Andrew Dalke Scientific AB , SE-461 30 Trollhättan , Sweden.
Roche Pharma Research and Early Development , Roche Innovation Center, CH-4070 Basel , Switzerland.
J Chem Inf Model. 2018 May 29;58(5):902-910. doi: 10.1021/acs.jcim.8b00173. Epub 2018 May 17.
Matched molecular pair analysis (MMPA) enables the automated and systematic compilation of medicinal chemistry rules from compound/property data sets. Here we present mmpdb, an open-source matched molecular pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large data sets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. It is freely available from https://github.com/rdkit/mmpdb .
匹配分子对分析（MMPA）使从化合物/性质数据集自动系统地编译药物化学规则成为可能。这里我们介绍 mmpdb，这是一个开源的匹配分子对（MMP）平台，用于创建、编译、存储、检索和使用 MMP 规则。mmpdb 适用于制药和农化公司中通常发现的大型数据集，并提供用于片段规范化和立体化学处理的新算法。该平台是用 Python 编写的，并基于 RDKit 工具包。它可以从 https://github.com/rdkit/mmpdb 免费获得。
