{"title":"Extraction of Chemical Substance Names from Patent Publications","authors":"Rumiko Tanaka, Shin-ichi Nakayama","doi":"10.2477/jccj.2021-0047","DOIUrl":"https://doi.org/10.2477/jccj.2021-0047","url":null,"abstract":"","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"1 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69048060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"In Memory of Mr. Senda with Winmostar","authors":"Tadayosi Yoshimura","doi":"10.2477/jccj.2022-0017","DOIUrl":"https://doi.org/10.2477/jccj.2022-0017","url":null,"abstract":"","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"1 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69049262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Uika Koshimizu, Junichi Ono, Y. Fukunishi, Hiromi Nakai
Hybrid in silico drug discovery was performed by combining large-scale quantum molecular dynamics (QMD) simulations with the conventional in silico drug discovery, focusing on developing covalent inhibitors against the main protease (M-pro) of SARS-CoV-2, the virus responsible for ongoing COVID-19 pandemic. The crystal structures and instantaneous structures obtained from the large-scale QMD simulations for M-pro were used as receptors in ensemble docking to estimate the binding affinities of the four ligands: the natural substrate recognized by M-pro, that recognized by the other enzyme of SARS-CoV-2, approved covalent inhibitor (PF-07321332), and the new candidate compound X determined from virtual screening. The present result shows that the binding affinity of X was comparable to that of PF-07321332, demonstrating the potency of our drug discovery.
{"title":"Hybrid in Silico Drug Discovery Study toward the Development of Oral Antivirals for COVID-19","authors":"Uika Koshimizu, Junichi Ono, Y. Fukunishi, Hiromi Nakai","doi":"10.2477/jccj.2022-0029","DOIUrl":"https://doi.org/10.2477/jccj.2022-0029","url":null,"abstract":"Hybrid in silico drug discovery was performed by combining large-scale quantum molecular dynamics (QMD) simulations with the conventional in silico drug discovery, focusing on developing covalent inhibitors against the main protease (M-pro) of SARS-CoV-2, the virus responsible for ongoing COVID-19 pandemic. The crystal structures and instantaneous structures obtained from the large-scale QMD simulations for M-pro were used as receptors in ensemble docking to estimate the binding affinities of the four ligands: the natural substrate recognized by M-pro, that recognized by the other enzyme of SARS-CoV-2, approved covalent inhibitor (PF-07321332), and the new candidate compound X determined from virtual screening. The present result shows that the binding affinity of X was comparable to that of PF-07321332, demonstrating the potency of our drug discovery.","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"1 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69050012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Houjou, Hirota Nakajima, Shota Okamura, Ryutaro Kikuoka
{"title":"Mechanical Interpretation of Coarse-grained Stiffness Matrix Based on Elastic-body Modeling of Molecular Assemblies.","authors":"H. Houjou, Hirota Nakajima, Shota Okamura, Ryutaro Kikuoka","doi":"10.2477/jccj.2023-0006","DOIUrl":"https://doi.org/10.2477/jccj.2023-0006","url":null,"abstract":"","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"11 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69051076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learning Organotransition Metal Reactions Using Graph Neural Networks","authors":"Motoji Sakai, Mitsunori Kaneshige, Koji Yasuda","doi":"10.2477/jccj.2023-0012","DOIUrl":"https://doi.org/10.2477/jccj.2023-0012","url":null,"abstract":"","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"5 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69051932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Science Communication Activities with Senda-san","authors":"Keiko Nakamura","doi":"10.2477/jccj.2022-0018","DOIUrl":"https://doi.org/10.2477/jccj.2022-0018","url":null,"abstract":"","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"1 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69049276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rui Saito, Koji Okuwaki, Y. Mochizuki, Ryutaro Nagai, Takumi Kato, K. Sugisaki, Yuichiro Minato
{"title":"Protein Folding Model Using Quantum Computation","authors":"Rui Saito, Koji Okuwaki, Y. Mochizuki, Ryutaro Nagai, Takumi Kato, K. Sugisaki, Yuichiro Minato","doi":"10.2477/jccj.2022-0022","DOIUrl":"https://doi.org/10.2477/jccj.2022-0022","url":null,"abstract":"","PeriodicalId":41909,"journal":{"name":"Journal of Computer Chemistry-Japan","volume":"58 1","pages":""},"PeriodicalIF":0.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69049406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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