Baber J Christian, Thompson David C, Cross Jason B, Humblet Christine
Chemical Sciences, Wyeth Research, Cambridge, MA 02140, USA.
J Chem Inf Model. 2009 Aug;49(8):1889-900. doi: 10.1021/ci9001074.
The root-mean-squared deviation (rmsd) is a widely used measure of distance between two aligned objects -- often chemical structures. However, rmsd has a number of known limitations including difficulty of interpretation, no limit on weighting for any portion of the alignment, and a lack of normalization. In this work, a Generally Applicable Replacement for rmsD (GARD) is proposed. In this implementation atomic contributions are weighted by their relative importance to binding, as determined statistically by Andrews et al. (1) , and as such this method is 'chemically aware'. This novel measure is normalized and does not have many of the failings of traditional rmsd. It is, thus, perfectly suited for a wide variety of uses, including the assessment of the quality of poses produced from molecular docking programs and the comparison of conformers. Rmsd and GARD are compared in their ability to assess docking software and multiple examples of the use of GARD to rescue essentially correct poses with a high rmsd are presented.
均方根偏差（rmsd）是一种广泛用于衡量两个对齐对象（通常是化学结构）之间距离的指标。然而，rmsd存在许多已知的局限性，包括难以解释、对齐的任何部分的权重没有限制以及缺乏归一化。在这项工作中，提出了一种rmsD的通用替代方法（GARD）。在这个实现中，原子贡献根据它们对结合的相对重要性进行加权，这是由安德鲁斯等人（1）通过统计确定的，因此这种方法是“化学感知的”。这种新的度量是归一化的，并且没有传统rmsd的许多缺点。因此，它非常适合各种用途，包括评估分子对接程序产生的构象质量以及比较构象异构体。比较了rmsd和GARD评估对接软件的能力，并展示了多个使用GARD挽救具有高rmsd的基本正确构象的示例。
