stk: A python toolkit for supramolecular assembly

A tool for the automated assembly, molecular optimization and property calculation of supramolecular materials is presented. stk is a modular, extensible and open‐source Python library that provides a simple Python API and integration with third party computational codes. stk currently supports the construction of linear polymers, small linear oligomers, organic cages in multiple topologies and covalent organic frameworks (COFs) in multiple framework topologies, but is designed to be easy to extend to new, unrelated, supramolecules or new topologies. Extension to metal–organic frameworks (MOFs), metallocycles or supramolecules, such as catenanes, would be straightforward. Through integration with third party codes, stk offers the user the opportunity to explore the potential energy landscape of the assembled supramolecule and then calculate the supramolecule's structural features and properties. stk provides support for high‐throughput screening of large batches of supramolecules at a time. The source code of the program can be found at https://github.com/supramolecular-toolkit/stk . © 2018 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.     

PepFun: Open Source Protocols for Peptide-Related Computational Analysis

Peptide research has increased during the last years due to their applications as biomarkers, therapeutic alternatives or as antigenic sub-units in vaccines. The implementation of computational resources have facilitated the identification of novel sequences, the prediction of properties, and the modelling of structures. However, there is still a lack of open source protocols that enable their straightforward analysis. Here, we present PepFun, a compilation of bioinformatics and cheminformatics functionalities that are easy to implement and customize for studying peptides at different levels: sequence, structure and their interactions with proteins. PepFun enables calculating multiple characteristics for massive sets of peptide sequences, and obtaining different structural observables derived from protein-peptide complexes. In addition, random or guided library design of peptide sequences can be customized for screening campaigns. The package has been created under the python language based on built-in functions and methods available in the open source projects BioPython and RDKit. We present two tutorials where we tested peptide binders of the MHC class II and the Granzyme B protease.     

Thermodynamic coefficients of ideal Fermi gas

We present analytical formulae for the first and second derivatives of the Helmholtz free energy of non-relativistic ideal Fermi gas. Important thermodynamic quantities such as heat capacity, sound velocity, heat capacity ratio, and others are explicitly expressed through the derivatives. We demonstrate correct ideal Boltzmann gas and low-temperature Fermi gas asymptotes and derive corrections to thermodynamic functions for these limiting cases. Numerical computations of thermodynamic properties of ideal Fermi gas can be accurately performed using the developed freely available Python module ifg .     

molSimplify: A toolkit for automating discovery in inorganic chemistry

We present an automated, open source toolkit for the first‐principles screening and discovery of new inorganic molecules and intermolecular complexes. Challenges remain in the automatic generation of candidate inorganic molecule structures due to the high variability in coordination and bonding, which we overcome through a divide‐and‐conquer tactic that flexibly combines force‐field preoptimization of organic fragments with alignment to first‐principles‐trained metal‐ligand distances. Exploration of chemical space is enabled through random generation of ligands and intermolecular complexes from large chemical databases. We validate the generated structures with the root mean squared (RMS) gradients evaluated from density functional theory (DFT), which are around 0.02 Ha/au across a large 150 molecule test set. Comparison of molSimplify results to full optimization with the universal force field reveals that RMS DFT gradients are improved by 40%. Seamless generation of input files, preparation and execution of electronic structure calculations, and post‐processing for each generated structure aids interpretation of underlying chemical and energetic trends. © 2016 Wiley Periodicals, Inc.     

CCSfind: A tool for chemically informed LC-IM-MS database building

In addition to providing critical knowledge of the accurate mass of ions, ion mobility-mass spectrometry (IM-MS) delivers complementary data relating to the conformation and size of ions in the form of an ion mobility spectrum and derived parameters, namely, the ion's mobility (K) and the IM-derived collision cross section (CCS). However, the maximum amount of information obtained in IM-MS measurements is not currently transferred into analytical databases including the full mobility spectra (CCS distributions) as well as capturing of additional ion species (e.g., adducts) into the same compound entry. We introduce CCSfind, a new tool for building comprehensive databases from experimental IM-MS measurements of small molecules. CCSfind allows predicted ion species to be chosen for input chemical formulae, which are then targeted by CCSfind after parsing open source mzML input files to provide a unified set of results within a single data processing step. CCSfind can handle both chromatographically separated isomers and IM separation of isomeric ions (e.g., “protomers” or conformers of the same ion species) with simple user control over the output for new database entries in SQL format. Files of up to 1 GB can be processed in less than 2 min on a desktop computer with 32 GB RAM with computational time scaling linearly with the size of the input mzML file or the number of input molecular formulae. Results are manually reviewed, annotated with experimental settings, before committing the database where the full dataset can be retrieved.     

缅甸蟒蛇腹鳞表面的摩擦机理及摩擦各向异性研究

采用原子力显微镜观察缅甸蟒蛇腹鳞表面的微观结构,采用UMT-2型摩擦磨损试验机研究不同载荷及运动方向的腹鳞表面的宏观摩擦各向异性,建立了摩擦运动的接触模型,分析了腹鳞表面的磨损机理.结果表明:腹鳞表面的微观结构由指状微突体和板结构部分周期排列而成,其结构可用9个特征参数定量描述;腹鳞表面摩擦力由分子作用力、表面微突体的犁沟力、楔形作用力以及材料弹性滞后共同引起;腹鳞表面的摩擦系数在0.07左右并与运动方向有关,摩擦系数随载荷增加而减小;后向运动及左、右侧向运动时摩擦系数基本相等,比前向运动时高33%左右;腹鳞表面微突体不同方向上倾斜角度的差异是引起摩擦各向异性的主要原因.研究结果对仿生制造摩擦各向异性表面提供实验依据.     

基于Python的运营商风险操作分析工具

运营商在网络风险操作之前需要统计受影响的网络设备和用户,并通知相关人员。探讨了人工割接分析的方法和缺陷,并从分析流程出发,通过基于PYTHON的pexpect、urllib、pandas等模块,设计并实现了一种网络设备配置收集分析,专线用户Web接口提取的风险操作分析工具。     

用Python语言分析银行自助设备交易流水文件

无人值守银行自助设备的运行状况是一项非常重要的内容,维护者必须能够及时分析并处理设备所出现的各种故障。自助设备交易流水文件详细记录了设备的运行状况,为了分析该文件,基于＂-3前流行的Python语言,并配合wxPython GUI包为软件开发平台,开发了自助取款设备运行状况分析程序,该软件具有开发周期短、界面友好、操作简单的优点。     

Performance of group additivity methods for predicting the stability of uranyl complexes

Herein, we investigated the viability of two group additivity methods for predicting Gibbs energies of a set of uranyl complexes. In first place, we proved that both density functional theory (DFT)-based methods and Serezhkin's stereoatomic model provide equivalent answers in terms of stability. Moreover, we proposed a novel methodology based on Mayer's population analysis for estimating Serezhkin's empirical parameters theoretically. On the other hand, we showed that Cheong and Persson linear algebra methodology can be successfully applied to uranyl complexes, and analyzed its performance in connection with the chemical nature of the compounds employed in the model.     

一种TD-LTE终端射频一致性自动测试系统的设计与实现

介绍了自动测试系统与TD-LTE的发展现状,针对当前TD-LTE终端测试自动化的需求,对射频一致性自动测试进行了分析,阐述了自动测试系统的框架结构与基本功能,介绍了系统的基本工作流程与各功能模块,采用面向对象的思想设计了自动测试管理系统,利用Python完成综测仪相关控制的功能实现。对数据卡型终端进行了实际测试,系统在实际使用中可以较好的完成测试工作。