by Marina Chenery | Oct 14, 2022 | General, In Silico Modelling, Metabolism, Publications and presentations
This paper describes the prediction of the regioselectivity of metabolism by AOs, FMOs and UGTs for humans and CYPs for three preclinical species. The research extends from previous work developing the StarDrop™ P450 module. Visit the P450 webpage to discover how...
by Marina Chenery | Nov 18, 2019 | In Silico Modelling, Publications and presentations
Summary The ability to predict the propensity of a molecule to lose or gain a proton in water is crucial for the development of new chemical entities with desirable pharmacokinetic (PK), absorption, distribution, metabolism and excretion (ADME) and binding properties....
by Marina Chenery | Feb 14, 2019 | In Silico Modelling, Publications and presentations
This article describes a novel deep learning neural network method and its application for the imputation of assay pIC50 values. These deep learning methods underpin our Cerella™ technology, part of our Augmented Chemistry® suite. Summary In this study, the...
by Marina Chenery | Aug 23, 2018 | In Silico Modelling, Publications and presentations
Hydrogen Bonding: Ab Initio Accuracy From Fast Interatomic Gaussian Approximation Potentials Mario Öeren gave this presentation at the ACS Fall 2018 National Meeting & Exposition held in Boston, USA. Abstract Non-covalent, electrostatic interactions play a...
by Marina Chenery | Mar 7, 2018 | In Silico Modelling, Publications and presentations
Deep Learning and Chemistry At our 2018 Drug Discovery Consultants’ Day, Professor Bobby Glen of the University of Cambridge gave an excellent overview of developments in deep learning and its application to chemistry. You can download his slides as...
by Marina Chenery | Mar 7, 2018 | In Silico Modelling, Publications and presentations
Imputation of Protein Activity Data using Deep Learning Presentation 2 At Optibrium’s 2018 Drug Discovery Consultants’ Day, Dr Gareth Conduit from University of Cambridge and Intellegens Ltd. described their deep learning methods for predicting compound...