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Nguyen H, Nguyen HL, Lan PD, Thai NQ, Sikora M, Li MS. Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation. Chem Soc Rev 2023; 52:6497-6553. [PMID: 37650302 DOI: 10.1039/d1cs01170g] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.
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Affiliation(s)
- Hung Nguyen
- Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland.
| | - Hoang Linh Nguyen
- Institute of Fundamental and Applied Sciences, Duy Tan University, Ho Chi Minh City 700000, Vietnam
- Faculty of Environmental and Natural Sciences, Duy Tan University, Da Nang 550000, Vietnam
| | - Pham Dang Lan
- Life Science Lab, Institute for Computational Science and Technology, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, 729110 Ho Chi Minh City, Vietnam
- Faculty of Physics and Engineering Physics, VNUHCM-University of Science, 227, Nguyen Van Cu Street, District 5, 749000 Ho Chi Minh City, Vietnam
| | - Nguyen Quoc Thai
- Dong Thap University, 783 Pham Huu Lau Street, Ward 6, Cao Lanh City, Dong Thap, Vietnam
| | - Mateusz Sikora
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland.
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2
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Shen H, Yang H. Binding of synthetic nanobodies to the SARS-CoV-2 receptor-binding domain: the importance of salt bridges. Phys Chem Chem Phys 2023; 25:24129-24142. [PMID: 37655617 DOI: 10.1039/d3cp02628k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
In this study, five different SARS-CoV-2 receptor-binding domain (RBD) models were created based on the crystal structures of RBD complexes with two synthetic nanobodies (Sb16 and Sb45). Microsecond all-atom MD simulations revealed that Sb16 and Sb45 substantially stabilized the flexible RBD loop (residues GLU471-SER494) due to the salt bridges and hydrogen bonding interactions between RBD and the synthetic nanobodies. However, the calculation of binding free energy displayed that Sb45 had a higher binding affinity to RBD than Sb16, in agreement with the experimental result. This is because Sb45 has stronger electrostatic attraction to RBD as compared to Sb16. In particular, the salt bridge GLU484-ARG33 in Sb45-RBD is stronger than the GLU484-LYS32 in Sb16-RBD. Furthermore, by comparing the binding affinity of Sb16 for two RBD mutants (E484K and K417N), we found that E484K mutation substantially reduced the binding affinity to Sb16, and K417N mutation had no significant effect, qualitatively in agreement with experimental studies. According to the binding free energy calculation, the strong electrostatic repulsion between LYS32 and LYS484 caused by E484K mutation destroys the salt bridge between LYS32 and GLU484 in the RBD wild type (WT). In contrast, the binding of the K417N mutant to Sb16 effectively maintains the salt bridge between LYS32 and GLU484. Therefore, our research suggests that the salt bridges between RBD and synthetic nanobodies are crucial for binding synthetic nanobodies to RBD, and a SARS-CoV-2 variant can escape neutralization from nanobodies by creating electrostatic repulsion between them.
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Affiliation(s)
- Hujun Shen
- Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Guizhou Education University, Guiyang, 550018, China.
| | - Hengxiu Yang
- Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Guizhou Education University, Guiyang, 550018, China.
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Qerqez AN, Silva RP, Maynard JA. Outsmarting Pathogens with Antibody Engineering. Annu Rev Chem Biomol Eng 2023; 14:217-241. [PMID: 36917814 PMCID: PMC10330301 DOI: 10.1146/annurev-chembioeng-101121-084508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
There is growing interest in identifying antibodies that protect against infectious diseases, especially for high-risk individuals and pathogens for which no vaccine is yet available. However, pathogens that manifest as opportunistic or latent infections express complex arrays of virulence-associated proteins and are adept at avoiding immune responses. Some pathogens have developed strategies to selectively destroy antibodies, whereas others create decoy epitopes that trick the host immune system into generating antibodies that are at best nonprotective and at worst enhance pathogenesis. Antibody engineering strategies can thwart these efforts by accessing conserved neutralizing epitopes, generating Fc domains that resist capture or degradation and even accessing pathogens hidden inside cells. Design of pathogen-resistant antibodies can enhance protection and guide development of vaccine immunogens against these complex pathogens. Here, we discuss general strategies for design of antibodies resistant to specific pathogen defense mechanisms.
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Affiliation(s)
- Ahlam N Qerqez
- Department of Chemical Engineering, The University of Texas, Austin, Texas, USA;
| | - Rui P Silva
- Department of Molecular Biosciences, The University of Texas, Austin, Texas, USA
| | - Jennifer A Maynard
- Department of Chemical Engineering, The University of Texas, Austin, Texas, USA;
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Xiao S, Verkhivker GM, Tao P. Machine learning and protein allostery. Trends Biochem Sci 2023; 48:375-390. [PMID: 36564251 PMCID: PMC10023316 DOI: 10.1016/j.tibs.2022.12.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/16/2022] [Accepted: 12/02/2022] [Indexed: 12/23/2022]
Abstract
The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric mechanisms will have an increasingly important role in bridging a wide spectrum of data-intensive experimental and theoretical technologies.
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Affiliation(s)
- Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75205, USA.
| | - Gennady M Verkhivker
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75205, USA.
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General Trends of the Camelidae Antibody V HHs Domain Dynamics. Int J Mol Sci 2023; 24:ijms24054511. [PMID: 36901942 PMCID: PMC10003728 DOI: 10.3390/ijms24054511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023] Open
Abstract
Conformational flexibility plays an essential role in antibodies' functional and structural stability. They facilitate and determine the strength of antigen-antibody interactions. Camelidae express an interesting subtype of single-chain antibody, named Heavy Chain only Antibody. They have only one N-terminal Variable domain (VHH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, VHH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of VHH domains contributing to these abilities have already been studied compared to classical antibodies. To have the broadest view and understand the changes in dynamics of these macromolecules, large-scale molecular dynamics simulations for a large number of non-redundant VHH structures have been performed for the first time. This analysis reveals the most prevalent movements in these domains. It reveals the four main classes of VHHs dynamics. Diverse local changes were observed in CDRs with various intensities. Similarly, different types of constraints were observed in CDRs, while FRs close to CDRs were sometimes primarily impacted. This study sheds light on the changes in flexibility in different regions of VHH that may impact their in silico design.
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Kuri P, Goswami P. Current Update on Rotavirus in-Silico Multiepitope Vaccine Design. ACS OMEGA 2023; 8:190-207. [PMID: 36643547 PMCID: PMC9835168 DOI: 10.1021/acsomega.2c07213] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/14/2022] [Indexed: 06/06/2023]
Abstract
Rotavirus gastroenteritis is one of the leading causes of pediatric morbidity and mortality worldwide in infants and under-five populations. The World Health Organization (WHO) recommended global incorporation of the rotavirus vaccine in national immunization programs to alleviate the burden of the disease. Implementation of the rotavirus vaccination in certain regions of the world brought about a significant and consistent reduction of rotavirus-associated hospitalizations. However, the efficacy of licensed vaccines remains suboptimal in low-income countries where the incidences of rotavirus gastroenteritis continue to happen unabated. The problem of low efficacy of currently licensed oral rotavirus vaccines in low-income countries necessitates continuous exploration, design, and development of new rotavirus vaccines. Traditional vaccine development is a complex, expensive, labor-intensive, and time-consuming process. Reverse vaccinology essentially utilizes the genome and proteome information on pathogens and has opened new avenues for in-silico multiepitope vaccine design for a plethora of pathogens, promising time reduction in the complete vaccine development pipeline by complementing the traditional vaccinology approach. A substantial number of reviews on licensed rotavirus vaccines and those under evaluation are already available in the literature. However, a collective account of rotavirus in-silico vaccines is lacking in the literature, and such an account may further fuel the interest of researchers to use reverse vaccinology to expedite the vaccine development process. Therefore, the main focus of this review is to summarize the research endeavors undertaken for the design and development of rotavirus vaccines by the reverse vaccinology approach utilizing the tools of immunoinformatics.
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Verkhivker G. Structural and Computational Studies of the SARS-CoV-2 Spike Protein Binding Mechanisms with Nanobodies: From Structure and Dynamics to Avidity-Driven Nanobody Engineering. Int J Mol Sci 2022; 23:ijms23062928. [PMID: 35328351 PMCID: PMC8951411 DOI: 10.3390/ijms23062928] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 03/06/2022] [Accepted: 03/07/2022] [Indexed: 11/28/2022] Open
Abstract
Nanobodies provide important advantages over traditional antibodies, including their smaller size and robust biochemical properties such as high thermal stability, high solubility, and the ability to be bioengineered into novel multivalent, multi-specific, and high-affinity molecules, making them a class of emerging powerful therapies against SARS-CoV-2. Recent research efforts on the design, protein engineering, and structure-functional characterization of nanobodies and their binding with SARS-CoV-2 S proteins reflected a growing realization that nanobody combinations can exploit distinct binding epitopes and leverage the intrinsic plasticity of the conformational landscape for the SARS-CoV-2 S protein to produce efficient neutralizing and mutation resistant characteristics. Structural and computational studies have also been instrumental in quantifying the structure, dynamics, and energetics of the SARS-CoV-2 spike protein binding with nanobodies. In this review, a comprehensive analysis of the current structural, biophysical, and computational biology investigations of SARS-CoV-2 S proteins and their complexes with distinct classes of nanobodies targeting different binding sites is presented. The analysis of computational studies is supplemented by an in-depth examination of mutational scanning simulations and identification of binding energy hotspots for distinct nanobody classes. The review is focused on the analysis of mechanisms underlying synergistic binding of multivalent nanobodies that can be superior to single nanobodies and conventional nanobody cocktails in combating escape mutations by effectively leveraging binding avidity and allosteric cooperativity. We discuss how structural insights and protein engineering approaches together with computational biology tools can aid in the rational design of synergistic combinations that exhibit superior binding and neutralization characteristics owing to avidity-mediated mechanisms.
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Affiliation(s)
- Gennady Verkhivker
- Graduate Program in Computational and Data Sciences, Keck Center for Science and Engineering, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; ; Tel.: +1-714-516-4586
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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Allosteric Determinants of the SARS-CoV-2 Spike Protein Binding with Nanobodies: Examining Mechanisms of Mutational Escape and Sensitivity of the Omicron Variant. Int J Mol Sci 2022; 23:ijms23042172. [PMID: 35216287 PMCID: PMC8877688 DOI: 10.3390/ijms23042172] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/13/2022] [Accepted: 02/14/2022] [Indexed: 02/04/2023] Open
Abstract
Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against the SARS-CoV-2 virus and resilience against mutational escape. In this study, we performed a comprehensive computational analysis of the SARS-CoV-2 spike trimer complexes with single nanobodies Nb6, VHH E, and complex with VHH E/VHH V nanobody combination. We combined coarse-grained and all-atom molecular simulations and collective dynamics analysis with binding free energy scanning, perturbation-response scanning, and network centrality analysis to examine mechanisms of nanobody-induced allosteric modulation and cooperativity in the SARS-CoV-2 spike trimer complexes with these nanobodies. By quantifying energetic and allosteric determinants of the SARS-CoV-2 spike protein binding with nanobodies, we also examined nanobody-induced modulation of escaping mutations and the effect of the Omicron variant on nanobody binding. The mutational scanning analysis supported the notion that E484A mutation can have a significant detrimental effect on nanobody binding and result in Omicron-induced escape from nanobody neutralization. Our findings showed that SARS-CoV-2 spike protein might exploit the plasticity of specific allosteric hotspots to generate escape mutants that alter response to binding without compromising activity. The network analysis supported these findings showing that VHH E/VHH V nanobody binding can induce long-range couplings between the cryptic binding epitope and ACE2-binding site through a broader ensemble of communication paths that is less dependent on specific mediating centers and therefore may be less sensitive to mutational perturbations of functional residues. The results suggest that binding affinity and long-range communications of the SARS-CoV-2 complexes with nanobodies can be determined by structurally stable regulatory centers and conformationally adaptable hotspots that are allosterically coupled and collectively control resilience to mutational escape.
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