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Cited by in F6Publishing
For: Sepehri B, Kohnehpoushi M, Ghavami R. High predictive QSAR models for predicting the SARS coronavirus main protease inhibition activity of ketone-based covalent inhibitors. J IRAN CHEM SOC 2022;19:1865-76. [DOI: 10.1007/s13738-021-02426-2] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Sengottiyan S, Mikolajczyk A, Jagiełło K, Swirog M, Puzyn T. Core, Coating, or Corona? The Importance of Considering Protein Coronas in nano-QSPR Modeling of Zeta Potential. ACS Nano 2023;17:1989-97. [PMID: 36651824 DOI: 10.1021/acsnano.2c06977] [Reference Citation Analysis]
2 Ivanova YO, Voronina AI, Skvortsov VS. [The prediction of SARS-CoV-2 main protease inhibition with filtering by position of ligand]. Biomed Khim 2022;68:444-58. [PMID: 36573412 DOI: 10.18097/PBMC20226806444] [Reference Citation Analysis]
3 La Monica G, Bono A, Lauria A, Martorana A. Targeting SARS-CoV-2 Main Protease for Treatment of COVID-19: Covalent Inhibitors Structure-Activity Relationship Insights and Evolution Perspectives. J Med Chem 2022. [PMID: 36169610 DOI: 10.1021/acs.jmedchem.2c01005] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Gousiadou C, Sarimveis H. Predicting the Activity of Molecules against SARS-CoV-2 using Machine Learning Techniques and Stacked Generalization.. [DOI: 10.21203/rs.3.rs-1909128/v1] [Reference Citation Analysis]
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