Schrödinger Equation Solutions for the Central Field Power Potential Energy I. V(r) = V 0(r/a 0)2ν−2, ν ≥ 1

The solution of a generalized non-relativistic Schrödinger equation with radial potential energy V(r)=V ₀(r/a ₀)^2–2 is presented. After reviewing the general properties of the radial ordinary differential equation, power series solutions are developed. The Green's function is constructed, its trace and the trace of its first iteration are calculated, and the ability of the traces to provide upper and lower bounds for the ground eigenvalue is examined. In addition, WKB-like solutions for the eigenvalues and eigenfunctions are derived. The approximation method yields valid eigenvalues for large quantum numbers (Rydberg states).     

Modified AutoDock for accurate docking of protein kinase inhibitors

Protein kinases are an important class of enzymes controlling virtually all cellular signaling pathways. Consequently, selective inhibitors of protein kinases have attracted significant interest as potential new drugs for many diseases. Computational methods, including molecular docking, have increasingly been used in the inhibitor design process [1]. We have considered several docking packages in order to strengthen our kinase inhibitor work with computational capabilities. In our experience, AutoDock offered a reasonable combination of accuracy and speed, as opposed to methods that specialize either in fast database searches or detailed and computationally intensive calculations.However, AutoDock did not perform well in cases where extensive hydrophobic contacts were involved, such as docking of SB203580 to its target protein kinase p38. Another shortcoming was a hydrogen bonding energy function, which underestimated the attraction component and, thus, did not allow for sufficiently accurate modeling of the key hydrogen bonds in the kinase-inhibitor complexes.We have modified the parameter set used to model hydrogen bonds, which increased the accuracy of AutoDock and appeared to be generally applicable to many kinase-inhibitor pairs without customization. Binding to largely hydrophobic sites, such as the active site of p38, was significantly improved by introducing a correction factor selectively affecting only carbon and hydrogen energy grids, thus, providing an effective, although approximate, treatment of solvation.     

Comparison of the Dynamics of Water Molecules in Crystals of Proton-Ordered Ice IX and Its Proton-Disordered Analog III

A computer simulation of proton-ordered ice IX and its proton-disordered analog III (768 molecules, 90 K) was carried out by the molecular dynamics method using Poltev–Malenkov's potential. For ice IX, the differences in the dynamic characteristics of molecules with O(1) and O(2) are much wider than those in the case of ice III. The libration spectrum of ice IX has a number of distinct acute peaks, and the spectrum of ice III is strongly smoothed. These peculiarities are explained by the proton ordering of ice IX and disordering of ice III. The latter is responsible for the great differences in the short- and especially long-range environment of water molecules in ice crystals and hence for the presence of many molecules with different dynamic characteristics. Thus averaging over a large number of different vibrational spectra of molecules leads to a smoothed total spectrum in the case of the proton-disordered crystal modification of ice.     

NEMCA effect: why are the work function changes of the gas exposed catalyst-electrode surface one-to-one related to the changes in the catalyst working electrode potential?

In the present work, an important point concerning the NEMCA effect is addressed. We analyse the reasons why the changes in the work function of the gas exposed catalyst-electrode surface are one to one related to the changes in the catalyst working electrode potential E with respect to a reference electrode. It is concluded that this is due to the unique properties of the catalyst/solid electrolyte interface: the structure of the double layer in this region is very different from that in liquid electrolytes, being the potential difference at this interface mainly determined by the specific adsorption of the mobile species in the solid electrolyte.

5-硝基-1-氢-四唑分子热分解反应机理的密度泛函理论研究

利用密度泛函理论研究了5-硝基-1-氢-四唑分子热分解的反应机理。首先用 B3LYP/6-31G（d）方法优化反应中反应物、过渡态、中间体以及产物的几何构型， 通过振动分析得到零点能校正值并确认反应的过渡态。此外，对各个构型作了 CCSD（T）/6-31G（d,p）水平下的单点计算。报道了三条可能的反应途径，即直接 开环途径和质子转移途径；其中N（1）-N（2）键断裂直接开环的机理与文献报道 一致；而涉及质子转移的反应途径则是一个新的发现；另一条关于N（4）-C（5） 键断裂直接开环的途径由于能垒较高，因此发生的几率较小。     

Two-beam interference detection of the changes in fibre structural parameters during low drawing process

A Pluta polarizing interference microscope with a fibre stretching device attached was used to detect the changes in molecular structure that occur during the fibre cold drawing process. Fibres drawn with low draw ratios show different types of deformation mechanisms. The interference patterns recorded at different draw ratios are used to relate the deformation mechanisms with the measured structural parameters. Some optical parameters are measured such as; refractive indices nand n birefringence n, the polarizability per unit volume , the orientation distribution function f(θ), the angle θ between the stretching direction and the chain axis, and the angle θ_m which the transition dipole moment of the molecular species makes with the molecular axis (chain axis). Three polymeric fibres (Polyethylene terephthalate PET, Polypropylene PP and Polyamide PA) were used in this study and their interferograms are illustrated.     

A deep learning ensemble for function prediction of hypothetical proteins from pathogenic bacterial species

Protein function prediction is a crucial task in the post-genomics era due to their diverse irreplaceable roles in a biological system. Traditional methods involved cost-intensive and time-consuming molecular biology techniques but they proved to be ineffective after the outburst of sequencing data through the advent of cost-effective and advanced sequencing techniques. To manage the pace of annotation with that of data generation, there is a shift to computational approaches which are based on homology, sequence and structure-based features, protein-protein interaction networks, phylogenetic profiles, and physicochemical properties, etc. A combination of these features has proven to be promising for protein function prediction in terms of improving prediction accuracy. In the present work, we have employed a combination of features based on sequence, physicochemical property, subsequence and annotation features with a total of 9890 features extracted and/or calculated for 171,212 reviewed prokaryotic proteins of 9 bacterial phyla from UniProtKB, to train a supervised deep learning ensemble model with the aim to categorize a bacterial hypothetical/unreviewed protein’s function into 1739 GO terms as functional classes. The proposed system being fully dedicated to bacterial organisms is a novel attempt amongst various existing machine learning based protein function prediction systems based on mixed organisms. Experimental results demonstrate the success of the proposed deep learning ensemble model based on deep neural network method with F1 measure of 0.7912 on the prepared Test dataset 1 of reviewed proteins.     

(ClAlNH)n簇合物的结构与稳定性

用量子化学从头算方法（HF／6－31G）和密度泛函理论（DFT）的B3LYP方法，以6－31G标准基组加一个极化函数，对（ClAlNH)n(n=1-10)簇合物的几何构型，电子结构和红外光谱进行了优化，并讨论了聚合反应（ClAlNH)m→(ClAlNH)n的热力学效应，结果表明，（ClAlNH)n系列簇合物的基态稳定结构为Cs(n=1),D2h(n=2),D3h(n=3),Td(n=4),Cs(n=5),D3d(n=6),Cs(n=7),S4(n=8),D3h(n=9),C2h(n=10,n=2,4,6,8,10等偶数对应的（ClAlNH)n簇化合物的结构比n等于奇数量更稳定。     

Segmentation of Heteropolymer Sequences Specifying Subsequences with Different Composition and Statistical Properties

We have studied the segmentation of two‐letter AB heterosequences composed of subsequences with different composition and distribution of A and B monomer units along the chain. Our approach is based on the segmentation function S(k) introduced in the present work and on the Jensen–Shannon divergence measure determined with respect to the probabilities of the lengths of uniform blocks of A and B monomer units. It is shown that the function S(k) is extremely sensitive to the sequence statistics. Even visual analysis of S(k) allows judgment on some features of sequence statistics. In particular, function S(k) is constant for random copolymers, it is an oscillating function for random block copolymers and shows monotonic growth up to some constant value for proteinlike copolymers. However, due to significant fluctuations observed for short sequences, the function S(k) can be effectively used only for segmentation of a heterosequence composed of very long subsequences. On the other hand, we find that the Jensen–Shannon divergence measure does not allow one to judge the type of statistics, but is extremely efficient for segmentation of a heterosequence. Therefore, the two introduced functions, being mutually complementary, provide an effective approach for recognizing and segmentation of heterosequences. As an example, the methods developed are applied for concatenating sequences of different proteins.

Segmentation function S(k, l, x) as a function of parameter k and starting number x of “window” for a sequence composed of elastin and ribonuclease sequences.