A review on the structural characterization of nanomaterials for nano-QSAR models.

IF 2.6 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY Beilstein Journal of Nanotechnology Pub Date : 2024-07-11 eCollection Date: 2024-01-01 DOI:10.3762/bjnano.15.71
Salvador Moncho, Eva Serrano-Candelas, Jesús Vicente de Julián-Ortiz, Rafael Gozalbes
{"title":"A review on the structural characterization of nanomaterials for nano-QSAR models.","authors":"Salvador Moncho, Eva Serrano-Candelas, Jesús Vicente de Julián-Ortiz, Rafael Gozalbes","doi":"10.3762/bjnano.15.71","DOIUrl":null,"url":null,"abstract":"<p><p>Quantitative structure-activity relationship (QSAR) models are routinely used to predict the properties and biological activity of chemicals to direct synthetic advances, perform massive screenings, and even to register new substances according to international regulations. Currently, nanoscale QSAR (nano-QSAR) models, adapting this methodology to predict the intrinsic features of nanomaterials (NMs) and quantitatively assess their risks, are blooming. One of the challenges is the characterization of the NMs. This cannot be done with a simple SMILES representation, as for organic molecules, because their chemical structure is complex, including several layers and many inorganic materials, and their size and geometry are key features. In this review, we survey the literature for existing predictive models for NMs and discuss the variety of calculated and experimental features used to define and describe NMs. In the light of this research, we propose a classification of the descriptors including those that directly describe a component of the nanoform (core, surface, or structure) and also experimental features (related to the nanomaterial's behavior, preparation, or test conditions) that indirectly reflect its structure.</p>","PeriodicalId":8802,"journal":{"name":"Beilstein Journal of Nanotechnology","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11250003/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Beilstein Journal of Nanotechnology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.3762/bjnano.15.71","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Quantitative structure-activity relationship (QSAR) models are routinely used to predict the properties and biological activity of chemicals to direct synthetic advances, perform massive screenings, and even to register new substances according to international regulations. Currently, nanoscale QSAR (nano-QSAR) models, adapting this methodology to predict the intrinsic features of nanomaterials (NMs) and quantitatively assess their risks, are blooming. One of the challenges is the characterization of the NMs. This cannot be done with a simple SMILES representation, as for organic molecules, because their chemical structure is complex, including several layers and many inorganic materials, and their size and geometry are key features. In this review, we survey the literature for existing predictive models for NMs and discuss the variety of calculated and experimental features used to define and describe NMs. In the light of this research, we propose a classification of the descriptors including those that directly describe a component of the nanoform (core, surface, or structure) and also experimental features (related to the nanomaterial's behavior, preparation, or test conditions) that indirectly reflect its structure.

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
综述纳米材料的结构特征以建立纳米 QSAR 模型。
定量结构-活性关系(QSAR)模型通常用于预测化学品的性质和生物活性,以指导合成进展,进行大规模筛选,甚至根据国际法规注册新物质。目前,纳米尺度 QSAR(纳米 QSAR)模型正在蓬勃发展,这种方法可用于预测纳米材料(NMs)的内在特征并定量评估其风险。挑战之一是纳米材料的特征描述。这不能像有机分子那样用简单的 SMILES 表示法来完成,因为它们的化学结构复杂,包括多层和多种无机材料,而且它们的尺寸和几何形状是关键特征。在这篇综述中,我们调查了有关现有 NM 预测模型的文献,并讨论了用于定义和描述 NM 的各种计算和实验特征。根据这项研究,我们提出了一种描述符分类方法,其中包括直接描述纳米形式成分(核心、表面或结构)的描述符,以及间接反映其结构的实验特征(与纳米材料的行为、制备或测试条件有关)。
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
Beilstein Journal of Nanotechnology
Beilstein Journal of Nanotechnology NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
5.70
自引率
3.20%
发文量
109
审稿时长
2 months
期刊介绍: The Beilstein Journal of Nanotechnology is an international, peer-reviewed, Open Access journal. It provides a unique platform for rapid publication without any charges (free for author and reader) – Platinum Open Access. The content is freely accessible 365 days a year to any user worldwide. Articles are available online immediately upon publication and are publicly archived in all major repositories. In addition, it provides a platform for publishing thematic issues (theme-based collections of articles) on topical issues in nanoscience and nanotechnology. The journal is published and completely funded by the Beilstein-Institut, a non-profit foundation located in Frankfurt am Main, Germany. The editor-in-chief is Professor Thomas Schimmel – Karlsruhe Institute of Technology. He is supported by more than 20 associate editors who are responsible for a particular subject area within the scope of the journal.
期刊最新文献
New design of operational MEMS bridges for measurements of properties of FEBID-based nanostructures. Functional morphology of cleaning devices in the damselfly Ischnura elegans (Odonata, Coenagrionidae). The role of a tantalum interlayer in enhancing the properties of Fe3O4 thin films. Dual-functionalized architecture enables stable and tumor cell-specific SiO2NPs in complex biological fluids. Enhanced catalytic reduction through in situ synthesized gold nanoparticles embedded in glucosamine/alginate nanocomposites.
×
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