Bioinformatics Centre, Indian Institute of Science, Bangalore - 560012, India +91 80 22932892 ; +91 80 23600551 ;
Expert Opin Drug Discov. 2009 Dec;4(12):1221-36. doi: 10.1517/17460440903380422.
The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation.
This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself.
The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained.
Systems thinking has now come of age enabling a 'bird's eye view' of the biological systems under study, at the same time allowing us to 'zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.
在过去的二三十年中，研究药物发现的重点从基于配体的设计方法转变为基于靶标的发现，这是一个重要的里程碑。目前，它正在见证另一个重大的范式转变，即倾向于基于整体系统的方法，而不是基于还原的单个分子方法。这种新趋势的影响可能会在治疗干预的新策略、单独和联合的新靶标以及设计特定和更安全的药物方面产生强烈的影响。计算建模和模拟是新时代生物学的重要组成部分，因为它们对于理解高通量实验生成的大规模数据以及生成假设至关重要，这些假设通常需要经过实验验证进行迭代。
本综述重点介绍了当前可用于靶标识别的系统级计算方法。本综述首先讨论了生物系统的抽象层次，并描述了为此目的可用的不同建模方法。然后，综述重点介绍了如何将此类建模和模拟应用于药物靶标发现。最后，它讨论了用于研究其他重要问题的方法，例如了解靶标可及性、确定靶标组合和预测药物耐药性，并在靶标识别阶段本身考虑这些问题。
读者将了解用于靶标发现的各种方法和对系统方法的需求，然后概述已经开发的不同建模和模拟方法。还将获得对各种方法和观点的承诺和局限性的想法，以及对未来发展的看法。
系统思维现在已经成熟，可以提供正在研究的生物系统的“鸟瞰图”，同时允许我们根据需要“放大”，以详细描述各个组件。可用于计算生物学系统建模和模拟的许多不同方法可有效地用于药物靶标发现。
