Title |
Computer-Aided Drug Design in Epigenetics
|
---|---|
Published in |
Frontiers in Chemistry, March 2018
|
DOI | 10.3389/fchem.2018.00057 |
Pubmed ID | |
Authors |
Wenchao Lu, Rukang Zhang, Hao Jiang, Huimin Zhang, Cheng Luo |
Abstract |
Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Germany | 1 | 50% |
Switzerland | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 166 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 15% |
Student > Master | 23 | 14% |
Student > Bachelor | 17 | 10% |
Student > Doctoral Student | 16 | 10% |
Researcher | 14 | 8% |
Other | 24 | 14% |
Unknown | 47 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 33 | 20% |
Biochemistry, Genetics and Molecular Biology | 29 | 17% |
Pharmacology, Toxicology and Pharmaceutical Science | 18 | 11% |
Agricultural and Biological Sciences | 7 | 4% |
Computer Science | 5 | 3% |
Other | 17 | 10% |
Unknown | 57 | 34% |