AIMC Topic: Receptors, Serotonin

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Practical application of the Average Information Content Maximization (AIC-MAX) algorithm: selection of the most important structural features for serotonin receptor ligands.

Molecular diversity Feb 9, 2017
The Average Information Content Maximization algorithm (AIC-MAX) based on mutual information maximization was recently introduced to select the most discriminatory features. Here, this methodology was applied to select the most significant bits from ...
Machine Learning Drug Discovery Structure-Activity Relationship Ligands Informatics Receptors, Serotonin
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Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7).

Journal of chemical information and modeling Apr 8, 2015
Molecular docking, despite its undeniable usefulness in computer-aided drug design protocols and the increasing sophistication of tools used in the prediction of ligand-protein interaction energies, is still connected with a problem of effective resu...
Machine Learning Algorithms Molecular Docking Simulation Ligands Automation Protein Conformation Receptors, Adrenergic, beta-2 Receptors, Serotonin
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