Molecular Simulation Method Research Articles

Applications of molecular modeling to flavoproteins: Insights and challenges.

The general field of molecular simulation provides a wide spectrum of methods for studying the structure and function of biomolecules. Depending on the scale and question of interest, appropriate approaches may range from ab initio quantum mechanical calculations (when detailed aspects of and changes in electronic structure must be considered) to Brownian dynamics and coarse-grained molecular dynamics (to track large scale conformational motions, diffusion, and inter-molecular interactions). The entire range of molecular simulation methods has been fruitfully applied to a range of flavoenzymes, allowing researchers to address everything from the specific intermediates involved in the photoreactions of flavin chromophore-containing light sensors, to the very long timescale motions induced by covalent modifications to bound flavin. The unique challenge posed by flavoproteins to all types of molecular simulation arises from the chemistry of the flavin isoalloxazine moiety, which presents an unusually large delocalized electron system which must be carefully treated in order to represent its contributions to the overall behavior of the system. Here we outline the particular considerations required for appropriate treatment of flavoproteins in simulations ranging from electronic structure calculations to long-timescale modeling of flavoprotein conformational transitions.

UiO-66(Zr) as sorbent for porous membrane protected micro-solid-phase extraction androgens and progestogens in environmental water samples coupled with LC-MS/MS analysis: The application of experimental and molecular simulation method

Four water stable metal-organic frameworks (MOFs), MIL-101(Cr), MIL-100(Fe), MIL-53(Al), and UiO-66(Zr), were used as adsorbents for concentration of four androgens and progestogens from water. The adsorption abilities of target analytes on the four MOFs were investigated by experimental and molecular simulation strategies, and UiO-66(Zr) was ultimately selected as the sorbent to develop a porous membrane protected micro-solid-phase extraction (μ-SPE) method for simultaneous extraction androgens and progestogens in environmental water samples followed by LC-MS/MS detection. Several variables affecting the extraction efficiency were systematically investigated, including pH, salt concentration, extraction time, kind of desorption solvent, and desorption time. Under the optimized conditions, excellent linearity was obtained in the range of 20.32–2032 ng/L for T, 10.24–1024 ng/L for P, 7.624–762.4 ng/L for TP, and 8.376–837.6 ng/L for MPA. Limits of detection (LODs) and limits of quantification (LOQs) were 10 ng/L and 20 ng/L for T, 4.0 ng/L and 10 ng/L for P, 2.0 ng/L and 7.0 ng/L for TP, and 3.0 ng/L and 8.0 ng/L for MPA, respectively. The recoveries were ranged from 80.5% to 102.4%. Furthermore, the μ-SPE device could be used for at least 10 extractions (RSD < 10.0%). Meanwhile, comparison was made with solid-phase extraction, and the developed method was demonstrated to be a convenient and eco-friendly pretreatment method for water samples.

Multiscale simulations of critical interfacial failure in carbon nanotube-polymer composites.

Computational investigation of interfacial failure in composite materials is challenging because it is inherently multi-scale: the bond-breaking processes that occur at the covalently bonded interface and initiate failure involve quantum mechanical phenomena, yet the mechanisms by which external stresses are transferred through the matrix occur on length and time scales far in excess of anything that can be simulated quantum mechanically. In this work, we demonstrate and validate an adaptive quantum mechanics (QM)/molecular mechanics simulation method that can be used to address these issues and apply it to study critical failure at a covalently bonded carbon nanotube (CNT)-polymer interface. In this hybrid approach, the majority of the system is simulated with a classical forcefield, while areas of particular interest are identified on-the-fly and atomic forces in those regions are updated based on QM calculations. We demonstrate that the hybrid method results are in excellent agreement with fully QM benchmark simulations and offers qualitative insights missing from classical simulations. We use the hybrid approach to show how the chemical structure at the CNT-polymer interface determines its strength, and we propose candidate chemistries to guide further experimental work in this area.

Application of molecular simulation in transformer oil–paper insulation

Molecular simulation technology is a new technology emerging with the rapid development of computer technology. It has the advantages of clear microscopic models, in-depth and precise calculation etc., it has been widely used in the oil–paper insulation system of transformer in recent years. Based on the application of molecular simulation technology in the oil–paper insulation system of transformers in this study, the current research status and progress of molecular simulation in these area are elaborated in detail from the aspects of transformer insulating oil and insulating paper according to the domestic and foreign literature, and the application of molecular simulation technology in plant insulating oil and nano-modified insulating oil is emphatically analysed. The complementing research method of molecular simulation and experiment is pointed out, which provides certain reference for solving many problems existing in the field of oil–paper insulation system of transformers.

Molecular dynamics simulation of the follicle-stimulating hormone receptor. Understanding the conformational dynamics of receptor variants at positions N680 and D408 from in silico analysis.

Follicle-stimulating hormone receptor (FSHR) is a G-protein coupled receptor (GPCR) and a prototype of the glycoprotein hormone receptors subfamily of GPCRs. Structural data of the FSHR ectodomain in complex with follicle-stimulating hormone suggests a “pull and lift” activation mechanism that triggers a conformational change on the seven α-helix transmembrane domain (TMD). To analyze the conformational changes of the FSHR TMD resulting from sequence variants associated with reproductive impairment in humans, we set up a computational approach combining helix modeling and molecular simulation methods to generate conformational ensembles of the receptor at room (300 K) and physiological (310 K) temperatures. We examined the receptor dynamics in an explicit membrane environment of polyunsaturated phospholipids and solvent water molecules. The analysis of the conformational dynamics of the functional (N680 and S680) and dysfunctional (mutations at D408) variants of the FSHR allowed us to validate the FSHR-TMD model. Functional variants display a concerted motion of flexible intracellular regions at TMD helices 5 and 6. Disruption of side chain interactions and conformational dynamics were detected upon mutation at D408 when replaced with alanine, arginine, or tyrosine. Dynamical network analysis confirmed that TMD helices 2 and 5 may share communication pathways in the functional FSHR variants, whereas no connectivity was detected in the dysfunctional mutants, indicating that the global dynamics of the FSHR was sensitive to mutations at amino acid residue 408, a key position apparently linked to misfolding and variable cell surface plasma membrane expression of FSHRs with distinct mutations at this position.

Enhanced sampling method in molecular simulations using genetic algorithm for biomolecular systems.

We propose a molecular simulation method using genetic algorithm (GA) for biomolecular systems to obtain ensemble averages efficiently. In this method, we incorporate the genetic crossover, which is one of the operations of GA, to any simulation method such as conventional molecular dynamics (MD), Monte Carlo, and other simulation methods. The genetic crossover proposes candidate conformations by exchanging parts of conformations of a target molecule between a pair of conformations during the simulation. If the candidate conformations are accepted, the simulation resumes from the accepted ones. While conventional simulations are based on local update of conformations, the genetic crossover introduces global update of conformations. As an example of the present approach, we incorporated genetic crossover to MD simulations. We tested the validity of the method by calculating ensemble averages and the sampling efficiency by using two kinds of peptides, ALA3 and (AAQAA)3 . The results show that for ALA3 system, the distribution probabilities of backbone dihedral angles are in good agreement with those of the conventional MD and replica-exchange MD simulations. In the case of (AAQAA)3 system, our method showed lower structural correlation of α-helix structures than the other two methods and more flexibility in the backbone ψ angles than the conventional MD simulation. These results suggest that our method gives more efficient conformational sampling than conventional simulation methods based on local update of conformations. © 2018 Wiley Periodicals, Inc.

Atomistic chemical computation of Olefin polymerization reaction catalyzed by (pyridylamido)hafnium(IV) complex: Application of Red Moon simulation

We have realized the microscopic simulation of olefin polymerization, that is, the simulation of the catalytic polymerization (CP) reaction system composed of (pyridylamido)hafnium(IV) complex as the catalyst. For this purpose, we adopted Red Moon (RM) method, a novel molecular simulation method to simulate the complex reaction system. First, according to the previous research, with the help of the QM calculation, we proposed a model system and elementary processes and explained the theoretical treatment of the simulation by the RM method (the RM simulation). In addition, we also proposed a macroscopic simulation based on chemical kinetics simulation. Then, we performed two simulations and compared them in terms of the effective time evolution of the three macroscopic physical quantities, the number-average molecular weight Mn , the mass-average molecular weight Mw , and the molar-mass dispersity ĐM . The comparison showed that the two simulations are in quantitative or partially qualitative agreement with each other. Therefore, it is concluded that the RM simulation could not only simulate the CP reaction process microscopically, but also it is connected essentially to reproduce the time evolution of the macroscopic physical quantities on the basis of its microscopic simulation data. © 2018 Wiley Periodicals, Inc.

Atomistic Simulation: A Unique and Powerful Computational Tool for Corrosion Inhibition Research

It is difficult to understand the atomistic information on the interaction at the metal/corrosion inhibitor interface experimentally which is a key to understanding the mechanism by which inhibitors prevent the corrosion of metals. Atomistic simulations (molecular dynamics and Monte Carlo) are mostly performed in corrosion inhibition research to give deeper insights into the mechanism of inhibition of corrosion inhibitors on metal surfaces at the atomic and molecular time scales. A lot of works on the use of molecular dynamics and Monte Carlo simulation to investigate corrosion inhibition phenomenon have appeared in the literature in recent times. However, there is still a lack of comprehensive review on the understanding of corrosion inhibition mechanism using these atomistic simulation methodologies. In this review paper, we first of all introduce briefly some important molecular modeling simulations methods. Thereafter, the basic theories of molecular dynamics and Monte Carlo simulations are highlighted. Several studies on the use of atomistic simulations as a modern tool in corrosion inhibition research are presented. Some mechanistic and energetic information on how organic corrosion inhibitors interact with iron and copper metals are provided. This atomic and molecular level information could aid in the design, synthesis and development of new and novel corrosion inhibitors for industrial applications.

Study of the interactions of bovine serum albumin with a molybdenum(II) carbonyl complex by spectroscopic and molecular simulation methods.

Therapy with inhaled carbon monoxide (CO) is being tested in human clinical trials, yet the alternative use of prodrugs, CO-Releasing Molecules (CORMs), is conceptually advantageous. These molecules are designed to release carbon monoxide in specific tissues, in response to some locally expressed stimulus, where CO can trigger a cytoprotective response. The design of such prodrugs, mostly metal carbonyl complexes, must consider their ADMET profiles, including their interaction with transport plasma proteins. However, the molecular details of this interaction remain elusive. To shed light into this matter, we focused on the CORM prototype [Mo(η5-Cp)(CH2COOH)(CO)3] (ALF414) and performed a detailed molecular characterization of its interaction with bovine serum albumin (BSA), using spectroscopic and computational methods. The experimental results show that ALF414 partially quenches the intrinsic fluorescence of BSA without changing its secondary structure. The interaction between BSA and ALF414 follows a dynamic quenching mechanism, indicating that no stable complex is formed between the protein Trp residues and ALF414. The molecular dynamics simulations are in good agreement with the experimental results and confirm the dynamic and unspecific character of the interaction between ALF414 and BSA. The simulations also provide important insights into the nature of the interactions of this CORM prototype with BSA, which are dominated by hydrophobic contacts, with a contribution from hydrogen bonding. This kind of information is useful for future CORM design.

Comparison of Potential Energy Surface and Computed Rate Coefficients for Dissociation

Comparisons are made between potential energy surfaces (PESs) for and collisions and between rate coefficients for dissociation that were computed using the quasi-classical trajectory (QCT) method on these PESs. For , Laganà’s empirical London–Eyring–Polanyi–Sato surface is compared with one from NASA Ames Research Center based on ab initio quantum chemistry calculations. For , two ab initio PESs (from NASA Ames and from the University of Minnesota) are compared. These use different methods for computing the ground state electronic energy for but give similar results. Thermal dissociation rate coefficients, for the 10,000–30,000 K temperature range, have been computed using each PES, and the results are in excellent agreement. Quasi-stationary state (QSS) rate coefficients using both PESs have been computed at these temperatures using the direct molecular simulation method (DMS) of Schwartzentruber and coworkers. The QSS rate coefficients are up to a factor of 5 lower than the thermal ones, and the thermal and QSS values bracket the results of shock-tube experiments. It is concluded that the combination of ab initio quantum chemistry PESs and QCT calculations provides an attractive approach for the determination of accurate high-temperature rate coefficients for use in aerothermodynamics modeling.

Erratum to: Review of Molecular Simulation Method for Gas Adsorption/desorption and Diffusion in Shale Matrix

In the originally published article version the family name of first author WANG Hui was misspellt “WAND”. The original article has been corrected.

Review of Molecular Simulation Method for Gas Adsorption/desorption and Diffusion in Shale Matrix

Shale gas is becoming an increasingly promising alternative energy resource because of its high efficiency and environment-friendly characteristic. The amount of adsorbed gas on the shale matrix surfaces and dissolved gas in the shale matrix bulk is the dominant factor in the long-term productivity of shale reservoir. Although experimental measurements have been extensively carried out to investigate the gas adsorption and diffusion properties in the shale matrix, they cannot provide the detailed information on the microscopic transport mechanism of shale gas during the gas production process. Molecular simulation can accurately visualize the gas adsorption/desorption and diffusion processes in the shale matrix. In the present study, the recent research advances of molecular simulation on gas adsorption/desorption and diffusion in the shale matrix are reviewed. Firstly, the density functional theory (DFT) for shale gas molecule desorption/adsorption on the surface of the matrix crystal is illustrated. Then, the grand canonical Monte Carlo (GCMC) method predicting the amount of shale gas desorption/adsorption in the shale matrix crystal is introduced. Finally, molecular dynamics simulation (MD) for gas diffusion in the shale matrix is elucidated. Further developments of the molecular simulation method in shale gas production are also discussed.

Molecular simulation study of CYP2B6 polymorphism with and without psoralen

ABSTRACTCYP2B6 is a polymorphic enzyme with a large number of variants which may lead to functional changes in enzyme activity and substrate selectivity. In this study, CYP2B6 and its three variants with and without psoralen, a mechanism-based inactivator, were investigated using molecular simulation method. The obtained docking orientation of psoralen was in agreement with previously identified site of metabolism. Stability analysis showed that the three variants displayed more flexibility than CYP2B6.1, and CYP2B6.34 was the most flexible one without psoralen binding. However, in the presence of psoralen, CYP2B6.34 became more rigidity. Tunnel analysis indicates that the bottleneck change of tunnels may be correlated to the increased or decreased activity of variants. Binding free energy analysis shows that van der Waals interaction dominates the binding of psoralen. CYP2B6.34 has the highest affinity to psoralen with lowest binding free energy. Ile114, Phe115 and heme contribute largely to the binding of psoralen with CYP2B6.6, while Phe206 and Leu363 play important roles for CYP2B6.1 and CYP2B6.4. These computational observations suggest that the increased activity of CYP2B6.4 and reduced activity of CYP2B6.6 may be due to changes in regional structures.

Confidence Analysis of DEER Data and Its Structural Interpretation with Ensemble-Biased Metadynamics

Given its ability to measure multicomponent distance distributions between electron-spin probes, double electron-electron resonance (DEER) spectroscopy has become a leading technique to assess the structural dynamics of biomolecules. However, methodologies to evaluate the statistical error of these distributions are not standard, often hampering a rigorous interpretation of the experimental results. Distance distributions are often determined from the experimental DEER data through a mathematical method known as Tikhonov regularization, but this approach makes rigorous error estimates difficult. Here, we build upon an alternative, model-based approach in which the distance probability distribution is represented as a sum of Gaussian components, and use propagation of errors to calculate an associated confidence band. Our approach considers all sources of uncertainty, including the experimental noise, the uncertainty in the fitted background signal, and the limited time span of the data collection. The resulting confidence band reveals the most and least reliable features of the probability distribution, thereby informing the structural interpretation of DEER experiments. To facilitate this interpretation, we also generalize the molecular simulation method known as ensemble-biased metadynamics (EBMetaD). This method, originally designed to generate maximal-entropy structural ensembles consistent with one or more probability distributions, now also accounts for the uncertainty in those target distributions exactly as dictated by their confidence bands. After careful benchmarks, we demonstrate the proposed techniques using DEER results from spin-labeled T4 lysozyme.

High temperature and pressure water/oil interfacial tension benchmark data for the Ninth Industrial Fluid Properties Simulation Challenge

The primary goal of the Ninth Industrial Fluid Properties Simulation Challenge was to test the ability of molecular simulation methods to predict water/oil interfacial tension at conditions of high temperature and pressure. The challenge focused on three oils: n-dodecane, toluene, and a 50:50 by weight blend of dodecane and toluene. A set of experiments were performed with a pendant drop tensiometer to establish the benchmark data to be used to judge the challenge, and these data were unavailable to the challenge entrants until after they had submitted their predictions. Among the three oils, dodecane exhibited the highest interfacial tension and strongest dependence of interfacial tension on temperature. The water/oil interfacial properties for the blend were much closer to those of toluene than dodecane, indicating the interface in the case of the blend may be enriched in toluene compared to the bulk composition of the blend.

3D matters! 3D-RISM and 3D convolutional neural network for accurate bioaccumulation prediction

In this work, we present a new method for predicting complex physical-chemical properties of organic molecules. The approach utilizes 3D convolutional neural network (ActivNet4) that uses solvent spatial distributions around solutes as input. These spatial distributions are obtained by a molecular theory called three-dimensional reference interaction site model. We have shown that the method allows one to achieve a good accuracy of prediction of bioconcentration factor which is difficult to predict by direct application of methods of molecular theory or simulations. Our research demonstrates that combination of molecular theories with modern machine learning approaches can be effectively used for predicting properties that are otherwise inaccessible to purely theory-based models.

Effects of antioxidant functionalized silica on reinforcement and anti-aging for solution-polymerized styrene butadiene rubber: Experimental and molecular simulation study

A new type of antioxidant functionalized silica (SiO2-g-MC) was prepared by grafting antioxidant N-(4-aniline phenyl) maleic imide (MC) onto the surface of silica via γ-mercaptopropyl trimethoxysilane (KH590). The effects of SiO2-g-MC on reinforcement and anti-aging for solution-polymerized styrene butadiene rubber (SSBR) were investigated by experimental and molecular simulation methods. It was found that the reinforcement of SiO2-g-MC was much more effective than that of the neat silica (SiO2) in SSBR matrix due to well-dispersion and strong interfacial interaction between SiO2-g-MC and SSBR. Compared with KH590 modified silica (SiO2-KH590) and SiO2, SiO2-g-MC had better vulcanization behavior and could greatly improve thermo-oxidation resistance of SSBR composite. Furthermore, grafting MC onto the surface of silica could not only restrain the migration of free MC, but also reduce the negative influence of free MC on cross-linking density of SSBR composite. Therefore, SiO2-g-MC/SSBR composite exhibited more preeminent mechanical properties than SiO2-KH590/MC/SSBR composites during the thermo-oxidation aging process. These results indicated that SiO2-g-MC could be used as a functional filler for the preparation of high performance SSBR composites, and moreover, the theoretical molecular simulation process can help us gain a better insight into the structure-property relationship for SSBR composite.

Molecular dynamics, grand canonical Monte Carlo and expert simulations and modeling of water–acetic acid pervaporation using polyvinyl alcohol/tetraethyl orthosilicates membrane

In this study, molecular dynamics (MD) and Monte Carlo (MC) simulations techniques were employed as well as artificial intelligence knowledge of ANFIS and GP to investigate water–acetic acid pervaporation (PV) separation through poly vinylalcohol (PVA)‑silicone based membranes under a wide range of experimental conditions. For the first time, three new optimization algorithms, namely ant colony optimization for continuous domains (ACOR), differential evolution (DE) and genetic algorithm (GA) were employed for improving ANFIS modeling. The GP creates a mathematical function or model for the estimation of pervaporation separation index (PSI) as a function of the input variables. ACOR-ANFIS and GA-ANFIS and GP had high accuracy (R2 = 0.9831, 0.9792 and 0.9722, respectively) but DE-ANFIS had a lower accuracy (R2 = 0.9610) as compared to other models. On the other hand, molecular simulation methods were used and the results of all simulation models were compared fairly to each other and to the experimental results of the literature. Also, some characterizations were taking place to investigate the characteristics of the simulated membranes with MS such as WAXD, and FFV and glass transition temperature was used to estimate the thermal properties of the simulated membranes.

Experimental and dynamics simulation studies of the molecular modeling and reactivity of the Yaojie oil shale kerogen

In this study, the chemical structural parameters of a kerogen from Yaojie oil shale were identified and investigated by using experimental data obtained from solid-state 13C nuclear magnetic resonance spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, flash pyrolysis–gas chromatography–mass spectrometry, and Fourier transform infrared spectroscopy. Twelve constitutional isomers of the Yaojie 2D models with different grids and their corresponding 3D models were constructed by the combination of molecular simulation methods and multiple testing techniques. Finally, a reasonable 3D model of Yaojie kerogen was determined by a series of anneal dynamics simulations and geometry optimization calculations. From the results obtained by Mulliken population analysis and electron density analysis, the π–π conjugation effect among the aromatic ring structures is significantly impacted by the heteroatoms, leading to the accumulation of electrons on heteroatoms. Meanwhile, sulfur, oxygen, and nitrogen in the heterocyclic structures exhibited higher electronic charge density and considerably more reactivity compared with those of other atoms. Moreover, the molecular orbitals of HOMO and LUMO were calculated to examine the properties of chemical reaction of kerogen. The HOMO–LUMO energy gap indicated that the Yaojie kerogen exhibited higher reactivities compared to Type Ⅰ kerogen.

High performance polyimides containing bio-molecule adenine building block from DNA

A series of PIs (APIs) containing naturally occurring adenine moiety in polymer backbone has been prepared from adenine-containing diamine (p-APA) and commercial dianhydrides by a two-step polymerization process. FTIR study confirmed the structures of APIs. The hydrogen-bonding interactions of APIs were studied by FTIR, in-situ FTIR and theoretical methods. The crystalline behavior of APIs were studied by XRD, and the results showed that the APIs have relatively high degree of crystalline. Birefringence and polarized ATR FTIR studies showed that the groups and chains in API films could be simultaneously self-arranged in the in-plane direction without any further stretching. Molecular simulation methods were introduced to study the relationship between self-arranged in-plane orientation and hydrogen-bonding interactions. Thermogravimetric analysis (TGA) showed that the 5% weight loss of APIs (T5) are in the range of 511–569 °C in nitrogen, and the char yields (CR) of APIs are in the range of 55–67% under nitrogen condition. Dynamic mechanical analysis showed that the glass-transition temperature (Tg) are in the range of 315–400 °C. The mechanical properties were studied by universal strength tester, and the results showed that the tensile modulus of API films were in the range of 4.43–9.21 GPa, and the tensile strength of API films were in the range of 124.9–162.9 MPa. Thermal mechanical analysis showed that the in-plane CTE of APIs are in the range of −5.85–37.82 ppm/°C.