| |
original article |
Date |
Title |
Authors All Authors |
| 1 |
[GO] |
2025―Nov―19 |
Integrated machine learning-driven QSAR modelling and systems biology approach for the identification of potential SARS-CoV-2 3CLpro inhibitors |
A. Manaithiya, R. Bhowmik, R. Ray, S. Kumar, S. Sharma, B. Mathew, et al. (+2) W. Gong, A. Aspatwar |
| 2 |
[GO] |
2024―Jul―30 |
A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods |
Y. Zhang, Y. Tian, A. Yan |
| 3 |
[GO] |
2024―Feb―14 |
Docking and other computing tools in drug design against SARS-CoV-2 |
A.V. Sulimov, I.S. Ilin, A.S. Tashchilova, O.A. Kondakova, D.C. Kutov, V.B. Sulimov |
| 4 |
[GO] |
2022―Dec―05 |
Insights from computational studies on the potential of natural compounds as inhibitors against SARS-CoV-2 spike omicron variant |
A.A. Alzain |
| 5 |
[GO] |
2022―Sep―09 |
Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation |
A. Arwansyah, A.R. Arif, A. Kade, M. Taiyeb, I. Ramli, T. Santoso, et al. (+4) P. Ningsih, H. Natsir, T. Tahril, K. Uday Kumar |
| 6 |
[GO] |
2022―May―03 |
Identifying SARS-CoV-2 main protease inhibitors by applying the computer screening of a large database of molecules |
B. Sepehri, R. Ghavami, F. Mahmoudi, M. Irani, R. Ahmadi, D. Moradi |
| 7 |
[GO] |
2022―Apr―05 |
Identification of potential antivirals against 3CLpro enzyme for the treatment of SARS-CoV-2: A multi-step virtual screening study |
V. Kumar, S. Kar, P. De, K. Roy, J. Leszczynski |
| 8 |
[GO] |
2021―Nov―25 |
Discovery of Zafirlukast as a novel SARS-CoV-2 helicase inhibitor using in silico modelling and a FRET-based assay |
N. Mehyar, A. Mashhour, I. Islam, H.A. Alhadrami, A.M. Tolah, B. Alghanem, et al. (+6) S. Alkhaldi, B.A. Somaie, M. Al Ghobain, Y. Alobaida, A.S. Alaskar, M. Boudjelal |
| 9 |
[GO] |
2021―Aug―16 |
Molecular modelling on SARS-CoV-2 papain-like protease: an integrated study with homology modelling, molecular docking, and molecular dynamics simulations |
A. Arwansyah, A.R. Arif, I. Ramli, I. Kurniawan, S. Sukarti, M. Nur Alam, et al. (+3) I. Illing, A. Farid Lewa, B. Manguntungi |
| 10 |
[GO] |
2021―Jul―23 |
The QSAR-search of effective agents towards coronaviruses applying the Monte Carlo method |
A.A. Toropov, A.P. Toropova, E. Benfenati |
| 11 |
[GO] |
2021―May―20 |
Robust classification-based molecular modelling of diverse chemical entities as potential SARS-CoV-2 3CLpro inhibitors: theoretical justification in light of experimental evidences |
N. Adhikari, S. Banerjee, S.K. Baidya, B. Ghosh, T. Jha |
| 12 |
[GO] |
2021―Jan―06 |
Using in silico modelling and FRET-based assays in the discovery of novel FDA-approved drugs as inhibitors of MERS-CoV helicase |
N. Mehyar, A. Mashhour, I. Islam, S. Gul, A.O. Adedeji, A.S. Askar, M. Boudjelal |
| 13 |
[GO] |
2020―Oct―26 |
Exploring RdRp-remdesivir interactions to screen RdRp inhibitors for the management of novel coronavirus 2019-nCoV |
P.K. Singh, S. Pathania, R.K. Rawal |
| 14 |
[GO] |
2020―Jun―16 |
Development of a simple, interpretable and easily transferable QSAR model for quick screening antiviral databases in search of novel 3C-like protease (3CLpro) enzyme inhibitors against SARS-CoV diseases |
V. Kumar, K. Roy |
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