6533b82bfe1ef96bd128dff9
RESEARCH PRODUCT
Prediction and Discrimination of Pharmacological Activity by Using Artificial Neural Networks
María José CastroWladimiro DíazPablo AibarJ. L. Domínguezsubject
Artificial neural networkCombinatorial Chemistry TechniquesComputer sciencebusiness.industryTopological indexMoleculeBiological activityArtificial intelligencebusinessBiological systemdescription
The design of new medical drugs is a very complex process in which combinatorial chemistry techniques are used. For this reason, it is very useful to have tools to predict and to discriminate the pharmacological activity of a given molecular compound so that the laboratory experiments can be directed to those molecule groups in which there is a high probability of finding new compounds with the desired properties. This work presents an application of Artificial Neural Networks to the problem of discriminating and predicting pharmacological characteristics of a molecular compound from its topological properties. A large amount of different configurations are tested, yielding very good performances.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2003-01-01 |