Dear Colleagues,

Medicinal plants have been discovered and used in traditional medical procedures. Plants produce hundreds of phytochemicals, plant-derived natural products, for use in various environmental and biological purposes. They also comprise more than a third of the approved drugs in the market. Eventually, the origination of drugs from phytochemicals declined to owe the redundancy of the identified compounds, together with the high cost of isolation, purification, and structure elucidation. To overcome these limitations, metabolomics was introduced as a modern technique for the holistic analysis of these phytochemicals.

Progress in mass-spectrometry-based platforms such as GC-MS and HRLC-MS helped in the rapid separation and identification of several major and minor metabolites. Such analysis can be a valuable tool for recognizing prospective bioactive molecules from medicinal plants and the speedy determination of their abundance in different plant parts.

Since many wild medicinal plants face a high risk of extinction due to climate change, more efforts are required to investigate metabolites of other related species that are available from the same genus or family to search for alternative sources of the same active compounds found in these rare and endangered medicinal species.

Molecular networking, also known as spectral similarity networks, is a computational tool for the organization of tandem mass spectrometry data that unveil the hidden connections of the chemical space within. Recently, it has benefited chemists in many research disciplines, especially natural product drug discoveries and metabolomics studies.

In the current Special Issue, entitled “Progress in Metabolomic Analysis in Medicinal Plants”, we welcome authors to submit original manuscripts that use metabolomics approaches, either alone or in conjunction with other bioinformatic strategies, to answer one or more of the following study objectives, related to the metabolomics of medicinal plants:

• Dereplication of metabolites via GC-MS and LC-MS analysis
• Metabolic investigation of available botanical taxa related to the known medicinal species that could be contained within the same bioactive constituents
• Metabolomic comparison of different plant organs and/or the whole plant from different locali-ties
• Molecular network-guided cataloging of the plant metabolome
• Metabolites’ computational in silico studies

Prof. Dr. Mona Mohamed Marzouk
Dr. Nesrine Mahmoud Hegazi
Dr. Mai Mohamed Farid Kotob
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• natural products
• secondary metabolites
• metabolomic pathway
• GC/MS, LC-MS/MS
• drug discovery
• molecular networking
• forthcoming medicinal plant