系统的计算策略用于识别蛋白质标和发现
Arti Kataria1, Ankit Srivastava2, Desh Deepak Singh3
1Laboratory of Bacteriology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH) Hamilton MT 59840 USA.
RSC medicinal chemistry
|July 19, 2024
概括
计算方法通过识别蛋白质标和优化分子来加速药物发现. 本概述涵盖了用于高效药物设计工作流程的算法,工具和数据库.
科学领域:
- 计算化学和生物信息学
- 药物的发现和开发.
背景情况:
- 药物发现时间表被计算算法和工具显著缩短.
- 对生物宏分子及其复合物的结构数据的日益增加的可用性提高了计算方法的相关性.
- 计算方法是药物发现的各个阶段的组成部分,包括目标识别,虚拟查和连接体设计.
研究的目的:
- 提供计算药物发现工作流程的概述.
- 突出在现代药物发现中使用的关键算法,工具和数据库.
- 专注于蛋白质标识和优化带选择.
主要方法:
- 审查最近报告的计算药物发现工作流程.
- 识别突出的算法,工具和数据库.
- 分析蛋白标识和带选择中的应用.
主要成果:
- 计算方法在药物发现中被广泛应用,包括目标识别,药物评估,虚拟查和分子动力学.
- 介绍了基本计算工具和数据库的全面概述.
- 该研究详细介绍了有效的蛋白质标识和化合物优化工作流程.
结论:
- 计算方法对于现代药物发现是不可或缺的,提供效率和精度.
- 集成先进的算法,工具和数据库简化了可行的候选药物的识别.
- 优化的工作流程有助于为治疗开发选择优质连接体.
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