Bioactivities and In Silico Study of Phytochemicals
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Natural Products Chemistry".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 59202
Special Issue Editors
Interests: bacteriology; phytocompounds; antimicrobial activities; pharmacokinetics; molecular docking; dynamic simulation; ADMET prediction
Special Issues, Collections and Topics in MDPI journals
Interests: bioactive compounds; biological activities; structure–activity relationship and modeling for natural drug design; pharmacokinetics; molecular docking and dynamic simulation; ADMET prediction; pharmacophore modeling; QSAR and 3D-QSAR
Special Issue Information
Dear Colleague,
Plant-based phytochemicals continue to be major sources of phytochemicals and bioactive compounds that offer many opportunities in the pharmaceutical field for researchers to scout new drugs and serve as drug candidates for the prevention and treatment of various chronic diseases. With the help of in silico methods which have gained a great importance in target identification and in the prediction of novel drugs, it has become possible to explore and analyze the various molecular targets of individual phytochemical compounds and determine their binding affinities. As one of the most exciting methods, ligand–receptor interactions are of great pharmaceutical interest and can help medicinal chemists and pharmacologists to predict and identify innovative leads for structure-based drug design.
Within this broad context, this Special Issue welcomes original research and review articles focusing on the biological study of phytochemicals combining both in vitro and in silico approaches.
Dr. Mejdi Snoussi
Prof. Dr. Adel Kadri
Guest Editors
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Keywords
- phytochemicals
- bioactive compounds
- biological activities
- health benefits
- phytochemical screening and composition
- computer-aided drug design
- structure–activity relationships and modeling for natural drug design
- phytochemical sources
- pharmacokinetics
- computational approaches applied to natural compounds
- multi-target rational drug design
- molecular docking and dynamics simulation
- ADMET prediction
- pharmacophore modeling
- virtual screening
- QSAR and 3D-QSAR
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