药物发现
计算生物学
药品
计算机科学
数据科学
生物信息学
生物
药理学
作者
Ngo Anh Dao,Thuy-Duong Vu,Dinh‐Toi Chu
标识
DOI:10.1007/978-981-99-8401-5_11
摘要
Drug discovery requires high cost and is a time-consuming process, and the facilitation of computer-based drug design methods is one of the most potential approaches to change this challenging situation. In fact, along with the current advancement of science and technology, especially in the field of bioinformatics, the stages of drug discovery can be significantly shortened while the cost is reduced and the efficacy of treatment increases. Bioinformatics tools and platforms can not only advance drug target identification and screening, but also support drug candidate selection and evaluate effectiveness of drug candidates. In recent years, bioinformatics tools have often been used to screen the sequences of gene fragments, uncovering potential binding sites for therapeutic drugs or also known as drug targets. Besides, the high-throughput screen method is a popular method for drug candidate identification for detecting potential small molecules among a large amount of information in available data libraries. Since the early years of the twenty-first century, research has applied bioinformatics to screen targeted molecules using the high-throughput screening model. Bioinformatics also has a huge contribution in virtual screening through the early elimination of substances with undesirable properties through computers and in silico screening, thereby finding the closest compounds to the desired drug. Based on these tools and techniques, the efficacy of drug candidates can be easily and quickly determined, especially in individuals, which revolutionarily benefits drug validation and personalized pharmacological therapies.
科研通智能强力驱动
Strongly Powered by AbleSci AI