Cargando…
Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors
A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776159/ https://www.ncbi.nlm.nih.gov/pubmed/35055023 http://dx.doi.org/10.3390/ijms23020838 |
_version_ | 1784636763861417984 |
---|---|
author | Jawad, Bahaa Adhikari, Puja Cheng, Kun Podgornik, Rudolf Ching, Wai-Yim |
author_facet | Jawad, Bahaa Adhikari, Puja Cheng, Kun Podgornik, Rudolf Ching, Wai-Yim |
author_sort | Jawad, Bahaa |
collection | PubMed |
description | A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a −1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2. |
format | Online Article Text |
id | pubmed-8776159 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87761592022-01-21 Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors Jawad, Bahaa Adhikari, Puja Cheng, Kun Podgornik, Rudolf Ching, Wai-Yim Int J Mol Sci Article A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a −1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2. MDPI 2022-01-13 /pmc/articles/PMC8776159/ /pubmed/35055023 http://dx.doi.org/10.3390/ijms23020838 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jawad, Bahaa Adhikari, Puja Cheng, Kun Podgornik, Rudolf Ching, Wai-Yim Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors |
title | Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors |
title_full | Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors |
title_fullStr | Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors |
title_full_unstemmed | Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors |
title_short | Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors |
title_sort | computational design of miniproteins as sars-cov-2 therapeutic inhibitors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776159/ https://www.ncbi.nlm.nih.gov/pubmed/35055023 http://dx.doi.org/10.3390/ijms23020838 |
work_keys_str_mv | AT jawadbahaa computationaldesignofminiproteinsassarscov2therapeuticinhibitors AT adhikaripuja computationaldesignofminiproteinsassarscov2therapeuticinhibitors AT chengkun computationaldesignofminiproteinsassarscov2therapeuticinhibitors AT podgornikrudolf computationaldesignofminiproteinsassarscov2therapeuticinhibitors AT chingwaiyim computationaldesignofminiproteinsassarscov2therapeuticinhibitors |