An in silico approach to study the role of epitope order in the multi-epitope-based peptide (MEBP) vaccine design.

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches, especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidates. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison and ranking for the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency (RMVP), MEBP vaccine potency (MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. Further, the MEBP variants with IDs, SPVC_446 and SPVC_537, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be preferred candidates for immediate experimental testing and validation. The method enables quicker selection and high throughput experimental validation of vaccine candidates. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time.

Computational approach to explore the inhibitory potential of biologically derived compounds against Spodoptera litura vitellogenin receptor (VgR) using structure based virtual screening and molecular dynamics.

In the everlasting combat against the pests of agricultural importance, it is essential to come up with a novel strategy for pest control. This can be achieved through understanding the insect pest at cellular and molecular levels. Vitellogenin (Vg) and vitellogenin receptor (VgR) are essential for successful reproduction in insect. The N-terminal Ligand Binding Domain (LBD) of VgR is responsible for the transportation of vital protein (Vg) to the developing oocyte through receptor mediated endocytosis pathway. This can be implemented to various predicaments and betterments for exploitation in pest management, in a target specific and eco-friendly manner. For this, natural metabolites isolated from various biological sources were used as ligand. The purpose of this study was to analyze the inhibitory potential of 14 biologically derived compounds against N-terminal (Ligand Binding Repeats) LBRs of S. litura by computational docking. 3 D structure of LBRs of S. litura was generated by Raptor X software and the structure was refined and validated. The validated structure was docked using autodock vina. Docking results revealed that spinosyn A and milbemycin A4 have inhibitory activity against VgR. Molecular dynamics (MD) simulation confirms the stable binding of the ligand. From the above results, spinosyn A and milbemycin A4 may be exploited for the pest management.Communicated by Ramaswamy H. Sarma.

Immunoglobulin interface redesigning to enhance lebrikizumab mediated immunomodulation of IL-13 hyper-response.

The overexpression of interleukin-13 (IL-13) leads to autoimmune and inflammatory diseases. These adverse responses can be neutralized by using lebrikizumab as a therapeutic monoclonal antibody (mAb). Herein, we have attempted to modulate the lebrikizumab mAb to enhance its binding affinity towards IL-13. The interface residues of the lebrikizumab-IL-13 complex were determined by the PyMOL and verified by the artificial neural network-based B-cell epitope prediction server (ABCpred server) and the Paratome web server. The Cologne University Protein Stability Analysis Tool (CUPSAT) web server based mutational approach was used to identify the stable and favorable interface mutations in the lebrikizumab. Only 40 mutations were selected to generate a single mutant library, and their binding affinity for IL-13 was analyzed by using the Z-Dock server. Based on high Z-score, mutants having a better affinity with IL-13 were selected to create a multi-mutant library. The multi-mutant library was again subjected to the Z-Dock server, and their binding affinity was determined. The highest-scoring ten mAb mutants were validated by using PatchDock and ClusPro servers. The best two potential mAb mutants were identified and subjected to molecular dynamics (MD) simulations to ensure its structural stability at the microscopic level. The changes in the different bonds as the effect of mutation were assessed by LigPlot + v2.1. The AllerTOP and ToxinPred web servers were used to analyze the non-allergic and nontoxic nature of the selected mutants. Therefore, these redesigned mAb could be used for potential treatment against IL-13 associated diseased conditions.Communicated by Ramaswamy H. Sarma.

Exploratory algorithm to devise multi-epitope subunit vaccine by investigating Leishmania donovani membrane proteins.

Visceral leishmaniasis (VL) is a deadly parasitic infection which affects poorest to poor population living in the endemic countries. Increasing resistant to existing drugs, disease burden and a significant number of deaths, necessitates the need for an effective vaccine to prevent the VL infection. This study employed a combinatorial approach to develop a multi-epitope subunit vaccine by exploiting Leishmania donovani membrane proteins. Cytotoxic T- and helper T-lymphocyte binding epitopes along with suitable adjuvant and linkers were joined together in a sequential manner to design the subunit vaccine. The occurrence of B-cell and IFN-γ inducing epitopes approves the ability of subunit vaccine to develop humoral and cell-mediated immune response. Physiochemical parameters of vaccine protein were also assessed followed by homology modeling, model refinement and validation. Moreover, disulfide engineering was performed for the increasing stability of the designed vaccine and molecular dynamics simulation was performed for the comparative stability purposes and to conform the geometric conformations. Further, molecular docking and molecular dynamics simulation study of a mutated and non-mutated subunit vaccine against TLR-4 immune receptor were performed and respective complex stability was determined. In silico cloning ensures the expression of designed vaccine in pET28a(+) expression vector. This study offers a cost-effective and time-saving way to design a novel immunogenic vaccine that could be used to prevent VL infection. Communicated by Ramaswamy H. Sarma.

Encapsulation and Systemic Delivery of 5-Fluorouracil Conjugated with Silkworm Pupa Derived Protein Nanoparticles for Experimental Lymphoma Cancer.

Protein-based drug delivery systems have an edge over conventional drug delivery systems due to their biodegradability, non-antigenicity, and excellent biocompatibility to improve the therapeutic properties of anticancer drugs. This study describes the increased anticancer efficacy of 5-fluorouracil (5-FU) conjugated with silkworm Bombyx mori pupal biowaste derived nanoparticles. Here, we have checked the toxicity of pupa-protein nanoparticles (PpNps) and their potential as a carrier for anticancer drugs. PpNps were prepared by a desolvation method which resulted in a uniform particle size of 162.7 ± 2.9 nm. The 5-FU loaded PpNps were formulated and characterized. The drug content of the developed 5-FU conjugated nanoparticles was evaluated by HPLC analysis. The entrapment efficiency and loading capacity of 5-FU were analyzed by HPLC and determined to be 93% and 88.6%, respectively. The release studies showed the biphasic release of 5-FU at pH 7.4 where rapid drug release was achieved for first 30 min, followed by a sustained release of 5-FU from the developed Nps achieved for the next 8 h. Mice with developed ascites tumors were intraperitoneally treated with 5-FU-PpNps and sacrificed. There was a significant increase in total red blood cells and hemoglobulin in 5-FU-PpNps treated mice, whereas a significant decrease in white blood cells which indicated the reduced inflammation of cancer. Subsequently, 5-FU-PpNps decreased the tumor volume and tumor cell viability, which proved its cytotoxic property to cancer cells. This study presents a novel approach to derive B. mori pupal protein nanoparticles, which can be safely used for cancer drug delivery.

Investigation of immunogenic properties of Hemolin from silkworm, Bombyx mori as carrier protein: an immunoinformatic approach.

Infectious diseases are the major cause of high mortality among infants and geriatric patients. Vaccines are the only weapon in our arsenal to defend us ourselves against innumerable infectious diseases. Though myriad of vaccines are available, still countless people die due to microbial infections. Subunit vaccine is an effective strategy of vaccine development, combining a highly immunogenic carrier protein with highly antigenic but non-immunogenic antigen (haptens). In this study we have made an attempt to utilize the immunoinformatic tool for carrier protein development. Immunogenic mediators (T-cell, B-cell, IFN-γ epitopes) and physiochemical properties of hemolin protein of silkworm, Bombyx mori were studied. Hemolin was found to be non-allergic and highly antigenic in nature. The refined tertiary structure of modelled hemolin was docked against TLR3 and TLR4-MD2 complex. Molecular dynamics study emphasized the stable microscopic interaction between hemolin and TLRs. In-silico cloning and codon optimization was carried out for effective expression of hemolin in E. coli expression system. The overall presence of Cytotoxic T Lymphocytes (CTL), Humoral T Lymphocytes (HTL), and IFN-γ epitopes with high antigenicity depicts the potential of hemolin as a good candidate for carrier protein.

Immunoinformatics approaches to design a novel multi-epitope subunit vaccine against HIV infection.

The end goal of HIV vaccine designing requires novel strategies to elicit a strong humoral and cell-mediated immune response. The emergence of drug resistance and the requirement of next line treatment necessitate the finding of the potential and immunogenic vaccine candidate. This study employed a novel immunoinformatics approach to design multi-epitope subunit vaccine against HIV infection. Here, we designed the subunit vaccine by the combination of CTL, HTL and BCL epitopes along with suitable adjuvant and linkers. Physiochemical characterization of subunit vaccine was assessed to ensure its thermostability, theoretical PI, and amphipathic behavior. In further assessment, subunit vaccine was found to be immunogenic with the capability to generate humoral and cell-mediated immune response. Further, homology modeling and refinement was performed and the refined modeled structure was used for molecular docking with the immune receptor (TLR-3) present on lymphocyte cells. Consequently, molecular dynamics simulation ensured the molecular interaction between TLR-3 and subunit vaccine candidate. Disulfide engineering was performed by placing the cysteine residues in the region of high mobility to enhance the vaccine stability. At last, in silico cloning was performed to warrant the translational efficiency and microbial expression of the designed vaccine.