HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA

Energetics of Spike Protein Opening of SARS-CoV-1 and SARS-CoV-2 and Its Variants of Concern: Implications in Host Receptor Scanning and Transmission

The receptor binding domain(s) (RBD) of spike (S) proteins of SARS-CoV-1 and SARS-CoV-2 (severe acute respiratory syndrome coronavirus) undergoes closed to open transition to engage with host ACE2 receptors. In this study, using multi atomistic (equilibrium) and targeted (non-equilibrium) molecular dynamics simulations, we have compared energetics of RBD opening pathways in full-length (modeled from cryo-EM structures) S proteins of SARS-CoV-1 and SARS-CoV-2. Our data indicate that amino acid variations at the RBD interaction interface can culminate into distinct free energy landscapes of RBD opening in these S proteins. We further report that mutations in the S protein of SARS-CoV-2 variants of concern can reduce the protein-protein interaction affinity of RBD(s) with its neighboring domains and could favor its opening to access ACE2 receptors. The findings can also aid in predicting the impact of future mutations on the rate of S protein opening for rapid host receptor scanning.

Designing mRNA- and Peptide-Based Vaccine Construct against Emerging Multidrug-Resistant Citrobacter freundii: A Computational-Based Subtractive Proteomics Approach

Background and Objectives: Citrobacter freundii (C. freundii) is an emerging and opportunistic Gram-negative bacteria of the human gastrointestinal tract associated with nosocomial and severe respiratory tract infections. It has also been associated with pneumonia, bloodstream, and urinary tract infections. Intrinsic and adaptive virulence characteristics of C. freundii have become a significant source of diarrheal infections and food poisoning among immune-compromised patients and newborns. Impulsive usage of antibiotics and these adaptive virulence characteristics has modulated the C. freundii into multidrug-resistant (MDR) bacteria. Conventional approaches are futile against MDR C. freundii. Materials and Methods: The current study exploits the modern computational-based vaccine design approach to treat infections related to MDR C. freundii. A whole proteome of C. freundii (strain: CWH001) was retrieved to screen pathogenic and nonhomologous proteins. Six proteins were shortlisted for the selection of putative epitopes for vaccine construct. Highly antigenic, nonallergen, and nontoxic eleven B-cell, HTL, and TCL epitopes were selected for mRNA- and peptide-based multi-epitope vaccine construct. Secondary and tertiary structures of the multi-epitope vaccine (MEVC) were designed, refined, and validated. Results: Evaluation of population coverage of MHC-I and MHC-II alleles were 72% and 90%, respectively. Docking MEVC with TLR-3 receptor with the binding affinity of 21.46 (kcal/mol) occurred through the mmGBSA process. Further validations include codon optimization with an enhanced CAI value of 0.95 and GC content of about 51%. Immune stimulation and molecular dynamic simulation ensure the antibody production upon antigen interaction with the host and stability of the MEVC construct, respectively. Conclusions: These interpretations propose a new strategy to combat MDR C. freundii. Further, in vivo and in vitro trials of this vaccine will be valuable in combating MDR pathogens.

Gasdermin B over-expression modulates HER2-targeted therapy resistance by inducing protective autophagy through Rab7 activation

Background

Gasdermin B (GSDMB) over-expression promotes poor prognosis and aggressive behavior in HER2 breast cancer by increasing resistance to therapy. Decoding the molecular mechanism of GSDMB-mediated drug resistance is crucial to identify novel effective targeted treatments for HER2/GSDMB aggressive tumors.

Methods

Different in vitro approaches (immunoblot, qRT-PCR, flow cytometry, proteomic analysis, immunoprecipitation, and confocal/electron microscopy) were performed in HER2 breast and gastroesophageal carcinoma cell models. Results were then validated using in vivo preclinical animal models and analyzing human breast and gastric cancer samples.

Results

GSDMB up-regulation renders HER2 cancer cells more resistant to anti-HER2 agents by promoting protective autophagy. Accordingly, the combination of lapatinib with the autophagy inhibitor chloroquine increases the therapeutic response of GSDMB-positive cancers in vitro and in zebrafish and mice tumor xenograft in vivo models. Mechanistically, GSDMB N-terminal domain interacts with the key components of the autophagy machinery LC3B and Rab7, facilitating the Rab7 activation during pro-survival autophagy in response to anti-HER2 therapies. Finally, we validated these results in clinical samples where GSDMB/Rab7/LC3B co-expression associates significantly with relapse in HER2 breast and gastric cancers.

Conclusion

Our findings uncover for the first time a functional link between GSDMB over-expression and protective autophagy in response to HER2-targeted therapies. GSDMB behaves like an autophagy adaptor and plays a pivotal role in modulating autophagosome maturation through Rab7 activation. Finally, our results provide a new and accessible therapeutic approach for HER2/GSDMB + cancers with adverse clinical outcome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02497-w.

Towards specie-specific ensemble vaccine candidates against mammarenaviruses using optimized structural vaccinology pipeline and molecular modelling approaches

Mammarena viruses are emerging pathogenic agents and cause hemorrhagic fevers in humans. These viruses accomplish host immune system evasion to replicate and spread in the host. There are only few available therapeutic options developed for Mammarena Virus (also called MMV). Currently, only a single candidate vaccine called Candid#1 is available against Junin virus. Similarly, the effective treatment Ribavirin is used only in Lassa fever treatments. Herein, immune-informatics pipeline has been used to annotate whole proteome of the seven human infecting Mammarena strains. The extensive immune based analysis reveals specie specific epitopes with a crucial role in immune response induction. This was achieved by construction of immunogenic epitopes (CTL "Cytotoxic T-Lymphocytes", HTL "Helper T-Lymphocytes", and B cell "B-Lymphocytes") based vaccine designs against seven different Mammarena virus species. Furthermore, validation of the vaccine constructs through exploring physiochemical properties was performed to confirm experimental feasibility. Additionally, in-silico cloning and receptor based immune simulation was performed to ensure induction of primary and secondary immune response. This was confirmed through expression of immune factors such as IL, cytokines, and antibodies. The current study provides with novel vaccine designs which needs further demonstrations through potential processing against MMVs. Future studies may be directed towards advanced evaluations to determine the efficacy and safety of the designed vaccines through further experimental procedures.

Evaluating the role of trypsin in silk degumming: An in silico approach

The trypsin being universal enzyme forming family of proteases catalyzes the hydrolysis of proteins into amino acids and regenerates the serine hydroxyl an active site. The trypsin enzyme from D. saccharalis, uses sericin as its preferred substrate. Presence of catalytic triad (serine, aspartic acid and histidine) at the substrate binding site of this enzyme is very important for the catalytic activity. In the current study, the interacting mechanism between the substrate sericin protein and enzyme trypsin protein were explored by integrating various computational approaches including physico-chemical properties, biophysical properties, dynamics, gene ontology, molecular docking, protein - protein interactions, binding free energy calculation and structural motifs were studied. The evolutionary study performed by MEGA X showed that trypsin protein sequence (ALE15212.1) is closely related to cocoonase protein sequence (ADG26770.1) from Antheraea pernyi. 3-D models of trypsin and sericin proteins were predicted using I-TASSER and further validated by PROCHECK, and ProSAweb softwares. The predicted trypsin structure model was assigned E.C. no. 3.4.21.4 which refers hydrolytic mechanism. Gene Ontology predicted by QuickGO showed that trypsin has serine hydrolase activity (GO: 00017171), and part of proteolysis (GO: 0006508) as well as protein metabolic process (GO:0019538) actvity. Molecular docking studies between trypsin and sericin proteins were conducted by the HADDOCK 2.4 having best docked protein complex with Z-score - 1.9. 2D and 3D protein-protein interaction was performed with LIGPLOT⁺ and HAWKDOCK, PDBsum, respectively. The amino acid residues interacting across proteins interface are sericin_chain A representing "Ser133, Tyr214, Thr188, Thr243, Ser225, Ser151, Ser156, His294, Arg293, Gly296″ and trypsin_chain B "Lys120, Tyr246, Asn119, Glu239, Ser62, Tyr194, Ile197, Ser171, Tyr169, Gly170″. Based on our results trypsin shows similarity with cocoonase and presumably trypsin can be used as an alternative source in cocoon degumming.

Discovery of Flavonoids as Novel Inhibitors of ATP Citrate Lyase: Structure–Activity Relationship and Inhibition Profiles

ATP citrate lyase (ACLY) is a key enzyme in glucolipid metabolism and its aberrantly high expression is closely associated with various cancers, hyperlipemia and atherosclerotic cardiovascular diseases. Prospects of ACLY inhibitors as treatments of these diseases are excellent. To date, flavonoids have not been extensively reported as ACLY inhibitors. In our study, 138 flavonoids were screened and 21 of them were subjected to concentration–response curves. A remarkable structure–activity relationship (SAR) trend was found: ortho-dihydroxyphenyl and a conjugated system maintained by a pyrone ring were critical for inhibitory activity. Among these flavonoids, herbacetin had a typical structure and showed a non–aggregated state in solution and a high inhibition potency (IC₅₀ = 0.50 ± 0.08 μM), and therefore was selected as a representative for the ligand–protein interaction study. In thermal shift assays, herbacetin improved the thermal stability of ACLY, suggesting a direct interaction with ACLY. Kinetic studies determined that herbacetin was a noncompetitive inhibitor of ACLY, as illustrated by molecular docking and dynamics simulation. Together, this work demonstrated flavonoids as novel and potent ACLY inhibitors with a remarkable SAR trend, which may help design high–potency ACLY inhibitors. In–depth studies of herbacetin deepened our understanding of the interactions between flavonoids and ACLY.

In silico prediction, characterization, docking studies and molecular dynamics simulation of human p97 in complex with p37 cofactor

Background

The AAA + ATPase p97 is an essential unfoldase/segragase involved in a multitude of cellular processes. It functions as a molecular machine critical for protein homeostasis, homotypic membrane fusion events and organelle biogenesis during mitosis in which it acts in concert with cofactors p47 and p37. Cofactors assist p97 in extracting and unfolding protein substrates through ATP hydrolysis. In contrast to other p97ʼs cofactors, p37 uniquely increases the ATPase activity of p97. Disease-causing mutations in p97, including mutations that cause neurodegenerative diseases, increase cofactor association with its N-domain, ATPase activity and improper substrate processing. Upregulation of p97 has also been observed in various cancers. This study aims towards the characterization of the protein–protein interaction between p97 and p37 at the atomic level. We defined the interacting residues in p97 and p37. The knowledge will facilitate the design of unique small molecules inhibiting this interaction with insights into cancer therapy and drug design.

Results

The homology model of human p37 UBX domain was built from the X-ray crystal structure of p47 C-terminus from rat (PDB code:1S3S, G) as a template and assessed by model validation analysis. According to the HDOCK, HAWKDOCK, MM-GBSA binding free energy calculations and Arpeggio, we found that there are several hydrophobic and two hydrogen-bonding interactions between p37 UBX and p97 N-D1 domain. Residues of p37 UBX predicted to be involved in the interactions with p97 N-D1 domain interface are highly conserved among UBX cofactors.

Conclusion

This study provides a reliable structural insight into the p37-p97 complex binding sites at the atomic level though molecular docking coupled with molecular dynamics simulation. This can guide the rational design of small molecule drugs for inhibiting mutant p97 activity.

Decoding the effects of spike receptor binding domain mutations on antibody escape abilities of omicron variants

Recent times witnessed an upsurge in the number of COVID19 cases which is primarily attributed to the emergence of several omicron variants, although there is substantial population vaccination coverage across the globe. Currently, many therapeutic antibodies have been approved for emergency usage. The present study critically evaluates the effect of mutations observed in several omicron variants on the binding affinities of different classes of RBD-specific antibodies using a combined approach of immunoinformatics and binding free energy calculations. Our binding affinity data clearly show that omicron variants achieve antibody escape abilities by incorporating mutations at the immunogenic hotspot residues for each specific class of antibody. K417N and Y505H point mutations are primarily accountable for the loss of class I antibody binding affinities. The K417N/Q493R/Q498R/Y505H combined mutant significantly reduces binding affinities for all the class I antibodies. E484A single mutation, on the other hand, drastically reduces binding affinities for most of the class II antibodies. E484A and E484A/Q493R double mutations cause a 33–38% reduction in binding affinity for an approved therapeutic monoclonal antibody. The Q498R RBD mutation observed across all the omicron variants can reduce ∼12% binding affinity for REGN10987, a class III therapeutic antibody, and the L452R/Q498R double mutation causes a ∼6% decrease in binding affinities for another class III therapeutic antibody, LY-CoV1404. Our data suggest that achieving the immune evasion abilities appears to be the selection pressure behind the emergence of omicron variants.

Evolutionary progression of collective mutations in Omicron sub-lineages towards efficient RBD-hACE2: Allosteric communications between and within viral and human proteins

The interaction between the Spike (S) protein of SARS-CoV-2 and the human angiotensin converting enzyme 2 (hACE2) is essential for infection, and is a target for neutralizing antibodies. Consequently, selection of mutations in the S protein is expected to be driven by the impact on the interaction with hACE2 and antibody escape. Here, for the first time, we systematically characterized the collective effects of mutations in each of the Omicron sub-lineages (BA.1, BA.2, BA.3 and BA.4) on both the viral S protein receptor binding domain (RBD) and the hACE2 protein using post molecular dynamics studies and dynamic residue network (DRN) analysis. Our analysis suggested that Omicron sub-lineage mutations result in altered physicochemical properties that change conformational flexibility compared to the reference structure, and may contribute to antibody escape. We also observed changes in the hACE2 substrate binding groove in some sub-lineages. Notably, we identified unique allosteric communication paths in the reference protein complex formed by the DRN metrics betweenness centrality and eigencentrality hubs, originating from the RBD core traversing the receptor binding motif of the S protein and the N-terminal domain of the hACE2 to the active site. We showed allosteric changes in residue network paths in both the RBD and hACE2 proteins due to Omicron sub-lineage mutations. Taken together, these data suggest progressive evolution of the Omicron S protein RBD in sub-lineages towards a more efficient interaction with the hACE2 receptor which may account for the increased transmissibility of Omicron variants.

Computer-aided molecular modeling and structural analysis of the human centromere protein–HIKM complex

Background

Protein–peptide and protein–protein interactions play an essential role in different functional and structural cellular organizational aspects. While Cryo-EM and X-ray crystallography generate the most complete structural characterization, most biological interactions exist in biomolecular complexes that are neither compliant nor responsive to direct experimental analysis. The development of computational docking approaches is therefore necessary. This starts from component protein structures to the prediction of their complexes, preferentially with precision close to complex structures generated by X-ray crystallography.

Results

To guarantee faithful chromosomal segregation, there must be a proper assembling of the kinetochore (a protein complex with multiple subunits) at the centromere during the process of cell division. As an important member of the inner kinetochore, defects in any of the subunits making up the CENP-HIKM complex lead to kinetochore dysfunction and an eventual chromosomal mis-segregation and cell death. Previous studies in an attempt to understand the assembly and mechanism devised by the CENP-HIKM in promoting the functionality of the kinetochore have reconstituted the protein complex from different organisms including fungi and yeast. Here, we present a detailed computational model of the physical interactions that exist between each component of the human CENP-HIKM, while validating each modeled structure using orthologs with existing crystal structures from the protein data bank.

Conclusions

Results from this study substantiate the existing hypothesis that the human CENP-HIK complex shares a similar architecture with its fungal and yeast orthologs, and likewise validate the binding mode of CENP-M to the C-terminus of the human CENP-I based on existing experimental reports.

Graphical abstract

Staphylococcal superantigen-like protein 10 induces necroptosis through TNFR1 activation of RIPK3-dependent signal pathways

Staphylococcal aureus (S. aureus) infection can lead to a wide range of diseases such as sepsis and pneumonia. Staphylococcal superantigen-like (SSL) proteins, expressed by all known S. aureus strains, are shown to be involved in immune evasion during S. aureus infection. Here, we show that SSL10, an SSL family protein, exhibits potent cytotoxicity against human cells (HEK293T and HUVEC) by inducing necroptosis upon binding to its receptor TNFR1 on the cell membrane. After binding, two distinct signaling pathways are activated downstream of TNFR1 in a RIPK3-dependent manner, i.e., the RIPK1-RIPK3-MLKL and RIPK3-CaMKII-mitochondrial permeability transition pore (mPTP) pathways. Knockout of ssl10 in S. aureus significantly reduces cytotoxicity of the culture supernatants of S. aureus, indicating that SSL10 is involved in extracellular cytotoxicity during infection. We determined the crystal structure of SSL10 at 1.9 Å resolution and identified a positively charged surface of SSL10 responsible for TNFR1 binding and cytotoxic activity. This study thus provides the description of cytotoxicity through induction of necroptosis by the SSL10 protein, and a potential target for clinical treatment of S. aureus-associated diseases.

The Staphylococcal superantigen like protein 10 induces necroptosis in human cells through binding to TNFR1 by both the N- and C-terminal domains and activating RIPK1-RIPK3-MLKL and RIPK3-CaMKII-mitochondrial permeability transition pore pathways.

In-silico design of an immunoinformatics based multi-epitope vaccine against Leishmania donovani

BACKGROUND

Visceral Leishmaniasis (VL) is a fatal vector-borne parasitic disorder occurring mainly in tropical and subtropical regions. VL falls under the category of neglected tropical diseases with growing drug resistance and lacking a licensed vaccine. Conventional vaccine synthesis techniques are often very laborious and challenging. With the advancement of bioinformatics and its application in immunology, it is now more convenient to design multi-epitope vaccines comprising predicted immuno-dominant epitopes of multiple antigenic proteins. We have chosen four antigenic proteins of Leishmania donovani and identified their T-cell and B-cell epitopes, utilizing those for in-silico chimeric vaccine designing. The various physicochemical characteristics of the vaccine have been explored and the tertiary structure of the chimeric construct is predicted to perform docking studies and molecular dynamics simulations.

RESULTS

The vaccine construct is generated by joining the epitopes with specific linkers. The predicted tertiary structure of the vaccine has been found to be valid and docking studies reveal the construct shows a high affinity towards the TLR-4 receptor. Population coverage analysis shows the vaccine can be effective on the majority of the world population. In-silico immune simulation studies confirms the vaccine to raise a pro-inflammatory response with the proliferation of activated T and B cells. In-silico codon optimization and cloning of the vaccine nucleic acid sequence have also been achieved in the pET28a vector.

CONCLUSION

The above bioinformatics data support that the construct may act as a potential vaccine. Further wet lab synthesis of the vaccine and in vivo works has to be undertaken in animal model to confirm vaccine potency.

Novel insertion/deletion polymorphisms and genetic features of the shadow of prion protein gene (SPRN) in dogs, a prion-resistant animal

Prion diseases are fatal infectious neurodegenerative disorders that are induced by misfolded prion protein (PrP^Sc). Previous studies have reported that the shadow of prion protein (Sho) encoded by the shadow of prion protein gene (SPRN) plays a critical role in stimulating the conversion process of normal PrP (PrP^C) into PrP^Sc, and genetic polymorphisms of the SPRN gene are significantly related to susceptibility to prion diseases. Recent studies have reported that dogs show prion resistance, and there have been several attempts to identify resistance factors to prion diseases in dogs. However, there has been no study of the canine SPRN gene thus far. We investigated genetic polymorphisms of the canine SPRN gene in 201 dogs using amplicon sequencing and compared the number of SPRN polymorphisms among prion-related species. In addition, we performed multiple sequence alignments of the amino acid sequences of Sho among prion-related species by ClustalW and analyzed the 3D structure of Sho using AlphaFold. Furthermore, we assessed the protein–protein interaction of canine PrP with canine Sho carrying wild-type and mutant alleles using HawkDock. We found four novel insertion/deletion polymorphisms of the SPRN gene in 201 dogs and identified a significant difference in the number of SPRN polymorphisms between prion-susceptible and prion-resistant animals. In addition, Sho has two α-helixes linked with the coil. Furthermore, we found different binding complexes and binding free energies between canine Sho and PrP according to SPRN polymorphisms. To the best of our knowledge, this is the first report of canine SPRN polymorphisms.

Improved antibody-specific epitope prediction using AlphaFold and AbAdapt

Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody‐antigen specific features for epitope prediction. In this study, we systematically assessed the impact of integrating the state‐of‐the‐art protein modeling method AlphaFold with the AbAdapt pipeline. By incorporating more accurate antibody models, we observed improvement in docking, paratope prediction, and prediction of antibody‐specific epitopes. We further applied AbAdapt‐AF in an anti‐receptor binding domain (RBD) antibody complex benchmark and found AbAdapt‐AF outperformed three alternative docking methods. Also, AbAdapt‐AF demonstrated higher epitope prediction accuracy than other tested epitope prediction tools in the anti‐RBD antibody complex benchmark. We anticipate that AbAdapt‐AF will facilitate prediction of antigen‐antibody interactions in a wide range of applications.

Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14

A key attribute of persistent or recurring bacterial infections is the ability of the pathogen to evade the host’s immune response. Many Enterobacteriaceae express type 1 pili, a pre-adapted virulence trait, to invade host epithelial cells and establish persistent infections. However, the molecular mechanisms and strategies by which bacteria actively circumvent the immune response of the host remain poorly understood. Here, we identified CD14, the major co-receptor for lipopolysaccharide detection, on mouse dendritic cells (DCs) as a binding partner of FimH, the protein located at the tip of the type 1 pilus of Escherichia coli. The FimH amino acids involved in CD14 binding are highly conserved across pathogenic and non-pathogenic strains. Binding of the pathogenic strain CFT073 to CD14 reduced DC migration by overactivation of integrins and blunted expression of co-stimulatory molecules by overactivating the NFAT (nuclear factor of activated T-cells) pathway, both rate-limiting factors of T cell activation. This response was binary at the single-cell level, but averaged in larger populations exposed to both piliated and non-piliated pathogens, presumably via the exchange of immunomodulatory cytokines. While defining an active molecular mechanism of immune evasion by pathogens, the interaction between FimH and CD14 represents a potential target to interfere with persistent and recurrent infections, such as urinary tract infections or Crohn’s disease.

SAT2 regulates Sertoli cell-germline interactions via STIM1-mediated ROS/WNT/β-catenin signaling pathway

As the main component of seminiferous tubules, Sertoli cells are in close contact with germ cells and generate niche signals, which exhibit pivotal functions in spermatogenesis and male fertility. However, the regulatory mechanisms of Sertoli cell-germline interactions (SGIs) in the testes of neonatal mice (NM) remain largely unclear. Previously, we identified spermidine/spermine N1-acetyl transferase 2 (SAT2) and stromal interaction molecule 1 (STIM1) to be potential regulators of testicular cord formation via comparative proteomics analysis. Here, we demonstrated a novel role of SAT2 for SGIs during testicular development in NM. Testicular explants lacking SAT2 affected the mislocation, but not the quantity, of Sertoli cells, which led to maintenance defects in spermatogonial stem cells (SSCs). Interestingly, SAT2 was essential for the migration of TM4 cells, a Sertoli cell line. Mechanistically, SAT2 was able to bind STIM1, repress its expression, and regulate homeostasis of a reactive oxygen species/wingless type (WNT)/β-catenin pathway in NM testes. Collectively, our study identified that SAT2 was able to regulate SGIs via a STIM1-mediated WNT signaling pathway.

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India

Background

The massive increase in COVID-19 infection had generated a second wave in India during May–June 2021 with a critical pandemic situation. The Delta variant (B.1.617.2) was a significant factor during the second wave. Conversely, the UK had passed through the crucial phase of the pandemic from November to December 2020 due to B.1.1.7. The study tried to comprehend the pandemic response in the UK and India to the spread of the B.1.1.7 (Alpha, UK) variant and B.1.617.2 (Delta, India) variant.

Methods

This study was performed in three directions to understand the pandemic response of the two emerging variants. First, we served comparative genomics, such as genome sequence submission patterns, mutational landscapes, and structural landscapes of significant mutations (N501Y, D614G, L452R, E484Q, and P681R). Second, we performed evolutionary epidemiology using molecular phylogenetics, scatter plots of the cluster evaluation, country-wise transmission pattern, and frequency pattern. Third, the receptor binding pattern was analyzed using the Wuhan reference strain and the other two variants.

Results

The study analyzed the country-wise and region-wise genome sequences and their submission pattern, molecular phylogenetics, scatter plot of the cluster evaluation, country-wise geographical distribution and transmission pattern, frequency pattern, entropy diversity, and mutational landscape of the two variants. The structural pattern was analyzed in the N501Y, D614G L452R, E484Q, and P681R mutations. The study found increased molecular interactivity between hACE2-RBD binding of B.1.1.7 and B.1.617.2 compared to the Wuhan reference strain. Our receptor binding analysis showed a similar indication pattern for hACE2-RBD of these two variants. However, B.1.617.2 offers slightly better stability in the hACE2-RBD binding pattern through MD simulation than B.1.1.7.

Conclusion

The increased hACE2-RBD binding pattern of B.1.1.7 and B.1.617.2 might help to increase the infectivity compared to the Wuhan reference strain.

Most frequently harboured missense variants of hACE2 across different populations exhibit varying patterns of binding interaction with spike glycoproteins of emerging SARS-CoV-2 of different lineages

Since the emergence of SARS-CoV-2 at Wuhan in the Hubei province of China in 2019, the virus has accumulated various mutations, giving rise to many variants. According to the combinations of mutations acquired, these variants are classified into lineages and greatly differ in infectivity and transmissibility. In 2021 alone, a variant of interest (VoI) Mu (B.1.621), as well as, variants of concern (VoC) Delta (B.1.617.2) and Omicron (BA.1, BA.2) and later in 2022, BA.4, BA.5, and BA.2.12.1 have emerged. Since then, the world has seen prominent surges in the rate of infection during short periods of time. However, not all populations have suffered equally, which suggests a possible role of host genetic factors. Here, we investigated the strength of binding of the spike glycoprotein receptor-binding domain (RBD) of the SARS-CoV-2 variants: Mu, Delta, Delta Plus (AY.1), Omicron sub-variants BA.1, BA.2, BA.4, BA.5, and BA.2.12.1 with the human angiotensin-converting enzyme 2 (hACE2) missense variants prevalent in major populations. In this purpose, molecular docking analysis, as well as, molecular dynamics simulation was performed of the above-mentioned SARS-CoV-2 RBD variants with the hACE2 containing the single amino acid substitutions prevalent in African (E37K), Latin American (F40L), non-Finnish European (D355 N), and South Asian (P84T) populations, in order to predict the effects of the lineage-defining mutations of the viral variants on receptor binding. The effects of these mutations on protein stability were also explored. The protein-protein docking and molecular dynamics simulation analyses have revealed variable strength of attachment and exhibited altered interactions in the case of different hACE2-RBD complexes. In vitro studies are warranted to confirm these findings which may enable early prediction regarding the risk of transmissibility of newly emerging variants across different populations in the future.

In silico Analysis of Peptide-Based Biomarkers for the Diagnosis and Prevention of Latent Tuberculosis Infection

Background

Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but there are no specific methods for diagnosing and preventing LTBI.

Methods

Dominant T and B cell epitopes predicted from five antigens related to LTBI and Mycobacterium tuberculosis region of difference (LTBI-RD) were used to construct a novel polypeptide molecule (PPM). Then, the physicochemical properties, secondary structure, tertiary structure of the PPM, and its binding ability to toll-like receptor 2 (TLR2) and TLR4 were analyzed by bioinformatics tools. Finally, immune stimulation and expression optimization of the PPM were carried out.

Results

Four helper T lymphocytes (HTL) epitopes, five cytotoxic T lymphocytes (CTL) epitopes, and three B cell epitopes were predicted and screened from five LTBI-RD related antigens. These epitopes were connected in series with linkers and adjuvants to construct a novel PPM termed C543P. The results indicated that antigenicity and immunogenicity scores of the C543P candidate were 0.936399 and 1.36469, respectively. The structural analysis results showed that the C543P candidate had good stability. Its secondary structure contained 43.6% α-helix, the Z-score after tertiary structure optimization was −7.9, and the Ramachandran diagram showed that 88.77% amino acid residues of the C543P candidate were in the allowable region. Furthermore, the C543P candidate showed an excellent affinity to TLR2 (−1091.7kcal/mol) and TLR4 (−1102.7kcal/mol). In addition, we also analyzed the immunological characteristics of the C543P candidate. Immune stimulation prediction showed that the C543P candidate could effectively activate T and B lymphocytes and produce high levels of Th1 cytokines such as IFN-γ and IL-2.

Conclusion

We constructed a novel PPM with acceptable antigenicity, immunogenicity, stability, and ability to induce robust immune responses. This study provides a new diagnostic biomarker or peptides-based vaccine for LTBI diagnosis and prevention.

Immunoinformatic Design of a Multivalent Peptide Vaccine Against Mucormycosis: Targeting FTR1 Protein of Major Causative Fungi

Mucormycosis is a potentially fatal illness that arises in immunocompromised people due to diabetic ketoacidosis, neutropenia, organ transplantation, and elevated serum levels of accessible iron. The sudden spread of mucormycosis in COVID-19 patients engendered massive concern worldwide. Comorbidities including diabetes, cancer, steroid-based medications, long-term ventilation, and increased ferritin serum concentration in COVID-19 patients trigger favorable fungi growth that in turn effectuate mucormycosis. The necessity of FTR1 gene-encoded ferrous permease for host iron acquisition by fungi has been found in different studies recently. Thus, targeting the transit component could be a potential solution. Unfortunately, no appropriate antifungal vaccine has been constructed as of yet. To date, mucormycosis has been treated with antiviral therapy and surgical treatment only. Thus, in this study, the FTR1 protein has been targeted to design a convenient and novel epitope-based vaccine with the help of immunoinformatics against four different virulent fungal species. Furthermore, the vaccine was constructed using 8 CTL, 2 HTL, and 1 LBL epitopes that were found to be highly antigenic, non-allergenic, non-toxic, and fully conserved among the fungi under consideration. The vaccine has very reassuring stability due to its high pI value of 9.97, conclusive of a basic range. The vaccine was then subjected to molecular docking, molecular dynamics, and immune simulation studies to confirm the biological environment’s safety, efficacy, and stability. The vaccine constructs were found to be safe in addition to being effective. Finally, we used in-silico cloning to develop an effective strategy for vaccine mass production. The designed vaccine will be a potential therapeutic not only to control mucormycosis in COVID-19 patients but also be effective in general mucormycosis events. However, further in vitro, and in vivo testing is needed to confirm the vaccine’s safety and efficacy in controlling fungal infections. If successful, this vaccine could provide a low-cost and effective method of preventing the spread of mucormycosis worldwide.

Insight Into Novel Anti-tuberculosis Vaccines by Using Immunoinformatics Approaches

Tuberculosis (TB), an infectious disease, has been a leading cause of morbidity and mortality for decades. The causative agent of TB is the Mycobacterium tuberculosis (Mtb) which can infects various parts of the body, mainly the lungs in pulmonary TB cases. Mycobacterium bovis Bacillus Calmette–Guerin (BCG) is the only approved vaccine for TB, but its efficiency to combat pulmonary TB is limited. Multidrug-resistant (MDR) TB and extensive drug-resistant (XDR) TB requires the evolution of more potent vaccines. Therefore, this research aims to generate a universal TB subunit vaccine using advanced immunoinformatics techniques. In generating a novel multiepitope subunit vaccine, we selected the conserved and experimentally confirmed antigens Rv0058, Rv0101, and Rv3343. After a rigorous evaluation, the top candidates from predicted Helper T-lymphocytes (HTL), Cytotoxic T-lymphocytes (CTL), and B-cell epitopes were considered potential vaccine candidates. Immunogenicity was enhanced by the addition of an adjuvant to the ultimate construct of the vaccine. B-cell epitopes predictions guaranteed the eventual induction of a humoral response. Thereafter, dynamics simulations and molecular docking validated the vaccine-receptor complex’s stability and high affinity for the immune receptor TLR-3. Also, immune simulations revealed the significantly elevated levels of immunoglobulins such as IgM, cytokines such as interleukin-2, helper T (Th) cells, and cytotoxic T-cell populations. These results agreed with the actual inflammatory response and showed rapid antigen clearance after manifold exposure. Finally, the E. coli K12 strain was confirmed via in-silico cloning for quality expression. Nevertheless, in vivo experiments should be performed to validate the safety of the proposed vaccine and its inherent ability to prevent TB infection.

The Glu143 Residue Might Play a Significant Role in T20 Peptide Binding to HIV-1 Receptor gp41: An In Silico Study

Despite the enormous efforts made to develop other fusion inhibitors for HIV, the enfuvirtide (known as T20) peptide is the only approved HIV-1 inhibitory drug so far. Investigating the role of potential residues of the T20 peptide’s conformational dynamics could help us to understand the role of potential residues of the T20 peptide. We investigated T20 peptide conformation and binding interactions with the HIV-1 receptor (i.e., gp41) using MD simulations and docking techniques, respectively. Although the mutation of E143 into alanine decreased the flexibility of the E143A mutant, the conformational compactness of the mutant was increased. This suggests a potential role of E143 in the T20 peptide’s conformation. Interestingly, the free energy landscape showed a significant change in the wild-type T20 minimum, as the E143A mutant produced two observed minima. Finally, the docking results of T20 to the gp41 receptor showed a different binding interaction in comparison to the E143A mutant. This suggests that E143 residue can influence the binding interaction with the gp41 receptor. Overall, the E143 residue showed a significant role in conformation and binding to the HIV-1 receptor. These findings can be helpful in optimizing and developing HIV-1 inhibitor peptides.

Proteome-Wide and Protein-Specific Multi-Epitope Vaccine Constructs Against the Rift Valley Fever Virus Outbreak Using Integrated Omics Approaches

Rift Valley fever (RVF) is a viral disease caused by a member of the Bunyavirales family causing severe infections in humans. The RVF virus is an enveloped, negative-sense, single-stranded RNA virus that can infect both animals and humans. The symptoms associated with these infections span from minor (fever and headaches) to severe (meningoencephalitis and hemorrhagic fever syndrome) symptoms. Despite the outbreaks of the RVF virus being reported in different parts of the world, no effective therapy is available. Herein, the development of an efficient vaccine is critical for the control of infections associated with the RVF virus. Moreover, computational vaccine approaches are helpful in the design of specific, safe, and stable peptide-based designs when compared to the conventional methods of vaccine development. In this study, the whole proteome of the virus, comprising four proteins (NP, L, GP, and NSP), was screened to find putative vaccine epitope sequences (T cell, B cell, and HTL) specific for each protein. These shortlisted epitopes were then combined with flexible linkers to design protein-specific and proteome-wide immunogenic multi-epitope-based vaccine constructs. The results revealed that these multi-epitope vaccine constructs (MEVCs) are strongly antigenic and non-allergenic in nature. The efficacy of these constructs was further validated by docking with immune receptors, which revealed strong binding interactions with human TLR8. Using the MD simulation approach, the binding stability and residual flexibility of the best vaccine construct (proteome-wide) were confirmed, which revealed stable dynamic and favorable features. Furthermore, in-silico cloning and immune simulation analysis confirmed the expression and production of immune factors, that is, IgM, IgG, and IL-6, against the proposed vaccine designs. Additionally, 3D models of all the MEVC constructs have been developed and evaluated for potential immunization against the RVF virus. Finally, the proteome-wide vaccine candidate (MEVC-PW-RVFV) with the highest immune reinforcement potential provides new insights into the development of future vaccines against the emerging RVF virus.

Potential of antiviral peptide-based SARS-CoV-2 inactivators to combat COVID-19

The appearance of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the lack of effective antiviral therapeutics for coronavirus disease 2019 (COVID-19), a highly infectious disease caused by the virus, demands the search for alternative therapies. Most antiviral drugs known are passive defenders which must enter the cell to execute their function and suffer from concerns such as permeability and effectiveness, therefore in this current study, we aim to identify peptide inactivators that can act without entering the cells. SARS-CoV-2 spike protein is an essential protein that plays a major role in binding to the host receptor angiotensin-converting enzyme 2 and mediates the viral cell membrane fusion process. SARS vaccines and treatments have also been developed with the spike protein as a target. The virtual screening experiment revealed antiviral peptides which were found to be non-allergen, non-toxic and possess good water solubility. U-1, GST-removed-HR2 and HR2-18 exhibit binding energies of -47.8 kcal/mol, -43.01 kcal/mol, and -40.46 kcal/mol, respectively. The complexes between these peptides and spike protein were stabilized through hydrogen bonds as well as hydrophobic interactions. The stability of the top-ranked peptide with the drug-receptor is evidenced by 50-ns molecular dynamics (MD) simulations. The binding of U-1 induces conformational changes in the spike protein with alterations in its geometric properties such as increased flexibility, decreased compactness, the increased surface area exposed to solvent molecules, and an increase in the number of total hydrogen bonds leading to its probable inactivation. Thus, the identified antiviral peptides can be used as anti-SARS-CoV-2 candidates, inactivating the virus’s spike proteins and preventing it from infecting host cells.

Subtractive proteomics assisted therapeutic targets mining and designing ensemble vaccine against Candida auris for immune response induction

The emergence of variants and the reports of co-infection caused by Candida auris in COVID-19 patients adds a further complication to the global pandemic situation. To date, no effective therapy is available for C. auris infections. Thus, characterization of therapeutic targets and designing effective vaccine candidates using subtractive proteomics and immune-informatics approaches is useful tool in controlling the emerging infections associated with SARS-CoV-2. In the current study, subtractive proteomics-assisted annotation of the vaccine targets was performed, which revealed seven vaccine targets. An immunoinformatic-driven approach was then employed to map protein-specific and proteome-wide immunogenic peptides (CTL, B cell, and HTL) for the design of multi-epitope vaccine candidates (MEVCs). The results demonstrated that the vaccine candidates possess strong antigenic features (>0.4 threshold score) and are classified as non-allergenic. Validation of the designed MEVCs through molecular docking, in-silico cloning, and immune simulation further demonstrated the efficacy of the vaccines by producing immune factor titers (ranging from 2500 to 16000 au/mL) i.e., IgM, IgG, IL-6, and Interferon-α. In conclusion, the current study provides a strong impetus in designing anti-fungal strategies against Candida auris.

Characterization of mutations modulating enhanced transmissibility of SARS-CoV-2 B.1.617+ (Delta) variant using In Silico tools

Since the beginning of the of SARS-CoV-2 (Covid-19) pandemic, variants of concern (VOC) have emerged taxing health systems worldwide. In October 2020, a new variant of SARS-CoV-2 (B.1.617+/Delta variant) emerged in India, triggering a deadly wave of Covid-19. Epidemiological data strongly suggests that B.1.617+ is more transmissible and previous reports have revealed that B.1.617+ has numerous mutations compared to wild type (WT), including several changes in the spike protein (SP). The main goal of this study was to use In Silico (computer simulation) techniques to examine mutations in the SP, specifically L452R and E484Q (part of the receptor binding domain (RBD) for human angiotensin-converting enzyme 2 (hACE2)) and P681R (upstream of the Furin cleavage motif), for effects in modulating the transmissibility of the B.1.617+ variant. Using computational models, the binding free energy (BFE) and H-bond lengths were calculated for SP-hACE2 and SP-Furin complexes. Comparison of the SP-hACE2 complex in the WT and B.1.617+ revealed both complexes have identical receptor-binding modes but the total BFE of B.1.617+ binding was more favorable for complex formation than WT, suggesting L452R and E484Q have a moderate impact on binding affinity. In contrast, the SP-Furin complex of B.1.617+ substantially lowered the BFE and revealed changes in molecular interactions compared to the WT complex, implying stronger complex formation between the variant and Furin. This study provides an insight into mutations that modulate transmissibility of the B.1.617+ variant, specifically the P681R mutation which appears to enhance transmissibility of the B.1.617+ variant by rendering it more receptive to Furin.

Repositioning of experimentally validated anti-breast cancer peptides to target FAK-PAX complex to halt the breast cancer progression: a biomolecular simulation approach

FAK (focal adhesin kinase), a tyrosine kinase, plays an imperative role in cell-cell communication, particularly in cell signaling systems. It is a multi-functional signaling protein, which integrates and transduces signals into cancer cells through growth factor receptors or integrin and its interaction with Paxillin (PAX). The molecular processes by which FAK promotes the development and progression of cancer have progressively established the possible relationship between FAK-PAX complex in many types of cancer. The interaction of FAX and PAX is very important in breast cancer and thus acts as an essential biomarker for drugs, vaccines or peptide inhibitor designing. In this regard, computational approaches, particularly peptide designing to target the binding interface of the interacting partners, would greatly assist the design of peptide inhibitors against various cancer. Accordingly, in this present study, we screened 236 experimentally validated anti-breast cancer peptides using computational drugs repositioning approach to design peptides targeting the FAK-PAX complex. Using protein-peptide docking the binding site for the HP1 was confirmed and a total of 236 anti-breast cancer peptides were screened. Among the 236, only 12 peptides reported a docking score better than the control. From these 12, Magainin with the docking score - 103.8 ± 10.3 kcal/mol, NRC-07 with the docking score - 100.8 ± 16.5 kcal/mol, and Indolicidin with the docking score - 101.7 ± 3.9 kcal/mol, peptides potentially inhibit the FAX-PAX binding. Calculation of protein's motion and FEL revealed the binding and inhibitory behavior. Moreover, binding free energy (MM/GBSA) confirmed that Magainin exhibited the total binding energy - 53.28 kcal/mol, NRC-07 possessed the TBE - 44.16 kcal/mol, and Indolicidin reported the TBE of - 40.48 kcal/mol, thus explaining the inhibitory potential of these peptides. In conclusion, these peptides exhibit strong inhibitory potential and could abrogate the FAK-PAX complex in in vitro models and thus may relieve the burden of breast cancer.

fastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation

Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein-ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein-ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of >80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/.

Characterization of proteome wide antigenic epitopes to design proteins specific and proteome-wide ensemble vaccines against heartland virus using structural vaccinology and immune simulation approaches

Heartland virus is a single-stranded negative-sense RNA virus that infects humans and causes lethargy, myalgia, headaches, nausea, diarrhea, weight loss, arthralgia, loss of appetite, leukopenia, and easy bruising due thrombocytopenia. The unavailability of antiviral drugs for HRTV infection is a major obstacle to treat this infection, therefore supportive care management is adopted in the case of a severe ailment. In this scientific study, proteins specific and proteome-wide Helper T-cell (HTL), linear B cell, and cytotoxic T-cell (CTL) epitopes mapping joined together with suitable linkers to design multi-epitopes subunit vaccine (MEVC). The constructed four vaccines from nucleocapsid protein, replicase, glycoprotein and finally whole proteome-wide constructs demonstrated stronger antigenic and non-allergenic behavior. Physiochemical properties evaluation also reported easy and efficient expression and downstream analysis of the constructs. Molecular docking of these constructs with toll-like receptor 7 (TLR7) revealed good binding and further validation based on MM/GBSA also demonstrated stronger interaction between the vaccine constructs and TLR7. Moreover, in silico cloning reported CAI value of 0.96 for each construct and excellent GC contents percentage required for experimental analysis. Furthermore, immune simulation-based immune response surveillance revealed that upon the injection of antigen the primary and secondary antibodies were produced between 5-15 days, and a more robust neutralization of the antigen by the proteome-wide vaccine construct was observed. This research could pave the way for the development of dynamic and efficient vaccines that contain a unique mix of numerous HRTV derived antigenic peptides to control HRTV infection.

Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants

The genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel epitopes were identified as immunogenic triggering immune responses and no toxic after investigation with in silico tools. Furthermore, we found these peptide vaccine candidates showed a significant binding affinity for MHC I and MHC II alleles in molecular docking investigations. We consider them to be promising targets for developing peptide-based vaccines against SARS-CoV-2. Subsequently, we designed two efficient multi-epitopes vaccines against the SARS-CoV-2, the first one based on potent MHC class I and class II T-cell epitopes of S (FPNITNLCPF-NYNYLYRLFR-MFVFLVLLPLVSSQC), M (MWLSYFIASF-GLMWLSYFIASFRLF), E (LTALRLCAY-LLFLAFVVFLLVTLA), and N (SPRWYFYYL-AQFAPSASAFFGMSR). The second candidate is the result of the tailoring of the first designed vaccine according to three classes of SARS-CoV-2 variants. Molecular docking showed that the protein-protein binding interactions between the vaccines construct and TLR2-TLR4 immune receptors are stable complexes. These findings confirmed that the final multi-epitope vaccine could be easily adapted to new viral variants. Our study offers a shortlist of promising epitopes that can accelerate the development of an effective and safe vaccine against the virus and its adaptation to new variants.Communicated by Ramaswamy H. Sarma.

Development of epitope-based chimeric protein as a vaccine against Lujo virus by utilizing immunoinformatic tools

Aim: Lujo is a modern zoonotic virus that is potentially fatal and spreads by bodily fluids. In this research, immunoinformatic tools are used to build a vaccine. Methodology: The epitopes of cytotoxic T-lymphocytes, helper T-lymphocytes and linear B-lymphocytes were predicted from the most antigenic protein. The designed vaccine's physiochemical properties and 3D structure have been forecasted. Low free energy and strong binding affinity estimated in molecular docking against toll-like receptor 4 (TLR4) and dynamic simulation. Furthermore, in silico cloning in the Escherichia coli K12 host system was performed for high level of expression. Conclusion: Finally, immune simulation was used to determine immune responses to the vaccine that was formulated confirming the developed vaccine as a good candidate against Lujo virus.

Reverse vaccinology approach to design a multi-epitope vaccine construct based on the Mycobacterium tuberculosis biomarker PE_PGRS17

Mycobacterium tuberculosis (Mtb) is responsible for high mortality rates in many low- and middle-income countries. This infectious disease remains accountable for around 1.4 million deaths yearly. Finding effective control measures against Mtb has become imperative. Vaccination has been regarded as the safe and lasting control measure to curtail the impact of Mtb. This study used the Mtb protein biomarker PE_PGRS17 to design a multi-epitope vaccine. A previous study predicted a strong antigenic property of PE_PGRS17. Immunogenic properties such as antigenicity, toxicity, and allergenicity were predicted for the PE_PGRS17 biomarker, specific B- and T-cell epitope sequences, and the final multiple epitope vaccine (MEV) construct. Algorithmic tools predicted the T- and B-cell epitopes and those that met the immunogenic properties were selected to construct the MEV candidate for predicted vaccine development. The epitopes were joined via linkers and an adjuvant was attached to the terminals of the entire vaccine construct. Immunogenic properties, and physicochemical and structural predictions gave insight into the MEV construct. The assembled vaccine candidate was docked with a receptor and validated using web-based tools. An immune simulation was performed to imitate the immune response after exposure to a dosed administrated predicted MEV subunit. An in silico cloning and codon optimisation gave insight into optimal expression conditions regarding the MEV candidate. In conclusion, the generated MEV construct may potentially emit both cellular and humoral responses which are vital in the development of a peptide-based vaccine against Mtb; nonetheless, further experimental validation is still required.

An Immunoinformatic Strategy to Develop New Mycobacterium tuberculosis Multi-epitope Vaccine

Mycobacterium tuberculosis causes a life-threatening disease known as tuberculosis (TB). In 2021, tuberculosis was the second cause of death after COVID-19 among infectious diseases. Latent life cycle and development of multidrug resistance in one hand and lack of an effective vaccine in another hand have made TB a global health issue. Here, a multi-epitope vaccine have been designed against TB using five new antigenic protein and immunoinformatic tools. To do so, immunodominant MHC-I/MHC-II binding epitopes of Rv2346, Rv2347, Rv3614, Rv3615 and Rv2031 antigenic proteins have been selected using advanced computational procedures. The vaccine was designed by linking ten epitopes from the antigenic proteins and flagellin and TpD as adjuvant. Three-dimensional (3D) structure of the vaccine was modeled, was refined and was evaluated using bioinformatics tools. The 3D structure of the vaccine was docked into the toll-like-receptors (TLR3, 4, 8) to evaluate potential interaction between the vaccine and TLRs. Evaluation of immunological and physicochemical properties of the constructed vaccine have demonstrated the vaccine construct can induce significant humoral and cellular immune responses, the vaccine is non-allergenic and can be recognized by TLR proteins. The immunoinformatic results reported in the present study demonstrates that it is worth following the designed vaccine by experimental investigations.

Structural and functional characterization of an auxiliary domain-containing PET hydrolase from Burkholderiales bacterium

Biodegradation of polyethylene terephthalate (PET) is one of fundamental ways to solve plastic pollution. As various microbial hydrolases have an extra domain unlike PETase from Ideonella sakaiensis (IsPETase), research on the role of these extra domain in PET hydrolysis is crucial for the identification and selection of a novel PET hydrolase. Here, we report that a PET hydrolase from Burkholderiales bacterium RIFCSPLOWO2_02_FULL_57_36 (BbPETase) with an additional N-terminal domain (BbPETase^AND) shows a similar hydrolysis activity toward microcrystalline PET and a higher thermal stability than IsPETase. Based on detailed structural comparisons between BbPETase and IsPETase, we generated the BbPETase^{S335N/T338I/M363I/N365G} variant with an enhanced PET-degrading activity and thermal stability. We further revealed that BbPETase^AND contributes to the thermal stability of the enzyme through close contact with the core domain, but the domain might hinder the adhesion of enzyme to PET substrate. We suggest that BbPETase is an enzyme in the evolution of efficient PET degradation and molecular insight into a novel PET hydrolase provides a novel strategy for the development of biodegradation of PET.

Protein interactions with metallothionein-3 promote vectorial active transport in human proximal tubular cells

Metallothionein 3 (MT-3) is a small, cysteine-rich protein that binds to essential metals required for homeostasis, as well as to heavy metals that have the potential to exert toxic effects on cells. MT-3 is expressed by epithelial cells of the human kidney, including the cells of the proximal tubule. Our laboratory has previously shown that mortal cultures of human proximal tubular (HPT) cells express MT-3 and form domes in the cell monolayer, a morphological feature indicative of vectorial active transport, an essential function of the proximal tubule. However, an immortalized proximal tubular cell line HK-2 lacks the expression of MT-3 and fails to form domes in the monolayer. Transfection of HK-2 cells with the MT-3 gene restores dome formation in these cells suggesting that MT-3 is required for vectorial active transport. In order to determine how MT-3 imparts this essential feature to the proximal tubule, we sought to identify proteins that interact either directly or indirectly with MT-3. Using a combination of pulldowns, co-immunoprecipitations, and mass spectrometry analysis, putative protein interactants were identified and subsequently confirmed by Western analysis and confocal microscopy, following which proteins with direct physical interactions were investigated through molecular docking. Our data shows that MT-3 interacts with myosin-9, aldolase A, enolase 1, β-actin, and tropomyosin 3 and that these interactions are maximized at the periphery of the apical membrane of doming proximal tubule cells. Together these observations reveal that MT-3 interacts with proteins involved in cytoskeletal organization and energy metabolism, and these interactions at the apical membrane support vectorial active transport and cell differentiation in proximal tubule cultures.

Production and characterization of bioactive peptides from rice beans using Bacillus subtilis

A bioprocess was developed for production of bioactive peptides on microbial fermentation of rice beans using proteolytic Bacillus subtilis strains. The peptides produced were identified by LC-MS/MS analysis, revealing the presence of many unique peptide sequences to individual hydrolysates. On functional properties prediction, antihypertensive peptides (3.90%) were found to be higher in comparison to other bioactive peptides. Among different strains, B. subtilis KN2B fermented hydrolysate exhibited highest angiotensin converting enzyme (ACE)-inhibitory activity (45.73%). Furthermore, 19 selected peptides, including the common and unique peptides were examined for their affinity towards the binding cavity of ACE using molecular docking. The results showed a common peptide PFPIPFPIPIPLP, and another IPFPPIPFLPPI unique to B. subtilis KN2B fermented hydrolysate exhibited promising binding at the ACE binding site with substantial free binding energy. The process developed can be used for the production of bioactive peptides from rice bean for application in nutraceutical industries.

Identification of Anti-TNFα VNAR Single Domain Antibodies from Whitespotted Bambooshark (Chiloscyllium plagiosum)

Tumor necrosis factor α (TNFα), an important clinical testing factor and drug target, can trigger serious autoimmune diseases and inflammation. Thus, the TNFα antibodies have great potential application in diagnostics and therapy fields. The variable binding domain of IgNAR (VNAR), the shark single domain antibody, has some excellent advantages in terms of size, solubility, and thermal and chemical stability, making them an ideal alternative to conventional antibodies. This study aims to obtain VNARs that are specific for mouse TNF (mTNF) from whitespotted bamboosharks. After immunization of whitespotted bamboosharks, the peripheral blood leukocytes (PBLs) were isolated from the sharks, then the VNAR phage display library was constructed. Through phage display panning against mTNFα, positive clones were validated through ELISA assay. The affinity of the VNAR and mTNFα was measured using ELISA and Bio-Layer Interferometry. The binding affinity of 3B11 VNAR reached 16.7 nM. Interestingly, one new type of VNAR targeting mTNF was identified that does not belong to any known VNAR type. To understand the binding mechanism of VNARs to mTNFα, the models of VNARs-mTNFα complexes were predicted by computational modeling combining HawkDock and RosettaDock. Our results showed that four VNARs’ epitopes overlapped in part with that of mTNFR. Furthermore, the ELISA assay shows that the 3B11 potently inhibited mTNFα binding to mTNFR. This study may provide the basis for the TNFα blockers and diagnostics applications.

Characterizing the stabilization effects of stabilizers in protein-protein systems with end-point binding free energy calculations

Drug design targeting protein-protein interactions (PPIs) associated with the development of diseases has been one of the most important therapeutic strategies. Besides interrupting the PPIs with PPI inhibitors/blockers, increasing evidence shows that stabilizing the interaction between two interacting proteins may also benefit the therapy, such as the development of various types of molecular glues/stabilizers that mostly work by stabilizing the two interacting proteins to regulate the downstream biological effects. However, characterizing the stabilization effect of a stabilizer is usually hard or too complicated for traditional experiments since it involves ternary interactions [protein-protein-stabilizer (PPS) interaction]. Thus, developing reliable computational strategies will facilitate the discovery/design of molecular glues or PPI stabilizers. Here, by fully analyzing the energetic features of the binary interactions in the PPS ternary complex, we systematically investigated the performance of molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) methods on characterizing the stabilization effects of stabilizers in 14-3-3 systems. The results show that both MM/PBSA and MM/GBSA are powerful tools in distinguishing the stabilizers from the decoys (with area under the curves of 0.90-0.93 for all tested cases) and are reasonable for ranking protein-peptide interactions in the presence or absence of stabilizers as well (with the average Pearson correlation coefficient of ~0.6 at a relatively high dielectric constant for both methods). Moreover, to give a detailed picture of the stabilization effects, the stabilization mechanism is also analyzed from the structural and energetic points of view for individual systems containing strong or weak stabilizers. This study demonstrates a potential strategy to accelerate the discovery of PPI stabilizers.

Potential Immunogenic Activity of Computationally Designed mRNA- and Peptide-Based Prophylactic Vaccines against MERS, SARS-CoV, and SARS-CoV-2: A Reverse Vaccinology Approach

The continued emergence of human coronaviruses (hCoVs) in the last few decades has posed an alarming situation and requires advanced cross-protective strategies against these pandemic viruses. Among these, Middle East Respiratory Syndrome coronavirus (MERS-CoV), Severe Acute Respiratory Syndrome coronavirus (SARS-CoV), and Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) have been highly associated with lethality in humans. Despite the challenges posed by these viruses, it is imperative to develop effective antiviral therapeutics and vaccines for these human-infecting viruses. The proteomic similarity between the receptor-binding domains (RBDs) among the three viral species offers a potential target for advanced cross-protective vaccine designs. In this study, putative immunogenic epitopes including Cytotoxic T Lymphocytes (CTLs), Helper T Lymphocytes (HTLs), and Beta-cells (B-cells) were predicted for each RBD-containing region of the three highly pathogenic hCoVs. This was followed by the structural organization of peptide- and mRNA-based prophylactic vaccine designs. The validated 3D structures of these epitope-based vaccine designs were subjected to molecular docking with human TLR4. Furthermore, the CTL and HTL epitopes were processed for binding with respective human Lymphocytes Antigens (HLAs). In silico cloning designs were obtained for the prophylactic vaccine designs and may be useful in further experimental designs. Additionally, the epitope-based vaccine designs were evaluated for immunogenic activity through immune simulation. Further studies may clarify the safety and efficacy of these prophylactic vaccine designs through experimental testing against these human-pathogenic coronaviruses.

TN strain proteome mediated therapeutic target mapping and multi-epitopic peptide-based vaccine development for Mycobacterium leprae

Leprosy is a significant universal health problem that is remarkably still a concern in developing countries due to infection frequency. New therapeutic molecules and next-generation vaccines are urgently needed to accelerate the leprosy-free world. In this direction, the present study was performed using two routes: proteome-mediated therapeutic target identification and mapping as well as multi-epitopic peptide-based novel vaccine development using state of the art of computational biology for the TN strain of M. leprae. The TN strain was selected from 65 Mycobacterium strains, and TN strain proteome mediated 83 therapeutic protein targets were mapped and characterized according to subcellular localization. Also, drug molecules were mapped with respect to protein targets localization. The Druggability potential of proteins was also evaluated. For multi-epitope peptide-based vaccine development, the four common types of B and T cell epitopes were identified (SLFQSHNRK, VVGIGQHAA, MMHRSPRTR, LGVDQTQPV) and combined with the suitable peptide linker. The vaccine component had an acceptable protective antigenic score (0.9751). The molecular docking of vaccine components with TLR4/MD2 complex exhibited a low ACE value (-244.12) which signifies the proper binding between the two molecules. The estimated free Gibbs binding energy ensured accurate protein-protein interactions (-112.46 kcal/mol). The vaccine was evaluated through adaptive immunity stimulation as well as immune interactions. The molecular dynamic simulation was carried out by using CHARMM topology-based parameters to minimize the docked complex. Subsequently, the Normal Mode Analysis in the internal coordinates showed a low eigen-value (1.3982892e-05), which also signifies the stability of molecular docking. Finally, the vaccine components were adopted for reverse transcription and codon optimization in E. coli strain K12 for the pGEX-4T1 vector, which supports in silico cloning of the vaccine components against the pathogen. The study directs the experimental study for therapeutics molecules discovery and vaccine candidate development with higher reliability.

Evaluation and identification of essential therapeutic proteins and vaccinomics approach towards multi-epitopes vaccine designing against Legionella pneumophila for immune response instigation

The Legionellaceae group comprises the Legionella, containing 58 species with 70 serotypes. For instance, Legionella pneumophila is the deadliest serotype to cause Legionnaires infectious and is responsible for 90% of the infections in humans. The bacterial pathogen is associated with a severe lung infection, known as legionaries' disease. It is resistant to multiple drugs, thus warranting novel vaccine candidates identification to immune the host against infections caused by the said pathogen. For this, we applied the subtractive proteomics and reverse vaccinology approaches to annotate the most essential genes suitable for vaccine designing. From the whole proteome, only five proteins (Q5ZVG4, Q5ZRZ1, Q5ZWE6, Q5ZT09, and Q5ZUZ8) as the best targets for further processing as they fulfill all the standard parameters set for in silico vaccine design. Immuno-informatics approaches were further applied to the selected protein sequences to prioritized antigenic epitopes for design a multi-epitope subunit vaccine. A multi-epitopes vaccine was designed by using suitable linkers to link the CTL (cytotoxic T lymphocytes), HTL (Helper T lymphocytes), B cell epitopes, and adjuvant to strengthen the vaccine's immunogenicity. The MEVC(multi-epitopes vaccine construct) was reported to interact with human immune receptor TLR-2 (toll-like receptor) robustly (docking score = -357.18 kcal/mol), and a higher expression was achieved in the Escherichia coli system (CAI = 0.88, and GC contents = 54.34%). Moreover, immune simulation revealed that on the 3rd day, the neutralization of the antigen started, while on the 5th day, the antigen was completely neutralized by the secreted immune factors. In conclusion, the designed vaccine candidate effectively triggered the immune response against eh pathogen; however, wet lab-based experimentations are highly recommended to prove the protective immunological proficiency of the vaccine against L. pneumophila.

Identification of single domain antibodies with insect cytotoxicity using phage-display antibody library screening and Plutella xylostella ATP-binding cassette transporter subfamily C member 2 (ABCC2) -based insect cell expression system

It is extremely imminent to study a new strategy to manage agricultural pest like Plutella xylostella (P. xylostella) which is currently resistant to most of pesticides, including three domain-Cry toxins from Bacillus thuringiensis (Bt). In this study, we reported a phage displayed single domain antibody screening from human domain antibody (DAb) library targeted on Spodoptera frugiperda 9 (Sf9) cells expressed Cry1Ac toxin receptor, ATP-dependent binding cassette transporter C2 in P. xylostella (PxABCC2). After three rounds of panning, three cytotoxic antibodies (1D2, 2B7, 3C4) were obtained from thirty-eight antibodies and displayed high binding ability towards PxABCC2-expressed Sf9 cells. Through homology modeling and molecular docking, the interaction mode indicated that the most cytotoxic 1D2 of the three antibodies presented the lowest binding free energy required and had the most hydrogen bond formed with PxABCC2 in molecular docking analysis. Functional assay of key regions in 1D2 via Alanine replacement indicated that complementarity-determining region (CDR) 3 played a crucial role in antibody exerts binding activity and cytotoxicity. This study provides the first trial for discovering of potential cytotoxic antibodies from the human antibody library via specific receptor-expressed insect cell system biopanning.

Whole Proteome-Based Therapeutic Targets Annotation and Designing of Multi-Epitope-Based Vaccines against the Gram-Negative XDR-Alcaligenes faecalis Bacterium

This study involved therapeutic targets mining for the extremely drug-resistant bacterial species called Alcaligenes faecalis, which is known to infect humans. The infections caused by this species in different parts of the human body have been linked with a higher degree of resistance to several classes of antibiotics. Meanwhile, alternate therapeutic options are needed to treat these bacterial infections in clinical settings. In the current study, a subtractive proteomics approach was adapted to annotate the whole proteome of Alcaligenes faecalis and prioritize target proteins for vaccine-related therapeutics design. This was followed by targeted protein-specific immune epitope prediction and prioritization. The shortlisted epitopes were further subjected to structural design and in silico validation of putative vaccines against Alcaligenes faecalis. The final vaccine designs were also evaluated for potential interaction analysis with human TLR-2 through molecular docking. Finally, the putative vaccines were subjected to in silico cloning and immune simulation approaches to ensure the feasibility of the target-specific vaccine constructs in further experimental designs.