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Designing Peptides Predicted to Bind to the Omicron Variant Better Than ACE2 via Computational Protein Design and Molecular Dynamics

Thassanai Sitthiyotha, Wantanee Treewattanawong, Surasak Chunsrivirot 

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). 

Introduction

The coronavirus disease 2019 (COVID-19) pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and brought about substantial worldwide cases and deaths [1, 2]. This virus has evolved its genome over time, and several variants of concern such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529) variants have emerged [3]. Some mutations may modify viral properties, transmissibility, and therapeutic solutions including the performance of vaccines [4]. Structurally, this virus has four principal components such as the spike (S) proteins, envelope (E), nucleocapsid (N) and membrane (M) [5, 6]. The receptor binding (S1) as well as membrane fusion (S2) subunits are in the spike protein. To attach to human cells, this virus uses its S1 subunit’s receptor binding domain (RBD) to bind to angiotensin-converting enzyme 2 (ACE2) receptor’s peptidase domain (PD) in human, while it uses its S2 subunit for the membrane fusion between its membrane and a host membrane [7, 8]. The previous study found that RBDs of Omicron and SARS-CoV-2 bound to monomeric human ACE2 receptor with the dissociation constant (KD) of 38.9 ± 10.5 nM and 75.5 ± 2.1 nM, respectively [9].

Methods

Preparation of structures

The complex structure of ACE2 binding to Omicron RBD was from PDB ID: 7TN0 [26]. SPB25 structure (21 IEEQAKTFLDKFNHEAEDLFYQSSL 45) binding to Omicron RBD was extracted from ACE2-PD’s α1 helix binding with Omicron RBD (PDB ID: 7TN0 [26]). These complexes were protonated at pH 7.4 (physiological pH) employing the H++ server [27]. AMBER18’s LEaP module [28] was utilized to create the final complex structure.

Results

Computational design of SPB25s of Omicron RBD

The template structure of SPB25 binding to Omicron RBD (Fig 1) was extracted from the structure of ACE2-PD’s α1 helix binding to Omicron RBD (PDB ID: 7TN0). Our design strategy is enhancing favorable BIs between the conserved residues of RBD (Y421, L455, F456, G485, F486 and Y489) [30] and SPB25. Designed positions of SPB25 were selected if favorable BIs could potentially form upon mutations between their side chains and the conserved residues of RBD. Q4(24), T7(27), F8(28), D10(30), K11(31) and H14(34) were chosen based on this criterion. Standard amino acids, except G and P due to their low occurring frequencies in an α-helix, were allowed in each designed position. In addition, P could cause the formation of a kink that can destabilize a helix [49]. Using these designed positions and amino acid types as inputs to Rosetta, 52 designed SPB25s that have single mutations (S1 Table) were produced. 

Discussion

The omicron variant (B.1.1.529) was the important variant of concern that was responsible for the COVID-19 pandemic. Similar to other variants, Omicron RBD firstly attaches to ACE2-PD to enter human cells. Disrupting BIs between ACE2-PD and Omicron RBD to prevent coronavirus from infecting and destroying human cells is a promising COVID-19 therapy. Since peptides have more similar interactions to native protein-protein interactions and functional groups than small molecules, which can be ineffective in disrupting large protein-binding interfaces[17, 18], peptides can be employed as inhibitors of SARS-CoV-2 to inhibit protein-protein interactions at their binding interfaces. To design novel 25-mer peptides with high potential to bind to Omicron RBD better than ACE2, we employed CPD, using the residues 21–45 of ACE2-PD’s α1 helix as a template, and MD. The design strategy of this study was increasing favorable BIs between SPB25 and the conserved residues of RBD (Y421, L455, F456, G485, F486 and Y489). Q4(24), T7(27), F8(28), D10(30), K11(31) and H14(34) were chosen as designed positions because their side chains are in the orientations that can possibly form favorable BIs with Omicron RBD upon mutations. Standard amino acids, except G and P, were allowed for all designed positions. After CPD by Rosetta, 52 designed SPB25s that have single mutations were generated. 

Acknowledgments

We would like to thank the Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Thailand for computer resources.

Citation: Sitthiyotha T, Treewattanawong W, Chunsrivirot S (2023) Designing peptides predicted to bind to the omicron variant better than ACE2 via computational protein design and molecular dynamics. PLoS ONE 18(10): e0292589. https://doi.org/10.1371/journal.pone.0292589

Editor: Syed Hani Abidi, Nazarbayev University School of Medicine, PAKISTAN

Received: April 25, 2023; Accepted: September 25, 2023; Published: October 10, 2023

Copyright: © 2023 Sitthiyotha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This study was funded by the Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Rachadaphiseksomphot Endowment Fund, Chulalongkorn University, Thailand. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

 

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0292589#sec001

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