Su, Bo-Han published the artcileIn Silico Binary Classification QSAR Models Based on 4D-Fingerprints and MOE Descriptors for Prediction of hERG Blockage, COA of Formula: C13H10F2, the publication is Journal of Chemical Information and Modeling (2010), 50(7), 1304-1318, database is CAplus and MEDLINE.
Blockage of the human ether-a-go-go related gene (hERG) potassium ion channel is a major factor related to cardiotoxicity. Hence, drugs binding to this channel have become an important biol. end point in side effects screening. A set of 250 structurally diverse compounds screened for hERG activity from the literature was assembled using a set of reliability filters. This data set was used to construct a set of two-state hERG QSAR models. The descriptor pool used to construct the models consisted of 4D-fingerprints generated from the thermodn. distribution of conformer states available to a mol., 204 traditional 2D descriptors and 76 3D VolSurf-like descriptors computed using the Mol. Operating Environment (MOE) software. One model is a continuous partial least-squares (PLS) QSAR hERG binding model. Another related model is an optimized binary classification QSAR model that classifies compounds as active or inactive. This binary model achieves 91% accuracy over a large range of mol. diversity spanning the training set. Two external test sets were constructed. One test set is the condensed PubChem bioassay database containing 876 compounds, and the other test set consists of 106 addnl. compounds found in the literature. Both of the test sets were used to validate the binary QSAR model. The binary QSAR model permits a structural interpretation of possible sources for hERG activity. In particular, the presence of a polar neg. group at a distance of 6-8 ? from a hydrogen bond donor in a compound is predicted to be a quite structure-specific pharmacophore that increases hERG blockage. Since a data set of high chem. diversity was used to construct the binary model, it is applicable for performing general virtual hERG screening.
Journal of Chemical Information and Modeling published new progress about 457-68-1. 457-68-1 belongs to catalysis-chemistry, auxiliary class Fluoride,Benzene, name is Bis(4-fluorophenyl)methane, and the molecular formula is C9H8BNO2, COA of Formula: C13H10F2.
Referemce:
https://courses.lumenlearning.com/boundless-chemistry/chapter/catalysis/,
Catalysis – Wikipedia