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OSADHI - An online structural and analytics based database for herbs of India.
Kiewhuo, Kikrusenuo; Gogoi, Dipshikha; Mahanta, Hridoy Jyoti; Rawal, Ravindra K; Das, Debabrata; S, Vaikundamani; Jamir, Esther; Sastry, G Narahari.
Afiliación
  • Kiewhuo K; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India.
  • Gogoi D; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India.
  • Mahanta HJ; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India.
  • Rawal RK; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India.
  • Das D; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India.
  • S V; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India.
  • Jamir E; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India.
  • Sastry GN; Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat 785006, Assam, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India. Electronic address: gnsastry@gmail.com.
Comput Biol Chem ; 102: 107799, 2023 Feb.
Article en En | MEDLINE | ID: mdl-36512929
ABSTRACT
The current study aims to develop a PAN India database of medicinal plants along with their phytochemicals and geographical availability. The database consists of 6959 unique medicinal plants belonging to 348 families which are available across 28 states and 8 union territories of India. The database sources the information on four different sections - traditional knowledge, geographical indications, phytochemicals, and chemoinformatics. The traditional knowledge reports the plant taxonomy with their vernacular names. A total of 27,440 unique phytochemicals associated with these plants were curated from various sources in this study. However, due to the non-availability of general information like IUPAC names, InChI key, etc. from reliable sources, only 22,314 phytochemicals have been currently reported in the database. Various analyses have been performed for the phytochemicals which include analysis of physicochemical and ADMET properties calculated from open-source web servers using in-house python scripts. The phytochemical data set has also been classified based on the class, superclass, and pathways respectively using NPClassifier, a deep learning framework. Additionally, the antiviral potency of the phytochemicals was also predicted using two machine learning models - Random Forest and XGBoost. The database aims to provide accurate and exhaustive data of the traditional practice of medicinal plants in India in a single platform integrating and analyzing the rich customary practices and facilitating the development and identification of plant-based therapeutics for a variety of diseases. The database can be accessed at https//neist.res.in/osadhi/.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Plantas Medicinales / Medicina Tradicional Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Comput Biol Chem Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Plantas Medicinales / Medicina Tradicional Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Comput Biol Chem Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: India