Monte Carlo Simulated Annealing Method Research Articles

Diagnostic value of tumor associated autoantibody panel in early detection of lung cancer in Chinese population: Protocol for a prospective, observational, and multicenter clinical trial

Lung cancer is the leading cause of cancer deaths. Although targeted therapies and programmed cell death protein 1 (PD-1) blockade have offered great advances, five-year survival rates remained low. Diagnosis of lung cancer at an earlier stage is the most efficient approach to improve survival. Tumor associated autoantibodies (TAAb) have been proven a promising innovative biomarker of lung cancer. We aimed to comprehensively evaluate the sensitivity, specificity, and accuracy of TAAbs in lung cancer detection, especially in early-stage patients, through a multicenter prospective observational clinical trial, and to screen out the novel combination of TAAbs with the best detection value for Chinese population. We aimed to enroll 1,400 participants from three clinical centers and divide into two cohorts. One cohort is participants with newly pathologically confirmed lung cancer as the case cohort, and the other is participants with benign nodules, matched healthy controls and other benign lung diseases as the control cohort. Cases and controls were randomly distributed into training or validation set. The level of 14 autoantibody candidates in their plasma were detected. A Monte-Carlo Simulated Annealing method was implemented to develop a composite panel of autoantibodies to distinguish between matched lung cancer cases and controls in the training set. The newly developed autoantibody panel was tested in the validation set for sensitivity, specificity and accuracy. This is the first and largest clinical trial designed to develop a novel autoantibody panel for lung cancer detection specifically for Chinese people. We performed a multicenter, prospective, observational study to find a novel panel of autoantibody markers that can help the diagnosis of lung cancer and the characterization of pulmonary nodules in Chinese population. The results may help to provide evidence-based recommendations to clinicians for lung cancer early detection and pulmonary nodule management. This study is registered in the ClinicalTrials.gov (NCT04216511).

Structure determination of riboflavin by synchrotron high-resolution powder X-ray diffraction

The crystal structure of the stable form of vitamin B2 or riboflavin (C17H20N4O6) was solved using high-resolution powder X-ray diffraction (PXRD). The high-resolution PXRD pattern of riboflavin was recorded at room temperature at the European Synchrotron Radiation Facility (Grenoble, France). The starting structural model was generated using a Monte Carlo simulated annealing method. The final structure was obtained through Rietveld refinement. The positions of the H atoms belonging to hydroxy groups were estimated from computational energy minimizations. The symmetry is orthorhombic with the space group P212121 and the following lattice parameters: a= 20.01308, b= 15.07337 and c= 5.31565 Å.

Structure determination of a new cocrystal of carbamazepine and DL-tartaric acid by synchrotron powder X-ray diffraction.

The crystal structure of a new cocrystal of carbamazepine (systematic name: 5H-dibenzo[b,f]azepine-5-carboxamide, C15H12N2O) and DL-tartaric acid (C4H6O6), obtained by liquid-assisted grinding, was solved by powder X-ray diffraction (PXRD). The high-resolution PXRD pattern of this new phase was recorded at room temperature thanks to synchrotron experiments at the European Synchrotron Radiation Facility (Grenoble, France). The starting structural model was generated by a Monte-Carlo simulated annealing method. The final structure was obtained through Rietveld refinement and an energy minimization simulation was used to estimate the H-atom positions. The stability of the proposed structure as a function of temperature was also assessed from molecular dynamics simulations. The symmetry is monoclinic (space group P21/c) and contains eight molecules per unit cell, namely, four DL-tartaric acid and four carbamazepine molecules.

A novel edge rewiring strategy for tuning structural properties in networks

Synthetic networks can be generated to mimic the dynamics and evolution of complex interconnected systems in real world. Many network models have been established based on various structure and topological characteristics, such as degree distribution, clustering coefficient, mixing parameter, etc. These generated network models can serve as null models in hypothesis testing to assess nontrivial results about real world data in terms of statistical significance and generality. Therefore, researchers have actively pursued the development of network generation models with some given topological characteristics. So far, Standard Monte Carlo method and Simulated Annealing method are popular to adjust the clustering coefficient and average path length of the existing networks. However, these methods require a large number of calculations and are easy to fall into local extremes, which might limit the adjusting range of the algorithm. In order to reduce the amount of calculation and expand the range of adjustment, we propose a local structure based edge rewiring method to adjust the clustering coefficient and average path length of the network. By selecting of an appropriate local neighborhood of the node, we compute the ‘local’ clustering coefficient and ‘local’ average path length on the “local neighborhood”, and then calculating cost in each adjusting iteration is greatly reduced. Focusing on the “local neighborhood” strategy helps the algorithm escape from local extreme. Therefore, our edge rewiring strategy provides a border adjustment range of clustering coefficient and average path length in reasonable computing time. Experiment results show that our edge rewiring strategy can provide a boarder adjusting range for clustering coefficient and average path length than standard Monte Carlo method and the Simulated Annealing method under the same computation condition.

Structure determination of phase II of the antifungal drug griseofulvin by powder X-ray diffraction.

Two new crystalline polymorphs of the widely used antifungal drug griseofulvin (phases II and III), which originate from the crystallization of the melt, have been detected recently. The crystal structure of phase II of griseofulvin {systematic name: (2S,6'R)-7-chloro-2',4,6-trimethoxy-6'-methyl-3H,4'H-spiro[1-benzofuran-2,1'-cyclohex-2-ene]-3,4'-dione}, C17H17ClO6, has been solved by powder X-ray diffraction (PXRD). The PXRD pattern of this new phase was recorded at room temperature using synchrotron radiation. The starting structural model was generated by a Monte Carlo simulated annealing method. The final structure was obtained through Rietveld refinement with soft restraints for interatomic bond lengths and angles, except for the aromatic ring, where a rigid-body constraint was applied. The symmetry is orthorhombic (space group P212121) and the asymmetric unit contains two molecules.

Pauli structures arising from confined particles interacting via a statistical potential

There have been suggestions that the Pauli exclusion principle alone can lead a non-interacting (free) system of identical fermions to form crystalline structures dubbed Pauli crystals. Single-shot imaging experiments for the case of ultra-cold systems of free spin-polarized fermionic atoms in a two-dimensional harmonic trap appear to show geometric arrangements that cannot be characterized as Wigner crystals. This work explores this idea and considers a well-known approach that enables one to treat a quantum system of free fermions as a system of classical particles interacting with a statistical interaction potential. The model under consideration, though classical in nature, incorporates the quantum statistics by endowing the classical particles with an effective interaction potential. The reasonable expectation is that possible Pauli crystal features seen in experiments may manifest in this model that captures the correct quantum statistics as a first order correction. We use the Monte Carlo simulated annealing method to obtain the most stable configurations of finite two-dimensional systems of confined particles that interact with an appropriate statistical repulsion potential. We consider both an isotropic harmonic and a hard-wall confinement potential. Despite minor differences, the most stable configurations observed in our model correspond to the reported Pauli crystals in single-shot imaging experiments of free spin-polarized fermions in a harmonic trap. The crystalline configurations observed appear to be different from the expected classical Wigner crystal structures that would emerge should the confined classical particles had interacted with a pair-wise Coulomb repulsion.

Domain wall structure in metals: A new approach to an old problem

The Monte Carlo Simulated Annealing (MCSA) method is used for performing micromagnetic simulations, in particular the determination of the domain wall structure originated from the energy’s minimization of known micromagnetic hamiltonians. Beside the new theoretical approach, we also discuss the influence of different models for the exchange energy on the wall structure. It was found that the existence of long range exchange, like the RKKY interactions, can significantly affects the domain wall width when compared to the results obtained for the typical Heisenberg like exchange, whose range is restricted to the nearest neighbors. The calculations also indicate that especially for phases with high magnetocrystalline anisotropy the modeling should be performed at atomistic level or, in other words, the Bloch wall continuum model is not valid.

Monte Carlo methods used in inverted hexagonal lipid phase and in simulations of thermally fluctuating lipid vesicles

Two different uses of Monte Carlo methods in soft matter physics are presented in the following work. Firstly, the Monte Carlo simulated annealing is used to minimize the elastistic energy of the inverted hexagonal phase (HII) optimal geometry. We will do a brief overview on the mechanics of the HII lipid phase. In our model the expression for the lipid monolayer free energy consists of two energy contributions: the bending energy which involves also a deviatoric term, and the interstitial energy which describes the deformation energy due to stretching of the phospholipid molecule chains. On the basis of the derived expression for the lipid monolayer free energy, we will theoretically predict optimal geometry and physical conditions for the stability of the inverted hexagonal phase. Using the Monte Carlo simulated annealing method, we will theoretically describe first steps in the LαHII phase transition. Another interesting subject investigated by means of Monte Carlo simulations are the thermal fluctuations of nearly spherical vesicles. The theoretical basis of this analysis was done by Milner and Safran (Phys Rev A 36(9):4371–4379, 1987. doi:10.1103/PhysRevA.36.4371) that uses the mean field approximation. In this work we will show the application of the Monte Carlo simulations and show the correlation between the time mean simulated thermal fluctuations decomposed into spherical harmonics and the bending stiffness in 2-dimensional and 3-dimensional space.

Simulation Study on the Coil‐Globule Transition and Surface Adsorption of HP Chains

The coil‐globule transition of short hydrophobic‐polar (HP) chains, composed of 24 hydrophilic monomers and 24 polar monomers, in solution and on hydrophobic surface and the adsorption of the HP chain on hydrophobic surface are simulated. The coil‐globule transition point of the HP chain is dependent on sequence of chain but is roughly independent of the surface adsorption strength. Whereas the critical adsorption point of the HP chain is roughly independent of sequence. In addition, the lowest energy states can be obtained for the HP chain in solution or on surface by Monte Carlo simulated annealing method. Results show that the statistical conformation is strongly dependent on the intrachain H‐H attraction strength and the surface adsorption strength. image

Theoretical investigation of fluorination effect on the charge carrier transport properties of fused anthra-tetrathiophene and its derivatives

The crystal structures of known anthra-tetrathiophene (ATT) and its three fluorinated derivatives (ATT1, ATT2 and ATT3) were predicted by the Monte Carlo-simulated annealing method with the embedded electrostatic potential (ESP) charges. The most stable crystal structures were further optimized by the density functional theory with the dispersion energy (DFT-D) method. In addition, the effect of the electron-withdrawing fluorine atoms on the molecular geometry, molecular stacking, electronic and transport properties of title compounds were investigated by the density functional theory and the incoherent charge-hopping model. The calculated results show that the introduction of fluorine atoms does not affect the molecular planarity but decreases the HOMO-LUMO gap, which is beneficial to electron injection and provides more charge carrier stabilization. The improved electron mobility from ATT to ATT3 is attributed to the favorable molecular packing with strong π–π interaction and the short stacking distance. ATT2 and ATT3 exhibit remarkable angular dependence of mobilities and anisotropic behaviors. The band structures reveal that all the paths with larger transfer integrals are along the directions of large dispersions in the valence band (VB) and conduction band (CB). ATT3 has the largest electron mobility (0.48 cm2V−1s−1) among the four compounds, indicating that fluorination is an effective approach to improve electron transport.

Theoretical design of benzo[1,2-b:3,4-b′:5,6-b′′]tristhianaphthene and its derivatives as high performance organic semiconductors

In order to probe the effects of substituents (F and CN) attached to benzo[1,2-b:3,4-[Formula: see text]:5,6-[Formula: see text]]tristhianaphthene (BTTP) on their charge carrier transport properties, we investigated the characteristics of molecular structures and charge transport properties of BTTP and its derivatives (BTTP1, BTTP2, BTTP3, BTTP4, and BTTP5). Six crystal structures were predicted by the Monte Carlo-simulated annealing method with the embedded electrostatic potential charges method. Even a subtle change of geometrical structures may result in a great change of the reorganization energy. With increasing numbers of substituted fluorine atoms, the reorganization energy of the BTTP derivative increases, which is disadvantageous to the electron transport. In contrast, the attachment of the electron-withdrawing cyano groups to BTTP decreases the reorganization energy and raises the electron affinity, which is beneficial to electron injection and charge carrier stabilization. The introduction of cyano groups also results in an enhancement of [Formula: see text]–[Formula: see text] interaction and leads to an increase in the transfer integrals. Among the six compounds, the novel compound BTTP4 has the largest electron mobility (1.154[Formula: see text]cm[Formula: see text]) on account of its larger transfer integral and smaller reorganization energy, indicating that BTTP4 is a promising high-performance n-type organic semiconductor and worth to synthesize. The analysis of angular-resolution anisotropic mobilities for the BTTP and BTTP4 shows that it is helpful to control the orientations of the conducting channels for a better charge transport efficiency. This work provides a rational strategy for the design of high-performance n-type organic semiconductors from molecule to crystal structure.

Identification of an Endogenous Allosteric Modulator's Binding Site at the Human Cannabinoid-1 Receptor, Using Forced-Biased Metropolis Monte Carlo Simulated Annealing Method (MMC) and Molecular Dynamics

The CB1 endogenous, positive allosteric modulator, lipoxin A4, increases the equilibrium binding and efficacy of CP55,940 and anandamide (orthosteric agonists), yet has no significant effect when applied alone. We have reported that ORG27569 (a negative CB1 allosteric modulator) binds in the THM3/6/7 region (Shore et al., JBC, 2013); here, ORG27569 sterically blocks movements of the second and third extracellular (EC) loops, as well as those of TMH6, that are necessary for G protein-mediated signaling. Because lipoxin A4 is a positive allosteric modulator, one would not expect it to sterically block these functionally-important conformational changes.To identify lipoxin A4's binding site(s) at CB1, we used the Forced-Biased Metropolis Monte Carlo simulated annealing program, MMC. In this method, lipoxin A4 was separated into 4 fragments. Four MMC runs were performed, in which our in silico CB1 receptor model (with CP55,940 docked) was immersed in a box filled with copies of one of these fragments. The system chemical potential was then systematically annealed, causing only those fragment copies with the best free energy of binding to the protein to remain. MMC results were used as a starting point for Glide automated-docking studies of lipoxin-A4. Molecular dynamics simulations were also performed to study how lipoxin A4 may enter CB1. Here, CB1 was placed in a fully hydrated, POPC bilayer; 14 lipoxin A4 molecules (7 per leaflet) were placed with random orientations, around the receptor. Altogether, these results suggest that lipoxin A4 may bind in the TMH3/6/7, extending extracellularly. Lipoxin A4 may act as a positive allosteric modulator by forming electrostatic interactions with the EC-1 and EC-3 loops, promoting an active loop conformations. [Support: RO1 DA003934 and KO5 DA021358 (PHR)]

Molecule‐adapted basis sets optimized with a quantum Monte Carlo method

The Monte Carlo simulated annealing method is adapted to optimize correlated Gaussian‐type functions in nonrelativistic molecular environments. Starting from an atom‐centered atomic Gaussian basis set, the uncontracted functions are reoptimized in the molecular environments corresponding to the H2O, CN−, N2, CO, BF, NO+, CO2, and CS systems. These new molecular adapted basis sets are used to calculate total energies, harmonic vibrational frequencies, and equilibrium geometries at a correlated level of theory. The present methodology is a simple and effective way to improve molecular correlated wave functions, without the need to enlarge the molecular basis set. Additionally, this methodology can be used to generate hierarchical sequences of molecular basis sets with increasing size, which are relevant to establish complete basis set limits. © 2014 Wiley Periodicals, Inc.

Identification of an Endogenous Allosteric Modulator's Binding Site at the Human Cannabinoid-1 Receptor, using the Forced-Biased Metropolis Monte Carlo Simulated Annealing Method (Mmc)

The CB1 endogenous, positive allosteric modulator, lipoxin A4, increases the equilibrium binding and efficacy of CP55,940 and anandamide (orthosteric agonists), yet has no significant effect when applied alone. Unlike ORG27569 (a negative allosteric modulator of CB1), lipoxin A4 does not significantly displace SR141716A (an orthosteric inverse agonist) in equilibrium binding assays. In addition, we have previously reported that ORG27569's binds in the THM3/TMH6/TMH7 region (Shore et al., ICRS, 2012); at this site, ORG27569 sterically blocks important movements of the second and third extracellular loops, as well as those of TMH6, that are necessary for G protein-mediated signaling. Because lipoxin A4 is a positive allosteric modulator, one would not expect it to sterically block these functionally-important conformational changes. Together, these results may suggest that lipoxin A4 binds in a topographically different region of CB1 than ORG27569. To identify lipoxin A4's binding site(s) at CB1, we are using the Forced-Biased Metropolis Monte Carlo simulated annealing program, MMC. In this method, lipoxin A4 was separated into 4 fragments. Four MMC runs are currently being performed, in which our in silico CB1 receptor model (with CP55,940 docked) was immersed in a box filled with copies of one of these fragments. The system chemical potential is then systematically annealed, causing only those fragment copies with the best free energy of binding to the protein surface to remain. Ultimately, analysis of these four MMC runs will suggest region(s) in which all four fragments cluster in the correct spatial proximity, thus suggesting a possible binding site(s). [Support: RO1 DA003934 and KO5 DA021358 (PHR)]

Structure determination of the crystalline phase ofn-butanol by powder X-ray diffraction and study of intermolecular associations by Raman spectroscopy

X-ray powder diffraction patterns of n-butanol at 110 K and the isothermal transformation above the glass transition temperature of the supercooled liquid into the glacial state were recorded with a laboratory diffractometer. The starting structural model of the crystalline stable phase was found by a Monte-Carlo simulated annealing method. The final structure was obtained through Rietveld refinements with soft restraints on the interatomic bond lengths and angles. The cell is triclinic with space group P1 and contains two molecules. The width of the Bragg peaks is interpreted by a phenomenological microstructural approach in terms of anisotropic strain effects. The study of the hydrogen bonds by Raman spectroscopy shows the existence of two main kinds of hydrogen bonds in the crystal, in agreement with the structure obtained by diffraction. The glacial state resulting from an abortive crystallization is composed of microcrystallites of the stable phase coexisting with non-transformed supercooled liquid. Crystalline features of the glacial state were determined as closely connected to the microstructural description of the crystal, leading to information about the origin of the glacial state.

Structure determination of the crystalline phase ofn-butanol by powder X-ray diffraction and study of intermolecular associations by Raman spectroscopy

X-ray powder diffraction patterns of n-butanol at 110 K and the isothermal transformation above the glass transition temperature of the supercooled liquid into the glacial state were recorded with a laboratory diffractometer. The starting structural model of the crystalline stable phase was found by a Monte-Carlo simulated annealing method. The final structure was obtained through Rietveld refinements with soft restraints on the interatomic bond lengths and angles. The cell is triclinic with space group P1 and contains two molecules. The width of the Bragg peaks is interpreted by a phenomenological microstructural approach in terms of anisotropic strain effects. The study of the hydrogen bonds by Raman spectroscopy shows the existence of two main kinds of hydrogen bonds in the crystal, in agreement with the structure obtained by diffraction. The glacial state resulting from an abortive crystallization is composed of microcrystallites of the stable phase coexisting with non-transformed supercooled liquid. Crystalline features of the glacial state were determined as closely connected to the microstructural description of the crystal, leading to information about the origin of the glacial state.

Topological defects in the buckling of elastic membranes

We investigate the effects of topological defects on the low-energy shapes of single-component two-dimensional elastic membranes with spherical topology. The membrane is described as a closed, triangulated two-dimensional manifold embedded in three-dimensional space using a dynamic triangulation model, thus allowing the creation of topological defects. Low-energy structures and connectivities are explored using a Monte Carlo simulated annealing method while also constraining the internal volume of the membrane to simulate incompressible contents within the membrane, such as in colloidosomes and viruses. We find that since the volume constraint partially suppresses the buckling transition such that the buckled icosahedral shape has a reduced asphericity, defect scars are favorable over a larger range of elastic parameters of the membrane compared with systems having no constraint on volume.

Structure determination of L-arabinitol by powder X-ray diffraction

Powder X-ray diffraction patterns of the commercial phase of L-arabinitol were recorded with a laboratory diffractometer. The starting structural model was found by a Monte-Carlo simulated annealing method. The final structure was obtained through Rietveld refinements with soft restraints on the interatomic bond lengths and bond angles. H atoms of hydroxyl groups were localized by minimization of the crystalline energy. The cell is triclinic with the space group P1 and contains two molecules. The crystalline cohesion is achieved by an important network of O-H···O hydrogen bonds.

In silico identification of human pregnane X receptor activators from molecular descriptors by machine learning approaches

In the current study, computational models for hPXR activators and hPXR non-activators were developed using support vector machine (SVM), k-nearest neighbor (k-NN), and artificial neural networks (ANN) algorithms. 73 molecular descriptors used for hPXR activator and hPXR non-activator prediction were selected from a pool of 548 descriptors by using a multi-step hybrid feature selection method combining Fischer's score and Monte Carlo simulated annealing method. The y-scrambling method was used to test if there is a chance correlation in the developed SVM model. In the meantime, five-fold cross validation of these machine learning methods results in the prediction accuracies of 87.2–92.5% for hPXR activators and 73.8–87.8% for hPXR non-activators, and the prediction accuracies for external test set are 93.8–95.8% for hPXR activators and 86.7–92.8% for hPXR non-activators. Our study suggested that the tested machine learning methods are potentially useful for hPXR activators identification.

Identification of DNA adduct formation of small molecules by molecular descriptors and machine learning methods

In this study, we developed new computational DNA adduct prediction models by using significantly more diverse training data-set of 217 DNA adducts and 1024 non-DNA adducts, and applying five machine learning methods which include support vector machine (SVM), k-nearest neighbour, artificial neural networks, logistic regression and continuous kernel discrimination. The molecular descriptors used for DNA adduct prediction were selected from a pool of 548 descriptors by using a multi-step hybrid feature selection method combining Fischer-score and Monte Carlo simulated annealing method. Some of the selected descriptors are consistent with the structural and physicochemical properties reported to be important for DNA adduct formation. The y-scrambling method was used to test whether there is a chance correlation in the developed SVM model. In the meantime, fivefold cross-validation of these machine learning methods results in the prediction accuracies of 64.1–82.5% for DNA adducts and 95.1–97.6% for non-DNA adducts, and the prediction accuracies for external test set are 78.2–100% for DNA adducts and 92.6–98.4% for non-DNA adducts. Our study suggested that the tested machine learning methods are potentially useful for DNA adducts identification.