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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Designing peptides predicted to bind to the omicron variant better than ACE2 via computational protein design and
Thassanai Sitthiyotha1, Wantanee Treewattanawong1, Surasak Chunsrivirot1
1Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Pathumwan, Bangkok, Thailand.
Abstract:
Brought about by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease (COVID-19) pandemic has resulted in large numbers of worldwide deaths and cases. Several SARS-CoV-2 variants have evolved, and Omicron (B.1.1.529) was one of the important variants of concern. It gets inside human cells by using its S1 subunit's receptor-binding domain (SARS-CoV-2-RBD) to bind to Angiotensin-converting enzyme 2 receptor's peptidase domain (ACE2-PD). Using peptides to inhibit binding interactions (BIs) between ACE2-PD and SARS-CoV-2-RBD is one of promising COVID-19 therapies. Employing computational protein design (CPD) as well as molecular dynamics (MD), this study used ACE2-PD's α1 helix to generate novel 25-mer peptide binders (SPB25) of Omicron RBD that have predicted binding affinities (ΔGbind (MM‑GBSA)) better than ACE2 by increasing favorable BIs between SPB25 and the conserved residues of RBD. Results from MD and the MM-GBSA method identified two best designed peptides (SPB25T7L/K11A and SPB25T7L/K11L with ΔGbind (MM‑GBSA) of -92.4 ± 0.4 and -95.7 ± 0.5 kcal/mol, respectively) that have better ΔGbind (MM‑GBSA) to Omicron RBD than ACE2 (-87.9 ± 0.5 kcal/mol) and SPB25 (-71.6 ± 0.5 kcal/mol). Additionally, they were predicted to have slightly higher stabilities, based on their percent helicities in water, than SBP1 (the experimentally proven inhibitor of SARS-CoV-2-RBD). Our two best designed SPB25s are promising candidates as omicron variant inhibitors.
Insights
Novel peptides were designed to inhibit the Omicron variant of SARS-CoV-2 by blocking its binding to human cells. These designed peptides show promising therapeutic potential against COVID-19, outperforming existing inhibitors.
Area of Science:
- Biochemistry
- Computational Biology
- Drug Discovery
Background:
- The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant global mortality.
- The emergence of SARS-CoV-2 variants, such as Omicron, poses ongoing public health challenges.
- Inhibition of the interaction between the SARS-CoV-2 receptor-binding domain (RBD) and ACE2 receptor is a key therapeutic strategy.
Purpose of the Study:
- To design novel peptide inhibitors targeting the Omicron variant's RBD using computational protein design.
- To enhance the binding affinity and stability of designed peptides compared to natural ACE2 and existing inhibitors.
- To identify promising peptide candidates for developing new COVID-19 therapies.
Main Methods:
- Computational protein design (CPD) was employed to generate 25-mer peptide binders (SPB25) based on the ACE2 receptor's α1 helix.
- Molecular dynamics (MD) simulations and MM-GBSA calculations were used to predict binding affinities (ΔGbind) and assess peptide stability.
- The binding interactions between designed peptides and Omicron RBD were analyzed to optimize favorable interactions with conserved residues.
Main Results:
- Two novel peptides, SPB25T7L/K11A and SPB25T7L/K11L, demonstrated superior binding affinities to Omicron RBD compared to native ACE2 and a previously studied peptide (SPB25).
- Predicted binding affinities (ΔGbind (MM‑GBSA)) for the top peptides were -92.4 ± 0.4 and -95.7 ± 0.5 kcal/mol, respectively.
- The designed peptides exhibited enhanced predicted stability and favorable binding interactions with conserved Omicron RBD residues.
Conclusions:
- The designed SPB25 peptides are effective inhibitors of Omicron RBD binding to ACE2.
- These peptides represent promising therapeutic candidates for combating Omicron variant infections.
- The study highlights the potential of CPD in developing novel antiviral agents against emerging SARS-CoV-2 variants.
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