Generic strategies for chemical space exploration.

Q4 Pharmacology, Toxicology and Pharmaceutics International Journal of Computational Biology and Drug Design Pub Date : 2014-01-01 Epub Date: 2014-05-28 DOI:10.1504/IJCBDD.2014.061649
Jakob L Andersen, Christoph Flamm, Daniel Merkle, Peter F Stadler
{"title":"Generic strategies for chemical space exploration.","authors":"Jakob L Andersen,&nbsp;Christoph Flamm,&nbsp;Daniel Merkle,&nbsp;Peter F Stadler","doi":"10.1504/IJCBDD.2014.061649","DOIUrl":null,"url":null,"abstract":"<p><p>The chemical universe of molecules reachable from a set of start compounds by iterative application of a finite number of reactions is usually so vast, that sophisticated and efficient exploration strategies are required to cope with the combinatorial complexity. A stringent analysis of (bio)chemical reaction networks, as approximations of these complex chemical spaces, forms the foundation for the understanding of functional relations in Chemistry and Biology. Graphs and graph rewriting are natural models for molecules and reactions. Borrowing the idea of partial evaluation from functional programming, we introduce partial applications of rewrite rules. A framework for the specification of exploration strategies in graph-rewriting systems is presented. Using key examples of complex reaction networks from carbohydrate chemistry we demonstrate the feasibility of this high-level strategy framework. While being designed for chemical applications, the framework can also be used to emulate higher-level transformation models such as illustrated in a small puzzle game. </p>","PeriodicalId":39227,"journal":{"name":"International Journal of Computational Biology and Drug Design","volume":"7 2-3","pages":"225-58"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJCBDD.2014.061649","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Biology and Drug Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCBDD.2014.061649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2014/5/28 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 37

Abstract

The chemical universe of molecules reachable from a set of start compounds by iterative application of a finite number of reactions is usually so vast, that sophisticated and efficient exploration strategies are required to cope with the combinatorial complexity. A stringent analysis of (bio)chemical reaction networks, as approximations of these complex chemical spaces, forms the foundation for the understanding of functional relations in Chemistry and Biology. Graphs and graph rewriting are natural models for molecules and reactions. Borrowing the idea of partial evaluation from functional programming, we introduce partial applications of rewrite rules. A framework for the specification of exploration strategies in graph-rewriting systems is presented. Using key examples of complex reaction networks from carbohydrate chemistry we demonstrate the feasibility of this high-level strategy framework. While being designed for chemical applications, the framework can also be used to emulate higher-level transformation models such as illustrated in a small puzzle game.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
化学空间探索的一般策略。
通过有限数量的反应的迭代应用,从一组初始化合物中获得的分子的化学宇宙通常是如此之大,以至于需要复杂而有效的探索策略来应对组合的复杂性。严格分析(生物)化学反应网络,作为这些复杂化学空间的近似,形成了理解化学和生物学中功能关系的基础。图形和图形改写是分子和反应的自然模型。借鉴函数式编程的部分求值思想,介绍了重写规则的部分应用。提出了图形重写系统中探索策略规范的框架。使用碳水化合物化学复杂反应网络的关键例子,我们证明了这种高级策略框架的可行性。虽然该框架是为化学应用而设计的,但它也可以用于模拟更高级别的转换模型,例如在一个小的益智游戏中所示的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Computational Biology and Drug Design
International Journal of Computational Biology and Drug Design Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
1.00
自引率
0.00%
发文量
8
期刊最新文献
Assessment and Validation of Emulgel Based Salicylic acid Formulation Development to Drug release and Optimization by Statistical Design EyeRIS: Image-Based Identification of Goats using Iris Advanced DEEPCNN Breast Cancer Mammogram Image Detection and Classification with Butterfly Optimization Algorithm A Unique Noise Detector Developed for the Filtering of X-Ray Images of Bone Fractures Residue Interaction Network analysis and Molecular dynamics simulation of 6K Viroporin: Chikungunya Virus Channel Proteins
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1