Unraveling DPP4 Receptor Interactions with SARS-CoV-2 Variants and MERS-CoV: Insights into Pulmonary Disorders via Immunoinformatics and Molecular Dynamics

Human coronaviruses like MERS CoV are known to utilize dipeptidyl peptidase 4 (DPP4), apart from angiotensin-converting enzyme 2(ACE2) as a potential co-receptor for viral cell entry. DPP4, the ubiquitous membrane-bound aminopeptidase, is closely associated with elevation of disease severity in comorbidities. In SARS-CoV-2, there is inadequate evidence for combination of spike protein variants with DPP4, and underlying adversity in COVID-19. To elucidate this mechanistic basis, we have investigated interaction of spike protein variants with DPP4 through molecular docking and simulation studies. The possible binding interactions between the receptor binding domain (RBD) of different spike variants of SARS-CoV-2 and DPP4 have been compared with interactions observed in the experimentally determined structure of the complex of MERS-CoV with DPP4. Comparative binding affinity confers that Delta-CoV-2: DPP4 shows close proximity with MERS-CoV:DPP4, as depicted from accessible surface area, radius of gyration and number of hydrogen bonding in the interface. Mutations in the delta variant, L452R and T478K directly participate in DPP4 interaction, enhancing DPP4 binding. E484K in alpha and gamma variants of spike protein is also found to interact with DPP4. Hence, DPP4 interaction with spike protein becomes more suitable due to mutation, especially due to L452R, T478K and E484K. Furthermore, perturbation in the nearby residues Y495, Q474 and Y489 is evident due to L452R, T478K and E484K, respectively. Virulent strains of spike protein are more susceptible to DPP4 interaction and are prone to be victimized in patients due to comorbidities. Our results will aid the rational optimization of DPP4 as a potential therapeutic target to manage COVID-19 disease severity.

SARS-CoV-2 variants and spike mutations involved in second wave of COVID-19 pandemic in India

Against the backdrop of the second wave of COVID-19 pandemic in India that started in March 2021, we have monitored the spike (S) protein mutations in all the reported (GISAID portal) whole-genome sequences of SARS-CoV-2 circulating in India from 1^st January 2021 to 31^st August 2021. In the 43,102 SARS-CoV-2 genomic sequences analysed, we have identified 24,260 amino acid mutations in the S protein, based on which 265 Pango lineages could be categorized. The dominant lineage in most of the 28 states of India and its 8 union territories was B.1.617.2 (the delta variant). However, the states Madhya Pradesh, Jammu & Kashmir, and Punjab had B.1.1.7 (alpha variant) as the major lineage, while the Himachal Pradesh state reported B.1.36 as the dominating lineage. A detailed analysis of various domains of S protein was carried out for detecting mutations having a prevalence of >1%; 70, 18, 7, 3, 9, 4, and 1 (N = 112) such mutations were observed in the N-terminal domain, receptor binding domain, C -terminal domain, fusion peptide region, heptapeptide repeat (HR)-1 domains, signal peptide domain, and transmembrane region, respectively. However, no mutations were recorded in the HR-2 and cytoplasmic domains of the S protein. Interestingly, 13.39% (N = 15) of these mutations were reported to increase the infectivity and pathogenicity of the virus; 2% (N = 3) were known to be vaccine breakthrough mutations, and 0.89% (N = 1) were known to escape neutralising antibodies. The biological significance of 82% (N = 92) of the reported mutations is yet unknown. As SARS-CoV-2 variants are emerging rapidly, it is critical to continuously monitor local viral mutations to understand national trends of virus circulation. This can tremendously help in designing better preventive regimens in the country, and avoid vaccine breakthrough infections. This article is protected by copyright. All rights reserved.

In Silico Comparative Analysis of the Functional, Structural, and Evolutionary Properties of SARS-CoV-2 Variant Spike Proteins

BACKGROUND

A recent global outbreak of COVID-19 caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) created a pandemic and emerged as a potential threat to humanity. The analysis of virus genetic composition has revealed that the spike protein, one of the major structural proteins, facilitates the entry of the virus to host cells.

OBJECTIVE

The spike protein has become the main target for prophylactics and therapeutics studies. Here, we compared the spike proteins of SARS-CoV-2 variants using bioinformatics tools.

METHODS

The spike protein sequences of wild-type SARS-CoV-2 and its 6 variants-D614G, alpha (B.1.1.7), beta (B.1.351), delta (B.1.617.2), gamma (P.1), and omicron (B.1.1.529)-were retrieved from the NCBI database. The ClustalX program was used to sequence multiple alignment and perform mutational analysis. Several online bioinformatics tools were used to predict the physiological, immunological, and structural features of the spike proteins of SARS-CoV-2 variants. A phylogenetic tree was constructed using CLC software. Statistical analysis of the data was done using jamovi 2 software.

RESULTS

Multiple sequence analysis revealed that the P681R mutation in the delta variant, which changed an amino acid from histidine (H) to arginine (R), made the protein more alkaline due to arginine's high pKa value (12.5) compared to histidine's (6.0). Physicochemical properties revealed the relatively higher isoelectric point (7.34) and aliphatic index (84.65) of the delta variant compared to other variants. Statistical analysis of the isoelectric point, antigenicity, and immunogenicity of all the variants revealed significant correlation, with P values ranging from <.007 to .04. The generation of a 2D gel map showed the separation of the delta spike protein from a grouping of the other variants. The phylogenetic tree of the spike proteins showed that the delta variant was close to and a mix of the Rousettus bat coronavirus and MERS-CoV.

CONCLUSIONS

The comparative analysis of SARS-CoV-2 variants revealed that the delta variant is more aliphatic in nature, which provides more stability to it and subsequently influences virus behavior.

Prediction and Evolution of the Molecular Fitness of SARS-CoV-2 Variants: Introducing SpikePro

The understanding of the molecular mechanisms driving the fitness of the SARS-CoV-2 virus and its mutational evolution is still a critical issue. We built a simplified computational model, called SpikePro, to predict the SARS-CoV-2 fitness from the amino acid sequence and structure of the spike protein. It contains three contributions: the inter-human transmissibility of the virus predicted from the stability of the spike protein, the infectivity computed in terms of the affinity of the spike protein for the ACE2 receptor, and the ability of the virus to escape from the human immune response based on the binding affinity of the spike protein for a set of neutralizing antibodies. Our model reproduces well the available experimental, epidemiological and clinical data on the impact of variants on the biophysical characteristics of the virus. For example, it is able to identify circulating viral strains that, by increasing their fitness, recently became dominant at the population level. SpikePro is a useful, freely available instrument which predicts rapidly and with good accuracy the dangerousness of new viral strains. It can be integrated and play a fundamental role in the genomic surveillance programs of the SARS-CoV-2 virus that, despite all the efforts, remain time-consuming and expensive.

Prediction and Evolution of the Molecular Fitness of SARS-CoV-2 Variants: Introducing SpikePro

The understanding of the molecular mechanisms driving the fitness of the SARS-CoV-2 virus and its mutational evolution is still a critical issue. We built a simplified computational model, called SpikePro, to predict the SARS-CoV-2 fitness from the amino acid sequence and structure of the spike protein. It contains three contributions: the inter-human transmissibility of the virus predicted from the stability of the spike protein, the infectivity computed in terms of the affinity of the spike protein for the ACE2 receptor, and the ability of the virus to escape from the human immune response based on the binding affinity of the spike protein for a set of neutralizing antibodies. Our model reproduces well the available experimental, epidemiological and clinical data on the impact of variants on the biophysical characteristics of the virus. For example, it is able to identify circulating viral strains that, by increasing their fitness, recently became dominant at the population level. SpikePro is a useful, freely available instrument which predicts rapidly and with good accuracy the dangerousness of new viral strains. It can be integrated and play a fundamental role in the genomic surveillance programs of the SARS-CoV-2 virus that, despite all the efforts, remain time-consuming and expensive.