Abstract
Background: A recent comparison showed the extensive similarities between the structural properties of metabolites in the reconstructed human metabolic network (“endogenites”) and those of successful, marketed drugs (“drugs”).Results: Clustering indicated the related but differential population of chemical space by endogenites and drugs. Differences between the drug-endogenite similarities resulting from various encodings and judged by Tanimoto similarity could be related simply to the fraction of the bitstrings set to 1. By extracting drug/endogenite substructures, we develop a novel family of fingerprints, the Drug Endogenite Substructure (DES) encodings, based on the ranked frequency of the various substructures. These provide a natural assessment of drug-endogenite likeness, and may be used as descriptors with which to derive quantitative structure-activity relationships (QSARs).Conclusions: “Drug-endogenite likeness” seems to have utility, and leads to a simple, novel and interpretable substructure-based molecular encoding for cheminformatics.
Highlights
At least for the Morgan and Feat Morgan encodings, that resemble ECFP and FCFP (Landrum et al, 2011), this can be ascribed in part to the much smaller number of bits in the encoding that have the value 1 (Figure 3B), since the value for the Tanimoto similarity (TS) is partly a function of this (Flower, 1998; Godden et al, 2000; Holliday et al, 2002, 2003; Wang et al, 2007; Al Khalifa et al, 2009). [In a similar vein, we looked at the use of a strategy that doubles the length of the bitstring encoding by adding its complement (Knuth, 1986), such that 50% of the bits are 1 and 50% 0
We looked to see whether metabolites that were known substrates for known transporters exhibited any greater likelihood to be those with the nearest TS to the query drug; FIGURE 5 | Relationships between endogenite and marketed drug spaces as judged by self-organizing feature maps trained on marketed drugs as encoded with the MACSS encoding. (A) A self-organizing map with 100 nodes and 10 clusters, trained to convergence
The concept of drug-endogenite likenesses continues to appear to have utility, and substructure analyses of drugs and endogenites show both similarities and differences that have led us to implement here a simple substructure-based cheminformatics encoding family, Drug Endogenite Substructure (DES), that has a clear and interpretable basis
Summary
In a recent study (O’Hagan et al, 2015), motivated by the recognition that drugs do, and probably have to, hitchhike on metabolite transporters in order to get into cells (Dobson and Kell, 2008; Dobson et al, 2009a,b; Giacomini et al, 2010; Kell et al, 2011, 2013, 2015; Kell, 2013, 2015; Kell and Goodacre, 2014; Kell and Oliver, 2014), we have used the recent availability of a curated reconstruction of the human metabolic network, Recon (Swainston et al, 2013; Thiele et al, 2013), to ask the question as to how similar in structural terms marketed drugs are to the molecules (hereafter “endogenites”) involved in endogenous human metabolism. Dalkescientific.com/writings/diary/archive/2014/10/17/maccs_key_44.html), there was at least one endogenite with a Tanimoto similarity (TS) exceeding 0.5 for more than 90% of marketed drugs. While the results depended quite considerably on the exact 2D descriptor used to encode the structures, it was noted that for the commonly used MACCS166 descriptor (Durant et al, 2002; Todeschini and Consonni, 2009) in the implementation described As noted in those references (Durant et al, 2002; Todeschini and Consonni, 2009), the MACCS166 descriptor consists of a string of 166 binary elements representing the presence or absence of 166 (slightly arbitrary and not necessarily druglike) features. A recent comparison showed the extensive similarities between the structural properties of metabolites in the reconstructed human metabolic network (“endogenites”) and those of successful, marketed drugs (“drugs”)
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