GSTDTAP  > 气候变化
Machine learning model helps characterize compounds for drug discovery
admin
2020-10-14
发布年2020
语种英语
国家美国
领域气候变化 ; 地球科学 ; 资源环境
正文(英文)

WEST LAFAYETTE, Ind. - Tandem mass spectrometry is a powerful analytical tool used to characterize complex mixtures in drug discovery and other fields.

Now, Purdue University innovators have created a new method of applying machine learning concepts to the tandem mass spectrometry process to improve the flow of information in the development of new drugs. Their work is published in Chemical Science.

"Mass spectrometry plays an integral role in drug discovery and development," said Gaurav Chopra, an assistant professor of analytical and physical chemistry in Purdue's College of Science. "The specific implementation of bootstrapped machine learning with a small amount of positive and negative training data presented here will pave the way for becoming mainstream in day-to-day activities of automating characterization of compounds by chemists."

Chopra said there are two major problems in the field of machine learning used for chemical sciences. Methods used do not provide chemical understanding of the decisions that are made by the algorithm, and new methods are not typically used to do blind experimental tests to see if the proposed models are accurate for use in a chemical laboratory.

"We have addressed both of these items for a methodology that is isomer selective and extremely useful in chemical sciences to characterize complex mixtures, identify chemical reactions and drug metabolites, and in fields such as proteomics and metabolomics," Chopra said.

The Purdue researchers created statistically robust machine learning models to work with less training data - a technique that will be useful for drug discovery. The model looks at a common neutral reagent - called 2-methoxypropene (MOP) - and predicts how compounds will interact with MOP in a tandem mass spectrometer in order to obtain structural information for the compounds.

"This is the first time that machine learning has been coupled with diagnostic gas-phase ion-molecule reactions, and it is a very powerful combination, leading the way to completely automated mass spectrometric identification of organic compounds," said Hilkka Kenttämaa, the Frank Brown Distinguished Professor of Analytical Chemistry and Organic Chemistry. "We are now introducing many new reagents into this method."

The Purdue team introduces chemical reactivity flowcharts to facilitate chemical interpretation of the decisions made by the machine learning method that will be useful to understand and interpret the mass spectra for structural information.

###

This work aligns with other innovations and research from Chopra's and Kenttämaa's labs, whose team members work with the Purdue Research Foundation Office of Technology Commercialization to patent numerous technologies. To find out more information about their patented inventions, contact otcip@prf.org.

About Purdue Research Foundation Office of Technology Commercialization

The Purdue Research Foundation Office of Technology Commercialization operates one of the most comprehensive technology transfer programs among leading research universities in the U.S. Services provided by this office support the economic development initiatives of Purdue University and benefit the university's academic activities through commercializing, licensing and protecting Purdue intellectual property. The office recently moved into the Convergence Center for Innovation and Collaboration in Discovery Park District, adjacent to the Purdue campus. In fiscal year 2020, the office reported 148 deals finalized with 225 technologies signed, 408 disclosures received and 180 issued U.S. patents. The office is managed by the Purdue Research Foundation, which received the 2019 Innovation and Economic Prosperity Universities Award for Place from the Association of Public and Land-grant Universities. In 2020, IPWatchdog Institute ranked Purdue third nationally in startup creation and in the top 20 for patents. The Purdue Research Foundation is a private, nonprofit foundation created to advance the mission of Purdue University. Contact otcip@prf.org for more information.

About Purdue University

Purdue University is a top public research institution developing practical solutions to today's toughest challenges. Ranked the No. 5 Most Innovative University in the United States by U.S. News & World Report, Purdue delivers world-changing research and out-of-this-world discovery. Committed to hands-on and online, real-world learning, Purdue offers a transformative education to all. Committed to affordability and accessibility, Purdue has frozen tuition and most fees at 2012-13 levels, enabling more students than ever to graduate debt-free. See how Purdue never stops in the persistent pursuit of the next giant leap at https://www.eurekalert.org/pub_releases/2020-10/purdue.edu.

Writer: Chris Adam, cladam@prf.org

Sources: Gaurav Chopra, gchopra@https://www.eurekalert.org/pub_releases/2020-10/purdue.edu

Hilkka Kenttämaa, hilkka@https://www.eurekalert.org/pub_releases/2020-10/purdue.edu

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

URL查看原文
来源平台EurekAlert
文献类型新闻
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/298441
专题气候变化
地球科学
资源环境科学
推荐引用方式
GB/T 7714
admin. Machine learning model helps characterize compounds for drug discovery. 2020.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[admin]的文章
百度学术
百度学术中相似的文章
[admin]的文章
必应学术
必应学术中相似的文章
[admin]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。