Most of the computational tools involved in drug discovery developed during the 1980s were largely based on computational chemistry, quantitative structure-activity relationship (QSAR) and cheminformatics. Subsequently, the advent of genomics in the 2000s gave rise to a huge number of databases and computational tools developed to analyze large quantities of data, through bioinformatics, to obtain valuable information about the genomic regulation of different organisms. Target identification and validation is a long process during which evidence for and against a target is accumulated in the pursuit of developing new drugs. Finally, the drug delivery system appears as a novel approach to improve drug targeting and releasing into the cells, leading to new opportunities to improve drug efficiency and avoid potential secondary effects. In each area: target discovery, drug discovery and drug delivery, different computational strategies are being developed to accelerate the process of selection and discovery of new tools to be applied to different scientific fields. Research on these three topics is growing rapidly, but still requires a global view of this landscape to detect the most challenging bottleneck and how computational tools could be integrated in each topic. This review describes the current state of the art in computational strategies for target discovery, drug discovery and drug delivery and how these fields could be integrated. Finally, we will discuss about the current needs in these fields and how the continuous development of databases and computational tools will impact on the improvement of those areas. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

中文翻译：

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目标发现，药物发现和药物递送的集成：计算策略综述。

1980年代开发的涉及药物发现的大多数计算工具主要基于计算化学，定量构效关系（QSAR）和化学信息学。随后，基因组学的出现在2000年代产生了大量的数据库和计算工具，它们通过生物信息学来分析大量数据，以获得有关不同生物体基因组调控的有价值的信息。目标识别和确认是一个漫长的过程，在此过程中，在开发新药的过程中会积累支持目标和反对目标的证据。最后，药物递送系统作为改善药物靶向性和释放到细胞中的新方法出现，从而为提高药物效率和避免潜在的次要作用提供了新的机会。在每个区域：目标发现，药物发现和药物输送，正在开发不同的计算策略，以加快选择和发现要应用于不同科学领域的新工具的过程。关于这三个主题的研究正在迅速发展，但是仍然需要对这种情况有一个全局的了解，以发现最具挑战性的瓶颈以及如何将计算工具集成到每个主题中。这篇综述描述了用于靶标发现，药物发现和药物递送的计算策略的最新技术以及如何整合这些领域。最后，我们将讨论这些领域的当前需求以及数据库和计算工具的持续发展将如何影响这些领域的改进。本文归类为：