Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors

Jawad, Bahaa; Adhikari, Puja; Cheng, Kun; Podgornik, Rudolf; Ching, Wai-Yim

doi:10.3390/ijms23020838

Title: Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors

Journal Article · 12 January 2022 · International Journal of Molecular Sciences (Online)

DOI: https://doi.org/10.3390/ijms23020838 · OSTI ID:2469729

^[1];

^[2]; Cheng, Kun ^[2]; Podgornik, Rudolf ^[3];

^[2]

University of Missouri, Kansas City, MO (United States); University of Technology, Baghdad (Iraq)
University of Missouri, Kansas City, MO (United States)
Wenzhou Institute of the University of Chinese Academy of Sciences, Wenzhou (China); University of Chinese Academy of Sciences, Beijing (China); Chinese Academy of Sciences, Beijing (China)

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.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE; National Science Foundation (NSF)

Grant/Contract Number:: AC03-76SF00098

OSTI ID:: 2469729

Journal Information:: International Journal of Molecular Sciences (Online), Journal Name: International Journal of Molecular Sciences (Online) Journal Issue: 2 Vol. 23; ISSN 1422-0067

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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Title: Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors

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