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Akhter, Sana, Tang, Zhichao, Wang, Jinan, Haboro, Mercy, Holmstrom, Erik D, Wang, Jingxin, Miao, Yinglong (2024) Mechanism of Ligand Binding to Theophylline RNA Aptamer. Journal of Chemical Information and Modeling, 64 (3) 1017-1029 doi:10.1021/acs.jcim.3c01454

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Reference TypeJournal (article/letter/editorial)
TitleMechanism of Ligand Binding to Theophylline RNA Aptamer
JournalJournal of Chemical Information and Modeling
AuthorsAkhter, SanaAuthor
Tang, ZhichaoAuthor
Wang, JinanAuthor
Haboro, MercyAuthor
Holmstrom, Erik DAuthor
Wang, JingxinAuthor
Miao, YinglongAuthor
Year2024 (February 12)Volume64
Issue3
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.3c01454Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID17156785Long-form Identifiermindat:1:5:17156785:6
GUID0
Full ReferenceAkhter, Sana, Tang, Zhichao, Wang, Jinan, Haboro, Mercy, Holmstrom, Erik D, Wang, Jingxin, Miao, Yinglong (2024) Mechanism of Ligand Binding to Theophylline RNA Aptamer. Journal of Chemical Information and Modeling, 64 (3) 1017-1029 doi:10.1021/acs.jcim.3c01454
Plain TextAkhter, Sana, Tang, Zhichao, Wang, Jinan, Haboro, Mercy, Holmstrom, Erik D, Wang, Jingxin, Miao, Yinglong (2024) Mechanism of Ligand Binding to Theophylline RNA Aptamer. Journal of Chemical Information and Modeling, 64 (3) 1017-1029 doi:10.1021/acs.jcim.3c01454
In(2024, February) Journal of Chemical Information and Modeling Vol. 64 (3) American Chemical Society (ACS)

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Wang, Yun-Peng, Eriksson, Leif A., Zhang, Ru-Bo (2024) Mechanism of Dual-Site Recognition in a Classic DNA Aptamer. Journal of Chemical Information and Modeling, 64 (19). doi:10.1021/acs.jcim.4c01389
Rasouli, Ali, Pickard, Frank C., Sur, Sreyoshi, Grossfield, Alan, Işık Bennett, Mehtap (2025) Essential Considerations for Free Energy Calculations of RNA–Small Molecule Complexes: Lessons from the Theophylline-Binding RNA Aptamer. Journal of Chemical Information and Modeling, 65 (1). doi:10.1021/acs.jcim.4c01505
Bosio, Stefano, Bernetti, Mattia, Rocchia, Walter, Masetti, Matteo (2024) Similarities and Differences in Ligand Binding to Protein and RNA Targets: The Case of Riboflavin. Journal of Chemical Information and Modeling, 64 (11) 4570-4586 doi:10.1021/acs.jcim.4c00420
Nguyen, Duc D., Xiao, Tian, Wang, Menglun, Wei, Guo-Wei (2017) Rigidity Strengthening: A Mechanism for Protein–Ligand Binding. Journal of Chemical Information and Modeling, 57 (7) 1715-1721 doi:10.1021/acs.jcim.7b00226
Du, Yu (2024) Binding Curve Viewer: Visualizing the Equilibrium and Kinetics of Protein–Ligand Binding and Competitive Binding. Journal of Chemical Information and Modeling, 64 (10) 4180-4192 doi:10.1021/acs.jcim.4c00130
Luo, Ding, Liu, Dandan, Qu, Xiaoyang, Dong, Lina, Wang, Binju (2024) Enhancing Generalizability in Protein–Ligand Binding Affinity Prediction with Multimodal Contrastive Learning. Journal of Chemical Information and Modeling, 64 (6) 1892-1906 doi:10.1021/acs.jcim.3c01961
Qu, Xiaoyang, Dong, Lina, Luo, Ding, Si, Yubing, Wang, Binju (2024) Water Network-Augmented Two-State Model for Protein–Ligand Binding Affinity Prediction. Journal of Chemical Information and Modeling, 64 (7) 2263-2274 doi:10.1021/acs.jcim.3c00567
Nordquist, Erik B., Zhao, Mingtian, Kumar, Anmol, MacKerell, Alexander D. (2024) Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots. Journal of Chemical Information and Modeling, 64 (19). doi:10.1021/acs.jcim.4c01189
Sun, Chuance; Zhang, Linghao; Zhang, Lingfeng; Song, Yuehua; Ma, Buyong; Wang, Yanjing (2025) GATRsite: RNA–Ligand Binding Site Prediction Using Graph Attention Networks and Pretrained RNA Language Models. Journal of Chemical Information and Modeling, 65 (16). doi:10.1021/acs.jcim.5c00605
Molani, Farzad, Webb, Simon, Cho, Art E. (2024) Correction to “Combining QM/MM Calculations with Classical Mining Minima to Predict Protein–Ligand Binding Free Energy”. Journal of Chemical Information and Modeling, 64 (3) 1105 doi:10.1021/acs.jcim.3c02002
Lee, Ho-Joon, Emani, Prashant S., Gerstein, Mark B. (2024) Improved Prediction of Ligand–Protein Binding Affinities by Meta-modeling. Journal of Chemical Information and Modeling, 64 (23). doi:10.1021/acs.jcim.4c01116
 
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