About this Research Topic
Research laboratories and pharmaceutical companies has been investing a large amount of time and resources on development of possible drugs for a particular disease. But these drugs can also be used for the management of other diseases. Rather than investing on new drugs, the already existing drugs with known pharmacodynamics and pharmacokinetics may aid in further, speedy, drug discovery. Different high end computational tools are now available and can aid in the screening and preliminary studies, which can again save much time and resources.
The aim of this Research Topic is to become the reference point for high quality research on the computational screening for the repurposing of known or reported medicinally active agents for the management of other diseases or conditions. The advent of high end computational methods like ab initio methods, DFT, molecular docking, molecular dynamics, statistical mechanics etc. in tandem with sophisticated computational facilities has hastened the drug repurposing study more than ever. Furthermore, the new algorithms, software and techniques available, utilize the recent developments in machine learning and artificial intelligence leading in fast high throughput drug screening easier than ever.
We welcome Original Research, Review, Mini Review and Perspective articles on computational studies (with or without experimental support) of already known drugs, natural products, reported synthesized compounds, newly synthesized compounds with screening and design of new suitable compounds. Specific themes may include, but are not limited to:
• High throughput combinatorial screening of compound libraries for medicinal activity.
• Electronic structure studies of existing drugs.
• Design of new molecules for medicinal use followed by in silico analysis.
• Natural products and their analogues for medicinal use.
• New methods or code development for drug discovery.
• Machine learning and artificial intelligence in drug discovery or repurposing.
• All topics related to computational study of drug repurposing/drug discovery
Please note that simple docking studies do not fit in the remit of Frontiers in Chemistry , and as such, we welcome drug modelling manuscripts beyond those stages.
Topic Editor Kenji Mizuguchi declares grants from Taisho Pharmaceutical Co., Ltd., Asahi Kasei Pharma Corporation, Lifematics Inc., and Suntory Wellness Ltd., and non-financial support from AstraZeneca plc and Mitsubishi Tanabe Pharma. The other editors declare no competing interests.
The aim of this Research Topic is to become the reference point for high quality research on the computational screening for the repurposing of known or reported medicinally active agents for the management of other diseases or conditions. The advent of high end computational methods like ab initio methods, DFT, molecular docking, molecular dynamics, statistical mechanics etc. in tandem with sophisticated computational facilities has hastened the drug repurposing study more than ever. Furthermore, the new algorithms, software and techniques available, utilize the recent developments in machine learning and artificial intelligence leading in fast high throughput drug screening easier than ever.
We welcome Original Research, Review, Mini Review and Perspective articles on computational studies (with or without experimental support) of already known drugs, natural products, reported synthesized compounds, newly synthesized compounds with screening and design of new suitable compounds. Specific themes may include, but are not limited to:
• High throughput combinatorial screening of compound libraries for medicinal activity.
• Electronic structure studies of existing drugs.
• Design of new molecules for medicinal use followed by in silico analysis.
• Natural products and their analogues for medicinal use.
• New methods or code development for drug discovery.
• Machine learning and artificial intelligence in drug discovery or repurposing.
• All topics related to computational study of drug repurposing/drug discovery
Please note that simple docking studies do not fit in the remit of Frontiers in Chemistry , and as such, we welcome drug modelling manuscripts beyond those stages.
Topic Editor Kenji Mizuguchi declares grants from Taisho Pharmaceutical Co., Ltd., Asahi Kasei Pharma Corporation, Lifematics Inc., and Suntory Wellness Ltd., and non-financial support from AstraZeneca plc and Mitsubishi Tanabe Pharma. The other editors declare no competing interests.
Keywords: Drug repurposing, Machine learning in drug discovery, Chemoinformatics, Computational chemistry, Drug design, Natural products as medicines
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.
