Plant Natural Products: From Classical to (Bio)Technological and AI Research

Dear Colleagues,

Despite rapid advances in artificial intelligence (AI) and technology, the lack of high-quality biological data remains a significant obstacle to fully utilizing these tools in plant natural product research. Therefore, in this Special Issue, the guest editors aim to fill this gap by collecting high-quality data from experimental studies. At the same time, we wish to highlight which areas of plant natural product research are most adapted to emerging cutting-edge technologies like AI in order to encourage more studies and advance the field.

There are two main aims for this Special Issue:

1. To gather recent research on classical plant natural products, such as their extraction, characterization, and bioactivity, which serve as a form of vital knowledge and a data source in our rapidly advancing and disruptive technological era, like AI.
2. To showcase research on plant natural products driven by biotechnology, technology, and AI, aiming to inspire traditional researchers to adopt new methods for advancing their studies.

Therefore, we invite all plant natural product researchers who are experts in their field to participate by submitting a research paper, either an original or review article, to our Special Issue.

Potential topics include, but are not limited to, the following:

• Classical plant natural product research includes the study of extraction, characterization, and bioactivity.
• Biotechnological research includes the study of biosynthetic enzymes and green extraction.
• Omics research includes proteomic and metabolomic studies.
• Computational research includes virtual drug screening (molecular docking and molecular dynamics) and chemoinformatics (SAR and QSAR) studies.
• AI research includes machine learning and deep learning.

We look forward to receiving your contributions.

Dr. Jennifer Munkert
Guest Editor

Dr. Thanet Pitakbut
Guest Editor Assistant

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