In-Silico Selection of Aptamer Targeting SARS-CoV-2 Spike Protein.
Yu-Chao LinWen-Yih ChenEdwin En-Te HwuWen-Pin HuPublished in: International journal of molecular sciences (2022)
Aptamers are single-stranded, short DNA or RNA oligonucleotides that can specifically bind to various target molecules. To diagnose the infected cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in time, numerous conventional methods are applied for viral detection via the amplification and quantification of DNA or antibodies specific to antigens on the virus. Herein, we generated a large number of mutated aptamer sequences, derived from a known sequence of receptor-binding domain (RBD)-1C aptamer, specific to the RBD of SARS-CoV-2 spike protein (S protein). Structural similarity, molecular docking, and molecular dynamics (MD) were utilized to screen aptamers and characterize the detailed interactions between the selected aptamers and the S protein. We identified two mutated aptamers, namely, RBD-1CM1 and RBD-1CM2, which presented better docking results against the S protein compared with the RBD-1C aptamer. Through the MD simulation, we further confirmed that the RBD-1CM1 aptamer can form the most stable complex with the S protein based on the number of hydrogen bonds formed between the two biomolecules. Based on the experimental data of quartz crystal microbalance (QCM), the RBD-1CM1 aptamer could produce larger signals in mass change and exhibit an improved binding affinity to the S protein. Therefore, the RBD-1CM1 aptamer, which was selected from 1431 mutants, was the best potential candidate for the detection of SARS-CoV-2. The RBD-1CM1 aptamer can be an alternative biological element for the development of SARS-CoV-2 diagnostic testing.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- molecular dynamics
- gold nanoparticles
- label free
- sensitive detection
- molecular docking
- nucleic acid
- binding protein
- protein protein
- amino acid
- magnetic nanoparticles
- small molecule
- mass spectrometry
- risk assessment
- cell free
- immune response
- coronavirus disease
- climate change
- big data
- dendritic cells
- density functional theory
- machine learning
- loop mediated isothermal amplification
- deep learning