An Inverse QSAR Method Based on a Two-Layered Model and Integer Programming

Author:

Shi Yu,Zhu Jianshen,Azam Naveed AhmedORCID,Haraguchi KazuyaORCID,Zhao Liang,Nagamochi Hiroshi,Akutsu TatsuyaORCID

Abstract

A novel framework for inverse quantitative structure–activity relationships (inverse QSAR) has recently been proposed and developed using both artificial neural networks and mixed integer linear programming. However, classes of chemical graphs treated by the framework are limited. In order to deal with an arbitrary graph in the framework, we introduce a new model, called a two-layered model, and develop a corresponding method. In this model, each chemical graph is regarded as two parts: the exterior and the interior. The exterior consists of maximal acyclic induced subgraphs with bounded height, the interior is the connected subgraph obtained by ignoring the exterior, and the feature vector consists of the frequency of adjacent atom pairs in the interior and the frequency of chemical acyclic graphs in the exterior. Our method is more flexible than the existing method in the sense that any type of graphs can be inferred. We compared the proposed method with an existing method using several data sets obtained from PubChem database. The new method could infer more general chemical graphs with up to 50 non-hydrogen atoms. The proposed inverse QSAR method can be applied to the inference of more general chemical graphs than before.

Funder

Japan Society for the Promotion of Science

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Inverse QSAR Method Based on Linear Regression and Integer Programming;Frontiers in Bioscience-Landmark;2022-06-10

2. A Method for Molecular Design Based on Linear Regression and Integer Programming;2022 12th International Conference on Bioscience, Biochemistry and Bioinformatics;2022-01-07

3. Adjustive Linear Regression and Its Application to the Inverse QSAR;Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies;2022

4. Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search;2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2021-12-09

5. 機械学習QSARの整数計画法に基づく逆解析法;Journal of Computer Chemistry, Japan;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3