Investigation of the Biological Properties of Natural Products Using Experimental Approaches and In Silico Methods

About this Research Topic

Background

Natural products are compounds derived from plants, animals, and microorganisms that possess a wide range of biological activities, making them an important source for the discovery of new drugs. Experimental methods such as biological assays, spectroscopic analyses, and compound synthesis have traditionally been used to investigate the biological properties of natural products. However, in recent years, computational techniques such as molecular docking, molecular dynamics simulations, and machine learning algorithms have also been employed to study the interactions between natural products and biomolecules. The combination of experimental and in silico methods has allowed researchers to accelerate the discovery of new bioactive compounds from natural sources, optimize their biological activity, and gain insights into their mechanisms of action. For example, computational methods have been used to screen large databases of natural products for compounds with specific biological activities, while experimental methods have been used to validate these findings. Overall, the use of experimental and in silico methods for investigating natural products and their biological properties has revolutionized the field of drug discovery and has the potential to lead to the development of new drugs and therapies for a wide range of diseases.

This Research Topic aims to address the challenge of discovering effective drugs and therapies for diseases using natural compounds. Natural products have long been recognized as a valuable source of bioactive compounds that can be used to develop new drugs and therapies. However, identifying the bioactive components from natural product mixtures can be difficult. To overcome this challenge, we propose the use of experimental and in silico methods to investigate the biological properties of natural products. Recent advances in computational techniques such as molecular docking, machine learning, and artificial intelligence have made it possible to rapidly screen large databases of natural products for compounds with specific biological activities. These computational methods can also be used to predict the potential biological activity of compounds based on their chemical structure, allowing researchers to prioritize compounds for further investigation. Experimental methods can then be used to validate the computational predictions and optimize the biological activity of the identified compounds. For example, high-throughput screening assays can be used to rapidly test the activity of large numbers of compounds against specific biological targets, while spectroscopic techniques can be used to identify the chemical structures of the bioactive compounds.

We welcome Original Research, Review, Mini Review and Perspective articles on themes including, but not limited to:
• Evaluation of biological properties of compounds obtained from microorganisms, marine organisms, and from plant and animal sources
• Extraction and characterization of bioactive compounds from natural sources
• Evaluation of biological properties of fixed and volatile natural compounds
• Semi-synthesis of bioactive compounds from natural sources
• In vitro and in vivo evaluations of natural compounds
• SAR and QSAR to optimize natural compound properties
• Investigation of ADMETox properties of natural compounds
• Virtual screening, docking, and molecular dynamics of natural compounds

Keywords: Natural Products, Biological Properties, Experimental Approaches, In silico Methods, Drug Discovery

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