1 |
Walesch S, Birkelbach J, Jézéquel G, Haeckl FPJ, Hegemann JD, Hesterkamp T, Hirsch AKH, Hammann P, Müller R. Fighting antibiotic resistance-strategies and (pre)clinical developments to find new antibacterials. EMBO Rep 2023;24:e56033. [PMID: 36533629 DOI: 10.15252/embr.202256033] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
|
2 |
Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022;122:11287-368. [PMID: 35594413 DOI: 10.1021/acs.chemrev.1c00965] [Cited by in Crossref: 13] [Cited by in F6Publishing: 11] [Article Influence: 13.0] [Reference Citation Analysis]
|
3 |
Kumar V, Roy K. Computational Modeling of Chloroquine Analogues for Development of Drugs Against Novel Coronavirus (nCoV). Methods in Pharmacology and Toxicology 2021. [DOI: 10.1007/7653_2020_55] [Reference Citation Analysis]
|
4 |
Kumar V, Roy K. Computational Modeling of RdRp Inhibitors for the Development of Drugs against Novel Coronavirus (nCoV). Methods in Pharmacology and Toxicology 2021. [DOI: 10.1007/7653_2020_51] [Reference Citation Analysis]
|
5 |
De P, Roy K. Computational Modeling of ACE2-Mediated Cell Entry Inhibitors for the Development of Drugs Against Coronaviruses. Methods in Pharmacology and Toxicology 2021. [DOI: 10.1007/7653_2020_49] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
|
6 |
Radaeva M, Dong X, Cherkasov A. The Use of Methods of Computer-Aided Drug Discovery in the Development of Topoisomerase II Inhibitors: Applications and Future Directions. J Chem Inf Model 2020;60:3703-21. [DOI: 10.1021/acs.jcim.0c00325] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
|
7 |
Mashayekh K, Sharifi S, Damghani T, Elyasi M, Avestan MS, Pirhadi S. Clustering and Sampling of the c-Met Conformational Space: A Computational Drug Discovery Study. Comb Chem High Throughput Screen 2019;22:635-48. [PMID: 31696808 DOI: 10.2174/1386207322666191024103902] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
|