Showing papers in "Journal of Molecular Graphics & Modelling in 2017"
TL;DR: The potential application of a B24N24 is explored as a drug delivery system for anti-cancer 5-fluorouracil based on the density functional theory, and it was found that the electronic properties of Al-doped BN are significantly sensitive to the drug adsorption.
Abstract: It has been previously indicated that BN nanostructures may be nontoxic and biocompatible. Here the potential application of a B24N24 is explored as a drug delivery system for anti-cancer 5-fluorouracil based on the density functional theory. This drug prefers to attach via its oxygen atoms to the B atoms of the cluster with adsorption energy about -11.90kcalmol-1 based on the dispersion corrected B3LYP level of theory. To make the cluster more appropriate for drug delivery, we replaced a B atom by Si or Al atom to improve the interaction strength. The calculated adsorption energies are about -50.13 and -34.19kcalmol-1 for Al and Si doped BN clusters, respectively. It was found that, in addition to the more negative adsorption energy, the electronic properties of Al-doped BN are significantly sensitive to the drug adsorption. Also, a drug release mechanism is proposed, indicating that in the low pH of the cancer cells the drug and BN cluster are considerably protonated, thereby separating the drug from the surface of the cluster.
98 citations
TL;DR: Time dependent density functional theory (TD-DFT) calculations along with frontier molecular orbitals, density of states (DOS), second hyperpolarizability density analysis and molecular electrostatic potential (MEP) diagrams are used to trace the origin of electro-optical as well as structure property relationships.
Abstract: Using first-principle methods, several key electronic, optical and nonlinear optical properties are calculated for two recently synthesized chalcone derivatives i.e. (2E)-3-(4-methylphenyl)-1-(3-nitrophenyl)prop-2-en-1-one (comp.1) and (2E)-3-[4-(dimethylamino)phenyl]-1-(3-nitrophenyl)prop-2-en-1-one (comp.2). The calculation of dipole moment, polarizability , anisotropy of polarizability as well as second hyperpolarizability (usually considered as a signature for two photon absorption phenomenon) are performed using density functional theory methods at PBE0/6-311G** level of theory. The linear average polarizability for comp.1 and comp.2 are found to be 32.15×10-24 and 38.76×10-24esu, respectively. Similarly, the second hyperpolarizability amplitudes of comp.1 and comp.2 are found to be reasonably larger mounting to 79.31×10-36 and 181.36×10-36esu, respectively. The importance of donor end is determined by comparing p-methylphenyl group of comp.1 with that of N,N-dimethylaniline group of comp.2 that results a remarkable increase in its amplitude, which is ∼2 times larger as compared with that of comp.1 owing to the stronger donor-acceptor configuration of comp.2. Interestingly, a comparison of average static third-order nonlinear polarizabilities shows that amplitudes of comp.1 and comp.2 are ∼13 times and ∼29 times larger than that of para-nitroaniline (a typical standard push-pull NLO-phore) at the same PBE0/6-311G** level of theory, which indicates a real time NLO application of our titled compounds. Time dependent density functional theory (TD-DFT) calculations along with frontier molecular orbitals, density of states (DOS), second hyperpolarizability density analysis and molecular electrostatic potential (MEP) diagrams are used to trace the origin of electro-optical as well as structure property relationships.
90 citations
TL;DR: Although various PSSP methods have been proposed, there still exist several further improvements or potential research directions, and the presented guidelines will help nonspecialists and specialists to learn the critical progress in PSSP in recent years.
Abstract: Protein secondary structure prediction (PSSP) is a fundamental task in protein science and computational biology, and it can be used to understand protein 3-dimensional (3-D) structures, further, to learn their biological functions. In the past decade, a large number of methods have been proposed for PSSP. In order to learn the latest progress of PSSP, this paper provides a survey on the development of this field. It first introduces the background and related knowledge of PSSP, including basic concepts, data sets, input data features and prediction accuracy assessment. Then, it reviews the recent algorithmic developments of PSSP, which mainly focus on the latest decade. Finally, it summarizes the corresponding tendencies and challenges in this field. This survey concludes that although various PSSP methods have been proposed, there still exist several further improvements or potential research directions. We hope that the presented guidelines will help nonspecialists and specialists to learn the critical progress in PSSP in recent years.
76 citations
TL;DR: The present results indicate that the screened compound 114 may act as a parent structure for designing potent derivatives against AbMurF in specific and MurF of other bacterial pathogens in general.
Abstract: MurF ligase catalyzes the final cytoplasmic step of bacterial peptidoglycan biosynthesis and, as such, is a validated target for therapeutic intervention. Herein, we performed molecular docking to identify putative inhibitors of Acinetobacter baumannii MurF (AbMurF). Based on comparative docking analysis, compound 114 (ethyl pyridine substituted 3-cyanothiophene) was predicted to potentially be the most active ligand. Computational pharmacokinetic characterization of drug-likeness of the compound showed it to fulfil all the parameters of Muegge and the MDDR rule. A molecular dynamic simulation of 114 indicated the complex to be stable on the basis of an average root mean square deviation (RMSD) value of 2.09 A for the ligand. The stability of the complex was further supported by root mean square fluctuation (RMSF), beta factor and radius of gyration values. Analyzing the complex using radial distribution function (RDF) and a novel analytical tool termed the axial frequency distribution (AFD) illustrated that after simulation the ligand is positioned in close vicinity of the protein active site where Thr42 and Asp43 participate in hydrogen bonding and stabilization of the complex. Binding free energy calculations based on the Poisson-Boltzmann or Generalized–Born Surface Area Continuum Solvation (MM(PB/GB)SA) method indicated the van der Waals contribution to the overall binding energy of the complex to be dominant along with electrostatic contributions involving the hot spot amino acids from the protein active site. The present results indicate that the screened compound 114 may act as a parent structure for designing potent derivatives against AbMurF in specific and MurF of other bacterial pathogens in general.
69 citations
TL;DR: The results indicate that the method proposed in this paper can effectively improve the prediction accuracy of protein structural class, which will be a reliable tool for prediction of proteinStructural class, especially for low-similarity sequences.
Abstract: Prediction of protein structural class plays an important role in protein structure and function analysis, drug design and many other biological applications. Prediction of protein structural class for low-similarity sequences is still a challenging task. Based on the theory of wavelet denoising, this paper presents a novel method of prediction of protein structural class for the first time. Firstly, the features of the protein sequence are extracted by using Chou's pseudo amino acid composition (PseAAC). Then the extracted feature information is denoised by two-dimensional (2D) wavelet. Finally, the optimal feature vectors are input to support vector machine (SVM) classifier to predict protein structural classes. We obtained significant predictive results using jackknife test on three low-similarity protein structural class datasets 25PDB, 1189 and 640, and compared our method with previous methods The results indicate that the method proposed in this paper can effectively improve the prediction accuracy of protein structural class, which will be a reliable tool for prediction of protein structural class, especially for low-similarity sequences.
64 citations
TL;DR: AIM analysis illustrates that the in the nucleobase-DMSO complexes, SO⋯H-N type interaction have strongest hydrogen bond strength with high EHB values, indicating the partial covalent nature of bonding in these systems, while the other bonds are classified as noncovalent interactions.
Abstract: This study aims to cast light on the physico-chemical nature and energetics of interactions between the nucleobases and water/DMSO molecules which occurs through the non-conventional CH⋯O/N-H bonds using a comprehensive quantum-chemical approach. The computed interaction energies do not show any appreciable change for all the nucleobase-solvent complexes, conforming the experimental findings on the hydration enthalpies. Compared to water, DMSO form complexes with high interaction energies. The quantitative molecular electrostatic potentials display a charge transfer during the complexation. NBO analysis shows the nucleobase-DMSO complexes, have higher stabilization energy values than the nucleobase-water complexes. AIM analysis illustrates that the in the nucleobase-DMSO complexes, SO⋯H-N type interaction have strongest hydrogen bond strength with high EHB values. Furthermore, the Laplacian of electron density and total electron density were negative indicating the partial covalent nature of bonding in these systems, while the other bonds are classified as noncovalent interactions. EDA analysis indicates, the electrostatic interaction is more pronounced in the case of nucleobase-water complexes, while the dispersion contribution is more dominant in nucleobase-DMSO complexes. NCI-RDG analysis proves the existence of strong hydrogen bonding in nucleobase-DMSO complex, which supports the AIM results.
63 citations
TL;DR: Feature analysis shows that some amino acid pairs such as 'KxG', 'KG' and 'PxP' may play an important role in the prediction of crotonylation sites, which is much better than those of the existing prediction methods.
Abstract: As one of the most important and common histones post-translational modifications, crotonylation plays a key role in regulating various biological processes. The accurate identification of crotonylation sites is crucial to elucidate the underlying molecular mechanisms of crotonylation. In this study, a novel bioinformatics tool named CKSAAP_CrotSite is developed to predict crotonylation sites. The highlight of CKSAAP_CrotSite is to adopt the composition of k-spaced amino acid pairs as input encoding, and the support vector machine is employed as the classifier. As illustrated by jackknife test, CKSAAP_CrotSite achieves a promising performance with a Sensitivity of 92.45%, a Specificity of 99.17%, an Accuracy of 98.11% and a Matthew's correlation coefficient of 0.9283, which is much better than those of the existing prediction methods. Feature analysis shows that some amino acid pairs such as 'KxG', 'KG' and 'PxP' may play an important role in the prediction of crotonylation sites. The results of analysis and prediction could offer useful information for elucidating the molecular mechanisms of crotonylation and related experimental validations. A user-friendly web-server for CKSAAP_CrotSite is available at 123.206.31.171/CKSAAP_CrotSite/.
60 citations
TL;DR: It is shown that encapsulation of different halides (X=F-, Cl-, or Br-) into BN cage significantly increases the cell voltage, and it is presented a strategy to increase the cell Voltage and performance of Na-ion batteries.
Abstract: It has been recently indicated that the Li-ion batteries may be replaced by Na-ion batteries because of their low safety, high cost, and low-temperature performance, and lack of the Li mineral reserves. Here, using density functional theory calculations, we studied the potential application of B12N12 nanoclusters as anode in Na-ion batteries. Our calculations indicate that the adsorption energy of Na+ and Na are about -23.4 and -1.4kcal/mol, respectively, and the pristine BN cage to improve suffers from a low cell voltage (∼0.92V) as an anode in Na-ion batteries. We presented a strategy to increase the cell voltage and performance of Na-ion batteries. We showed that encapsulation of different halides (X=F-, Cl-, or Br-) into BN cage significantly increases the cell voltage. By increasing the atomic number of X, the Gibbs free energy change of cell becomes more negative and the cell voltage is increased up to 3.93V. The results are discussed based on the structural, energetic, frontier molecular orbital, charge transfer and electronic properties and compared with the performance of other nanostructured anodes.
55 citations
TL;DR: A novel bioinformatics tool named PropPred is developed to predict propionylation sites by using multiple feature extraction and biased support vector machine, and feature analysis shows that some amino acid factors play the most important roles in the prediction of propionyation sites.
Abstract: Lysine propionylation is an important and common protein acylation modification in both prokaryotes and eukaryotes. To better understand the molecular mechanism of propionylation, it is important to identify propionylated substrates and their corresponding propionylation sites accurately. In this study, a novel bioinformatics tool named PropPred is developed to predict propionylation sites by using multiple feature extraction and biased support vector machine. On the one hand, various features are incorporated, including amino acid composition, amino acid factors, binary encoding, and the composition of k-spaced amino acid pairs. And the F-score feature method and the incremental feature selection algorithm are adopted to remove the redundant features. On the other hand, the biased support vector machine algorithm is used to handle the imbalanced problem in propionylation sites training dataset. As illustrated by 10-fold cross-validation, the performance of PropPred achieves a satisfactory performance with a Sensitivity of 70.03%, a Specificity of 75.61%, an accuracy of 75.02% and a Matthew's correlation coefficient of 0.3085. Feature analysis shows that some amino acid factors play the most important roles in the prediction of propionylation sites. These analysis and prediction results might provide some clues for understanding the molecular mechanisms of propionylation. A user-friendly web-server for PropPred is established at 123.206.31.171/PropPred/.
52 citations
TL;DR: The Aggregated Conformal Prediction procedure appears to be a promising approach for severely imbalanced datasets in order to retrieve a large majority of active minority class compounds while avoiding information loss or distortion.
Abstract: Aggregated Conformal Prediction is used as an effective alternative to other, more complicated and/or ambiguous methods involving various balancing measures when modelling severely imbalanced datasets. Additional explicit balancing measures other than those already apart of the Conformal Prediction framework are shown not to be required. The Aggregated Conformal Prediction procedure appears to be a promising approach for severely imbalanced datasets in order to retrieve a large majority of active minority class compounds while avoiding information loss or distortion.
51 citations
TL;DR: It was established that the drug-CNT-3H2PO4 was the most appropriate drug-carrier compound for both of the AL and ET drugs and it could be used as the most effective drug vehicle.
Abstract: The ability of (4,4)-armchair CNT and its three phosphate functionalized forms (CNT-nH2PO4, n=1-3) were evaluated as novel drug delivery systems (DDSs) for the two commercially well-known anti-osteoporosis drugs namely alendronate (AL) and etidronate (ET). For this purpose, the DFT calculations were accomplished at both B3LYP and B3PW91 levels using 6-31g(d) basis set. The binding energy was increased by increasing number of H2PO4 moieties attached on the CNT with the most negative binding energy was measured for the carrier containing three phosphate groups. The dipole moments of all phosphate containing CNTs were much greater (∼2.2-4.4D) than that of pristine CNT (∼0D). The contour maps proved that when the CNT was functionalized by H2PO4 groups, the symmetric distribution of electric charge was vanished with the charge distribution was the highest asymmetric for the CNT-2H2PO4 while it was the lowest asymmetric for CNT-3H2PO4 leading to the greatest dipole moment for the CNT-2H2PO4 (4.177D) while the smallest dipole moment for the CNT-3H2PO4 (1.614D). Among all compounds, those containing the CNT-3H2PO4 exhibited the smallest band gap energy, chemical potential and hardness but the greatest electronegativity and electrophilicity index which were all suitable and effective for the attachment of drugs onto the bone surface (having partial positive charge due to the presence of Ca2+ as CaCO3) and therefore inhibiting the osteoporosis. Consequently, it was established that the drug-CNT-3H2PO4 was the most appropriate drug-carrier compound for both of the AL and ET drugs and it could be used as the most effective drug vehicle. The attachment of AL, ET drugs as well as the AL-CNT-3H2PO4 and ET-CNT-3H2PO4 drug-carrier systems to the bone tissue was modelled by optimization of the structures of these compounds bonded to the hydroxyapatite (HA)-17water (w). It was found that among these four systems, the AL-CNT-3H2PO4 could be suggested as the most suitable DDS for application in the treatment of osteoporosis.
TL;DR: To inhibit the activity of NDM-1 a new strategy is proposed using computational methods and a hydrogen bonding network between ligand and enzyme active site is observed and key residues are identified ensuring that the ligand stays inside the active site and maintains its movement towards theactive site pocket.
Abstract: New Delhi Metallo-β-Lactamase-1 (NDM-1) has drawn great attention due to its diverse antibiotic resistant activity. It can hydrolyze almost all clinically available β-lactam antibiotics. To inhibit the activity of NDM-1 a new strategy is proposed using computational methods. Molecular dynamics (MD) simulations are used to analyze the molecular interactions between selected inhibitor candidates and NDM-1 structure. The enzyme-ligand complex is subject to binding free energy calculations using MM(PB/GB)SA methods. The role of each residue of the active site contributing in ligand binding affinity is explored using energy decomposition analysis. Furthermore, a hydrogen bonding network between ligand and enzyme active site is observed and key residues are identified ensuring that the ligand stays inside the active site and maintains its movement towards the active site pocket. A production run of 150ns is carried out and results are analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) to explain the stability of enzyme ligand complex. Important active site residue e.g. PHE70, VAL73, TRP93, HIS122, GLN123, ASP124, HIS189, LYS216, CYS208, LYS211, ALA215, HIS250, and SER251 were observed to be involved in ligand attachemet inside the active site pocket, hence depicting its inhibitor potential. Hydrogen bonds involved in structural stability are analyzed through radial distribution function (RDF) and contribution of important residues involved in ligand movement is explained using a novel analytical tool, axial frequency distribution (AFD) to observe the role of important hydrogen bonding partners between ligand atoms and active site residues.
TL;DR: The findings of the present work confirm that phosphorene molecular device can be used as a NO2 gas sensor and also the influence of Al substitution inosphorene nanosheet device is explored and reported.
Abstract: The electronic and NO2 adsorption properties of hydrogenated armchair phosphorene nanosheet device is investigated through density functional theory (DFT) and non-equilibrium Green’s function method (NEGF). The armchair phosphorene nanosheet is used for the detection of NO2 gas in phosphorene molecular device. The DOS spectrum demonstrates the change in peak maxima due to transfer of electrons between NO2 gas and phosphorene base material. The change in the peak amplitude is observed along the valance band as well as in the conduction band in the transmission spectrum of phosphorene device. I–V characteristics support the change in the current upon adsorption of NO2 gas molecule on phosphorene molecular device. Using formation energy, structural stability of phosphorene nanosheet has been studied. The adsorption properties of NO2 on phosphorene nanosheet have also been investigated with the help of adsorption energy, Mulliken charge and Bader charge analysis. In order to ascertain the selectivity of NO2 gas along phosphorene molecular device in the ambient condition, the adsorption behavior of O2 and CO2 is also studied. The findings of the present work confirm that phosphorene molecular device can be used as a NO2 gas sensor and also the influence of Al substitution in phosphorene nanosheet device is explored and reported.
TL;DR: Insight is provided into the structural features of PfCKI, which could contribute towards further understanding of related protein structures, dynamics of catalysis and phosphorylation mechanism in these important STKs from malarial parasite in near future.
Abstract: The protein kinases (PKs), belonging to serine/threonine kinase (STKs), are important drug targets for a wide spectrum of diseases in human. Among protein kinases, the Casein Kinases (CKs) are vastly expanded in various organisms, where, the malarial parasite Plasmodium falciparum possesses a single member i.e., PfCKI, which can phosphorylate various proteins in parasite extracts in vitro condition. But, the structure-function relationship of PfCKI and dynamics of ATP binding is yet to be understood. Henceforth, an attempt was made to study the dynamics, stability, and ATP binding mechanisms of PfCKI through computational modelling, docking, molecular dynamics (MD) simulations, and MM/PBSA binding free energy estimation. Bi-lobed catalytic domain of PfCKI shares a high degree of secondary structure topology with CKI domains of rice, human, and mouse indicating co-evolution of these kinases. Molecular docking study revealed that ATP binds to the active site where the glycine-rich ATP-binding motif (G16-X-G18-X-X-G21) along with few conserved residues plays a crucial role maintaining stability of the complex. Structural superposition of PfCKI with close structural homologs depicted that the location and length of important loops are different, indicating the dynamic properties of these loops among CKIs, which is consistent with principal component analysis (PCA). PCA displayed that the overall global motion of ATP-bound form is comparatively higher than that of apo form. The present study provides insights into the structural features of PfCKI, which could contribute towards further understanding of related protein structures, dynamics of catalysis and phosphorylation mechanism in these important STKs from malarial parasite in near future.
TL;DR: The findings suggest that the monolayer borophane nanosheet can be utilized to detect the presence of alcohol vapors in the atmosphere.
Abstract: The electronic properties of borophane nanosheet and adsorption behavior of three distinct alcohol vapors namely methanol, ethanol and 1-propanol on borophane nanosheet is studied using density functional theory method for the first time. The state-of-the-art provides insights on to the development of new two dimensional materials with the surface passivation on boron nanostructures. The density of states spectrum provides a clear perception on charge transfer upon adsorption of alcohol vapors on borophane nanosheets. The monolayer of borophane band gap widens upon adsorption of alcohol vapors, which can be used for the detection for volatile organic vapors. The adsorption properties of alcohol vapors on borophane base material are analyzed in terms of natural bond orbital, average energy gap variation, adsorption energy and energy gap. The most suitable adsorption sites of methanol, ethanol and 1-propanol molecules on borophane nanosheet are investigated in atomistic level. The adsorption of alcohol molecules on borophane nanosheet is found to be more favorable. The findings suggest that the monolayer borophane nanosheet can be utilized to detect the presence of alcohol vapors in the atmosphere.
TL;DR: Compared to the Ni-doped graphene, the Pt- doped surface has a relatively higher catalytic activity towards the CO2 reduction, which could be useful in practical applications for removal and transformation of CO2 to value-added chemical products.
Abstract: Today, the global greenhouse effect of carbon dioxide (CO2) is a serious environmental problem. Therefore, developing efficient methods for CO2 capturing and conversion to valuable chemicals is a great challenge. The aim of the present study is to investigate the catalytic activity of Pt- or Ni-doped graphene for the hydrogenation of CO2 by a hydrogen molecule. To gain a deeper insight into the catalytic mechanism of this reaction, the reliable density functional theory calculations are performed. The adsorption energies, geometric parameters, reaction barriers, and thermodynamic properties are calculated using the M06-2X density functional. Two reaction mechanisms are proposed for the hydrogenation of CO2. In the bimolecular mechanism, the reaction proceeds in two steps, initiating by the co-adsorption of CO2 and H2 molecules over the surface, followed by the formation of a OCOH intermediate by the transfer of H atom of H2 toward O atom of CO2. In the next step, formic acid is produced as a favorable product with the formation of CH bond. In our proposed termolecular mechanism, however, H2 molecule is directly activated by the two pre-adsorbed CO2 molecules. The predicted activation energy for the formation of the OCOH intermediate in the bimolecular mechanism is 20.8 and 47.9kcalmol-1 over Pt- and Ni-doped graphene, respectively. On the contrary, the formation of the first formic acid in the termolecular mechanism is found as the rate-determining step over these surfaces, with an activation energy of 28.8 and 45.5kcal/mol. Our findings demonstrate that compared to the Ni-doped graphene, the Pt-doped surface has a relatively higher catalytic activity towards the CO2 reduction. These theoretical results could be useful in practical applications for removal and transformation of CO2 to value-added chemical products.
TL;DR: In all four C60-drug interactions, the chemical characteristics of the drug molecule are least perturbed by the C60 moiety thereby suggesting it to be a good carrier for the delivery of these brain anticancer drug molecules to the target cells.
Abstract: The treatment of brain cancer like glioblastoma multiforme often uses chemotherapeutic drugs like temozolomide, procarbazine, carmustine, and lomustine. Fullerene loaded with these drugs help to cross the blood brain barriers. The adsorptions of the four drug molecules on the surface of the fullerene are studied mostly by using density functional theory (DFT) based method at the M06-2X/6-31G(d) level of calculations. In all four cases, the estimated interactions are noncovalent type and the average adsorption energy lies in between -5 and -11kcal/mol in the gas phase. In the aqueous and protein environment such interactions are weakened further. The binding affinity is further assessed by performing MP2 based calculations to provide interaction energies with a reasonable accuracy. Stabilities and reactivities of the drug adsorbed fullerene complexes are determined from chemical reactivity descriptors. The attached drug molecules increase the polarity of the pristine C60 thus facilitating the drug delivery within the biological systems. The semiconducting behavior of C60 is retained in the C60-drug composite systems. The computed DOS, IR, UV spectra, and molecular orbitals in the vicinity of Fermi level are analyzed to reveal the nature of the noncovalent interactions between C60 and drug molecules. The Wiberg bond order values are used to estimate the strength of the adsorption of the drug molecule on C60. In all four C60-drug interactions, the chemical characteristics of the drug molecule are least perturbed by the C60 moiety thereby suggesting it to be a good carrier for the delivery of these brain anticancer drug molecules to the target cells.
TL;DR: The results demonstrate that the adsorption of O2, CO2, and CH3OH gas molecules on pristine, Si, and B-doped SWCNTs are either physisorption or chemisor adaptation which provides the impact of selecting the best gas sensor materials towards detecting gas molecule.
Abstract: Carbon nanotubes (CNTs) have received enormous attention due to their fascinating properties to be used in various applications including electronics, sensing, energy storage and conversion. The first principles calculations within density functional theory (DFT) have been carried out in order to investigate the structural, electronic and optical properties of un-doped and doped CNT nanostructures. O2, CO2, and CH3OH have been chosen as gas molecules to study the adsorption properties based on zigzag (8,0) SWCNTs. The results demonstrate that the adsorption of O2, CO2, and CH3OH gas molecules on pristine, Si-doped and B-doped SWCNTs are either physisorption or chemisorption. Moreover, the electronic properties indicating SWCNT shows significant improvement toward gas adsorption which provides the impact of selecting the best gas sensor materials towards detecting gas molecule. Therefore, these pristine, Si-, and B-doped SWCNTs can be considered to be very good potential candidates for sensing application.
TL;DR: An augmented reality application called ChemPreview is presented with the potential to manipulate bio-molecular structures at an atomistic level and can be used to interact with a protein in an intuitive way using natural hand gestures, thereby making it appealing to computational chemists or structural biologists.
Abstract: Human computer interfaces make computational science more comprehensible and impactful. Complex 3D structures such as proteins or DNA are magnified by digital representations and displayed on two-dimensional monitors. Augmented reality has recently opened another door to access the virtual three-dimensional world. Herein, we present an augmented reality application called ChemPreview with the potential to manipulate bio-molecular structures at an atomistic level. ChemPreview is available at https://github.com/wallerlab/chem-preview/releases, and is built on top of the Meta 1 platform https://www.metavision.com/. ChemPreview can be used to interact with a protein in an intuitive way using natural hand gestures, thereby making it appealing to computational chemists or structural biologists. The ability to manipulate atoms in real world could eventually provide new and more efficient ways of extracting structural knowledge, or designing new molecules in silico.
TL;DR: The results of binding energy and its components show that the adsorption of alkyl polyoxyethylene ethers surfactant on lignite is physically adsorbed rather than electrostatically or chemisorbed, thus strengthening the hydrophobicity of lignites.
Abstract: Lignite is an important and useful fossil fuel in the world and the strong hydrophilicity of it limits its applications. Surfactant adsorption on lignite is an effective way to make it hydrophobic. In this work, aiming to examine the effect of the degree of ethoxylation on the adsorption behavior of dodecyl poly ethoxylated surfactants on lignite and the wettability modification of modified lignite by surfactant adsorption, different combined systems formed by surfactants, water and a model surface of Wender lignite have been studied using molecular dynamics simulation. The adsorption configurations vary with the degree of ethoxylation. At the same adsorption amounts, increasing the degree of ethoxylation can make the adsorption layer more compactness and bring stronger adsorption strength. The results of binding energy and its components show that the adsorption of alkyl polyoxyethylene ethers surfactant on lignite is physically adsorbed rather than electrostatically or chemisorbed. Meanwhile, van der Waals interaction plays a dominant role in the adsorption. The addition of surfactant could reduce the possibility of the interaction between water and lignite. Compared to the original lignite, the interaction between them is weakened after surfactant adsorption in water/surfactant/lignite system, thus strengthening the hydrophobicity of lignite. Similar to the adsorption strength, hydrophobicity of modified lignite increases with the increase of the degree of ethoxylation. The lignite surface properties are changed due to surfactant adsorption by analyzing the compositions of interaction energy and the change of hydrogen bonds.
TL;DR: It is demonstrated that by taking the effects of surface free energy into account, a very good agreement is achieved between the results of the developed size-dependent continuum shell model and those of MD simulation.
Abstract: Understanding the size-dependent behavior of structures at nanoscale is essential in order to have an effective design of nanosystems. In the current investigation, the surface elasticity theory is extended to study the nonlinear buckling and postbuckling response of axially loaded silicon cylindrical naoshells. Thereby, an efficient size-dependent shear deformable shell model is developed including the size effect of surface free energy. A boundary layer theory of shell buckling in conjunction with a perturbation-based solution methodology is employed to predict the size dependency in the buckling loads and postbuckling behavior of silicon nanoshells having various thicknesses. After that, on the basis of the Tersoff empirical potential, a molecular dynamics (MD) simulation is performed for a silicon cylindrical nanoshell with thickness of four times of silicon lattice constant, the critical buckling load and critical shortening of which are extracted and compared with those of the developed non-classical shell model. It is demonstrated that by taking the effects of surface free energy into account, a very good agreement is achieved between the results of the developed size-dependent continuum shell model and those of MD simulation.
TL;DR: Findings, in association with PPI network analysis, indicate that p.R183Q and p.Q209L mutations result in the over-activation of different downstream effectors, which in turn will determine the distinct cell responses and phenotype in SWS.
Abstract: Somatic activating mutations in the GNAQ have been recently associated with several congenital genetic disorders and tumors; however, the molecular mechanism/etiology that leads to GNAQ somatic mosaic mutation are unknown. Here, we reported a case of Sturge-Weber Syndrome (SWS) manifesting cutaneous vascular malformations (hemifacial Port-wine stain), cerebral and ocular vascular abnormalities (including epilepsy and glaucoma) and harboring a c.548G > A (p.R183Q) somatic mosaic mutation in GNAQ. Computational modeling studies were performed to assistant with the comprehension of the functional impact of p.R183Q and p.Q209L mutations in GNAQ, which encodes a G protein subunit alpha q (Gαq). The p.R183Q mutation was predicted to abolish hydrogen bonds between R183 residue and GDP molecule, destabilizing the inactive GDP-bound conformation of the Gαq mutants. Furthermore, replacement of R183 by Q183 residue was predicted to promote conformation changes in protein surface features affecting the switch I region, a key region that undergoes conformational changes triggered by receptor binding during signal transduction. In addition, replacement of Q209 by L209 residue was predicted to affect the molecular interaction between Gαq and Gβ subunit, impairing formation of the inactive heterotrimeric complex. These findings, in association with PPI network analysis, indicate that p.R183Q and p.Q209L mutations result in the over-activation of different downstream effectors, which in turn will determine the distinct cell responses and phenotype. These findings bring new insights on molecular etiology of vascular malformations associated to SWS and on different mechanisms underlying hyperactivation of downstream pathways to Gαq.
TL;DR: The obtained results are useful to the design and synthesize novel azo-dye-based molecules that give rise to higher photovoltaic performances of the dye-sensitized solar cells.
Abstract: Structural and electronic properties of eight isolated azo dyes (ArNNAr', where Ar and Ar' denote the aryl groups containing benzene and naphthalene skeletons, respectively) were investigated by density functional theory (DFT) based on the B3LYP/6-31G(d,p) and TD-B3LYP/6-311G(d,p) methods The effect of methanol solvent on the structural and electronic properties of the azo dyes was elucidated by employing a polarizable continuum model (PCM). Then, the azo dyes adsorbed onto the anatase TiO2 (101) slab surface through a carboxyl group. The geometries and electronic structures of the adsorption complexes were determined using periodic DFT based on the PWC/DNP method. The calculated adsorption energies indicate that the adsorbed dyes preferentially take configuration of the bidentate bridging rather than chelating or monodentate ester-type geometries. Furthermore, the azo compounds having two carboxyl groups are coordinated to the TiO2 surface more preferentially through the carboxyl group connecting to the benzene skeleton than through that connecting to the naphthalene skeleton. The dihedral angles (ΦB-N) between the benzene- and naphthalene-skeleton moieties are smaller than 10° for the adsorbed azo compounds containing one carboxyl group. In contrast, ΦB-N>30° are obtained for the adsorbed azo compounds containing two carboxyl groups. The almost planar conformations of the former appear to strengthen both π-electrons conjugation and electronic coupling between low-lying unoccupied molecular orbitals of the azo dyes and the conduction band of TiO2. On the other hand, such coupling is very weak for the latter, leading to a shift of the Fermi level of TiO2 in the lower-energy direction. The obtained results are useful to the design and synthesize novel azo-dye-based molecules that give rise to higher photovoltaic performances of the dye-sensitized solar cells.
TL;DR: The obtained results reveal that these BN nanosheets reach structural stability in the anionic form, where semiconductor and magnetic behaviors are promoted, signifying potential applicability in the transportation of pharmaceutical species in biological mediums.
Abstract: Design and characterization of the structural, electronic, and magnetic properties of armchair boron-nitride, BN (B27N27H18), nanosheets were performed by means of density functional theory all-electron calculations. The HSEh1PBE-GGA method together with 6-31G(d) basis sets were used. Non-stoichiometric B30N24H18 and B24N30H18 compositions: rich in boron or nitrogen atoms, forming homonuclear B or N bonds, respectively, were chosen. The obtained results reveal that these BN nanosheets reach structural stability in the anionic form, where semiconductor and magnetic behaviors are promoted. Effectively, the HOMO-LUMO gap is of 2.03 and 2.39eV, respectively and the magnetic moments are of 1.0 magneton bohrs, coming from the boron atoms in both systems. The rich in boron nanosheets present high-polarity, either in the gas phase or embedded in aqueous mediums like water, as well as low chemical reactivity, signifying potential applicability in the transportation of pharmaceutical species in biological mediums. These systems are also promising for the design of electronic devices, because they possess low-work functions, mainly arising from the homonuclear boron or nitrogen bond formation.
TL;DR: This work investigates the electronic, thermodynamic, optical, and structural properties of four C36X3Y3H18 NGs (X=B, and Al; and Y=N, and P) based on the density functional theory calculations and found that BN-NG is planar molecule and the others are buckybowl-shaped ones.
Abstract: Nanographenes (NGs) are a segment of graphene whose dangling bonds are saturated with hydrogen atoms, introducing different properties and promising applications. Here we investigate the electronic, thermodynamic, optical, and structural properties of four C36X3Y3H18 NGs (X=B, and Al; and Y=N, and P) based on the density functional theory calculations. It was mainly found that 1) BN-NG is planar molecule and the others are buckybowl-shaped ones, 2) The bowl-to-bowl inversion Gibbs free energies (ΔG#) of buckybowl shaped NGs are very huge and the rate constant is very small, hindering the inversion, 3) The relative energetic stability order based on the standard enthalpy of formation (ΔHf°) is as BN>AlN>BP>AlP, which the BN, and AlN doped NGs are stable at room temperature but the BP and AlP doped ones are instable, 4) The electrical conductivity order of magnitude is inverse of that of stability, 5) An exciton binding energy is predicted in the range of 0.57-0.75eV for the NGs which corresponds to Frenkel exciton type, 6) the NGs are not soluble in organic solvent in agreement with the experimental results and is partially soluble in water solvent with Gibbs free energy of solvation (ΔGsolv) in the range of -6.1 to -10.1kcal/mol.
TL;DR: An extensive replica exchange molecular dynamics simulation was performed to investigate the progress patterns of the inhibition of (-)-epigallocatechin-3-gallate (EGCG) on the Aβ16-22 hexamer, and results show that the π-π stacking is a critical factor of the interaction between EGCG and the peptides.
Abstract: An extensive replica exchange molecular dynamics (REMD) simulation was performed to investigate the progress patterns of the inhibition of (-)-epigallocatechin-3-gallate (EGCG) on the Aβ16-22 hexamer. Structural variations of the oligomers without and with EGCG were monitored and analyzed in detail. It has been found that EGCG prevents the formation of Aβ oligomer through two different ways by either accelerating the Aβ oligomerization or reducing the β-content of the hexamer. It also decreases the potential "highly toxic" conformations of Aβ oligomer, which is related to the conformations having high order β-sheet sizes. Both electrostatic and van der Waals interaction energies are found to be involved to the binding process. Computed results using quantum chemical methods show that the π-π stacking is a critical factor of the interaction between EGCG and the peptides. As a result, the binding free energy of the EGCG to the Aβ peptides is slightly larger than that of the curcumin.
TL;DR: Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented and it is revealed the docking positioning accuracies of the PM7 and PM6-D3H4X quantum- chemical methods and the CHARMM force field are better than the positioning accuracy of the MMFF94 force field.
Abstract: Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field.
TL;DR: ADFT computational study shows that Diels-Alder reactions of 1-chloro-1-nitroethene with cyclopentadiene and furan have polar nature, due to higher nucleophilicity of furan in comparison to cyclopENTadiene.
Abstract: DFT computational study shows that Diels-Alder (DA) reactions of 1-chloro-1-nitroethene with cyclopentadiene and furan have polar nature. However, their mechanism is substantially different. In particular, 1-chloro-1-nitroethene react with cyclopentadiene according to one-step mechanism. In the same time, more favourable channel associated with the P-DA reaction between furan and 1-chloro-1-nitroethene is a domino process, that comprises an initial hetero-Diels-Alder reaction yielding a [2+4] cycloadduct, which experiences a subsequent [3,3] sigmatropic shift to yield the expected formal [4+2] cycloadduct. This is a consequence of more polar nature of reaction, due to higher nucleophilicity of furan in comparison to cyclopentadiene.
TL;DR: The binding of EGCG on mutant SOD1 has reduced the formation of the toxic aggregates upon mutation, which could be a therapeutic potential against the treatment for the incurable neurodegenerative disorder (ALS) affecting the mankind.
Abstract: Amyloid formation and protein aggregation are considered to be at the core of the disease pathology for the various neurodegenerative disorders such as Amyotrophic lateral sclerosis (ALS). Considerable experimental reports have suggested that epigallocatechin-gallate (EGCG), a natural polyphenol from the green tea inhibits the amyloid formation in multiple neurodegenerative disease. Mutations in SOD1 protein are considered to a key factor that contributes towards the rapid disease progression and the pathogenesis in both, the sporadic and familial form. In our study, we computationally examined the inhibitory action of EGCG against the native and the mutant SOD1 through molecular docking, steered molecular dynamics and conformational sampling methods From the outcome, we could conjecture that the protein destabilization and increased β-sheet propensity that occurred due to mutation were regained upon the binding of EGCG. Moreover, the concepts of the free energy landscape analysis are introduced to establish the visual appearance of protein aggregation upon mutation. Altogether, we come to know that the binding of EGCG on mutant SOD1 has reduced the formation of the toxic aggregates upon mutation. Hence, our study could be an initiative in deciphering the inhibitory action of EGCG against the aggregated mutant SOD1, which could be a therapeutic potential against the treatment for the incurable neurodegenerative disorder (ALS) affecting the mankind.
TL;DR: The study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins, which is vital for helping biologists understand the electron transport chain process and energy production in cells.
Abstract: The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins.