Computer-Aided Drug Design (CADD) is an area of science that is rapidly growing, involving using computers to discover and design new drugs. CADD focuses on understanding the three-dimensional structure of the target and identifying important features and interactions, as well as the knowledge of known compounds to target specific biological pathways in the body.
Experimental methods are indispensable for studying the mechanistic insights into the function of biomolecules using biophysical and biochemical techniques. Additionally, as molecular biology has advanced, several new target discovery techniques have been extensively used to investigate the mechanisms of naturally bioactive compounds, reviving the pursuit of developing novel naturally derived pharmaceuticals. Although computational and experimental methods are sometimes seen as two distinct and independent approaches, there is no doubt in the benefits and potential of combining these two methods. The combination of their data can improve and support the interpretation and offer in-depth insights into the molecular mechanisms of various molecules.
The goal of this Research Topic is to be a source for high-quality research on using CADD in combination with experimental methods to find out natural metabolites that can be further developed to manage various diseases or health conditions. Also, this topic can foster collaborations and communication between experimental and computational expert researchers.
We invite researchers to submit Original Research, Review, Mini Review, and Perspective articles that focus on computational studies (with or without experimental evidence) of natural products with health benefits for humans. Specific areas of interest may include, but are not limited to:
• Creating pharmacophore models and conducting screening tests to identify potential natural compounds for treating diseases.
• Using virtual screening and molecular docking techniques to dock a large number of compounds.
• Predicting pharmacokinetics and toxicity properties of compounds.
• Running molecular dynamics simulations to understand how these compounds interact at the molecular level at simulating body conditions.
• Employing methods like QSAR (Quantitative Structure-Activity Relationship) and 3D-QSAR to analyze the properties of these compounds in detail.
• Experimental techniques for evaluating of various bioactivities.
• Possible mechanistic pathway illustration of bioactive metabolites.
Computer-Aided Drug Design (CADD) is an area of science that is rapidly growing, involving using computers to discover and design new drugs. CADD focuses on understanding the three-dimensional structure of the target and identifying important features and interactions, as well as the knowledge of known compounds to target specific biological pathways in the body.
Experimental methods are indispensable for studying the mechanistic insights into the function of biomolecules using biophysical and biochemical techniques. Additionally, as molecular biology has advanced, several new target discovery techniques have been extensively used to investigate the mechanisms of naturally bioactive compounds, reviving the pursuit of developing novel naturally derived pharmaceuticals. Although computational and experimental methods are sometimes seen as two distinct and independent approaches, there is no doubt in the benefits and potential of combining these two methods. The combination of their data can improve and support the interpretation and offer in-depth insights into the molecular mechanisms of various molecules.
The goal of this Research Topic is to be a source for high-quality research on using CADD in combination with experimental methods to find out natural metabolites that can be further developed to manage various diseases or health conditions. Also, this topic can foster collaborations and communication between experimental and computational expert researchers.
We invite researchers to submit Original Research, Review, Mini Review, and Perspective articles that focus on computational studies (with or without experimental evidence) of natural products with health benefits for humans. Specific areas of interest may include, but are not limited to:
• Creating pharmacophore models and conducting screening tests to identify potential natural compounds for treating diseases.
• Using virtual screening and molecular docking techniques to dock a large number of compounds.
• Predicting pharmacokinetics and toxicity properties of compounds.
• Running molecular dynamics simulations to understand how these compounds interact at the molecular level at simulating body conditions.
• Employing methods like QSAR (Quantitative Structure-Activity Relationship) and 3D-QSAR to analyze the properties of these compounds in detail.
• Experimental techniques for evaluating of various bioactivities.
• Possible mechanistic pathway illustration of bioactive metabolites.
