thaliana. We utilize solution-state nuclear magnetic resonance spectroscopy to establish the exact location of the APH and map the residues involved in protein-membrane interactions at atomic resolution. We find that the hydrophobic residues making up the membrane binding site are conserved throughout all A. thaliana reticulons. Our results also provide mechanistic insight that leads us to propose that membrane binding by this APH may act as a feedback element, only forming when ER tubules reach a critical size and adding stabilization to these structures without disrupting the bilayer. A shallow hydrophobic binding interface appears to be a feature shared more broadly across helical curvature sensors and would automatically restrict the penetration depth of these structures into the membrane. We also suggest this APH is highly tuned to the composition of the membrane in which it resides, and that this property may be universal in curvature sensors thus rationalizing the variety of mechanisms reported for these functional elements.

Rapid classification of group B Streptococcus serotypes based on matrix-assisted laser desorption ionization-time of flight mass spectrometry and machine learning techniques

Background

Group B streptococcus (GBS) is an important pathogen that is responsible for invasive infections, including sepsis and meningitis. GBS serotyping is an essential means for the investigation of possible infection outbreaks and can identify possible sources of infection. Although it is possible to determine GBS serotypes by either immuno-serotyping or geno-serotyping, both traditional methods are time-consuming and labor-intensive. In recent years, the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been reported as an effective tool for the determination of GBS serotypes in a more rapid and accurate manner. Thus, this work aims to investigate GBS serotypes by incorporating machine learning techniques with MALDI-TOF MS to carry out the identification.

Results

In this study, a total of 787 GBS isolates, obtained from three research and teaching hospitals, were analyzed by MALDI-TOF MS, and the serotype of the GBS was determined by a geno-serotyping experiment. The peaks of mass-to-charge ratios were regarded as the attributes to characterize the various serotypes of GBS. Machine learning algorithms, such as support vector machine (SVM) and random forest (RF), were then used to construct predictive models for the five different serotypes (Types Ia, Ib, III, V, and VI). After optimization of feature selection and model generation based on training datasets, the accuracies of the selected models attained 54.9–87.1% for various serotypes based on independent testing data. Specifically, for the major serotypes, namely type III and type VI, the accuracies were 73.9 and 70.4%, respectively.

Conclusion

The proposed models have been adopted to implement a web-based tool (GBSTyper), which is now freely accessible at http://csb.cse.yzu.edu.tw/GBSTyper/, for providing efficient and effective detection of GBS serotypes based on a MALDI-TOF MS spectrum. Overall, this work has demonstrated that the combination of MALDI-TOF MS and machine intelligence could provide a practical means of clinical pathogen testing.

Accelerating the Generalized Born with Molecular Volume and Solvent Accessible Surface Area Implicit Solvent Model Using Graphics Processing Units

The generalized Born with molecular volume and solvent accessible surface area (GBMV2/SA) implicit solvent model provides an accurate description of molecular volume and has the potential to accurately describe the conformational equilibria of structured and disordered proteins. However, its broader application has been limited by the computational cost and poor scaling in parallel computing. Here, we report an efficient implementation of both the electrostatic and nonpolar components of GBMV2/SA on graphics processing unit (GPU) within the CHARMM/OpenMM module. The GPU-GBMV2/SA is numerically equivalent to the original CPU-GBMV2/SA. The GPU acceleration offers ~60- to 70-fold speedup on a single NVIDIA TITAN X (Pascal) graphics card for molecular dynamic simulations of both folded and unstructured proteins of various sizes. The current implementation can be further optimized to achieve even greater acceleration with minimal reduction on the numerical accuracy. The successful development of GPU-GBMV2/SA greatly facilitates its application to biomolecular simulations and paves the way for further development of the implicit solvent methodology. © 2019 Wiley Periodicals, Inc.

Role of Acid in the Co-oligomerization of Formaldehyde and Pyrrole

Building on previous work (J. Phys. Chem. A 2017, 121, 8154-8166) under neutral conditions, we examined the co-oligomerization of CH₂O and pyrrole to form porphryinogen under acidic conditions using density functional theory (B3LYP//6-311G**). Thermodynamically, we found that azafulvene intermediates were significantly stabilized under highly acidic conditions. Kinetically, energy barriers were lowered for C-C bond formation, discriminating in favor of reactions that lead to porphyrinogen. However, it was challenging to satisfactorily combine our thermodynamic and kinetic profiles into a unified free-energy profile because of difficulties in optimizing transition states of cationic species involving proton hops. Instead, we used neutral carboxylic acids as a proxy to study how energy barriers changed. By combining data from both neutral and acidic conditions, we estimate a free-energy profile for the initial steps of oligomerization under milder acidic conditions more relevant to prebiotic chemistry.

Influence of Softness on the Stability of Binary Colloidal Crystals

Mixtures of two types of nanoparticles can self-assemble into a wide variety of binary colloidal crystals (also called binary nanoparticle superlattices), which are interesting for their structural diversity and potential applications. Although so-called packing models-which usually treat the particles as "hard" with only excluded volume interactions-seem to explain many reported dense crystalline phases, these models often fail to predict the right structure. Here, we examine the role of soft repulsive interparticle interactions on binary colloidal crystals comprising two sizes of spherical particles; such "softness" can arise due to ligand shells or screened electrostatics. We determine the ground state phase diagram of binary systems of particles interacting with an additive inverse power law potential using a basin hopping algorithm to calculate the enthalpy of an extremely large pool of candidate structures. We find that a surprisingly small amount of softness can destabilize dense packings in favor of less densely packed structures, which provides further evidence that considerations beyond packing are necessary for describing many of the observed phases of binary colloidal crystals. Importantly, we find that several of the phases stabilized by softness, which are characterized by relatively few interparticle contacts and a tendency for local icosahedral order, are more likely to be observed experimentally than those predicted by packing models. We also report a previously unknown dense AB₄ phase and conduct free energy calculations to examine how the stability of several crystals will vary with temperature. Our results further our understanding of why particular binary colloidal crystals form and will be useful as a reference for experimentalists working with softly repulsive colloids.

Human and Mouse TRPA1 Are Heat and Cold Sensors Differentially Tuned by Voltage

Transient receptor potential ankyrin 1 channel (TRPA1) serves as a key sensor for reactive electrophilic compounds across all species. Its sensitivity to temperature, however, differs among species, a variability that has been attributed to an evolutionary divergence. Mouse TRPA1 was implicated in noxious cold detection but was later also identified as one of the prime noxious heat sensors. Moreover, human TRPA1, originally considered to be temperature-insensitive, turned out to act as an intrinsic bidirectional thermosensor that is capable of sensing both cold and heat. Using electrophysiology and modeling, we compare the properties of human and mouse TRPA1, and we demonstrate that both orthologues are activated by heat, and their kinetically distinct components of voltage-dependent gating are differentially modulated by heat and cold. Furthermore, we show that both orthologues can be strongly activated by cold after the concurrent application of voltage and heat. We propose an allosteric mechanism that could account for the variability in TRPA1 temperature responsiveness.

Prediction of protein structural classes by different feature expressions based on 2-D wavelet denoising and fusion

BACKGROUND

Protein structural class predicting is a heavily researched subject in bioinformatics that plays a vital role in protein functional analysis, protein folding recognition, rational drug design and other related fields. However, when traditional feature expression methods are adopted, the features usually contain considerable redundant information, which leads to a very low recognition rate of protein structural classes.

RESULTS

We constructed a prediction model based on wavelet denoising using different feature expression methods. A new fusion idea, first fuse and then denoise, is proposed in this article. Two types of pseudo amino acid compositions are utilized to distill feature vectors. Then, a two-dimensional (2-D) wavelet denoising algorithm is used to remove the redundant information from two extracted feature vectors. The two feature vectors based on parallel 2-D wavelet denoising are fused, which is known as PWD-FU-PseAAC. The related source codes are available at https://github.com/Xiaoheng-Wang12/Wang-xiaoheng/tree/master.

CONCLUSIONS

Experimental verification of three low-similarity datasets suggests that the proposed model achieves notably good results as regarding the prediction of protein structural classes.

Identifying protein-protein interface via a novel multi-scale local sequence and structural representation

Background

Protein-protein interaction plays a key role in a multitude of biological processes, such as signal transduction, de novo drug design, immune responses, and enzymatic activities. Gaining insights of various binding abilities can deepen our understanding of the interaction. It is of great interest to understand how proteins in a complex interact with each other. Many efficient methods have been developed for identifying protein-protein interface.

Results

In this paper, we obtain the local information on protein-protein interface, through multi-scale local average block and hexagon structure construction. Given a pair of proteins, we use a trained support vector regression (SVR) model to select best configurations. On Benchmark v4.0, our method achieves average I_rmsd value of 3.28Å and overall F_nat value of 63%, which improves upon I_rmsd of 3.89Å and F_nat of 49% for ZRANK, and I_rmsd of 3.99Å and F_nat of 46% for ClusPro. On CAPRI targets, our method achieves average I_rmsd value of 3.45Å and overall F_nat value of 46%, which improves upon I_rmsd of 4.18Å and F_nat of 40% for ZRANK, and I_rmsd of 5.12Å and F_nat of 32% for ClusPro. The success rates by our method, FRODOCK 2.0, InterEvDock and SnapDock on Benchmark v4.0 are 41.5%, 29.0%, 29.4% and 37.0%, respectively.

Conclusion

Experiments show that our method performs better than some state-of-the-art methods, based on the prediction quality improved in terms of CAPRI evaluation criteria. All these results demonstrate that our method is a valuable technological tool for identifying protein-protein interface.

BioMedR: an R/CRAN package for integrated data analysis pipeline in biomedical study

BACKGROUND

With the increasing development of biotechnology and information technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these resources needs to be extracted and then transformed to useful knowledge by various data mining methods. However, a main computational challenge is how to effectively represent or encode molecular objects under investigation such as chemicals, proteins, DNAs and even complicated interactions when data mining methods are employed. To further explore these complicated data, an integrated toolkit to represent different types of molecular objects and support various data mining algorithms is urgently needed.

RESULTS

We developed a freely available R/CRAN package, called BioMedR, for molecular representations of chemicals, proteins, DNAs and pairwise samples of their interactions. The current version of BioMedR could calculate 293 molecular descriptors and 13 kinds of molecular fingerprints for small molecules, 9920 protein descriptors based on protein sequences and six types of generalized scale-based descriptors for proteochemometric modeling, more than 6000 DNA descriptors from nucleotide sequences and six types of interaction descriptors using three different combining strategies. Moreover, this package realized five similarity calculation methods and four powerful clustering algorithms as well as several useful auxiliary tools, which aims at building an integrated analysis pipeline for data acquisition, data checking, descriptor calculation and data modeling.

CONCLUSION

BioMedR provides a comprehensive and uniform R package to link up different representations of molecular objects with each other and will benefit cheminformatics/bioinformatics and other biomedical users. It is available at: https://CRAN.R-project.org/package=BioMedR and https://github.com/wind22zhu/BioMedR/.

Pushing the accuracy limit of shape complementarity for protein-protein docking

Background

Protein-protein docking is a valuable computational approach for investigating protein-protein interactions. Shape complementarity is the most basic component of a scoring function and plays an important role in protein-protein docking. Despite significant progresses, shape representation remains an open question in the development of protein-protein docking algorithms, especially for grid-based docking approaches.

Results

We have proposed a new pairwise shape-based scoring function (LSC) for protein-protein docking which adopts an exponential form to take into account long-range interactions between protein atoms. The LSC scoring function was incorporated into our FFT-based docking program and evaluated for both bound and unbound docking on the protein docking benchmark 4.0. It was shown that our LSC achieved a significantly better performance than four other similar docking methods, ZDOCK 2.1, MolFit/G, GRAMM, and FTDock/G, in both success rate and number of hits. When considering the top 10 predictions, LSC obtained a success rate of 51.71% and 6.82% for bound and unbound docking, respectively, compared to 42.61% and 4.55% for the second-best program ZDOCK 2.1. LSC also yielded an average of 8.38 and 3.94 hits per complex in the top 1000 predictions for bound and unbound docking, respectively, followed by 6.38 and 2.96 hits for the second-best ZDOCK 2.1.

Conclusions

The present LSC method will not only provide an initial-stage docking approach for post-docking processes but also have a general implementation for accurate representation of other energy terms on grids in protein-protein docking. The software has been implemented in our HDOCK web server at http://hdock.phys.hust.edu.cn/.

Computational approach to study the synthesis of noscapine and potential of stereoisomers against nsP3 protease of CHIKV

Chikungunya fever is a major public health issue in India affecting millions of people and occurs due to Chikungunya. Chikungunya virus (CHIKV) is a single stranded RNA virus from the family of Togaviridae and genus alpha virus. It contain three structural proteins: glycosylated E1 and E2, embedded in the viral envelope, and a non-glycosylated nucleocapsid protein. Till date, researchers are working on inhibition of CHIKV but till now no cheap and effective medicine is available in the market. Therefore, the authors of this work thought of isoquinoline based noscapine to inhibit the nsP3 protease of CHIKV. The aim of the work is to understand the mechanism for the synthesis of noscapine theoretically using DFT. Further study the potential of all four isomers of noscapines {(13 (S,R), 14 (R,R), 15 (R,S) and 16 (S,S)} against nsP3 protease of CHIKV with the help of docking and MD simulation. The integrated e-pharmacophore binding affinity based virtual screening, docking and molecular dynamics simulation recognized four hits isomers as inhibition nsP3 protease of CHIKV. The docking energies of all the isomers of noscapine (13–16) with nsP3 protease CHIKV was found out to be more negative than baicalin (−8.06 kcal/mol) on selected sites. Amongst the isomers of noscapine, CMPD 13 possessed best binding affinity with four hydrogen bonding interactions. Further, ADME properties and blood-brain barrier permeability properties have been calculated. DFT studies of all the isomers of noscapine was investigated.

Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps

Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time.

Theoretical Evidence for the Nonoccurrence of Tetrahedral Intermediates in the Deacylation Pathway of the Oxacillinase-24/Avibactam Complex

Oxacillinases (OXAs) β-lactamases are of special interest because of their capacity to hydrolyze antibacterial drugs such as cephalosporins and carbapenems, which are frequently used as the last option for the treatment of multidrug-resistant bacteria. Although the comprehension of the involved mechanisms at the atomic level is crucial for the rational design of new inhibitors and antibiotics, currently there is no study on the acylation/deacylation mechanisms of the OXA-24/avibactam complex from first principles; therefore, mechanistic details such as activation barriers, characterization of intermediates, and transition states are still uncertain. In this article, we address the deacylation of the OXA-24/avibactam complex by molecular dynamics simulations and hybrid quantum mechanics/molecular mechanics computations. The study supplies mechanistic details not available so far, namely, topology of the potential energy surfaces, characterization of transition states and intermediates, and calculation of the respective activation barriers. The results show that the deacylation occurs via a mechanism of two stages; the first one involves the formation of a dianionic intermediate with a computed activation barrier of 24 kcal/mol. The second stage corresponds to the cleavage of the O_S81-C bond promoted by the protonation of the O_S81 atom by the carboxylated Lys84 and the concomitant formation of the C₇-N₆ bond, allowing the liberation of avibactam and recovery of the enzyme. The calculated activation barrier for the second stage is 13 kcal/mol. The structure of the intermediate, formed in the first stage, does not fulfill the characteristics of a tetrahedral intermediate. These results suggest that the recyclization of avibactam from the OXA-24/avibactam complex may occur without the emergence of tetrahedral intermediates, unlike that observed in the class A CTX-M-15.

Crystal Structure, Morphology, and Surface Termination of Cyan-Emissive, Six-Monolayers-Thick CsPbBr3 Nanoplatelets from X-ray Total Scattering

Highly anisotropic colloidal CsPbBr₃ nanoplatelets (NPLs) represent an appealing class of colloidal quantum wells with enhanced light emissivity. Strong quantum confinement imposed by the small platelet thickness and atomic flatness gives rise to enhanced oscillator strength, higher exciton binding energy, and narrow emission linewidth. While discrete thicknesses manifest themselves in discrete bandgap energies, fine-tuning of the emission energy can be achieved by compositional modulations. Here we address one of the most debated aspects of perovskite nanoplatelets: their crystal structure. Starting with the direct imaging by high-resolution electron microscopy (providing a clue on the pseudocubic faceting of the NPLs), we focus the study on X-ray total scattering techniques, based on the Debye scattering equation (DSE) approach, to obtain better atomistic insight. The nanoplatelets are six-monolayers thick and exhibit an orthorhombic structure. A thorough structure-morphology characterization unveils a specific orientation of the axial and equatorial bromides of the PbBr₆ octahedra versus the NPLs thickness; we found that {010} and {101} planes of the orthorhombic CsPbBr₃ lattice (Pnma space group) correspond to the six facets of the NPL, with basal planes being of {101} type. The NPLs undergo a lattice relaxation in comparison to cuboidal CsPbBr₃ NCs; the major deformation is observed in the axial direction, which suggests a structural origin of the higher compliance along the b axis. The DSE-based analysis also supports a CsBr surface termination model, with half Cs sites and a half (or slightly more) Br sites vacant.

Mechanistic Insights into the Effect of Ligands on Structural Stability and Selectivity of Sulfotransferase 2A1 (SULT2A1)

Cytosolic sulfotransferases (SULTs) acting as phase II metabolic enzymes can be used in the sulfonation of small molecules by transferring a sulfonate group from the unique co-factor 3'-phosphoadenosine 5'-phosphosulfate (PAPS) to the substrates. In the present study, molecular dynamics (MD) simulations and ensemble docking study were employed to theoretically characterize the mechanism for the effect of co-factor (PAP) and ligands (LCA, raloxifene, α-hydroxytamoxifen, ouabain, and 3'-phosphoadenylyl sulfate) on structural stability and selectivity of SULT2A1 from the perspective of the dynamic behavior of SULT2A1 structures. Structural stability and network analyses indicated that the cooperation between PAP and LCA may enhance the thermal stability and compact communication in enzymes. During the MD simulations, the obviously rigid region and inward displacement were detected in the active-site cap (loop16) of the conformation containing PAP, which may be responsible for the significant changes in substrate accessibility and catalytic activity. The smaller substrates such as LCA could bind stably to the active pocket in the presence of PAP. However, the substrates or inhibitors with a large spatial structure needed to bind to the open conformation (without PAP) prior to PAPS binding.

Self-Consistent Scheme Combining MD and Order-N DFT Methods: An Improved Set of Nonpolarizable Force Fields for Ionic Liquids

The nonpolarizable force field of ionic liquids is tuned by using the self-consistent scheme of molecular dynamics (MD) simulation and first-principles calculation based on the order-N density functional theory (DFT). The atomic charges are determined by using the whole MD cell for DFT calculation and accounts effectively for the many-body effects of charge transfer and intramolecular polarization. The charges represent effective interactions in the condensed phase within the framework of the nonpolarizable force field and can be an alternative for an explicitly many-body model incorporating, for example, polarizability. Here we demonstrate the performance of nonpolarizable force field determined with the MD-DFT self-consistent scheme in imidazolium-, pyrrolidinium-, and ammonium-based ionic liquids. The variation ranges of molecular charges are much larger with the compositions of the ionic liquid than with the thermodynamic conditions, and the charge-ordering structures become systematically weaker with the effective charges. For energetic properties, while the calculated heat of vaporization depends on the atomic and molecular charges, the corresponding heat capacity is not strongly affected by the DFT-based variation. For transport properties, the self-diffusion coefficient, electrical conductivity, and viscosity vary much more in the self-consistent scheme. The effective DFT charge is observed to enhance the fluidity of ionic liquids and improve the accuracy of electrical conductivity and viscosity. This is due to the weakened interactions among the ions, and the too slow motions observed with a full-charge model are well corrected through the iteration of MD and DFT. We therefore conclude that the set of nonpolarizable force fields obtained with the MD-DFT self-consistent scheme leads to better description of transport properties of ionic liquids.