Christine Humblet

The medicinal chemistry community has become increasingly aware of the value of tracking calculated physical properties such as molecular weight, topological polar surface area, rotatable bonds, and hydrogen bond donors and acceptors. We hypothesized that the shift to high-throughput synthetic practices over the past decade may be another factor that may predispose molecules to fail by steering discovery efforts toward achiral, aromatic compounds. We have proposed two simple and interpretable measures of the complexity of molecules prepared as potential drug candidates. The first is carbon bond saturation as defined by fraction sp(3) (Fsp(3)) where Fsp(3) = (number of sp(3) hybridized carbons/total carbon count). The second is simply whether a chiral carbon exists in the molecule. We demonstrate that both complexity (as measured by Fsp(3)) and the presence of chiral centers correlate with success as compounds transition from discovery, through clinical testing, to drugs. In an attempt to explain these observations, we further demonstrate that saturation correlates with solubility, an experimental physical property important to success in the drug discovery setting.

Molecular docking programs are widely used modeling tools for predicting ligand binding modes and structure based virtual screening. In this study, six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) were evaluated using metrics intended to assess docking pose and virtual screening accuracy. Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-ray conformation more often than the other docking programs. GLIDE and Surflex also outperformed the other docking programs when used for virtual screening, based on mean ROC AUC and ROC enrichment values obtained for the 40 protein targets in the Directory of Useful Decoys (DUD). Further analysis uncovered general trends in accuracy that are specific for particular protein families. Modifying basic parameters in the software was shown to have a significant effect on docking and virtual screening results, suggesting that expert knowledge is critical for optimizing the accuracy of these methods.

The design, synthesis, and pharmacological properties of a novel type of 4-(1,2,5,6-tetrahydro-1-alkyl-3-pyridinyl)-2-thiazolamine with dopaminergic properties are described. In particular, 4-(1,2,5,6-tetrahydro-1-propyl-3-pyridinyl)-2-thiazolamine (4c, PD 118440) and its allyl analogue (4i, PD 120697) have been identified as orally active dopamine (DA) agonists with pronounced central nervous system effects in tests that include [3H]-haloperidol and [3H]-N-propylnorapomorphine binding, inhibition of striatal DA synthesis, inhibition of DA neuronal firing, inhibition of spontaneous locomotor activity, and reversal of reserpine-induced depression in rats. The DA autoreceptor selectivity of these heterocyclic analogues of 3-(1-propyl-3-piperidinyl)phenol (3-PPP) was also evaluated. In this series, DA agonist activity was found to be highly dependent on the size of the N-alkyl substituent, the saturation level of the six-membered ring, and the mode of attachment of the 2-aminothiazole ring.

An algorithm, Stigmata, is described, which extracts structural commonalities from chemical datasets. It is discussed using several illustrative examples and a pharmaceutically interesting set of dopamine D2 agonists. The commonalities are determined using two-dimensional topological chemical descriptions and are incorporated into the key feature of the algorithm, the modal fingerprint. Flexibility is built into the algorithm by means of a user-defined threshold value, which affects the information content of the modal fingerprint. The use of the modal fingerprint as a diversity assessment tool, as a database similarity query, and as a basis for color mapping the determined commonalities back onto the chemical structures is demonstrated.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTMolecular modeling software and methods for medicinal chemistryN. Claude Cohen, Jeffrey M. Blaney, Christine Humblet, Peter Gund, and David C. BarryCite this: J. Med. Chem. 1990, 33, 3, 883–894Publication Date (Print):March 1, 1990Publication History Published online1 May 2002Published inissue 1 March 1990https://pubs.acs.org/doi/10.1021/jm00165a001https://doi.org/10.1021/jm00165a001research-articleACS PublicationsRequest reuse permissionsArticle Views1049Altmetric-Citations123LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts