计算(机)化学学科进展(2011-2013)

计算(机)化学已成为化学学科的重要组成部分,在理论计算、分子模拟、数据挖掘以及复杂体系分析中发挥了重要作用。本文总结了近年来化学信息学的研究进展,包括化学信息学方法、软件及数据库技术以及化学信息学在结构、性质、相互作用、反应机理,蛋白质及功能材料的性能研究,复杂体系化学数据分析中的应用。共引用参考文献78篇。     

化学计量学/信息学助推化学与分析测试科学研究范式转换

该文回顾了科学研究范式的形成并讨论了化学与分析测试科学的相关发展历程。实验科学向理论科学演进实际是现代科学的形成过程,对化学而言是一个困难的数学化进程,直到第三即计算科学范式形成,化学的现代科学地位才得以确定。分析化学或分析测试科学发展过程中遇到类似的问题,化学计量学/信息学在助推其完善分析化学“数学化”进程的同时,也能够挖掘更多有效信息。随着现代分析仪器的快速发展和数据海啸的到来,化学计量学/信息学作为成熟的化学学科分支和有力“武器”,正在协助并推动化学和分析测试科学步入第四即“数据密集型”的科学新范式。该文以作者实验室的研究工作为基础,论述了化学计量学/信息学助力推动化学与分析测试科学研究范式的转换过程中的相关进展,并对未来的研究动向进行了展望。     

第九届全国计算（机）化学学术会议（第一轮通知）

主办单位:中国化学会计算机化学专业委员会协办单位:化学生物传感与计量学国家重点实验室(湖南大学)承办单位:四川大学国际计算机化学包括化学信息学研究的发展方兴未艾,近几年来伴随着理论与计算化学、分子模拟与设计、数据挖掘技术,因特网资源综合利用以及化学计量学等领域的发展,取得了令世人瞩目的重要进展.我国的计算(机)化学包括化学信息学研究也伴随着这些学科的飞速进步得到快速发展,通过学科相互交叉、相互渗透,目前发展快速、成效显著,在某些研究方面接近或达到国际先进水平.为更好地总结、交流我国在计算(机)化学包括化学信息学…     

深度学习在化学信息学中的应用研究进展

在知识、数据、算法与算力的多重驱动下，深度学习不仅在计算机视觉、自然语言处理等研究领域取得了突破，并随着各学科间的迁移应用于交叉融合，逐渐衍生出多个新兴研究方向。化学信息学作为以应用信息学方法以解决化学问题的学科，深度学习技术凭借其强大的非线性学习能力，通过深度学习模型可以从数据集中对其进行筛选预测，再基于理论计算对结果可行性进行理论验证，最后通过实验表征结果，缩短了实验周期、降低了人力成本、加速了化学信息学智能化。本文简要介绍了深度学习发展历史及主要网络模型架构，介绍了近年来深度学习在在化合物合成路线规划、化合物结构活性与性质及催化剂设计的最新研究和应用现状，并对未来的发展方向进行讨论与展望。     

化学信息学的涵义及教育

化学信息学是近年来发展起来的新学科 ,它的产生与发展是基于化学信息量指数般增长 ,特别是组合化学及高通量筛选的迅速发展。组合化学方法能像搭积木块一样快速合成及制备大量的化合物。一个组合化学库包括数百个至数十万个化合物 ,为药物开发提供丰富的化合物源。高通量筛选能达到 1× 1 0 4～ 1× 1 0 5 个化合物 /天。组合化学及高通量筛选为药物研制提供新的技术支柱 ,同时也为化学信息学的产生与发展提供良好的机遇。　　人类基因组计划为药物开发与疾病的治疗提供众多的新靶标。据 1 996年统计用于药物研制的靶标有 483个分子靶 (其…     

化学基元组学与药物创新

化学基元组学(chemomics)是与化学信息学、生物信息学、合成化学等学科相关的交叉学科.生物系统从内源性小分子(天然砌块)出发,通过酶催化的化学反应序列制造天然产物.生物系统通过化学反应和天然砌块向目标天然产物"砌入"一组原子,这样的一组原子称为化学基元(chemoyl).化学基元组(chemome)是生物组织中所含有的化学基元的全体.化学基元组学研究各种化学基元的结构、组装与演化的基本规律.在生存压力和繁衍需求的驱动下,生物系统已经进化出有效手段来合成天然产物以应付环境的变化,并产生了丰富多彩的生物和化学多样性.近年来,人们意识到药物创新的瓶颈之一是药物筛选资源的日益枯竭.化学基元组学可以解决这个瓶颈问题,它通过揭示生物系统制备化学多样性的规律,发展仿生合成方法制备类天然化合物库(quasi natural product libraries)以供药物筛选.本文综述了化学基元组学的主要研究内容及其在药物创新各领域中的潜在应用.     

化学品数据信息搜索引擎ChemDB Portal

化学品的性质、用途、安全使用等相关的知识是专业人员、特别是工业界的从业人员最大程度地降低健康和环境风险,合理地合成新化学品以及利用已有化学品的基础,也是公众消除对化学的误解、客观认识化学品在日常生活中功用和使用限度的前提。利用网络化、可公开访问的化学数据库资源获取化学品数据信息日益成为首选的途径,但目前对这些数据库的检...     

化学信息学网络化教学系统的研制

本文介绍了化学信息学的基本概念与基本内容 ,并重点介绍了我们建立的基于Internet的网络化教学系统。该系统包括课堂教学系统、作业系统以及教学需要的其他内容 ,由HTML文件构成 ,可通过浏览器 (Netscape或InternetExplorer等 )直接调用 ,用于化学信息学课程的教学工作。     

《广州化学》征订启事

《广州化学》是中国科学院广州化学研究所主办的国内外公开发行的学术期刊。自1976年创刊以来,已先后入编美国《化学文摘》(CA)、“中国科学引文数据库”、“中国学术期刊综合评价数据库统计刊源”、“中国核心期刊(遴选)数据库”、中国知网“中国期刊全文数据库”、《中国学术期刊(光盘版)》、“万方数字化期刊群”、“中文科技期刊数据库”等。办刊宗旨是打造化学与化工行业“学、研、产”信息交流平台,报道有机化学、天然产物化学、高分子材料、药物化学以及相关的环境保护、分析测试、化工技术等领域的基础研究、应用研究及技术创新方面的新成果和新技术。辟有研究报告、综述评论、研究快报、科技简讯、工程案例、产品介绍、广告之窗等栏目。读者对象是国内外化学与化工行业科技工作者、大专院校师生。     

化学信息学发展现状

本文叙述了目前化学领域的发展热点之一——化学信息学（Chemoinformatics)的发展概况,从信息学角度对其产生、成长及未来发展趋势进行了探讨。     

The Blue Obelisk-interoperability in chemical informatics

The Blue Obelisk Movement (http://www.blueobelisk.org/) is the name used by a diverse Internet group promoting reusable chemistry via open source software development, consistent and complimentary chemoinformatics research, open data, and open standards. We outline recent examples of cooperation in the Blue Obelisk group: a shared dictionary of algorithms and implementations in chemoinformatics algorithms drawing from our various software projects; a shared repository of chemoinformatics data including elemental properties, atomic radii, isotopes, atom typing rules, and so forth; and Web services for the platform-independent use of chemoinformatics programs.     

Open Chemistry,JupyterLab, REST,and quantum chemistry

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the worldwide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open‐source framework that offers an end‐to‐end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open‐source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state‐of‐the‐art computational chemistry codes including NWChem and Psi4, and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.     

Basic overview of chemoinformatics

There is no particular point in time that determines when chemoinformatics was founded or established. It slowly evolved from several, often quite humble beginnings. Scientists in various fields of chemistry struggled with the development of computer methods which allowed them to manage the enormous amount of chemical information and to find relationships between the structure and properties of a compound. During the 1960s some early developments appeared that led to a flurry of activities in the 1970s. This review provides a general overview of basic methods in the specific fields of chemoinformatics, from encoding chemical compounds, storing and searching data in databases, to generating and analyzing these data. In addition, the chief interconnecting points of chemoinformatics applications are highlighted including the contributions of Johann Gasteiger to this field.     

Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery$

Abstract

Molecular property diagnostic suite (MPDS) is a Galaxy-based open source drug discovery and development platform. MPDS web portals are designed for several diseases, such as tuberculosis, diabetes mellitus, and other metabolic disorders, specifically aimed to evaluate and estimate the drug-likeness of a given molecule. MPDS consists of three modules, namely data libraries, data processing, and data analysis tools which are configured and interconnected to assist drug discovery for specific diseases. The data library module encompasses vast information on chemical space, wherein the MPDS compound library comprises 110.31 million unique molecules generated from public domain databases. Every molecule is assigned with a unique ID and card, which provides complete information for the molecule. Some of the modules in the MPDS are specific to the diseases, while others are non-specific. Importantly, a suitably altered protocol can be effectively generated for another disease-specific MPDS web portal by modifying some of the modules. Thus, the MPDS suite of web portals shows great promise to emerge as disease-specific portals of great value, integrating chemoinformatics, bioinformatics, molecular modelling, and structure- and analogue-based drug discovery approaches.     

Mass spectrometry and Web 2.0

The term Web 2.0 is a convenient shorthand for a new era in the Internet in which users themselves are both generating and modifying existing web content. Several types of tools can be used. With social bookmarking, users assign a keyword to a web resource and the collection of the keyword 'tags' from multiple users form the classification of these resources. Blogs are a form of diary or news report published on the web in reverse chronological order and are a popular form of information sharing. A wiki is a website that can be edited using a web browser and can be used for collaborative creation of information on the site. This article is a tutorial that describes how these new ways of creating, modifying, and sharing information on the Web are being used for on-line mass spectrometry resources.     

Some solved and unsolved problems of chemoinformatics

The field of chemoinformatics has developed from different roots, starting in the 1960s. These branches have now merged into a scientific discipline of its own, exchanging ideas and methods across different areas of chemistry. In the last 40 years chemoinformatics has achieved a lot. Without access to the databases in chemistry developed with chemoinformatics methods, modern chemical research would not be able to work at its present high level of competence. However, there are quite a few challenges, such as drug design and understanding the effect of chemicals on human health and on the environment, as well as furthering our knowledge of chemistry and of biological systems, that can benefit from a more intensive use of chemoinformatics methods. Approaches to meet these challenges will be briefly outlined. All this emphasizes that chemoinformatics has matured into a scientific discipline of its own that reaches out to many other chemical fields and will increase in attractiveness to students and researchers.     

Web service infrastructure for chemoinformatics

The vast increase of pertinent information available to drug discovery scientists means that there is a strong demand for tools and techniques for organizing and intelligently mining this information for manageable human consumption. At Indiana University, we have developed an infrastructure of chemoinformatics Web services that simplifies the access to this information and the computational techniques that can be applied to it. In this paper, we describe this infrastructure, give some examples of its use, and then discuss our plans to use it as a platform for chemoinformatics application development in the future.     

Chemical documents: machine understanding and automated information extraction

Automatically extracting chemical information from documents is a challenging task, but an essential one for dealing with the vast quantity of data that is available. The task is least difficult for structured documents, such as chemistry department web pages or the output of computational chemistry programs, but requires increasingly sophisticated approaches for less structured documents, such as chemical papers. The identification of key units of information, such as chemical names, makes the extraction of useful information from unstructured documents possible.