基于人工智能(AI)的疟疾药物设计

B. Ghosh, Soham Choudhuri
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引用次数: 2

摘要

疟疾是一种由疟原虫引起的致命疾病。每年约有2.1亿人感染疟疾,造成50万人死亡。在几种寄生虫中,恶性疟原虫是导致严重感染和死亡的主要原因。市场上有几种治疗疟疾的药物,但疟原虫多年来已经成功地对许多药物产生了耐药性。这对治疗的效力构成严重威胁,必须继续发现新的药物来解决这一问题,特别是由于未能设计出有效的疫苗。人们现在正试图利用人工智能技术设计新的疟疾药物,这可以大大减少传统药物发现项目所需的时间和成本。在本章中,我们全面概述了几种基于人工智能的计算技术的路线图,这些技术可以在疟疾药物发现计划中实现。传统计算机的计算能力有限。因此,研究人员也在试图利用量子机器学习来加速药物发现过程。
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Drug Design for Malaria with Artificial Intelligence (AI)
Malaria is a deadly disease caused by the plasmodium parasites. Approximately 210 million people get affected by malaria every year resulting in half a million deaths. Among several species of the parasite, Plasmodium falciparum is the primary cause of severe infection and death. Several drugs are available for malaria treatment in the market but plasmodium parasites have successfully developed resistance against many drugs over the years. This poses a serious threat to efficacy of the treatments and continuing discovery of new drug is necessary to tackle the situation, especially due to failure in designing an effective vaccine. People are now trying to design new drugs for malaria using AI technologies which can substantially reduce the time and cost required in classical drug discovery programs. In this chapter, we provide a comprehensive overview of a road map for several AI based computational techniques which can be implemented in a malaria drugs discovery program. Classical computers has limiting computing power. So, researchers are also trying to harness quantum machine learning to speed up the drug discovery processes.
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Stable Artesunate Resistance in A Humanized Mouse Model of Plasmodium falciparum Molecular Approaches for Malaria Therapy P. falciparum and Its Molecular Markers of Resistance to Antimalarial Drugs Drug Design for Malaria with Artificial Intelligence (AI) Malaria: Introductory Concepts, Resistance Issues and Current Medicines
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