Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis.

Tuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette-Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine's physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system's intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine's efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.

Development of multi-epitope based subunit vaccine against Mycobacterium Tuberculosis using immunoinformatics approach.

The etiological agent of tuberculosis (TB), Mycobacterium tuberculosis, is a deadly pathogen that adapts to thrive within the host. Since 2020, the COVID-19 pandemic has had colossal health, societal, and economic consequences, which have affected the reporting of new incidences and mortality cases of TB. As per the WHO 2022 report, 10.6 million people were diagnosed with TB, and 1.6 million died worldwide. The increase in resistant strains of tuberculosis is making it more burdensome to reach the End TB strategy. A reliable and efficient TB vaccine that may avert both primary infection and recurrence of latent TB in adults and adolescents is of the utmost importance. In this study, we used computational techniques to predict the ability of HLA molecules to display epitopes for six TB proteins (PPE68, PE_PGRS17, EspC, LDT4, RpfD, and RpfC) to design the multi-epitope subunit vaccine. From the aimed proteins, the potential B-cell, helper T lymphocyte (HTL), and cytotoxic T lymphocyte (CTL) epitopes were predicted and linked together with LPA adjuvant, and the vaccine was designed. The vaccine's physicochemical analysis demonstrates that it is non-allergic, non-toxic, and antigenic. Then, the vaccine structure was predicted, improved, and verified to yield the optimal structure. The developed vaccine's binding mechanism with distinct immunogenic receptors (Tlr2 and MHC-II) was assessed utilizing molecular docking. The molecular dynamic simulation and MMPBSA analysis were performed to comprehend the complexes' dynamics and stability. The immune simulation was utilized to anticipate the vaccine's immunogenic attributes. In silico cloning was employed to demonstrate the efficient expression of the designed vaccine in E. coli as a host. Moreover, in vitro and in vivo animal testing is required to determine the efficacy of the in silico developed vaccine.Communicated by Ramaswamy H. Sarma.

Structure based exploration of potential lead molecules against the extracellular cysteine protease (EcpA) of Staphylococcus epidermidis: a therapeutic halt.

Nosocomial infection caused by Staphylococcus epidermidis is one of the most widely spread diseases affecting the world's population. No strategies have been developed to overcome this infection and inhibit its spread in immunocompromised patients or patients with indwelling medical devices. EcpA is an extracellular cysteine protease protein involved in biofilm formation on medical devices. Thus, blocking this mechanism may be viable for developing a drug against S. epidermidis. The current research aimed to find new, potent inhibitors that could stop the S. epidermidis EcpA protein from functioning. This study attempted to identify the most promising drug candidates using structure-based virtual screening (SBVS) from libraries of natural ligands. The top-scored molecules were shortlisted based on their IC50 values and pharmacophore properties and further validated through density functional theory (DFT) studies. We found five inhibitors using virtual screening, and the results indicate that these drugs had the highest energy binding potential towards the EcpA targets when compared to the reference molecule E-64, a known cysteine protease inhibitor. In order to evaluate the binding conformational stability of protein-ligand complexes, molecular dynamics (MD) simulations were performed in triplicate for 100 ns, revealing the significant stability of anticipated molecules at the docked site. Furthermore, principal component analysis and binding free energy calculations were performed to understand the dynamics and stability of the complexes. The current study indicated that these compounds looked to be suitable novel inhibitors of the EcpA protein and pave the path for further discovery of novel inhibitors of EcpA.Communicated by Ramaswamy H. Sarma.

Design of multi-epitope based vaccine against Mycobacterium tuberculosis: a subtractive proteomics and reverse vaccinology based immunoinformatics approach.

Tuberculosis is an airborne transmissible disease caused by Mycobacterium tuberculosis that infects millions of lives worldwide. There is still no single comprehensive therapy or preventative available for the lethal illness. Currently, the available vaccine, BCG is ineffectual in preventing the prophylactic adult pulmonary TB and reactivation of latent tuberculosis. Therefore, this investigation was intended to design a new multi-epitope vaccine that can address the existing problems. The subtractive proteomics approach was implemented to prioritize essential, virulence, druggable, and antigenic proteins as suitable vaccine candidates. Furthermore, a reverse vaccinology-based immunoinformatics technique was employed to identify potential B-cell, helper T lymphocytes (HTL), and cytotoxic T lymphocytes (CTL) epitopes from the target proteins. Immune-stimulating adjuvant, linkers, and PADRE (Pan HLA-DR epitopes) amino acid sequences along with the selected epitopes were used to construct a chimeric multi-epitope vaccine. The molecular docking and normal mode analysis (NMA) were carried out to evaluate the binding mode of the designed vaccine with different immunogenic receptors (MHC-I, MHC-II, and Tlr4). In addition, the MD simulation, followed by essential dynamics study and MMPBSA analysis, was carried out to understand the dynamics and stability of the complexes. In-silico cloning was accomplished using E.coli as an expression system to express the designed vaccine successfully. Finally, the immune simulation study has foreseen that our designed vaccine could induce a significant immune response by elevation of different immunoglobulins in the host. However, there is an imperative need for the experimental validation of the designed vaccine in animal models to confer effectiveness and safety.HIGHLIGHTSMulti-epitope based vaccine was designed against Mycobacterium tuberculosis using subtractive proteomics and Immunoinformatics approach.The vaccine was found to be antigenic, non-allergenic, immunogenic, and stable based on in-silico prediction.Population coverage analysis of the proposed vaccine predicts an effective response in the world population.The molecular docking, MD simulation, and MM-PBSA study confirm the stable interaction of the vaccine with immunogenic receptors.In silico cloning and immune simulation of the vaccine demonstrated its successful expression in E.coli and induction of immune response in the host. Communicated by Ramaswamy H. Sarma.

Pyridine appended 2-hydrazinylthiazole derivatives: design, synthesis, in vitro and in silico antimycobacterial studies.

An array of pyridine appended 2-hydrazinylthiazole derivatives has been synthesized to discover novel chemotherapeutic agents for Mycobacterium tuberculosis (Mtb). The drug-likeness of pyridine appended 2-hydrazinylthiazole derivatives was validated using the Lipinski and Veber rules. The designed thiazole molecules have been synthesized through Hantzsch thiazole methodologies. The in vitro antimycobacterial studies have been conducted using Luciferase reporter phage (LRP) assay. Out of thirty pyridine appended 2-hydrazinylthiazole derivatives, the compounds 2b, 3b, 5b, and 8b have exhibited good antimycobacterial activity against Mtb, an H37Rv strain with the minimum inhibitory concentration in the range of 6.40-7.14 µM. In addition, in vitro cytotoxicity of active molecules has been observed against Human Embryonic Kidney Cell lines (HEK293t) using MTT assay. The compounds 3b and 8b are nontoxic and their cell viability is 87% and 96.71% respectively. The in silico analyses of the pyridine appended 2-hydrazinylthiazole derivatives have been studied to find the mode of binding of the active compounds with KasA protein of Mtb. The active compounds showed a strong binding score (-5.27 to -6.23 kcal mol-1).

Multi-epitope based vaccine design against Staphylococcus epidermidis: A subtractive proteomics and immunoinformatics approach.

Staphylococcus epidermidis has emerged as a major contributor of nosocomial infections across the world. With the increased rate of emerging resistant and previously undefined infectious diseases, there is a growing need to develop a novel vaccine possessing required immunogenic properties. The adopted reverse vaccinology approach identified "IMPNQILTI" of LysM domain protein, "YSYTYTIDA" of staphylococcal secretory antigen SsaA, and "YNYDANTGQ" neutral metalloproteinaseas potential peptides for vaccine design. The 9-mer epitope of target proteins is antigenic, virulent, surface-exposed, non-allergenic, and conserved across various strains of S. epidermidis. Protein-protein interactions study indicated the involvement of target proteins in major biological pathways for S. epidermidis pathogenesis. Protein-peptide docking was performed, and population coverage analysis showed significant interactions of T-cell epitopes with the HLA-binding molecules while covering 90.58% of the world's population. Further, a multi-epitope vaccine of 177 amino acids long was constructed. Docking with Toll-like receptor (TLR-2) molecule confirmed the effective interaction of the vaccine with the receptor. The vaccine efficiency in generating an effective immune response in the host was evaluated by immune simulation. Finally, in silico cloning confirmed that the constructed vaccine can be efficiently expressed in E. coli. However, the designed vaccine needs experimental validation to determine the effectiveness and immunogenicity profile, which will ensure an active immunity against S. epidermidis.

Identification and design of a multi-epitope subunit vaccine against the opportunistic pathogen Staphylococcus epidermidis: An immunoinformatics approach.

Staphylococcus epidermidis is one of the major causes of nosocomial infections around the globe that leads to a high rate of mortality and morbidity in both immunocompromised patients and preterm infants. Despite the alarming increase in multi-drug resistance, no promising vaccines are readily available against this pathogen. Thus, the present study is focused on designing a multi-epitope subunit vaccine using five antigenic proteins of S. epidermidis through an immunoinformatics approach. The final vaccine comprised B-cell, HTL, and CTL binding epitopes followed by Lipoprotein LprA adjuvant added at N-terminal to augment the immunogenicity. Physicochemical assessment of the vaccine reveals the antigenic and non-allergic nature. The vaccine structure was designed, refined, validated, and disulfide engineered to obtain the best model. Molecular docking and dynamics simulation of the proposed vaccine with toll-like receptors (TLR-2 and TLR-4) showed strong and stable interactions. MM-PBSA analysis was implemented as an efficient tool to determine the intermolecular binding free energies of the system. The vaccine was subjected to immune simulation to predict its immunogenic profile. In silico cloning suggested that the proposed vaccine can be expressed efficiently in E.coli. Furthermore, in vivo animal experiment is needed to determine the effectiveness of the in silico designed vaccine.Communicated by Ramaswamy H. Sarma.

Molecular docking and simulation studies of gustatory receptor of Aedes aegypti: A potent drug target to distract host-seeking behaviour in mosquitoes.

BACKGROUND & OBJECTIVES: It is well reported that exhaled CO 2 and skin odour from human being assist female mosquitoes to locate human host. Basically, the receptors for this activity are expressed in cpA neurons. In both Aedes aegypti and Anopheles gambiae, this CO 2-sensitive olfactory neuron detects myriad number of chemicals present in human skin. Therefore, manipulation of gustatory receptors housing these neurons may serve as important targets for behavioural intervention. The study was aimed towards virtual screening of small molecules in the analyzed conserved active site residues of gustatory receptor and molecular dynamics simulation study of optimum protein-ligand complex to identify a suitable lead molecule for distracting host-seeking behaviour of mosquitoes. METHODS: The conserved residue analysis of gustatory receptor (GR) of Ae. aegypti and An. gambiae was performed. The structure of GR protein from Ae. aegypti was modeled and validated, and then molecular docking was performed to screen 2903 small molecules against the predicted active residues of GR. Further, simulation studies were also carried out to prove protein-ligand stability. RESULTS: The glutamine 154 residue of GR was found to be highly conserved in Ae. aegypti and An. gambiae. Docking results indicated that the dodecanoic acid, 1,2,3-propanetriyl ester (dynasan 112) was interacting with this residue, as it showed better LibDock score than previously reported ethyl acetate used as mosquito repellant. Simulation studies indicated the structural instability of GR protein in docked form with dynasan 112 suggesting its involvement in structural changes. Based on the interaction energies and stability, this compound has been proposed to be used in mosquitoes' repellant. INTERPRETATION & CONCLUSION: A novel effective odorant acting as inhibitor of GR is proposed based on its stability, docking score, interactions and RMSD, considering ethyl pyruvate as a standard inhibitor. Host preference and host-seeking ability of mosquito vectors play key roles in disease transmission, a clear understanding of these aspects is essential for preventing the spread of the disease.