{"title":"针对COVID - 19的药物再利用","authors":"Fahmida Minna, Maya Mohan","doi":"10.1007/s40995-024-01763-0","DOIUrl":null,"url":null,"abstract":"<div><p>Drug discovery is a distinctive method of testing a drug before medical use, which is a vital step before drug development. Targets are proteins in the human cells. The drug compounds interact with the target, which helps to cure diseases of human beings. One of the most important areas of research in the field of drugs discovery is drug–target interaction (Öztürk et al. in Bioinformatics 34(17):i821–i829, 2018). It identifies interactions between proteins and targets in the human body and the chemical compounds in drugs. Several resources were wasted in terms of the cost and the time spent on research laboratory experiments to find the drug discovery. It is essential for drug discovery to make accurate predictions of drug–target interactions (DTI). A recent study found that deep learning (DL) models perform well at predicting DTI. Here now introduce Deep Purpose, an extensive and user-friendly DL library for DTI prediction. Drug repurposing is a technique for expanding or improving the use of a current drug or creating new uses for current drugs. In this case, gave pre-existing medications for the SARS CoV2 3CL protease repurposing method. The results were the ratings for each drug’s binding affinity to the SARS CoV2 3CL protease inhibitor. Building a machine learning regression model using the SARS CoV2 3CL protease inhibitor’s ChEMBL bioactivity data is also possible. It is to discover a drug’s bioactivity information for its possible effectiveness against a virus.</p></div>","PeriodicalId":600,"journal":{"name":"Iranian Journal of Science and Technology, Transactions A: Science","volume":"49 2","pages":"319 - 330"},"PeriodicalIF":1.4000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drug Repurposing for COVID 19\",\"authors\":\"Fahmida Minna, Maya Mohan\",\"doi\":\"10.1007/s40995-024-01763-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Drug discovery is a distinctive method of testing a drug before medical use, which is a vital step before drug development. Targets are proteins in the human cells. The drug compounds interact with the target, which helps to cure diseases of human beings. One of the most important areas of research in the field of drugs discovery is drug–target interaction (Öztürk et al. in Bioinformatics 34(17):i821–i829, 2018). It identifies interactions between proteins and targets in the human body and the chemical compounds in drugs. Several resources were wasted in terms of the cost and the time spent on research laboratory experiments to find the drug discovery. It is essential for drug discovery to make accurate predictions of drug–target interactions (DTI). A recent study found that deep learning (DL) models perform well at predicting DTI. Here now introduce Deep Purpose, an extensive and user-friendly DL library for DTI prediction. Drug repurposing is a technique for expanding or improving the use of a current drug or creating new uses for current drugs. In this case, gave pre-existing medications for the SARS CoV2 3CL protease repurposing method. The results were the ratings for each drug’s binding affinity to the SARS CoV2 3CL protease inhibitor. Building a machine learning regression model using the SARS CoV2 3CL protease inhibitor’s ChEMBL bioactivity data is also possible. It is to discover a drug’s bioactivity information for its possible effectiveness against a virus.</p></div>\",\"PeriodicalId\":600,\"journal\":{\"name\":\"Iranian Journal of Science and Technology, Transactions A: Science\",\"volume\":\"49 2\",\"pages\":\"319 - 330\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-02-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iranian Journal of Science and Technology, Transactions A: Science\",\"FirstCategoryId\":\"4\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40995-024-01763-0\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Science and Technology, Transactions A: Science","FirstCategoryId":"4","ListUrlMain":"https://link.springer.com/article/10.1007/s40995-024-01763-0","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
药物发现是一种独特的药物使用前测试方法,是药物开发前的重要步骤。目标是人体细胞中的蛋白质。药物化合物与靶标相互作用,有助于治疗人类疾病。药物发现领域最重要的研究领域之一是药物-靶标相互作用(Öztürk et al. in Bioinformatics 34(17): i821-i829, 2018)。它能识别人体内蛋白质和靶标之间的相互作用,以及药物中的化合物。在花费在研究实验室实验以发现药物方面的成本和时间方面浪费了一些资源。准确预测药物-靶标相互作用(DTI)对药物发现至关重要。最近的一项研究发现,深度学习(DL)模型在预测DTI方面表现良好。现在介绍Deep Purpose,这是一个用于DTI预测的广泛且用户友好的深度学习库。药物再利用是一种扩大或改善现有药物使用或为现有药物创造新用途的技术。在这种情况下,给予已有的药物用于SARS CoV2 3CL蛋白酶再利用方法。结果为每种药物与SARS CoV2 3CL蛋白酶抑制剂的结合亲和力评分。利用SARS CoV2 3CL蛋白酶抑制剂的ChEMBL生物活性数据构建机器学习回归模型也是可能的。它是发现药物的生物活性信息,以确定其对病毒的可能有效性。
Drug discovery is a distinctive method of testing a drug before medical use, which is a vital step before drug development. Targets are proteins in the human cells. The drug compounds interact with the target, which helps to cure diseases of human beings. One of the most important areas of research in the field of drugs discovery is drug–target interaction (Öztürk et al. in Bioinformatics 34(17):i821–i829, 2018). It identifies interactions between proteins and targets in the human body and the chemical compounds in drugs. Several resources were wasted in terms of the cost and the time spent on research laboratory experiments to find the drug discovery. It is essential for drug discovery to make accurate predictions of drug–target interactions (DTI). A recent study found that deep learning (DL) models perform well at predicting DTI. Here now introduce Deep Purpose, an extensive and user-friendly DL library for DTI prediction. Drug repurposing is a technique for expanding or improving the use of a current drug or creating new uses for current drugs. In this case, gave pre-existing medications for the SARS CoV2 3CL protease repurposing method. The results were the ratings for each drug’s binding affinity to the SARS CoV2 3CL protease inhibitor. Building a machine learning regression model using the SARS CoV2 3CL protease inhibitor’s ChEMBL bioactivity data is also possible. It is to discover a drug’s bioactivity information for its possible effectiveness against a virus.
期刊介绍:
The aim of this journal is to foster the growth of scientific research among Iranian scientists and to provide a medium which brings the fruits of their research to the attention of the world’s scientific community. The journal publishes original research findings – which may be theoretical, experimental or both - reviews, techniques, and comments spanning all subjects in the field of basic sciences, including Physics, Chemistry, Mathematics, Statistics, Biology and Earth Sciences