BigSMARTS: A Topologically Aware Query Language and Substructure Search Algorithm for Polymer Chemical Structures
BigSMARTS: A Topologically Aware Query Language and Substructure Search Algorithm for Polymer Chemical Structures
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BigSMARTS：一种用于聚合物化学结构的拓扑感知查询语言和子结构搜索算法
DOI：
10.1021/acs.jcim.3c00978
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发表时间：
2023
影响因子：
5.6
通讯作者：
Olsen, Bradley D.
中科院分区：
文献类型：
--
作者：
Rebello, Nathan J.;Lin, Tzyy-Shyang;Nazeer, Heeba;Olsen, Bradley D.
分子搜索在化学、生物学和信息学中非常重要，可以识别大型数据集中的分子结构，促进知识发现和创新，并使化学数据公平（可查找、可访问、可互操作、可重用）。聚合物的搜索算法明显不如小分子的搜索算法发达，因为聚合物搜索依赖于聚合物名称搜索，这可能具有挑战性，因为聚合物命名过于宽泛（例如，聚乙烯），对于复杂的化学结构来说很复杂，并且通常不符合IUPAC的官方约定。聚合物的化学结构搜索仅限于亚结构，如单体，没有连接或拓扑的意识。这项工作为聚合物引入了一种新的查询语言和图遍历搜索算法，它提供了第一种能够完全捕获聚合物中存在的所有化学结构的搜索方法。BigSMARTS查询语言是小分子SMARTS语言的扩展，允许用户编写查询，将单体和官能团搜索定位到聚合物的不同部分，如三嵌段的中间嵌段、接枝的侧链和重复单元的主干。子结构搜索算法是基于对聚合物随机图生成函数的图表示的遍历。在操作上，该算法首先识别代表单体的循环，然后是末端基团，最后执行深度优先搜索以匹配整个子图。为了验证该算法，针对文献中的数百种目标化学和拓扑搜索了数百个查询，大约有44万个查询-目标对。该工具提供了一个详细的算法，可以在搜索引擎中实现，以提供与单体连通性和聚合物拓扑结构完全匹配的搜索结果。
Molecular search is important in chemistry, biology, and informatics for identifying molecular structures within large data sets, improving knowledge discovery and innovation, and making chemical data FAIR (findable, accessible, interoperable, reusable). Search algorithms for polymers are significantly less developed than those for small molecules because polymer search relies on searching by polymer name, which can be challenging because polymer naming is overly broad (i.e., polyethylene), complicated for complex chemical structures, and often does not correspond to official IUPAC conventions. Chemical structure search in polymers is limited to substructures, such as monomers, without awareness of connectivity or topology. This work introduces a novel query language and graph traversal search algorithm for polymers that provides the first search method able to fully capture all of the chemical structures present in polymers. The BigSMARTS query language, an extension of the small-molecule SMARTS language, allows users to write queries that localize monomer and functional group searches to different parts of the polymer, like the middle block of a triblock, the side chain of a graft, and the backbone of a repeat unit. The substructure search algorithm is based on the traversal of graph representations of the generating functions for the stochastic graphs of polymers. Operationally, the algorithm first identifies cycles representing the monomers and then the end groups and finally performs a depth-first search to match entire subgraphs. To validate the algorithm, hundreds of queries were searched against hundreds of target chemistries and topologies from the literature, with approximately 440,000 query–target pairs. This tool provides a detailed algorithm that can be implemented in search engines to provide search results with full matching of the monomer connectivity and polymer topology.
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影响因子：
18.2
作者：
Lin, Tzyy-Shyang;Coley, Connor W.;Olsen, Bradley D.
通讯作者：
Olsen, Bradley D.
DOI：
10.1021/ci049860f
发表时间：
2004-11-01
期刊：
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
影响因子：
--
作者：
Harper, G;Bravi, GS;Green, DVS
通讯作者：
Green, DVS
影响因子：
3.6
作者：
Jeliazkova, Nina;Kochev, Nikolay
通讯作者：
Kochev, Nikolay
影响因子：
1.8
作者：
Kahovec, J;Fox, RB;Hatada, K
通讯作者：
Hatada, K