SAR Matrix Method for Large-Scale Analysis of Compound Structure-Activity Relationships and Exploration of Multitarget Activity Spaces

Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications

Analogue series play a key role in drug discovery. They arise naturally in lead optimization efforts where analogues are explored based on one or a few core structures. However, it is much harder to accurately identify and extract pairs or series of analogue molecules in large compound databases with no predefined core structures. This methodological review outlines the most common and recent methodological developments to automatically identify analogue series in large libraries. Initial approaches focused on using predefined rules to extract scaffold structures, such as the popular Bemis-Murcko scaffold. Later on, the matched molecular pair concept led to efficient algorithms to identify similar compounds sharing a common core structure by exploring many putative scaffolds for each compound. Further developments of these ideas yielded, on the one hand, approaches for hierarchical scaffold decomposition and, on the other hand, algorithms for the extraction of analogue series based on single-site modifications (so-called matched molecular series) by exploring potential scaffold structures based on systematic molecule fragmentation. Eventually, further development of these approaches resulted in methods for extracting analogue series defined by a single core structure with several substitution sites that allow convenient representations, such as R-group tables. These methods enable the efficient analysis of large data sets with hundreds of thousands or even millions of compounds and have spawned many related methodological developments.

Promiscuous Ligands from Experimentally Determined Structures, Binding Conformations, and Protein Family-Dependent Interaction Hotspots

Compound promiscuity is often attributed to nonspecific binding or assay artifacts. On the other hand, it is well-known that many pharmaceutically relevant compounds are capable of engaging multiple targets in vivo, giving rise to polypharmacology. To explore and better understand promiscuous binding characteristics of small molecules, we have searched X-ray structures (and very few qualifying solution structures) for ligands that bind to multiple distantly related or unrelated target proteins. Experimental structures of a given ligand bound to different targets represent high-confidence data for exploring promiscuous binding events. A total of 192 ligands were identified that formed crystallographic complexes with proteins from different families and for which activity data were available. These "multifamily" compounds included endogenous ligands and were often more polar than other bound compounds and active in the submicromolar range. Unexpectedly, many promiscuous ligands displayed conserved or similar binding conformations in different active sites. Others were found to conformationally adjust to binding sites of different architectures. A comprehensive analysis of ligand-target interactions revealed that multifamily ligands frequently formed different interaction hotspots in binding sites, even if their bound conformations were similar, thus providing a rationale for promiscuous binding events at the molecular level of detail. As a part of this work, all multifamily ligands we have identified and associated activity data are made freely available.