Using random forest to classify T-cell epitopes based on amino acid properties and molecular features

T-lymphocyte (T-cell) is a very important component in human immune system. T-cell epitopes can be used for the accurately monitoring the immune responses which activation by major histocompatibility complex (MHC), and rationally designing vaccines. Therefore, accurate prediction of T-cell epitopes is crucial for vaccine development and clinical immunology. In current study, two types peptide features, i.e., amino acid properties and chemical molecular features were used for the T-cell epitopes peptide representation. Based on these features, random forest (RF) algorithm, a powerful machine learning algorithm, was used to classify T-cell epitopes and non-T-cell epitopes. The classification accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and area under the curve (AUC) values for proposed method are 97.54%, 97.22%, 97.60%, 0.9193, and 0.9868, respectively. These results indicate that current method based on the combined features and RF is effective for T-cell epitopes prediction.     

Synthesis and tailoring phase behavior of mesogen jacketed liquid crystalline copolymers based on 2, 5‐bis[(4‐alkoxyphenyl)oxycarbonyl]styrenes

Based on 2, 5‐bis[(4‐alkoxyphenyl)oxycarbonyl]styrenes (M‐OCm, m is the number of the carbons of alkyl tails, m = 1, 4, and 18), three series of binary copolymers with high‐molecular weights, {poly(M‐OC1‐co‐M‐OC4), poly(M‐OC1‐co‐M‐OC18), and poly(M‐OC4‐co‐M‐OC18)} have been prepared via free‐radical polymerization. The random nature of the copolymers was expected on the basis of the assumed similar reactivities because of the analogous monomers. The phase behaviors of copolymers were studied by DSC, POM, and one‐dimensional wide‐angle X‐ray diffraction. The results showed that liquid crystalline (LC) phase structures of copolymers, containing smectic phase, reentrant isotropic phase, columnar phase. and isotropic phase, were strongly depended on the composition and the alkyl length due to the competing among the steric effect, the microphase separation and the driving force of the entropy. When one of them occupied a dominant position, the LC phase structure can be presented for the copolymers. Otherwise, the LC phase structure is lost despite the pair of corresponding homopolymers forming mesogenic structure. Therefore, through copolymerization, LC behavior of the mesogen‐jacketed liquid crystalline polymers can be greatly varied. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013, 51, 2804–2816     

Quasi‐random integration in quantum chemistry: Efficiency,stability, and application to the study of small atoms and molecules constrained in spherical boxes

This project consists of two parts. In the first part, a series of test calculations is performed to verify that the integrals involved in the determination of atomic and molecular properties by standard self‐consistent field (SCF) methods can be obtained through Halton, Korobov, or Hammersley quasi‐random integration procedures. Through these calculations, we confirm that all three methods lead to results that meet the levels of precision required for their use in the calculation of properties of small atoms or molecules at least at a Hartree–Fock level. Moreover, we have ensured that the efficiency of quasi‐random integration methods that we have tested is Halton=Korobov>Hammersley?pseudo‐random. We also find that these results are comparable to those yielded by ordinary Monte Carlo (pseudo‐random) integration, with a calculation effort of two orders of smaller magnitude. The second part, which would not have been possible without the integration method previously analyzed, contains a first study of atoms constrained in spherical boxes through SCF calculations with basis functions adapted to the features of the problem: Slater‐type orbitals (STOs) trimmed by multiplying them by a function that yields 1 for 0 < r < (R‐δ), polynomial values for (R‐δ) < r < R and null for r > R, R being the radius of the box and δ a variationally determined interval. As a result, we obtain a equation of state for electrons of small systems, valid just in the limit of low temperatures, but fairly simple. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

Linear regression model of DNA sequences and its application

We constructed six new models to analyze the DNA sequences. First, we regarded a DNA primary sequence as a random process in t and gave three ways to define nucleotides' random distribution functions. We extracted some parameters from the linear model and analyzed the changes of the nucleotides' distributions. In order to facilitate the comparison of DNA sequences, we proposed two ways to measure their similarities. Finally, we compared the six models by analyzing the similarities of the DNA primary sequences presented in Table 1 and selected the optimal one.     

Analytical excited state forces for the time-dependent density-functional tight-binding method

An analytical formulation for the geometrical derivatives of excitation energies within the time-dependent density-functional tight-binding (TD-DFTB) method is presented. The derivation is based on the auxiliary functional approach proposed in [Furche and Ahlrichs, J Chem Phys 2002, 117, 7433]. To validate the quality of the potential energy surfaces provided by the method, adiabatic excitation energies, excited state geometries, and harmonic vibrational frequencies were calculated for a test set of molecules in excited states of different symmetry and multiplicity. According to the results, the TD-DFTB scheme surpasses the performance of configuration interaction singles and the random phase approximation but has a lower quality than ab initio time-dependent density-functional theory. As a consequence of the special form of the approximations made in TD-DFTB, the scaling exponent of the method can be reduced to three, similar to the ground state. The low scaling prefactor and the satisfactory accuracy of the method makes TD-DFTB especially suitable for molecular dynamics simulations of dozens of atoms as well as for the computation of luminescence spectra of systems containing hundreds of atoms.     

Three-dimensional NMR Spectroscopy of organic molecules by random sampling of evolution time space and multidimensional Fourier transformation

In this communication we present the application of a new method, which enables one to acquire 3D NMR spectra in a reasonable time and preserves high resolution in indirectly detected domains. The new method is based on random distribution of time domain data points followed by Quaternion FT with respect to two time variables in one step.The experimental examples include three-dimensional spectra of strychnine in CDCl3, TOCSY-HSQC, COSY-HMBC, and the new technique proposed here: heteronuclear single quantum multiple bond correlation (HSQMBC). The obtained spectra are compared to those recorded at the same time employing the conventional acquisition scheme. We show that high-quality 3D spectra of organic compounds can be obtained in reasonable experimental time and that they are of great interest in cases when direct analysis of 2D spectra is difficult.     

Dissipative Particle Dynamics Simulations on the Self-Assembly of New Segmented Random-Block Copolymers in Selective Solvents

Dissipative particle dynamics simulation was applied to investigate the self-assembly of new segmented random-block copolymers (A-co-B)-b-B in selective solvents. The coarse-grained models of random-block copolymers were built. The effects of the composition of the copolymer, the interaction parameters, the volume fractions, as well as the ratio of hydrophilic particles to hydrophobic particles in the random segment, on the morphology of the aggregations were systematically investigated. The results showed that new segmented random-block copolymers (A-co-B)-b-B could self-assemble into rodlike micelle, spherical micelle and two-compartment micelle. Oval-shaped micelle and spherical micelle could be formed at different volume fractions. The simulation results provide an important reference to the design and synthesis of specific micelles.     

Application of SSA thermal fractionation and X‐ray diffraction to elucidate comonomer inclusion or exclusion from the crystalline phases in poly(butylene succinate‐ran‐butylene azelate) random copolymers

Poly(butylene succinate‐ran‐butylene azelate) random copolyesters were thermally fractionated by successive self‐nucleation and annealing (SSA). The samples before and after SSA were analyzed by differential scanning calorimetry (DSC) and X‐ray diffraction (WAXS and SAXS). WAXS results indicate that a small degree of comonomer inclusion is present in the crystalline phases that are formed in the copolymers depending on composition: a PBS‐like unit cell or/and a PBAz‐like unit cell, thus confirming the isodimorphic behavior of the samples. SSA on the other hand demonstrated that the degree of comonomer exclusion during crystallization is far larger than comonomer inclusion, as judged by the increase in fractionation degree with compositions leading to the pseudo‐eutectic point. Furthermore, WAXS, SAXS, and SSA results show that the isodimorphic behavior is not highly dependent on kinetic factors, as the degree of comonomer inclusion or exclusion in the samples was not significantly altered by SSA thermal fractionation, a thermal treatment that promotes annealing and molecular segregation of defects to the amorphous regions of the material. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 2346–2358     

Multi walled carbon nanotubes induced viscoelastic response of polypropylene copolymer nanocomposites: Effect of filler loading on rheological percolation

Polypropylene random copolymer nanocomposites having 0.2–7.0 vol% multi-walled carbon nanotubes (MWCNTs) were prepared via melt processing. Transmission electron microscopy (TEM) was employed to determine the nano scale dispersion of carbon nanotubes. Linear viscoelastic behavior of these nanocomposites was investigated using parallel plate rheometry. Incorporation of carbon nanotubes in the polymer matrix resulted in higher complex viscosity (η*), storage (G′) and loss modulus (G″) as compared to neat polymer, especially in the low-frequency region, suggesting a change from liquid to solid-like behavior in the nanocomposites. By plotting storage modulus vs. carbon nanotube loading and fitting with a power law function, the rheological percolation threshold in these nanocomposites was observed at a loading of ∼0.27 vol% of MWCNTs. However, electrical percolation threshold was reported at ∼0.19 vol% of MWCNTs loading. The difference in the percolation thresholds is understood in terms of nanotube connectivity with nanotubes and polymer chain required for electrical conductivity and rheological percolation.