Modelling and simulation: a computational perspective in anticancer drug discovery.

Federico Gago
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引用次数: 12

Abstract

The availability of high-quality molecular graphics tools in the public domain is changing the way macromolecular structure is perceived by researchers, educators and students alike. Computational methods have become increasingly important in a number of areas such as comparative or homology modelling, functional site location, characterization of ligand-binding sites in proteins, docking of small molecules into protein binding sites, protein-protein docking, and molecular dynamics simulations. The results obtained yield information that sometimes is beyond current experimental possibilities and can be used to guide and improve a vast array of experiments. On the basis of our improved level of understanding of molecular recognition and the widespread availability of target structures, it is reasonable to assume that computational methods will continue aiding not only in the design and interpretation of hypothesis-driven experiments in the field of cancer research but also in the rapid generation of new hypotheses.

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建模和模拟:抗癌药物发现的计算视角。
公共领域中高质量分子图形工具的可用性正在改变研究人员、教育工作者和学生对大分子结构的认知方式。计算方法在许多领域变得越来越重要,如比较或同源建模、功能位点定位、蛋白质中配体结合位点的表征、小分子与蛋白质结合位点的对接、蛋白质-蛋白质对接以及分子动力学模拟。所获得的结果产生的信息有时超出了当前实验的可能性,可以用来指导和改进大量的实验。基于我们对分子识别的理解水平的提高和目标结构的广泛可用性,我们可以合理地假设,计算方法不仅将继续帮助设计和解释癌症研究领域的假设驱动实验,而且还将帮助快速生成新的假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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