Nanobody-peptide-conjugate (NPC) for passive immunotherapy against SARS-CoV-2 variants of concern (VoC): a prospective pan-coronavirus therapeutics.

The COVID-19 crisis, incited by the zoonotic SARS-CoV-2 virus, has quickly escalated into a catastrophic public health issue and a grave threat to humankind owing to the advent of mutant viruses. Multiple pharmaceutical therapies or biologics envision stopping the virus from spreading further; however, WHO has voiced concerns about the variants of concern (VoCs) inability to respond. Nanobodies are a new class of antibody mimics with binding affinity and specificity similar to classical mAbs, as well as the privileges of a small molecular weight, ease of entry into solid tissues, and binding cryptic epitopes of the antigen. Herein, we investigated multiple putative anti-SARS-CoV-2 nanobodies targeting the Receptor binding domain of the WHO-listed SARS-CoV-2 variants of concern using a comprehensive computational immunoinformatics methodology. With affinity maturation via alanine scanning mutagenesis, we remodeled an ultrapotent nanobody with substantial breadth and potency, exhibiting pico-molar binding affinities against all the VoCs. An antiviral peptide with specificity for ACE-2 receptors was affixed to make it multispecific and discourage viral entry. Collectively, we constructed a broad-spectrum therapeutic biparatopic nanobody-peptide conjugate (NPC) extending coverage to SARS-CoV-2 VoCs RBDs. We PEGylated the biparatopic construct with 20kD maleimide-terminated PEG (MAL-(PEG)n-OMe) to improve its clinical efficacy limiting rapid renal clearance, and performed in silico cloning to facilitate future experimental studies. Our findings suggest that combining biparatopic nanobody conjugate with standard treatment may be a promising bivariate tool for combating viral entry during COVID-19 illness.

Mutational Effect of Some Major COVID-19 Variants on Binding of the S Protein to ACE2.

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has many variants that accelerated the spread of the virus. In this study, we investigated the quantitative effect of some major mutants of the spike protein of SARS-CoV-2 binding to the human angiotensin-converting enzyme 2 (ACE2). These mutations are directly related to the Variant of Concern (VOC) including Alpha, Beta, Gamma, Delta and Omicron. Our calculations show that five major mutations (N501Y, E484K, L452R, T478K and K417N), first reported in Alpha, Beta, Gamma and Delta variants, all increase the binding of the S protein to ACE2 (except K417N), consistent with the experimental findings. We also studied an additional eight mutations of the Omicron variant that are located on the interface of the receptor binding domain (RDB) and have not been reported in other VOCs. Our study showed that most of these mutations (except Y505H and G446S) enhance the binding of the S protein to ACE2. The computational predictions helped explain why the Omicron variant quickly became dominant worldwide. Finally, comparison of several different computational methods for binding free energy calculation of these mutants was made. The alanine scanning method used in the current calculation helped to elucidate the residue-specific interactions responsible for the enhanced binding affinities of the mutants. The results show that the ASGB (alanine scanning with generalized Born) method is an efficient and reliable method for these binding free energy calculations due to mutations.

Binding mode characterization of 13b in the monomeric and dimeric states of SARS-CoV-2 main protease using molecular dynamics simulations.

The main protease, Mpro/3CLpro, plays an essential role in processing polyproteins translated from viral RNA to produce functional viral proteins and therefore serve as an attractive target for discovering COVID-19 therapeutics. The availability of both monomer and dimer crystal bound with a common ligand, '13b' (α-ketoamide inhibitor), opened up opportunities to understand the Mpro mechanism of action. A comparative analysis of both forms of Mpro was carried out to elucidate the binding site architectural differences in the presence and absence of '13b'. Molecular dynamics simulations suggest that the presence of '13b' enhances the stability of Mpro than the unbound APO form. The N- and C- terminals of both the protomers stabilize each other, and making it's interface essential for the active form of Mpro. In comparison to monomer, the relatively high affinity of '13b' is gained in dimer pocket due to the high stability of the pocket by the interaction of S1 residue of chain B with residues F140, E166 and H172 of chain A, which is absent in monomer. The comprehensive essential dynamics, protein structure network analysis and thermodynamic profiling highlight the hot-spots, pivotal in molecular recognition process at protein-ligand and protein-protein interaction levels, cross-validated through computational alanine scanning study. A comparative description of '13b' binding mechanism in both forms illustrates valuable insights into the inhibition mechanism and the selection of critical residues suitable for the structure-based approaches for the identification of more potent Mpro inhibitors.Communicated by Ramaswamy H. Sarma.

An in-silico approach to identify the potential hot spots in SARS-CoV-2 spike RBD to block the interaction with ACE2 receptor.

A novel acute viral pneumonia induced by SARS-CoV-2 exploded at the end of 2019, causing a severe medical and economic crisis. For developing specific pharmacotherapy against SARS-CoV-2, an in silico virtual screening was developed for the available in-house molecules. The conserved domain analysis was performed to identify the highly conserved and exposed amino acid regions in the SARS-CoV-2-S RBD sites. The Protein-Protein interaction analyses demonstrated the higher affinity between the SARS-CoV-2-S and ACE2 due to varieties of significant interactions between them. The computational alanine scanning mutation study has recognized the highly stabilized amino acids in the SARS-CoV-2-S RBD/ACE2 complex. The cumulative sequence investigations have inferred that Lys417, Phe486, Asn487, Tyr489, and Gln493 are perhaps the iconic target amino acids to develop a drug molecule or vaccine against SARS-CoV-2 infection. Most of the selected compounds include luteolin, zhebeirine, 3-dehydroverticine, embelin, andrographolide, ophiopogonin D, crocin-1, sprengerinin A, B, C, peimine, etc. were exhibited distinguish drug actions through the strong hydrogen bonding with the hot spots of the RBD. Besides, the 100 ns molecular dynamics simulation and free energy binding analysis showed the significant efficacy of luteolin to inhibit the infection of SARS-CoV-2. Highlights:Highly conserved and exposed amino acids in the SARS-CoV-2-S-RBD sites has been identifiedComputational alanine scanning mutation study has recognized the highly stabilized hot spots in the SARS-CoV-2-S RBD/ACE2 complex.Virtual screening has been executed to identify the drug actions in the RBD regionMost of the selected natural products were involved in the distinctive strong interactions with hot spots of RBD to inhibit the infection of SARS-CoV-2.[Formula: see text] Communicated by Ramaswamy H. Sarma.

HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.

Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http://chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http://agroda.gzu.edu.cn:9999/ccb/server/HISNAPI/.

Computational Hot-Spot Analysis of the SARS-CoV-2 Receptor Binding Domain/ACE2 Complex*.

Infection and replication of SARS CoV-2 (the virus that causes COVID-19) requires entry to the interior of host cells. In humans, a protein-protein interaction (PPI) between the SARS CoV-2 receptor-binding domain (RBD) and the extracellular peptidase domain of ACE2 on the surface of cells in the lower respiratory tract is an initial step in the entry pathway. Inhibition of the SARS CoV-2 RBD/ACE2 PPI is currently being evaluated as a target for therapeutic and/or prophylactic intervention. However, relatively little is known about the molecular underpinnings of this complex. Employing multiple computational platforms, we predicted "hot-spot" residues in a positive-control PPI (PMI/MDM2) and the CoV-2 RBD/ACE2 complex. Computational alanine scanning mutagenesis was performed to predict changes in Gibbs' free energy that are associated with mutating residues at the positive control (PMI/MDM2) or SARS RBD/ACE2 binding interface to alanine. Additionally, we used the Adaptive Poisson-Boltzmann Solver to calculate macromolecular electrostatic surfaces at the interface of the positive-control PPI and SARS CoV-2/ACE2 PPI. Finally, a comparative analysis of hot-spot residues for SARS-CoV and SARS-CoV-2, in complex with ACE2, is provided. Collectively, this study illuminates predicted hot-spot residues, and clusters, at the SARS CoV-2 RBD/ACE2 binding interface, potentially guiding the development of reagents capable of disrupting this complex and halting COVID-19.

Coevolution, Dynamics and Allostery Conspire in Shaping Cooperative Binding and Signal Transmission of the SARS-CoV-2 Spike Protein with Human Angiotensin-Converting Enzyme 2.

Binding to the host receptor is a critical initial step for the coronavirus SARS-CoV-2 spike protein to enter into target cells and trigger virus transmission. A detailed dynamic and energetic view of the binding mechanisms underlying virus entry is not fully understood and the consensus around the molecular origins behind binding preferences of SARS-CoV-2 for binding with the angiotensin-converting enzyme 2 (ACE2) host receptor is yet to be established. In this work, we performed a comprehensive computational investigation in which sequence analysis and modeling of coevolutionary networks are combined with atomistic molecular simulations and comparative binding free energy analysis of the SARS-CoV and SARS-CoV-2 spike protein receptor binding domains with the ACE2 host receptor. Different from other computational studies, we systematically examine the molecular and energetic determinants of the binding mechanisms between SARS-CoV-2 and ACE2 proteins through the lens of coevolution, conformational dynamics, and allosteric interactions that conspire to drive binding interactions and signal transmission. Conformational dynamics analysis revealed the important differences in mobility of the binding interfaces for the SARS-CoV-2 spike protein that are not confined to several binding hotspots, but instead are broadly distributed across many interface residues. Through coevolutionary network analysis and dynamics-based alanine scanning, we established linkages between the binding energy hotspots and potential regulators and carriers of signal communication in the virus-host receptor complexes. The results of this study detailed a binding mechanism in which the energetics of the SARS-CoV-2 association with ACE2 may be determined by cumulative changes of a number of residues distributed across the entire binding interface. The central findings of this study are consistent with structural and biochemical data and highlight drug discovery challenges of inhibiting large and adaptive protein-protein interfaces responsible for virus entry and infection transmission.

Mechanistic Insights to the Binding of Antibody CR3022 Against RBD from SARS-CoV and HCoV-19/SARS-CoV-2: A Computational Study.

Aims & Objective: Coronavirus Disease 2019 (COVID-19) caused by the human coronavirus 2019 (HCoV-19, also known as SARS-CoV-2) infection is currently in a global outbreak. COVID-19 has posed a huge threat to public health and economic stability worldwide. CR3022, a human monoclonal neutralizing antibody isolated from a Severe Acute Respiratory Syndrome (SARS) recovery patient, was confirmed to be able to bind the S protein of HCoV-19 with a certain degree of neutralizing activity. Crystal structural information indicated that CR3022 could bind to the epitope on the receptor binding domain (RBD) of HCoV-19, whose epitope consists of 28 amino acids, and 24 of them are conserved in SARS-CoV of SARS. However, the crystal structure is only a static conformation at a certain moment in time, and it cannot provide dynamic details of the interaction between antigen and antibody. METHODS: In this study, molecular dynamics (MD) simulation combined with MM/PBSA and CAS methods were performed to investigate the mechanism of binding of CR3022 against SARS-CoVRBD and HCoV-19-RBD in order to determine their holographic dynamic information. RESULTS: It was found that the CR3022-SARS-CoV-RBD complex was more stable during 100ns MD run than that of the CR3022-HCoV-19-RBD system. There were common conservative amino acids on the ß2 sheet of RBD, including Tyr369, Phe377, Lys378, Tyr380, Gly381, Lys386, Leu390 and others. These conservative amino acids play significant roles in the binding process of CR3022 antibody against SARS-CoV-RBD and HCoV-19-RBD. It was also found that the binding mode of CR3022 to its native target SARS-CoV-RBD is more comprehensive and uniform. Moreover, the ß2 sheet residue Thr385 and non-ß2 sheet residues Arg408 and Asp428 of the CR3022-SARS-CoV-RBD system were found to be crucial for their binding affinities, thus forming a special conformational epitope. However, these key amino acids are not present in the CR3022-HCoV-19-RBD system. The binding mode of CR3022 and HCoV-19-RBD is similar to that of SARS-CoV-RBD, but the deficiency of crucial hydrogen-bonds and salt-bridges. Therefore, the binding of CR3022 and HCoV-19-RBD only draws on the partial mode of the binding of CR3022 and SARS-CoV-RBD, so there is a loss of affinity. CONCLUSION: Thus, in order to better fight the epidemic of COVID-19 with the CR3022 antibody, this antibody needs to further improve the neutralization efficiency of HCoV-19 through mutation of it's CDR region.

Computational Alanine Scanning and Structural Analysis of the SARS-CoV-2 Spike Protein/Angiotensin-Converting Enzyme 2 Complex.

The recent emergence of the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent for the coronavirus disease 2019 (COVID-19), is causing a global pandemic that poses enormous challenges to global public health and economies. SARS-CoV-2 host cell entry is mediated by the interaction of the viral transmembrane spike glycoprotein (S-protein) with the angiotensin-converting enzyme 2 gene (ACE2), an essential counter-regulatory carboxypeptidase of the renin-angiotensin hormone system that is a critical regulator of blood volume, systemic vascular resistance, and thus cardiovascular homeostasis. Accordingly, this work reports an atomistic-based, reliable in silico structural and energetic framework of the interactions between the receptor-binding domain of the SARS-CoV-2 S-protein and its host cellular receptor ACE2 that provides qualitative and quantitative insights into the main molecular determinants in virus/receptor recognition. In particular, residues D38, K31, E37, K353, and Y41 on ACE2 and Q498, T500, and R403 on the SARS-CoV-2 S-protein receptor-binding domain are determined as true hot spots, contributing to shaping and determining the stability of the relevant protein-protein interface. Overall, these results could be used to estimate the binding affinity of the viral protein to different allelic variants of ACE2 receptors discovered in COVID-19 patients and for the effective structure-based design and development of neutralizing antibodies, vaccines, and protein/protein inhibitors against this terrible new coronavirus.

Structural insights into the mechanism of RNA recognition by the N-terminal RNA-binding domain of the SARS-CoV-2 nucleocapsid phosphoprotein.

The emergence of recent SARS-CoV-2 has become a global health issue. This single-stranded positive-sense RNA virus is continuously spreading with increasing morbidities and mortalities. The proteome of this virus contains four structural and sixteen nonstructural proteins that ensure the replication of the virus in the host cell. However, the role of phosphoprotein (N) in RNA recognition, replicating, transcribing the viral genome, and modulating the host immune response is indispensable. Recently, the NMR structure of the N-terminal domain of the Nucleocapsid Phosphoprotein has been reported, but its precise structural mechanism of how the ssRNA interacts with it is not reported yet. Therefore, here, we have used an integrated computational pipeline to identify the key residues, which play an essential role in RNA recognition. We generated multiple variants by using an alanine scanning strategy and performed an extensive simulation for each system to signify the role of each interfacial residue. Our analyses suggest that residues T57A, H59A, S105A, R107A, F171A, and Y172A significantly affected the dynamics and binding of RNA. Furthermore, per-residue energy decomposition analysis suggests that residues T57, H59, S105 and R107 are the key hotspots for drug discovery. Thus, these residues may be useful as potential pharmacophores in drug designing.