未来展望:利用人工智能的力量生成新的多肽药物。

IF 4.8 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Biomolecules Pub Date : 2024-10-15 DOI:10.3390/biom14101303
Nour Nissan, Mitchell C Allen, David Sabatino, Kyle K Biggar
{"title":"未来展望:利用人工智能的力量生成新的多肽药物。","authors":"Nour Nissan, Mitchell C Allen, David Sabatino, Kyle K Biggar","doi":"10.3390/biom14101303","DOIUrl":null,"url":null,"abstract":"<p><p>The expansive field of drug discovery is continually seeking innovative approaches to identify and develop novel peptide-based therapeutics. With the advent of artificial intelligence (AI), there has been a transformative shift in the generation of new peptide drugs. AI offers a range of computational tools and algorithms that enables researchers to accelerate the therapeutic peptide pipeline. This review explores the current landscape of AI applications in peptide drug discovery, highlighting its potential, challenges, and ethical considerations. Additionally, it presents case studies and future prospectives that demonstrate the impact of AI on the generation of new peptide drugs.</p>","PeriodicalId":8943,"journal":{"name":"Biomolecules","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11505729/pdf/","citationCount":"0","resultStr":"{\"title\":\"Future Perspective: Harnessing the Power of Artificial Intelligence in the Generation of New Peptide Drugs.\",\"authors\":\"Nour Nissan, Mitchell C Allen, David Sabatino, Kyle K Biggar\",\"doi\":\"10.3390/biom14101303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The expansive field of drug discovery is continually seeking innovative approaches to identify and develop novel peptide-based therapeutics. With the advent of artificial intelligence (AI), there has been a transformative shift in the generation of new peptide drugs. AI offers a range of computational tools and algorithms that enables researchers to accelerate the therapeutic peptide pipeline. This review explores the current landscape of AI applications in peptide drug discovery, highlighting its potential, challenges, and ethical considerations. Additionally, it presents case studies and future prospectives that demonstrate the impact of AI on the generation of new peptide drugs.</p>\",\"PeriodicalId\":8943,\"journal\":{\"name\":\"Biomolecules\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11505729/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomolecules\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3390/biom14101303\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomolecules","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3390/biom14101303","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

广阔的药物发现领域一直在寻求创新方法,以确定和开发新型肽类治疗药物。随着人工智能(AI)的出现,新的多肽药物的产生发生了转变。人工智能提供了一系列计算工具和算法,使研究人员能够加快多肽治疗管道的发展。这篇综述探讨了当前人工智能在多肽药物发现中的应用情况,重点介绍了其潜力、挑战和伦理考虑因素。此外,它还介绍了案例研究和未来展望,展示了人工智能对多肽新药研发的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Future Perspective: Harnessing the Power of Artificial Intelligence in the Generation of New Peptide Drugs.

The expansive field of drug discovery is continually seeking innovative approaches to identify and develop novel peptide-based therapeutics. With the advent of artificial intelligence (AI), there has been a transformative shift in the generation of new peptide drugs. AI offers a range of computational tools and algorithms that enables researchers to accelerate the therapeutic peptide pipeline. This review explores the current landscape of AI applications in peptide drug discovery, highlighting its potential, challenges, and ethical considerations. Additionally, it presents case studies and future prospectives that demonstrate the impact of AI on the generation of new peptide drugs.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Biomolecules
Biomolecules Biochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
9.40
自引率
3.60%
发文量
1640
审稿时长
18.28 days
期刊介绍: Biomolecules (ISSN 2218-273X) is an international, peer-reviewed open access journal focusing on biogenic substances and their biological functions, structures, interactions with other molecules, and their microenvironment as well as biological systems. Biomolecules publishes reviews, regular research papers and short communications.  Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信