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Review Article

基于配体和结构的药物设计和优化使用KNIME

卷 27, 期 38, 2020

页: [6458 - 6479] 页: 22

弟呕挨: 10.2174/0929867326666190409141016

价格: $65

摘要

近年来，在如何使用数据进行早期药物发现活动方面，从命中识别到候选物选择发生了范式转变。 数据挖掘方法的重大发展和研究科学家工具的可访问性在减少药物发现时间和增加化学实体实现药物开发里程碑的可能性方面发挥了作用。 Konstanz Information Miner KNIME是领先的开源数据分析平台，在过去十年中一直支持药物发现工作。 KNIME提供了丰富的工具，并得到了广泛的贡献者社区的支持，以实现基于配体和结构的药物设计。 这篇综述将研究KNIME平台内的最新发展，以支持小分子药物设计，并就该领域的挑战和未来发展提供一个视角。

关键词: 命中扩展，虚拟筛选，预测毒理学，配体优化，数据挖掘，KNIME，ADME建模，大数据，工作流程，计算机辅助药物设计。

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