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布鲁图斯:用于刚体分子叠加的基于网格的相似性函数的优化。II. 描述与表征。

BRUTUS: optimization of a grid-based similarity function for rigid-body molecular superposition. II. Description and characterization.

作者信息

Rönkkö Toni, Tervo Anu J, Parkkinen Jussi, Poso Antti

机构信息

Department of Pharmaceutical Chemistry, University of Kuopio, P.O. Box 1627, FIN-70211, Kuopio, Finland.

出版信息

J Comput Aided Mol Des. 2006 Apr;20(4):227-36. doi: 10.1007/s10822-006-9052-4. Epub 2006 Jul 20.

Abstract

Finding novel lead molecules is one of the primary goals in early phases of drug discovery projects. However, structurally dissimilar compounds may exhibit similar biological activity, and finding new and structurally diverse lead compounds is difficult for computer algorithms. Molecular energy fields are appropriate for finding structurally novel molecules, but they are demanding to calculate and this limits their usefulness in virtual screening of large chemical databases. In our approach, energy fields are computed only once per superposition and a simple interpolation scheme is devised to allow coarse energy field lattices having fewer grid points to be used without any significant loss of accuracy. The resulting processing speed of about 0.25 s per conformation on a 2.4 GHz Intel Pentium processor allows the method to be used for virtual screening on commonly available desktop machines. Moreover, the results indicate that grid-based superposition methods could be efficiently used for the virtual screening of compound libraries.

摘要

寻找新型先导分子是药物发现项目早期阶段的主要目标之一。然而,结构不同的化合物可能表现出相似的生物活性,并且对于计算机算法而言,寻找新的且结构多样的先导化合物具有一定难度。分子能量场适用于寻找结构新颖的分子,但计算量较大,这限制了它们在大型化学数据库虚拟筛选中的应用。在我们的方法中,能量场仅在每次叠加时计算一次,并设计了一种简单的插值方案,以便在不显著损失准确性的情况下使用网格点较少的粗糙能量场晶格。在2.4 GHz英特尔奔腾处理器上,每个构象的处理速度约为0.25秒,这使得该方法可用于普通台式机上的虚拟筛选。此外,结果表明基于网格的叠加方法可有效地用于化合物库的虚拟筛选。

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