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A Computational Simulation Appraisal of Banana Lectin as a Potential Anti-SARS-CoV-2 Candidate by Targeting the Receptor-Binding Domain

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dc.contributor.author Hessel, Sofia Safitri
dc.contributor.author Dwivany, Fenny Martha
dc.contributor.author Zainuddin, Ima Mulyama
dc.contributor.author Wikantika, Ketut
dc.contributor.author Celik, Ismail
dc.contributor.author Emran, Talha Bin
dc.contributor.author Tallei, Trina Ekawati
dc.date.accessioned 2024-04-21T03:30:34Z
dc.date.available 2024-04-21T03:30:34Z
dc.date.issued 2023-11-28
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12066
dc.description.abstract Background The ongoing concern surrounding coronavirus disease 2019 (COVID-19) primarily stems from continuous mutations in the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to the emergence of numerous variants. The receptor-binding domain (RBD) in the S1 subunit of the S protein of the virus plays a crucial role in recognizing the host’s angiotensin-converting enzyme 2 (hACE2) receptor and facilitating cell membrane fusion processes, making it a potential target for preventing viral entrance into cells. This research aimed to determine the potential of banana lectin (BanLec) proteins to inhibit SARS-CoV-2 attachment to host cells by interacting with RBD through computational modeling. Materials and methods The BanLecs were selected through a sequence analysis process. Subsequently, the genes encoding BanLec proteins were retrieved from the Banana Genome Hub database. The FGENESH online tool was then employed to predict protein sequences, while web-based tools were utilized to assess the physicochemical properties, allergenicity, and toxicity of BanLecs. The RBDs of SARS-CoV-2 were modeled using the SWISS-MODEL in the following step. Molecular docking procedures were conducted with the aid of ClusPro 2.0 and HDOCK web servers. The three-dimensional structures of the docked complexes were visualized using PyMOL. Finally, molecular dynamics simulations were performed to investigate and validate the interactions of the complexes exhibiting the highest interactions, facilitating the simulation of their dynamic properties. Results The Banec proteins were successfully modeled based on the RNA sequences from two species of banana (Musa sp.). Moreover, an amino acid modification in the BanLec protein was made to reduce its mitogenicity. Theoretical allergenicity and toxicity predictions were conducted on the BanLecs, which suggested they were likely non-allergenic and contained no discernible toxic domains. Molecular docking analysis demonstrated that both altered and wild-type BanLecs exhibited strong affinity with the RBD of different SARS-CoV-2 variants. Further analysis of the molecular docking results showed that the BanLec proteins interacted with the active site of RBD, particularly the key amino acids residues responsible for RBD’s binding to hACE2. Molecular dynamics simulation indicated a stable interaction between the Omicron RBD and BanLec, maintaining a root-mean-square deviation (RMSD) of approximately 0.2 nm for a duration of up to 100 ns. The individual proteins also had stable structural conformations, and the complex demonstrated a favorable binding-free energy (BFE) value. Conclusions These results confirm that the BanLec protein is a promising candidate for developing a potential therapeutic agent for combating COVID-19. Furthermore, the results suggest the possibility of BanLec as a broad-spectrum antiviral agent and highlight the need for further studies to examine the protein’s safety and effectiveness as a potent antiviral agent. en_US
dc.language.iso en_US en_US
dc.publisher Springer en_US
dc.subject Covid-19 en_US
dc.subject Coronavirus disease en_US
dc.title A Computational Simulation Appraisal of Banana Lectin as a Potential Anti-SARS-CoV-2 Candidate by Targeting the Receptor-Binding Domain en_US
dc.type Article en_US


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