Natural compounds therapeutic features in brain disorders by experimental, bioinformatics and cheminformatics methods
This publication appears in: Current Medicinal Chemistry
Authors: S. Avram, A. Puia, A. Maria Udrea, D. Mihailescu, M. Alexandra Mernea, A. Dinischiotu, F. Oancea and J. Stiens
Publication Date: Oct. 2018
Background. Synthetic compounds with pharmaceutical applications in brain disorders are daily designed and synthesized, with well first effects but also seldom severe side effects. This imposes the search for alternative therapies based on the pharmaceutical potentials of natural compounds. The natural compounds isolated from various plants and arthropods venom are well known for their antimicrobial (antibacterial, antiviral) and anti-inflammatory activities, but more studies are needed for a better understanding of their structural and pharmacological features with new therapeutic applications. Objectives. Here we present some structural and pharmaceutical features of natural compounds isolated from plants and arthropods venom relevant for their efficiency and potency in brain disorders. We present the polytherapeutic effects of natural compounds belonging to terpenes (limonene), monoterpenoids (1,8-cineole) and stilbenes (resveratrol), as well as natural peptides (apamin, mastoparan and melittin). Methods. Various experimental and in silico methods are presented, with special attention on bioinformatics (natural compounds database, artificial neural network) and cheminformatics (QSAR, drug design, computational mutagenesis, molecular docking). Results. In the present paper we reviewed: (i) recent studies regarding the pharmacological potential of natural compounds in the brain, (ii) the most useful databases containing molecular and functional features of natural compounds and (iii) the most important molecular descriptors of natural compounds in comparison with a few synthetic compounds. Conclusion. Our paper indicates that natural compounds are a real alternative for nervous system therapy and represents a helpful tool for the future papers focused on the study of the natural compounds.