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机器学习:用于研究生物分子和药物设计的Python工具。

Machine learning: Python tools for studying biomolecules and drug design.

作者信息

Ryzhkov Fedor V, Ryzhkova Yuliya E, Elinson Michail N

机构信息

N. D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, 47 Leninsky Prospekt, 119991, Moscow, Russia.

出版信息

Mol Divers. 2025 Apr 29. doi: 10.1007/s11030-025-11199-2.

Abstract

The increasing adoption of computational methods and artificial intelligence in scientific research has led to a growing interest in versatile tools like Python. In the fields of medical chemistry, biochemistry, and bioinformatics, Python has emerged as a key language for tackling complex challenges. It is used to solve various tasks, such as drug discovery, high-throughput and virtual screening, protein and genome analysis, and predicting drug efficacy. This review presents a list of tools for these tasks, including scripts, libraries, and ready-made programs, and serves as a starting point for scientists wishing to apply automation or optimization to routine tasks in medical chemistry and bioinformatics.

摘要

科学研究中计算方法和人工智能的日益广泛应用,引发了人们对Python等通用工具的兴趣日益浓厚。在药物化学、生物化学和生物信息学领域,Python已成为应对复杂挑战的关键语言。它被用于解决各种任务,如药物发现、高通量和虚拟筛选、蛋白质和基因组分析以及预测药物疗效。本综述列出了用于这些任务的工具清单,包括脚本、库和现成的程序,为希望在药物化学和生物信息学的日常任务中应用自动化或优化的科学家提供了一个起点。

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