Plants have long served as a source of natural products and bioactive and therapeutic compounds, playing a key role in both traditional medicine and the story of modern pharmaceuticals. With the advent of bioinformatics and more recently machine learning (ML) and artificial intelligence (AI), our ability to analyze, predict, and harness plant-derived molecules for drug discovery has dramatically improved. This topic explores the intersection of "plant omics", bioinformatics, cheminformatics, and computational biology in the identification, characterization, and optimization of phytochemicals and plant-based drug candidates.
We invite contributions that showcase innovative applications of tools and databases in phytochemical profiling, molecular docking, systems biology, and network pharmacology of compounds from plants that demonstrate their utility with prospective experimental validation. Studies that leverage ML and AI, genomics, transcriptomics, or metabolomics to unravel biosynthetic pathways, reveal genotype-phenotype relationships, and accelerate the discovery of novel bioactive molecules are particularly welcome. By bridging computational approaches with experimental validation, this collection aims to advance our understanding of plant-based therapeutics and their potential in tackling pressing health challenges.
This Research Topic aims to showcase the latest scientific evidence and perspectives on bioinformatics and drug discovery approaches using plants, natural products, and phytochemicals. This Topic will advance the discovery and development of plant-based therapeutics.
To gather further insights within the defined boundaries of bioinformatics and drug discovery, we welcome articles addressing, but not limited to, the following themes:
- The importance and applications of bioinformatics in plant sciences as it relates to drug discovery - Genome-wide analysis of macromolecules in plants for their predictive roles in therapeutics — understanding protein function and interactions, analyzing the three-dimensional structures of biomolecules with special reference to protein-based therapeutics (biologics) - Drug discovery using plants - Identification of phytochemicals and phytocompounds in early-stage drug discovery - Applications of protein-ligand docking, protein-protein docking, and co-folding — but only with prospective experimental validation of predictions - Development and application of structure-based, ligand-based, and hybrid virtual screening methods using phytochemicals and phytocompounds — but only with prospective experimental validation of predictions - Structure-activity relationship modelling for plant-related molecules and subsequent pharmaceutical development - Novel ML and AI methods using natural products, phytochemicals, and phytocompounds
Contributors from interdisciplinary backgrounds are encouraged to submit original research, reviews, and perspectives highlighting recent advances, challenges, and future directions in bioinformatics-based and drug discovery using plants.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
