title: [Computer evaluation of hidden potential of phytochemicals of medicinal plants of the traditional Indian ayurvedic medicine].
abstract: Applicability of our computer programs PASS and PharmaExpert to prediction of biological activity spectra of rather complex and structurally diverse phytocomponents of medicinal plants, both separately and in combinations has been evaluated. The web-resource on phytochemicals of 50 medicinal plants used in Ayurveda was created for the study of hidden therapeutic potential of Traditional Indian Medicine (TIM) (http://ayurveda.pharmaexpert.ru). It contains information on 50 medicinal plants, their using in TIM and their pharmacology activities, also as 1906 phytocomponents. PASS training set was updated by addition of information about 946 natural compounds; then the training procedure and validation were performed, to estimate the quality of PASS prediction. It was shown that the difference between the average accuracy of prediction obtained in leave-5%-out cross-validation (94,467%) and in leave-one-out cross-validation (94,605%) is very small. These results showed high predictive ability of the program. Results of biological activity spectra prediction for all phytocomponents included in our database are in good correspondence with the experimental data. Additional kinds of biological activity predicted with high probability provide the information about most promising directions of further studies. The analysis of prediction results of sets of phytocomponents in each of 50 medicinal plants was made by PharmaExpert software. Based on this analysis, we found that the combination of phytocomponents from Passiflora incarnata may exhibit nootropic, anticonvulsant and antidepressant effects. Experiments carried out in mice models confirmed the predicted effects of Passiflora incarnata extracts.
authors.affiliation: Institute of Biomedical Chemistry, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia.
authors.forename: A A
authors.initials: AA
authors.lastname: Lagunin
authors.affiliation: Institute of Biomedical Chemistry, Moscow, Russia.
authors.forename: D S
authors.initials: DS
authors.lastname: Druzhilovsky
authors.affiliation: Institute of Biomedical Chemistry, Moscow, Russia.
authors.forename: A V
authors.initials: AV
authors.lastname: Rudik
authors.affiliation: Institute of Biomedical Chemistry, Moscow, Russia.
authors.forename: D A
authors.initials: DA
authors.lastname: Filimonov
authors.affiliation: Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala-147002 India.
authors.forename: D
authors.initials: D
authors.lastname: Gawande
authors.affiliation: Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala-147002 India.
authors.forename: K
authors.initials: K
authors.lastname: Suresh
authors.affiliation: Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala-147002 India.
authors.forename: R
authors.initials: R
authors.lastname: Goel
authors.affiliation: Institute of Biomedical Chemistry, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia.
authors.forename: V V
authors.initials: VV
authors.lastname: Poroikov
mesh_terms: D000818:Animals; D000928:Antidepressive Agents / Q000737:chemistry / Q000494:pharmacology; D030024:Curcuma / Q000737:chemistry; D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D008515:Medicine, Ayurvedic; D051379:Mice; D029598:Passiflora / Q000737:chemistry; D064209:Phytochemicals / Q000737:chemistry / Q000494:pharmacology*; D010936:Plant Extracts / Q000494:pharmacology; D010946:Plants, Medicinal / Q000737:chemistry*; D015203:Reproducibility of Results; D012984:Software
chemical_list: D000928:Antidepressive Agents; D064209:Phytochemicals; D010936:Plant Extracts
keywords: Ayurveda; PASS; PharmaExpert; SAR; biological activity; computational prediction; medicinal plants; phytocomponents