Rognan, Didier

Protein-based virtual screening of chemical databases. 1, evaluation of different docking/scoring combinations.

Bissantz, C., Folkers, G., & Rognan, D. (2000) · Journal of Medicinal Chemistry

Computational Drug Discovery MethodsCholinesterase and Neurodegenerative Diseases

Cited by 740

Comparative evaluation of eight docking tools for docking and virtual screening accuracy

Kellenberger, E., Rodrigo, J., Muller, P., & Rognan, D. (2004) · Proteins: Structure, Function, and Bioinformatics

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 577

Identification of a low–molecular weight TrkB antagonist with anxiolytic and antidepressant activity in mice

Cazorla, M., Prémont, J., Mann, A., Girard, N., Kellendonk, C., & Rognan, D. (2011) · Journal of Clinical Investigation

Treatment of Major DepressionNerve injury and regeneration

Cited by 392

Beware of machine learning-based scoring functions-on the danger of developing black boxes.

Gabel, J., Desaphy, J., & Rognan, D. (2014) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 143

Customized versus universal scoring functions

Logean, A., Sette, A., & Rognan, D. (2001) · Bioorganic & Medicinal Chemistry Letters

Computational Drug Discovery Methodsvaccines and immunoinformatics approaches

Cited by 46

Behavioral and neurochemical characterization of TrkB-dependent mechanisms of agomelatine in glucocorticoid receptor-impaired mice

Boulle, F., Velthuis, H., Koedam, K., Steinbusch, H. W., van den Hove, D. L. A., Kenis, G., Gabriel, C., Mocaer, E., Franc, B., Rognan, D., et al. (2016) · European Neuropsychopharmacology

Treatment of Major DepressionStress Responses and Cortisol

Cited by 24