Computational Immune Proteomics Approach to Target COVID-19

Updates on drug designing approach through computational strategies: a review

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

A New Strategy for Mapping Epitopes of LACK and PEPCK Proteins of Leishmania amazonensis Specific for Major Histocompatibility Complex Class I

Leishmaniasis represents a complex of diseases with a broad clinical spectrum and epidemiological diversity, considered a major public health problem. Although there is treatment, there are still no vaccines for cutaneous leishmaniasis. Because Leishmania spp. is an intracellular protozoan with several escape mechanisms, a vaccine must provoke cellular and humoral immune responses. Previously, we identified the Leishmania homolog of receptors for activated C kinase (LACK) and phosphoenolpyruvate carboxykinase (PEPCK) proteins as strong immunogens and candidates for the development of a vaccine strategy. The present work focuses on the in silico prediction and characterization of antigenic epitopes that might interact with mice or human major histocompatibility complex class I. After immunogenicity prediction on the Immune Epitope Database (IEDB) and the Database of MHC Ligands and Peptide Motifs (SYFPEITHI), 26 peptides were selected for interaction assays with infected mouse lymphocytes by flow cytometry and ELISpot. This strategy identified nine antigenic peptides (pL1-H2, pPL3-H2, pL10-HLA, pP13-H2, pP14-H2, pP15-H2, pP16-H2, pP17-H2, pP18-H2, pP26-HLA), which are strong candidates for developing a peptide vaccine against leishmaniasis.

Comparative highlights on MERS-CoV, SARS-CoV-1, SARS-CoV-2, and NEO-CoV

The severe acute respiratory syndrome (SARS-CoV, now SARS-CoV-1), middle east respiratory syndrome (MERS-CoV), Neo-CoV, and 2019 novel coronavirus (SARS-CoV-2/COVID-19) are the most notable coronaviruses, infecting the number of people worldwide by targeting the respiratory system. All these viruses are of zoonotic origin, predominantly from bats which are one of the natural reservoir hosts for coronaviruses. Thus, the major goal of our review article is to compare and contrast the characteristics and attributes of these coronaviruses. The SARS-CoV-1, MERS-CoV, and COVID-19 have many viral similarities due to their classification, they are not genetically related. COVID-19 shares approximately 79 % of its genome with SARS-CoV-1 and about 50 % with MERS-CoV. The shared receptor protein, ACE2 exhibit the most striking genetic similarities between SARS-CoV-1 and SARS-CoV-2. SARS-CoV primarily replicates in the epithelial cells of the respiratory system, but it may also affect macrophages, monocytes, activated T cells, and dendritic cells. MERS-CoV not only infects and replicates inside the epithelial and immune cells, but it may lyse them too, which is one of the common reasons for MERS's higher mortality rate. The details of infections caused by SARS-CoV-2 and lytic replication mechanisms in host cells are currently mysterious. In this review article, we will discuss the comparative highlights of SARS-CoV-1, MERS-CoV, SARS-CoV-2, and Neo-CoV, concerning their structural features, morphological characteristics, sources of virus origin and their evolutionary transitions, infection mechanism, computational study approaches, pathogenesis and their severity towards several diseases, possible therapeutic approaches, and preventive measures.

Synthetic lethality-based prediction of anti-SARS-CoV-2 targets

Novel strategies are needed to identify drug targets and treatments for the COVID-19 pandemic. The altered gene expression of virus-infected host cells provides an opportunity to specifically inhibit viral propagation via targeting the synthetic lethal and synthetic dosage lethal (SL/SDL) partners of such altered host genes. Pursuing this disparate antiviral strategy, here we comprehensively analyzed multiple in vitro and in vivo bulk and single-cell RNA-sequencing datasets of SARS-CoV-2 infection to predict clinically relevant candidate antiviral targets that are SL/SDL with altered host genes. The predicted SL/SDL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. We further selected a focused subset of 26 genes that we experimentally tested in a targeted siRNA screen using human Caco-2 cells. Notably, as predicted, knocking down these targets reduced viral replication and cell viability only under the infected condition without harming noninfected healthy cells.

Looking at COVID-19 from a Systems Biology Perspective

The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus-human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus-host interactions, and in the development of disease classifiers and tools for drug repurposing.

Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia

BACKGROUND

Klebsiella pneumoniae is an emerging human pathogen causing neonatal lung disease, catheter-associated infections, and nosocomial outbreaks with high fatality rates. Capsular polysaccharide (CPS) protein plays a major determinant in virulence and is considered as a promising target for vaccine development.

RESEARCH DESIGN AND METHODS

In this study, we used immunoinformatic approaches to design a multi-peptide vaccine against K. pneumonia. The epitopes were selected through several immune filters, such as antigenicity, conservancy, nontoxicity, non-allergenicity, binding affinity to HLA alleles, overlapping epitopes, and peptides having common epitopes.

RESULTS

Finally, a construct comprising 2 B-Cell, 8 CTL, 2 HTL epitopes, along with adjuvant, linkers was designed. Peptide-HLA interaction analysis showed strong binding of these epitopes with several common HLA molecules. The in silico immune simulation and population coverage analysis of the vaccine showed its potential to evoke strong immune responses.. Further, the interaction between vaccine and immune was evaluated by docking and simulation, revealing high affinity and complex stability. Codon adaptation and in silico cloning revealed higher expression of vaccine in E. coli K12 expression system.

CONCLUSIONS

Conclusively, the findings of the present study suggest that the designed novel multi-epitopic vaccine holds potential for further experimental validation against the pathogen.

Synthetic lethality-based prediction of anti-SARS-CoV-2 targets

Novel strategies are needed to identify drug targets and treatments for the COVID-19 pandemic. The altered gene expression of virus-infected host cells provides an opportunity to specifically inhibit viral propagation via targeting the synthetic lethal (SL) partners of such altered host genes. Pursuing this antiviral strategy, here we comprehensively analyzed multiple in vitro and in vivo bulk and single-cell RNA-sequencing datasets of SARS-CoV-2 infection to predict clinically relevant candidate antiviral targets that are SL with altered host genes. The predicted SL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. Integrating our predictions with the results of these screens, we further selected a focused subset of 26 genes that we experimentally tested in a targeted siRNA screen using human Caco-2 cells. Notably, as predicted, knocking down these targets reduced viral replication and cell viability only under the infected condition without harming non-infected cells. Our results are made publicly available, to facilitate their in vivo testing and further validation.

In-silico immunoinformatic analysis of SARS-CoV-2 virus for the development of putative vaccine construct

COVID-19 (CoronaVirus disease 2019) is caused by the SARS-CoV-2 virus (severe acute respiratory syndrome corona virus 2). SARS-CoV-2 virus is highly contagious and affects the human respiratory tract resulting in symptoms such as high fever, body ache, cough, dysfunctions of tastebuds and smelling sense of body. The objective of the present study involves immunoinformatic analysis to predict COVID-19 protein for vaccine construct based on the genomic information SARS-CoV-2 virus. At present, as per WHO estimates, around 133 COVID-19 novel vaccines under development. Three amino acid sequences of SARS-CoV-2 were retrieved from the NCBI database for the analysis of vaccine construct. This study involves computational and immunoinformatic methods. The Immunoinformatic tools used in the present study are NetCTL server, IFN epitope server, Toxin PRED, BCPred, CTL + HTL + ADJUVANTS + LINKERS, AlgPredserver, VaxiJenserver, ProtParam to predict vaccine construct. The secondary and tertiary structure prediction is done by PSIPRED, I-TASSER, Galaxy refine, prosA + Ramachandran. Finally, docking of the vaccine constructs and ligand was done with the help of Cluspro 2.0. C-ImmSimm webserver to simulate the potential vaccine construct. The present study demonstrated three potential Vaccine constructs for the SARS-CoV-2 virus, which were docked with TLR8 (Toll-likereceptor8). Interestingly from these, all constructs one having a high potential for the inhibition effect of the SARS-CoV-2virus. Immunological simulation data shows significant elevated amount of memory B cell; also, the high response was seen in TH(Helper) and TC(cytotoxic) cell population from the vaccine construct proposed in the current study. Hence, these constructs are suitable vaccine candidates that might be useful in developing a novel vaccine.

Exploring peptide studies related to SARS-CoV to accelerate the development of novel therapeutic and prophylactic solutions against COVID-19

Recent advances in peptide research revolutionized therapeutic discoveries for various infectious diseases. In view of the ongoing threat of the COVID-19 pandemic, there is an urgent need to develop potential therapeutic options. Intense and accomplishing research is being carried out to develop broad-spectrum vaccines and treatment options for corona viruses, due to the risk of recurrent infection by the existing strains or pandemic outbreaks by new mutant strains. Developing a novel medicine is costly and time consuming, which increases the value of repurposing existing therapies. Since, SARS-CoV-2 shares significant genomic homology with SARS-CoV, we have summarized various peptides identified against SARS-CoV using in silico and molecular studies and also the peptides effective against SARS-CoV-2. Dissecting the molecular mechanisms underlying viral infection could yield fundamental insights in the discovery of new antiviral agents, targeting viral proteins or host factors. We postulate that these peptides can serve as effective components for therapeutic options against SARS-CoV-2, supporting clinical scientists globally in selectively identifying and testing the therapeutic and prophylactic agents for COVID-19 treatment. In addition, we also summarized the latest updates on peptide therapeutics against SARS-CoV-2.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

Food Safety Concerns in “COVID-19 Era”

In March 2020, the World Health Organization (WHO) declared that the COVID-19 outbreak can be characterized as a pandemic. Human-to-human transmission of the SARS-CoV-2 virus may initially be blamed as the first cause of spread, but can an infection be contracted by ingestion of contaminated food or touching contaminated food surfaces? Recently cold-chain food contamination has been indicated as a possible source of many human cases in China. However, the risk of a food-related COVID-19 infection is still debated since the virus may reach people through a fresh product or packaging, which have been touched/sneezed on by infected people. This review summarizes the most recent evidence on the zoonotic origin of the pandemic, reports the main results regarding the transmission of SARS-CoV-2 through food or a food chain, as well as the persistence of the virus at different environmental conditions and surfaces. Emphasis is also posed on how to manage the risk of food-related COVID-19 spread and potential approaches that can reduce the risk of SARS-CoV-2 contamination.

Proteomics in the COVID-19 Battlefield: First Semester Check-Up

Proteomics offers a wide collection of methodologies to study biological systems at the finest granularity. Faced with COVID‐19, the most worrying pandemic in a century, proteomics researchers have made significant progress in understanding how the causative virus hijacks the host's cellular machinery and multiplies exponentially, how the disease can be diagnosed, and how it develops, as well as its severity predicted. Numerous cellular targets of potential interest for the development of new antiviral drugs have been documented. Here, the most striking results obtained in the proteomics field over this first semester of the pandemic are presented. The molecular machinery of SARS‐CoV‐2 is much more complex than initially believed, as many post‐translational modifications can occur, leading to a myriad of proteoforms and a broad heterogeneity of viral particles. The interplay of protein–protein interactions, protein abundances, and post‐translational modifications has yet to be fully documented to provide a full picture of this intriguing but lethal biological threat. Proteomics has the potential to provide rapid detection of the SARS‐CoV‐2 virus by mass spectrometry proteotyping, and to further increase the knowledge of severe respiratory syndrome COVID‐19 and its long‐term health consequences.