Modular computational models for predicting the pharmaceutical properties of chemical compounds
OwnerAlbert Benight, Peter Riccelli +2inventors
InventorsAlbert Benight, Peter Riccelli, Anton Hopfinger, Petr Pancoska
Life of this patent
Estimating the term…
Abstract
The methods of the invention allow for the construction and/or use of modular computational models to accurately predict the therapeutic properties, including both therapeutic potency and one or more ADMET properties, of all or part of a chemical compound. The modular computational models can be used to rapidly screen libraries of chemical compounds, and reliably identify small subsets of those chemical compounds that have desirable therapeutic potency and ADMET properties, and are thus the best overall drug candidates.
Claims18
A method of constructing a modular computational model for predicting one or more therapeutic properties of a chemical compound, comprising:
- obtaining a first set of data describing the interaction between each training compound of a first set of training compounds and a first interaction partner;
- and
- using the first set of data, along with data about the chemical structures and/or physical properties thereof of the first set of training compounds and, optionally, data about the three dimensional structure and/or physical properties thereof of the first interaction partner, to construct a first module that uses data about the chemical structures and/or physical properties thereof of chemical compounds to predict values describing the interaction between a chemical compound and the first interaction partner, wherein the predicted values are the same type of data as the data contained in the first set of data;
- thereby constructing a single module modular computational model for predicting one or more therapeutic properties of a chemical compound.
18-28. (canceled)
Dependencies are inferred from the claim text.