Global Assessment of Substituents on the Basis of Analogue Series

Abstract

While bioisosteric replacements have been extensively investigated, comprehensive analyses of R-/functional groups have thus far been rare in medicinal chemistry. We introduce a new analysis concept for the exploration of chemical substituent space that is based upon bioactive analogue series as a source. From ∼24,000 analogue series, more than 19,000 substituents were isolated that were differently distributed. A subset of ∼400 substituent fragments occurred most frequently in different structural contexts. These substituents contained well-known R-groups as well as novel structures. Substitution site-specific replacement and network analysis revealed that chemically similar substituents preferentially occurred at given sites and identified intuitive substitution pathways that can be explored for compound design. Taken together, the results of our analysis provide new insights into substituent space and identify preferred substituents on the basis of analogue series. As a part of our study, all the data reported are made freely available.

Introducing a Chemically Intuitive Core-Substituent Fingerprint Designed to Explore Structural Requirements for Effective Similarity Searching and Machine Learning

“…All extracted cores contained ring structures, and these cores were then decomposed into fused and single rings, as described below. The resulting core fragments were complemented with an equally sized set of most frequently occurring substituent fragments selected from an R-group replacement database we have recently generated and made publicly available [ 31 ], resulting from a new methodology for systematically extracting R-groups from compounds [ 32 ].…”

“…Accordingly, the benzene ring was only permitted as a ring fragment, thereby avoiding ambiguous assignments that would occur with high frequency. From the R-group resource, the 500 most frequent substituents obtained by random bond fragmentation and by fragmentation on the basis of retrosynthetic rules [ 32 ], respectively, were selected and combined. These subsets displayed a large overlap, as to be expected, and yielded a total of 661 unique substituent fragments.…”

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

“…For the design of analogue compounds, the investigation of substituent fragments and the popularity of analogue sets is of considerable interest. Takeuchi and Bajorath [ 87 , 88 ] investigated the substituent space utilizing CCR analogue series obtained from ChEMBL [ 10 ]. For the 500 most popular fragments, preferential replacements were identified and organized in a hierarchical structure.…”

R-group Replacement Database for Medicinal Chemistry

“…Apart from the analysis of bioisosteres, only few studies have investigated R-groups in a general way. For example, algorithms have been introduced for extracting R-groups from individual compounds [ 7 ] or ASs [ 8 ] and two recent studies have systematically identified R-groups across currently available bioactive compounds [ 8 , 9 ]. We have further extended the assessment of R-groups on the basis of ASs [ 8 ] by generalizing the approach and identified all R-groups that currently occur in ASs (unpublished results).…”

“…For example, algorithms have been introduced for extracting R-groups from individual compounds [ 7 ] or ASs [ 8 ] and two recent studies have systematically identified R-groups across currently available bioactive compounds [ 8 , 9 ]. We have further extended the assessment of R-groups on the basis of ASs [ 8 ] by generalizing the approach and identified all R-groups that currently occur in ASs (unpublished results). As a part of this study, we have generated a searchable database of frequent R-groups and their preferred replacements.…”