ADMET rules of thumb II: A comparison of the effects of common substituents on a range of ADMET parameters

Gleeson, M. Paul; Bravi, Gianpaolo; Modi, Sandeep; Lowe, Daniel M.

doi:10.1016/j.bmc.2009.07.002

Cited by 98 publications

(96 citation statements)

References 22 publications

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“…Two studies have been published recently that are dedicated to the analysis of the influence of physicochemical properties and most popular substituents of organic compounds on ADME and toxicity parameters, including CYP3A4 inhibition [42,45]. The predictions of the baseline model obtained for virtual compounds in Table 5 are within a good agreement with results of these studies.…”

Section: Resultssupporting

confidence: 70%

Trainable structure–activity relationship model for virtual screening of CYP3A4 inhibition

Didžiapetris¹,

Dapkūnas

Sazonovas³

et al. 2010

J Comput Aided Mol Des

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A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC₅₀ threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis.

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Section: Resultssupporting

confidence: 70%

Trainable structure–activity relationship model for virtual screening of CYP3A4 inhibition

Didžiapetris¹,

Dapkūnas

Sazonovas³

et al. 2010

J Comput Aided Mol Des

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“…More recent studies [7][8][9] have shown, however, that compounds close to the Lipinski limits actually have a lower probability of success in development with significantly lower mw and LogP values favored in successful medicines. These observations have led to several revised guidelines suggesting, for example, that molecules with LogP < 3 and polar surface area [10] > 75 2 will show greater safety in pre-clinical studies [9] or that molecules with mw < 400 and LogP < 4 appear to be more successful in a range of assays of drug-like character.…”

Section: Properties Of Successful Hits and Drugsmentioning

confidence: 93%

Lead‐Oriented Synthesis: A New Opportunity for Synthetic Chemistry

2012

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The pharmaceutical industry remains solely reliant on synthetic chemistry methodology to prepare compounds for small-molecule drug discovery programmes. The importance of the physicochemical properties of these molecules in determining their success in drug development is now well understood but we present here data suggesting that much synthetic methodology is unintentionally predisposed to producing molecules with poorer drug-like properties. This bias may have ramifications to the early hit- and lead-finding phases of the drug discovery process when larger numbers of compounds from array techniques are prepared. To address this issue we describe for the first time the concept of lead-oriented synthesis and the opportunity for its adoption to increase the range and quality of molecules used to develop new medicines.

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“…Along these lines, matched molecular pairs have been analysed for the effect against various antitargets, such as CYPs or hERG. [18,21] Generally, a stronger effect was observed for those substituents which have a large influence on lipophilicity (logD). [21] Both for progressive and conservative substituent changes, a significant number of matched molecular pairs without significant effects on the antitarget response has been observed.…”

Section: Discussionmentioning

confidence: 93%

“…[21] Both for progressive and conservative substituent changes, a significant number of matched molecular pairs without significant effects on the antitarget response has been observed. [18,21] These results indicate, that the exact position of the modification imposes a significant influence on the biological effect on top of a general trend set by physicochemical property modulation.…”

Section: Discussionmentioning

confidence: 97%

Identification and Application of Antitarget Activity Hotspots to Guide Compound Optimization

Heßler

Matter

Schmidt

et al. 2011

Molecular Informatics

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The optimization of a lead structure to a development candidate often requires removal of undesirable antitarget activities. To this end, we have developed an approach to extract antitarget activity hotspots from larger databases and to transfer this knowledge onto novel chemical series. These antitarget activity hotspots will be captured as pairs of informative molecules, which are chemically closely related, but differ significantly in biological activity. We illustrate the application of antitarget activity hotspots as informative compound pairs for the optimization of side effects in lead structures for relevant antitargets in pharmaceutical research. The use for prospective design requires establishing a structural link between known antitarget hotspot pairs and a new lead structure: we employ 3D-based similarity comparison for this task. The entire workflow serves as idea generator in early optimization. The feasibility of this approach is demonstrated in several optimization problems related to hERG inhibition, and CYP3A4 inhibition. Several structural examples demonstrate the ability of the 3D-shape searching to identify related scaffolds and the usefulness of the antitarget hotspot information to guide optimization by modulating the undesirable antitarget activity. Such a concept based on the analysis of local similarities and the transfer to 3D-related series is especially promising in those cases, where the construction of antitarget QSAR models fails to detect local SAR trends for guiding the next optimization cycle.

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ADMET rules of thumb II: A comparison of the effects of common substituents on a range of ADMET parameters

Cited by 98 publications

References 22 publications

Trainable structure–activity relationship model for virtual screening of CYP3A4 inhibition

Trainable structure–activity relationship model for virtual screening of CYP3A4 inhibition

Lead‐Oriented Synthesis: A New Opportunity for Synthetic Chemistry

Identification and Application of Antitarget Activity Hotspots to Guide Compound Optimization

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