2022-07-01 17:00


Conference: Bucharest University Faculty of Physics 2019 Meeting

Section: Biophysics; Medical Physics

The therapeutic role of natural compounds in depressive pathology. Bioinformatics and cheminformatics approach

Adina MIRICĂ (1), Speranța AVRAM (2)

1) Faculty of Biology, University of Bucharest, Splaiul Independenței 91-95, Bucharest, Romania

2) Department of Anatomy, Animal Physiology an Biophysics, Faculty of Biology, University of Bucharest, Splaiul Independenței 91-95, Bucharest, Romania


Bioinformatics, cheminformatics, natural compounds, prediction

Clinical depression is defined as a state of sadness that persists over prolonged periods. It is one of the most common mental disorders, affecting a growing segment of the population worldwide. It is believed that only a small part of those who suffer from depression become aware of this condition and undergo appropriate treatment. Today, clinicians benefit from a wide range of options when it comes to antidepressants. However, no drug is free from side effects, so at present scientific literature data confirms the possible antidepressant role of natural compounds, side effects being less present in their case. In this study, employing bioinformatics and cheminformatics techniques, we were able to identify the possible antidepressant role of the natural compounds. The scientific literature provided extensive data regarding these natural compounds: camazulene, lavandulyl acetate, linalyl acetate, morin, nerol, neryl acetate, pinosylvin, quercitin. Our research involved: obtaining the SMILES files to identify the molecular mechanisms and targets of the compounds of interest in the depressive pathology and their expression in the brain, and also identifying ADMET properties (absorption, distribution, metabolism, excretion and toxicity). These results allowed further studies, in order to obtain new classes of antidepressants, based on natural compounds and characterized by a reduced side effects, enabling a more efficient action on the main causes of depression.


1.Avram, Speranța; Puia, Alin; Udrea, Ana, Maria; Mihăilescu, Dan; Mernea, Maria; Dinischiotu, Anca; Oancea, Florin; Stiens, Johan; 2017. Natural Compounds therapeutic features in brain disorders by experimental, bioinformatics and cheminformatics methods. Curr. Med. Chem., 1.

2.Ruiz, N. A. L., del Ángel, D. S., Olguín, H. J., & Silva, M. L., 2018 . Neuroprogression: the hidden mechanism of depression. Neuropsychiatr. Dis. Treat., 14, 2837–2845.

3.Gfeller, D., Grosdidier, A., Wirth, M., Daina, A., Michielin, O., & Zoete, V., 2014. SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Nucleic Acids Res., 42(Web Server issue), W32-38.