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Treasuring the computational approach in medicinal plant research
Harshita Singh1, Navneeta Bharadvaja1
1Plant Biotechnology Laboratory, Delhi Technological University, Delhi, 110042, India.
Progress in Biophysics and Molecular Biology
|May 18, 2021
Summary
Computational methods like molecular docking, simulation, and AI accelerate medicinal plant research for drug discovery. These in silico tools offer faster, cost-effective alternatives to traditional screening, advancing drug design.
Area of Science:
- Computational Biology
- Pharmacology
- Bioinformatics
Background:
- Medicinal plants are vital sources of bioactive compounds for drug discovery.
- Traditional pharmacological screening is time-consuming and expensive.
- Computational methods offer efficient alternatives for analyzing plant-derived compounds.
Purpose of the Study:
- To review the evolution of computational tools in medicinal plant research.
- To highlight the advancements from molecular docking to artificial intelligence.
- To demonstrate the impact of these tools on drug design and development.
Main Methods:
- Molecular Docking: Simulates phytochemical interactions with target sites.
- Molecular Dynamic (MD) Simulation: Analyzes biomolecular behavior at the atomic level.
- Artificial Intelligence (AI): Employs machine learning algorithms (e.g., ANNs, DNNs) for accelerated analysis.
Main Results:
- Computational tools significantly reduce the time and cost of drug discovery.
- Advancements in computing power and algorithms enhance the accuracy and scope of in silico studies.
- AI, particularly machine learning, offers a paradigm shift in accelerating scientific discovery.
Conclusions:
- Computational research, evolving from docking to AI, is revolutionizing medicinal plant studies.
- These in silico approaches provide a roadmap for efficient drug design and development.
- The integration of AI promises further breakthroughs in understanding and utilizing medicinal plant resources.
