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Software tools for structure based rational drug design

机译:用于基于结构的合理药物设计的软件工具

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摘要

Scientific advancements during the past two decades have altered the way pharmaceutical research produces new bio-active molecules. Traditional `trial and error' drug discovery efforts are gradually being replaced by structure based rational drug design. A key technique is the use of methods including X-ray crystallography and NMR for the determination of the 3-dimensional structure of a target protein followed by various modelling techniques for the design of small molecule ligands that could interact with the target structure. The first generation of the software tools were limited to energy calculations and molecular dynamics simulations based on simple force field models. More automated methods, like flexible ligand docking and de novo ligand design programs have emerged in the 90s. However, many of these software systems relied on stochastic algorithms to perform the search, effectively performing a computerised `trial and error' search. SimBioSys provides ligand design and docking tools that are systematic, exhaustive, rely on rational rules, heuristics and dynamic knowledge bases. The novel algorithms designed and optimised to solve the specific problems greatly outperform the general random methods. The presentation gives a brief overview of the efficient algorithms behind the SPROUT (de novo ligand design) and eHiTS (flexible ligand docking and virtual high throughput screening) software tools. Validation test results are presented to demonstrate the effectiveness of these tools for the solution of practical drug design problems.
机译:过去二十年来的科学进步改变了药物研究生产新的生物活性分子的方式。传统的“尝试和错误”药物发现方法正逐渐被基于结构的合理药物设计所取代。一项关键技术是使用包括X射线晶体学和NMR在内的方法来确定目标蛋白质的3维结构,然后使用各种建模技术来设计可与目标结构相互作用的小分子配体。第一代软件工具仅限于基于简单力场模型的能量计算和分子动力学模拟。 90年代出现了更多的自动化方法,例如柔性配体对接和从头配体设计程序。但是,许多这些软件系统都依靠随机算法来执行搜索,从而有效地执行了计算机化的“反复试验”搜索。 SimBioSys提供的配体设计和对接工具是系统的,详尽的,依赖于合理规则,启发式方法和动态知识库的。为解决特定问题而设计和优化的新颖算法大大优于常规随机方法。该演讲简要概述了SPROUT(从头配体设计)和eHiTS(柔性配体对接和虚拟高通量筛选)软件工具背后的高效算法。提出了验证测试结果,以证明这些工具对于解决实际药物设计问题的有效性。

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