Chemoinformatics at the University of Sheffield 2002–2014

Gillet, Valerie J.; Holliday, John D.; Willett, Peter

doi:10.1002/minf.201500004

Cited by 6 publications

(9 citation statements)

References 86 publications

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“…Willett and colleagues have suggested that 'fusing' the results of different fingerprint encodings may give more robust analyses [139][140][141][142][143][144][145]. Our strategy is somewhat similar in that we recognise the highly variable rank orders (and Tanimoto similarities) that result from the different encodings, such that their variance tends to increase with their mean rank order.…”

Section: Different Similarities From Different Encodingsmentioning

confidence: 97%

“…Our strategy is somewhat similar in that we recognise the highly variable rank orders (and Tanimoto similarities) that result from the different encodings, such that their variance tends to increase with their mean rank order. Summing (equivalently, averaging) the rank orders (see also [139,145]) was a particularly convenient means of combining the data. When this was done, there was a clear trend to the effect that there was much less variance among those molecules with the most reliably high rank order (numerically small values), leading to a conclusion that for Tanimoto similarity values over ~0.75 or 0.8 the similarities are fairly robust to the specific encoding used, and on that basis may reasonably be considered 'reliable' or 'significant'.…”

Section: Different Similarities From Different Encodingsmentioning

confidence: 99%

See 1 more Smart Citation

Consensus rank orderings of molecular fingerprints illustrate the most genuine similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

O’Hagan¹,

Kell

2017

ADMET DMPK

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We compare several molecular fingerprint encodings for marketed, small molecule drugs, and assess how their rank order varies with the fingerprint in terms of the Tanimoto similarity to the most similar endogenous human metabolite as taken from Recon2. For the great majority of drugs, the rank order varies very greatly depending on the encoding used, and also somewhat when the Tanimoto similarity (TS) is replaced by the Tversky similarity. However, for a subset of such drugs, amounting to some 10 % of the set and a Tanimoto similarity of ~0.8 or greater, the similarity coefficient is relatively robust to the encoding used. This leads to a metric that, while arbitrary, suggests that a Tanimoto similarity of 0.75-0.8 or greater genuinely does imply a considerable structural similarity of two molecules in the drug-endogenite space. Although comparatively few (<10 % of) marketed drugs are, in this sense, robustly similar to an endogenite, there is often at least one encoding with which they are genuinely similar (e.g. TS > 0.75). This is referred to as the Take Your Pick Improved Cheminformatic Analytical Likeness or TYPICAL encoding, and on this basis some 66 % of drugs are within a TS of 0.75 to an endogenite.We next explicitly recognise that natural evolution will have selected for the ability to transport dietary substances, including plant, animal and microbial ‘secondary’ metabolites, that are of benefit to the host. These should also be explored in terms of their closeness to marketed drugs. We thus compared the TS of marketed drugs with the contents of various databases of natural products. When this is done, we find that some 80 % of marketed drugs are within a TS of 0.7 to a natural product, even using just the MACCS encoding. For patterned and TYPICAL encodings, 80 % and 98 % of drugs are within a TS of 0.8 to (an endogenite or) an exogenous natural product. This implies strongly that it is these exogeneous (dietary and medicinal) natural products that are more to be seen as the ‘natural’ substrates of drug transporters (as is recognised, for instance, for the solute carrier SLC22A4 and ergothioneine). This novel analysis casts an entirely different light on the kinds of natural molecules that are to be seen as most like marketed drugs, and hence potential transporter substrates, and further suggests that a renewed exploitation of natural products as drug scaffolds would be amply rewarded.

show abstract

Section: Different Similarities From Different Encodingsmentioning

confidence: 97%

Section: Different Similarities From Different Encodingsmentioning

confidence: 99%

Consensus rank orderings of molecular fingerprints illustrate the most genuine similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

O’Hagan¹,

Kell

2017

ADMET DMPK

View full text Add to dashboard Cite

show abstract

“…That task has been ably accomplished by Willett [1] and by Gillet, Holliday and Willett [5], among others. Nor does it seek to identify what was at any stage the cutting edge of developments, particularly in computerised structure handling; that is well-documented in a number sources over the period [6][7][8][9][10].…”

Section: B(mentioning

confidence: 97%

“…It should particularly be noted that this does not amount to a systematic chronological survey of the development of chemical information systems, and of their intended and actual use. That task has been ably accomplished by Willett [1] and by Gillet et al [5], among others. Nor does it seek to identify what was at any stage the cutting edge of developments, particularly in computerized structure handling; that is well documented in a number sources over the period [6–10].…”

Section: Introductionmentioning

confidence: 99%

‘An intensity around information’: the changing face of chemical information literacy

Bawden

Robinson

2016

Journal of Information Science

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Indeed, Zass [3, p. 946] reminds us that problems in practitioner use of chemical information are long-standing: "sometimes it is forgotten that these 'old times' were not as good as they now seem to be, due to the fact that many chemists lacked appropriate instruction in doing these manual searches. as they now often lack knowledge and experience to make the best use of present databases." The purpose of this paper is to examine the development of the idea of chemical information literacy over time, from the early times before the concept was described in those terms. One intention is to identify which aspects of chemical information literacy have remained constant over time, and which have emerged, disappeared, or changed with changing technologies and changing information environments. A second intention is to identify those aspects which are specific to the domain of chemistry, and those which are generic information literacy concepts which happen to appear in chemistry as in other domains. This latter is a contribution to the long-standing and on-going debate about how far there can be a generic information literacy, and how much it must always be context and subject dependent [4]. A third intention is to identify any threshold concepts of information literacy which may relate specifically to the chemistry domain. While this issue is of particular importance to academic librarians, who have been in the forefront of developing the theory and practice of information literacy, it is relevant to all information specialists dealing with subject-specific materials. Permanent repository link:

show abstract

“…Willett and colleagues have suggested that 'fusing' the results of different fingerprint encodings may give more robust analyses [138][139][140][141][142][143][144]. Our strategy is somewhat similar in that we recognise the highly variable rank orders (and Tanimoto similarities) that result from the different encodings, such that their variance tends to increase with their mean rank order.…”

Section: Different Similarities From Different Encodingsmentioning

confidence: 97%

Consensus rank orderings of molecular fingerprints illustrate the ‘most genuine’ similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

O’Hagan

Kell

2017

Preprint

View full text Add to dashboard Cite

We compare several molecular fingerprint encodings for marketed, small molecule drugs, and assess how their rank order varies with the fingerprint in terms of the Tanimoto similarity to the most similar endogenous human metabolite as taken from Recon2. For the great majority of drugs, the rank order varies very greatly depending on the encoding used, and also somewhat when the Tanimoto similarity (TS) is replaced by the Tversky similarity. However, for a subset of such drugs, amounting to some 10% of the set and a Tanimoto similarity of ~0.8 or greater, the similarity coefficient is relatively robust to the encoding used. This leads to a metric that, while arbitrary, suggests that a Tanimoto similarity of 0.75-0.8 or greater genuinely does imply a considerable structural similarity of two molecules in the drug-endogenite space. Although comparatively few (<10% of) marketed drugs are, in this sense, robustly similar to an endogenite, there is often at least one encoding with which they are genuinely similar (e.g. TS > 0.75). This is referred to as the Take Your Pick Improved Cheminformatic Analytical Likeness or TYPICAL encoding, and on this basis some 66% of drugs are within a TS of 0.75 to an endogenite.We next explicitly recognise that natural evolution will have selected for the ability to transport dietary substances, including plant, animal and microbial 'secondary' metabolites, that are of benefit to the host. These should also be explored in terms of their closeness to marketed drugs. We thus compared the TS of marketed drugs with the contents of various databases of natural products. When this is done, we find that some 80% of marketed drugs are within a TS of 0.7 to a natural product, even using just the MACCS encoding. For patterned and TYPICAL encodings, 80% and 98% of drugs are within a TS of 0.8 to (an endogenite or) an exogenous natural product. This implies strongly that it is these exogeneous (dietary and medicinal) natural products that are more to be seen as the 'natural' substrates of drug transporters (as is recognised, for instance, for the solute carrier SLC22A4 and ergothioneine). This novel analysis casts an entirely different light on the kinds of natural molecules that are to be seen as most like marketed drugs, and hence potential transporter substrates, and further suggests that a renewed exploitation of natural products as drug scaffolds would be amply rewarded.

show abstract

Chemoinformatics at the University of Sheffield 2002–2014

Cited by 6 publications

References 86 publications

Consensus rank orderings of molecular fingerprints illustrate the most genuine similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

Consensus rank orderings of molecular fingerprints illustrate the most genuine similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

‘An intensity around information’: the changing face of chemical information literacy

Consensus rank orderings of molecular fingerprints illustrate the ‘most genuine’ similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

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