Gupta-Ostermann Disha, Bajorath Jürgen
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, D-53113, Germany.
F1000Res. 2014 May 16;3:113. doi: 10.12688/f1000research.4185.2. eCollection 2014.
We describe the 'Structure-Activity Relationship (SAR) Matrix' (SARM) methodology that is based upon a special two-step application of the matched molecular pair (MMP) formalism. The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets. It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces. The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.
我们描述了基于匹配分子对(MMP)形式主义的特殊两步应用的“构效关系(SAR)矩阵”(SARM)方法。SARM方法最初是为从化合物数据集中提取、组织和可视化化合物系列及相关SAR信息而设计的。它已得到进一步发展并适用于其他应用,包括化合物设计、活性预测、库扩展以及多靶点活性空间的导航。本文介绍了SARM方法及其扩展,以引入不同类型的应用,并为药物研究中计算方法的发展提供一个示例。