Co-Authors
This is a "connection" page, showing publications co-authored by Sanjeev Singh and Chandrabose Selvaraj.
Connection Strength
3.214
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High-Throughput Screening and Quantum Mechanics for Identifying Potent Inhibitors Against Mac1 Domain of SARS-CoV-2 Nsp3. IEEE/ACM Trans Comput Biol Bioinform. 2021 Jul-Aug; 18(4):1262-1270.
Score: 0.960
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Microsecond MD Simulation and Multiple-Conformation Virtual Screening to Identify Potential Anti-COVID-19 Inhibitors Against SARS-CoV-2 Main Protease. Front Chem. 2020; 8:595273.
Score: 0.924
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Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19. J Biomol Struct Dyn. 2021 08; 39(13):4582-4593.
Score: 0.888
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Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation. Curr Top Med Chem. 2020; 20(24):2146-2167.
Score: 0.215
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Structure-Based Virtual Screening Reveals Ibrutinib and Zanubrutinib as Potential Repurposed Drugs against COVID-19. Int J Mol Sci. 2021 Jun 30; 22(13).
Score: 0.060
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Targeting COVID-19 (SARS-CoV-2) main protease through active phytochemicals of ayurvedic medicinal plants - Withania somnifera (Ashwagandha), Tinospora cordifolia (Giloy) and Ocimum sanctum (Tulsi) - a molecular docking study. J Biomol Struct Dyn. 2022 Jan; 40(1):190-203.
Score: 0.056
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Bacterial protein azurin and derived peptides as potential anti-SARS-CoV-2 agents: insights from molecular docking and molecular dynamics simulations. J Biomol Struct Dyn. 2021 Sep; 39(15):5706-5721.
Score: 0.056
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Identification of new anti-nCoV drug chemical compounds from Indian spices exploiting SARS-CoV-2 main protease as target. J Biomol Struct Dyn. 2021 06; 39(9):3428-3434.
Score: 0.055