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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Siripat Chaichit | en_US |
dc.contributor.author | Pathomwat Wongrattanakamon | en_US |
dc.contributor.author | Busaban Sirithunyalug | en_US |
dc.contributor.author | Piyarat Nimmanpipug | en_US |
dc.contributor.author | Supat Jiranusornkul | en_US |
dc.date.accessioned | 2022-05-27T08:27:33Z | - |
dc.date.available | 2022-05-27T08:27:33Z | - |
dc.date.issued | 2022-03-01 | en_US |
dc.identifier.issn | 20763417 | en_US |
dc.identifier.other | 2-s2.0-85126281313 | en_US |
dc.identifier.other | 10.3390/app12052621 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85126281313&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/72649 | - |
dc.description.abstract | Osteoporosis is a complex bone disease indicating porous bone with low bone mass density and fragility. Cathepsin K, V-ATPase, and αV β3 integrin are exhibited as novel targets for osteoporosis treatment. Our preliminary study uses a state-of-the-art method, including target-based virtual screening and clustering methods to determine promising candidates with multitarget properties. Phytochemicals with osteoprotective properties from the literature are used to elucidate the molecular interactions toward three targets. The binding scores of compounds are normalized and rescored. The K-means and hierarchical clustering methods are applied to filter and define the promising compounds, and the silhouette analysis is supposed to validate the clustering method. We explore 108 herbal compounds by virtual screening and the cluster approach, and find that rutin, sagittatoside A, icariin, and kaempferitrin showed strong binding affinities against Cathepsin K, V-ATPase, and αV β3 integrin. Dockings of candidates toward three targets also provide the protein-ligand interactions and crucial amino acids for binding. Our study provides a straightforward and less time-consuming approach to exploring the new multitarget candidates for further investigations, using a combination of in silico methods. | en_US |
dc.subject | Chemical Engineering | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.subject | Materials Science | en_US |
dc.subject | Physics and Astronomy | en_US |
dc.title | Multitarget-Based Virtual Screening for Identification of Herbal Substances toward Potential Osteoclastic Targets | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Applied Sciences (Switzerland) | en_US |
article.volume | 12 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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