AB INITIO CI CHARACTERIZATION OF THE LOW-LYING EXCITED SINGLET AND TRIPLET STATES OF PYRAZINE, PORPHINE, AND MAGNESIUM PORPHIN

This work was supported, in part, by the Division of Physical Research, ERDA.Author Institution: Chemistry Division, Argonne National Laboratory; Department of Chemistry, University of Kansas; Department of Biochemistry, University of KansasAb initio CI calculations in an FSGO basis have been carried out the lower excited singlet and triplet states of the title molecules. The calculated $S_{o} \rightarrow S_{n}$ and $S_{o} \rightarrow T_{n}$ energies were found to be linearly related to the experimentally observed transition energies. Transition energies, polarizations, and oscillator strengths have been compared with experimental data, where available. It was found that this method treats singlet $\pi-\pi^{*}$, triplet $\pi-\pi^{*}$, singlet $\pi-\pi^{*}$, and triplet $\pi-\pi^{*}$ transition energies equally well

Conditional Probabilities of Activity Landscape Features for Individual Compounds

Activity landscape representations aid in the analysis of structure–activity relationships (SARs) of large compound data sets. Landscapes are characterized by features with different SAR information content such as, for example, regions formed by structurally diverse compounds having similar activity or, alternatively, structurally similar compounds with large activity differences, so-called activity cliffs. Modeling of activity landscapes typically requires pairwise comparisons of molecular similarity and potency relationships of compounds in a data set. Consequently, landscape features are generally resolved at the level of compound pairs. Herein, we introduce a methodology to assign feature probabilities to individual compounds. This makes it possible to organize compounds comprising activity landscapes into well-defined SAR categories. Specifically, the calculation of conditional feature probabilities of active compounds provides a balanced and further refined view of activity landscapes with a focus on individual molecules

A cell-based fascin bioassay identifies compounds with potential anti-metastasis or cognition-enhancing functions

Le Centre de cartographie du monde antique de l'Université de Caroline du Nord (AWMC) se donne pour vocation de diffuser de l'information sur la cartographie et la géographie historique et de développer des ressources cartographiques à destination des communautés de recherches impliquées dans l'étude du Monde antique. L'AWMC reprend et continue le travail de numérisation et de diffusion de cartes de la Méditerranée antique amorcé par l'Interactive Ancient Mediterranean. Dans sa rubrique « fre..

Consensus Models of Activity Landscapes with Multiple Chemical, Conformer, and Property Representations

We report consensus Structure–Activity Similarity (SAS) maps that address the dependence of activity landscapes on molecular representation. As a case study, we characterized the activity landscape of 54 compounds with activities against human cathepsin B (hCatB), human cathepsin L (hCatL), and Trypanosoma brucei cathepsin B (TbCatB). Starting from an initial set of 28 descriptors we selected ten representations that capture different aspects of the chemical structures. These included four 2D (MACCS keys, GpiDAPH3, pairwise, and radial fingerprints) and six 3D (4p and piDAPH4 fingerprints with each including three conformers) representations. Multiple conformers are used for the first time in consensus activity landscape modeling. The results emphasize the feasibility of identifying consensus data points that are consistently formed in different reference spaces generated with several fingerprint models, including multiple 3D conformers. Consensus data points are not meant to eliminate data, disregarding, for example, “true” activity cliffs that are not identified by some molecular representations. Instead, consensus models are designed to prioritize the SAR analysis of activity cliffs and other consistent regions in the activity landscape that are captured by several molecular representations. Systematic description of the SARs of two targets give rise to the identification of pairs of compounds located in the same region of the activity landscape of hCatL and TbCatB suggesting similar mechanisms of action for the pairs involved. We also explored the relationship between property similarity and activity similarity and found that property similarities are suitable to characterize SARs. We also introduce the concept of structure–property-activity (SPA) similarity in SAR studies