Chemical Biology, Chulabhorn Graduate Institute, 54 Kamphaeng Phet 6 Road, Talat Bang Khen sub-district, Lak Si district, Bangkok, 10210, Thailand.
School of Chemical Sciences, University of Auckland Private Bag 92019, Auckland, 1142, New Zealand.
Mol Inform. 2019 Mar;38(3):e1800068. doi: 10.1002/minf.201800068. Epub 2018 Oct 22.
1880 known drugs were collected and analysed for their mainstream molecular descriptors: MW, log P, HA, HD, RB and PSA. The statistical distributions were fitted to Gaussian functions for each of the descriptors. This gave a mathematical tool to calculate a weighted score, or an Index, for each descriptor. Known Drug Indexes (KDIs) were derived either by summation or multiplication of the Indexes, giving one number for each molecule calculated. The KDI summation and multiplication methods give a theoretical maxima of 6 and 1 respectively. According to both methods, methysergide (5.89/0.90), amsacrine (5.89/0.89) and fluorometholone (5.88/0.88) have the scores of the most well-balanced pharmaceuticals. The KDIs are advantageous tools in identifying the most well-balanced screening compounds based on the properties of known drugs; the screening collection can be optimised to only include quality compounds, which in turn produce tractable hit and lead compounds from the screening campaign.
收集了 1880 种已知药物，并对其主流分子描述符进行了分析：MW、log P、HA、HD、RB 和 PSA。为每个描述符的统计分布拟合了高斯函数。这为计算每个描述符的加权分数（或指数）提供了一个数学工具。通过对指数进行求和或相乘，可以得到已知药物指数（KDIs），从而为每个计算的分子生成一个数字。KDI 求和法和乘法法的理论最大值分别为 6 和 1。根据这两种方法，麦角乙脲（5.89/0.90）、安吖啶（5.89/0.89）和氟米龙（5.88/0.88）具有最平衡药物的评分。KDIs 是根据已知药物的特性识别最平衡筛选化合物的有利工具；筛选集可以优化为仅包含优质化合物，这反过来又可以从筛选活动中产生易于处理的命中和先导化合物。
