PEP-FOLD: an online resource for de novo peptide structure prediction

Dynamics of Amyloid Formation from Simplified Representation to Atomistic Simulations

Amyloid fibril formation is an intrinsic property of short peptides, non-disease proteins, and proteins associated with neurodegenerative diseases. Aggregates of the Aβ and tau proteins, the α-synuclein protein, and the prion protein are observed in the brain of Alzheimer's, Parkinson's, and prion disease patients, respectively. Due to the transient short-range and long-range interactions of all species and their high aggregation propensities, the conformational ensemble of these devastating proteins, the exception being for the monomeric prion protein, remains elusive by standard structural biology methods in bulk solution and in lipid membranes. To overcome these limitations, an increasing number of simulations using different sampling methods and protein models have been performed. In this chapter, we first review our main contributions to the field of amyloid protein simulations aimed at understanding the early aggregation steps of short linear amyloid peptides, the conformational ensemble of the Aβ40/42 dimers in bulk solution, and the stability of Aβ aggregates in lipid membrane models. Then we focus on our studies on the interactions of amyloid peptides/inhibitors to prevent aggregation, and long amyloid sequences, including new results on a monomeric tau construct.

Prediction of suitable T and B cell epitopes for eliciting immunogenic response against SARS-CoV-2 and its mutant

Spike glycoprotein of SARS-CoV-2 is mainly responsible for the recognition and membrane fusion within the host and this protein has an ability to mutate. Hence, T cell and B cell epitopes were derived from the spike glycoprotein sequence of wild SARS-CoV-2. The proposed T cell and B cell epitopes were found to be antigenic and conserved in the sequence of SARS-CoV-2 mutant (B.1.1.7). Thus, the proposed epitopes are effective against SARS-CoV-2 and its B.1.1.7 mutant. MHC-I that best interacts with the proposed T cell epitopes were found, using immune epitope database. Molecular docking and molecular dynamic simulations were done for ensuring a good binding between the proposed MHC-I and T cell epitopes. The finally proposed T cell epitope was found to be antigenic, non-allergenic, non-toxic and stable. Further, the finally proposed B cell epitopes were also found to be antigenic. The population conservation analysis has ensured the presence of MHC-I molecule (respective to the finally proposed T cell) in human population of most affected countries with SARS-CoV-2. Thus the proposed T and B cell epitope could be effective in designing an epitope-based vaccine, which is effective on SARS-CoV-2 and its B.1.1.7mutant.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13721-021-00348-w.

APPTEST is a novel protocol for the automatic prediction of peptide tertiary structures

Good knowledge of a peptide's tertiary structure is important for understanding its function and its interactions with its biological targets. APPTEST is a novel computational protocol that employs a neural network architecture and simulated annealing methods for the prediction of peptide tertiary structure from the primary sequence. APPTEST works for both linear and cyclic peptides of 5-40 natural amino acids. APPTEST is computationally efficient, returning predicted structures within a number of minutes. APPTEST performance was evaluated on a set of 356 test peptides; the best structure predicted for each peptide deviated by an average of 1.9Å from its experimentally determined backbone conformation, and a native or near-native structure was predicted for 97% of the target sequences. A comparison of APPTEST performance with PEP-FOLD, PEPstrMOD and PepLook across benchmark datasets of short, long and cyclic peptides shows that on average APPTEST produces structures more native than the existing methods in all three categories. This innovative, cutting-edge peptide structure prediction method is available as an online web server at https://research.timmons.eu/apptest, facilitating in silico study and design of peptides by the wider research community.

Epitope-imprinted polymers: Design principles of synthetic binding partners for natural biomacromolecules

Molecular imprinting (MI) has been explored as an increasingly viable tool for molecular recognition in various fields. However, imprinting of biologically relevant molecules like proteins is severely hampered by several problems. Inspired by natural antibodies, the use of epitopes as imprinting templates has been explored to circumvent those limitations, offering lower costs and greater versatility. Here, we review the latest innovations in this technology, as well as different applications where MI polymers (MIPs) have been used to target biomolecules of interest. We discuss the several steps in MI, from the choice of epitope and functional monomers to the different production methods and possible applications. We also critically explore how MIP performance can be assessed by various parameters. Last, we present perspectives on future breakthroughs and advances, offering insights into how MI techniques can be expanded to new fields such as tissue engineering.

Fractal-like R5 assembly promote the condensation of silicic acid into silica particles

HYPOTHESIS

Despite advances in understanding the R5 (SSKKSGSYSGKSGSKRRIL) peptide-driven bio-silica process, there remains significant discrepancies regarding the physicochemical characterization and the self-assembling mechanistic driving forces of the supramolecular R5 template. This paper investigates the self-assembly of R5 as a function of monovalent (sodium chloride) and multivalent salt (phosphate) to determine if assembly is phosphate ion concentration dependent. Additionally, we hypothesize that the assembled R5 aggregates do not resemble a micelle or unimer structure as proposed in current literature.

EXPERIMENTS

R5 peptides were synthesized, and aggregates evaluated for their size, morphology, and association state as a function of salt and ionic strength concentration via dynamic and static light scattering, small angle X-ray and neutron scattering and cryogenic transmission electron microscopy. Furthermore, we compare the proposed R5 template to precipitated silica by scanning electron microscopy.

FINDINGS

R5 peptides assemble into large aggregates due to multivalence bridging and the decrease in electrostatic repulsion due to ionic strength. We elucidate the structure of R5 aggregates as mass-fractals composed of small spherical aggregates. Moreover, we discover that phosphate ions not only have a significant role in driving the growth of the R5 scaffold, but additionally in driving the polycondensation of silicic acid during the bio-silification process via electrostatic interactions.

Immunoinformatics aided design of peptide-based vaccines against ebolaviruses

Ebolaviruses are at the forefront of emerging viruses and present a very perceptible threat to global peace and harmony. In the last decade, Ebola virus disease has claimed more than 90% of total lives since its inception in 1976. Owing to multiple host immune evasion methods employed by the virus and the limitations of traditional vaccine development approaches, finding a globally effective and reliable counter measure against Ebola virus remains a challenge. Highly conserved peptide fragments belonging to critical viral proteins and containing multiple epitopes which have the capacity to interact with a wide array of HLA molecules present a viable solution. Immunoinformatics or computational immunology enables rapid screening and shortlisting of plausible epitopes with a high immunogenic potential, thus, supporting expeditious elucidation of efficacious vaccine candidates. In light of above facts, we describe a computational methodology in this chapter for identification of potent peptide vaccine candidates against human infecting viruses. By applying this stringent methodology, we were able to identify multiple, immunogenic ebolavirus peptide fragments which, after verification in animal models, might be considered as part of future synthetic Ebola vaccine.

Computational screening of 645 antiviral peptides against the receptor-binding domain of the spike protein in SARS-CoV-2

The receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein plays a vital role in binding and internalization through the alpha-helix (AH) of human angiotensin-converting enzyme 2 (hACE2). Thus, it is a potential target for designing and developing antiviral agents. Inhibition of RBD activity of the S protein may be achieved by blocking RBD interaction with hACE2. In this context, inhibitors with large contact surface area are preferable as they can form a potentially stable complex with RBD of S protein and would not allow RBD to come in contact with hACE2. Peptides represent excellent features as potential anti-RBD agents due to better efficacy, safety, and tolerability in humans compared to that of small molecules. The present study has selected 645 antiviral peptides known to inhibit various viruses and computationally screened them against the RBD of SARS-CoV-2 S protein. In primary screening, 27 out of 645 peptides exhibited higher affinity for the RBD of S protein compared to that of AH of the hACE2 receptor. Subsequently, AVP1795 appeared as the most promising candidate that could inhibit hACE2 recognition by SARS-CoV 2 as was predicted by the molecular dynamics simulation. The critical residues in RBD found for protein-peptide interactions are TYR 489, GLY 485, TYR 505, and GLU 484. Peptide-protein interactions were substantially influenced by hydrogen bonding and hydrophobic interactions. This comprehensive computational screening may provide a guideline to design the most effective peptides targeting the spike protein, which could be studied further in vitro and in vivo for assessing their anti-SARS CoV-2 activity.

Endoglin Is an Endothelial Housekeeper against Inflammation: Insight in ECFC-Related Permeability through LIMK/Cofilin Pathway

Endoglin (Eng) is an endothelial cell (EC) transmembrane glycoprotein involved in adhesion and angiogenesis. Eng mutations result in vessel abnormalities as observed in hereditary hemorrhagic telangiectasia of type 1. The role of Eng was investigated in endothelial functions and permeability under inflammatory conditions, focusing on the actin dynamic signaling pathway. Endothelial Colony-Forming Cells (ECFC) from human cord blood and mouse lung/aortic EC (MLEC, MAEC) from Eng^+/+ and Eng^+/- mice were used. ECFC silenced for Eng with Eng-siRNA and ctr-siRNA were used to test tubulogenesis and permeability +/- TNFα and +/- LIM kinase inhibitors (LIMKi). In silico modeling of TNFα-Eng interactions was carried out from PDB IDs 5HZW and 5HZV. Calcium ions (Ca²⁺) flux was studied by Oregon Green 488 in epifluorescence microscopy. Levels of cofilin phosphorylation and tubulin post-translational modifications were evaluated by Western blot. F-actin and actin-tubulin distribution/co-localization were evaluated in cells by confocal microscopy. Eng silencing in ECFCs resulted in a decrease of cell sprouting by 50 ± 15% (p < 0.05) and an increase in pseudo-tube width (41 ± 4.5%; p < 0.001) compared to control. Upon TNFα stimulation, ECFC Eng-siRNA displayed a significant higher permeability compared to ctr-siRNA (p < 0.01), which is associated to a higher Ca²⁺ mobilization (p < 0.01). Computational analysis suggested that Eng mitigated TNFα activity. F-actin polymerization was significantly increased in ECFC Eng-siRNA, MAEC^+/-, and MLEC^+/- compared to controls (p < 0.001, p < 0.01, and p < 0.01, respectively) as well as actin/tubulin distribution (p < 0.01). Furthermore, the inactive form of cofilin (P-cofilin at Ser3) was significantly decreased by 36.7 ± 4.8% in ECFC Eng-siRNA compared to ctr-siRNA (p < 0.001). Interestingly, LIMKi reproduced the absence of Eng on TNFα-induced ECFC-increased permeability. Our data suggest that Eng plays a critical role in the homeostasis regulation of endothelial cells under inflammatory conditions (TNFα), and loss of Eng influences ECFC-related permeability through the LIMK/cofilin/actin rearrangement-signaling pathway.

Effect of L- to D-Amino Acid Substitution on Stability and Activity of Antitumor Peptide RDP215 against Human Melanoma and Glioblastoma

The study investigates the antitumor effect of two cationic peptides, R-DIM-P-LF11-215 (RDP215) and the D-amino acid variant 9D-R-DIM-P-LF11-215 (9D-RDP215), targeting the negatively charged lipid phosphatidylserine (PS) exposed by cancer cells, such as of melanoma and glioblastoma. Model studies mimicking cancer and non-cancer membranes revealed the specificity for the cancer-mimic PS by both peptides with a slightly stronger impact by the D-peptide. Accordingly, membrane effects studied by DSC, leakage and quenching experiments were solely induced by the peptides when the cancer mimic PS was present. Circular dichroism revealed a sole increase in β-sheet conformation in the presence of the cancer mimic for both peptides; only 9D-RDP215 showed increased structure already in the buffer. Ex vitro stability studies by SDS-PAGE as well as in vitro with melanoma A375 revealed a stabilizing effect of D-amino acids in the presence of serum, which was also confirmed in 2D and 3D in vitro experiments on glioblastoma LN-229. 9D-RDP215 was additionally able to pass a BBB model, whereupon it induced significant levels of cell death in LN-229 spheroids. Summarized, the study encourages the introduction of D-amino acids in the design of antitumor peptides for the improvement of their stable antitumor activity.

Novel anti-PD-L1 peptide selected from combinatorial phage library inhibits tumor cell growth and restores T-cell activity

PD-L1 overexpression on tumour cells forms a protective shield against cytotoxic T-cell killing, which consequently leads to immune evasion. Engagement of PD-1 in tumour infiltrating T cells with PD-L1 results in an exhausted T-cell phenotype, thus preventing an effective immune response against tumour cells. In the present study, we employed phage display combinatorial peptide library to discover anti-PD-L1 peptides. The peptides discovered here, could computationally exhibit specific interactions with PD-L1 at residues with which PD-1 also interacts. Binding affinity and specificity of the peptides were examined by flow cytometry. Anti- tumour activity of peptides was also investigated using several cell-based assays. Surprisingly, we demonstrated that Pep-39 can inhibit PDL-1, and reduce MDA-MB-231, CT-26, and DU-145 cells survival. In co-culture experiments, Pep-39 restored proliferation of Jurkat cells cultured in the presence of MDA-MB-231 cells. In addition, Jurkat cells apoptosis was impeded, indicating blocking potential of Pep-39 against PD-1/PD-L1 interaction.

Natural Selection on the Phase-Separation Properties of FUS during 160 My of Mammalian Evolution

Protein phase separation can help explain the formation of many nonmembranous organelles. However, we know little about its ability to change in evolution. Here we studied the evolution of the mammalian RNA-binding protein Fused in Sarcoma (FUS), a protein whose prion-like domain (PLD) contributes to the formation of stress granules through liquid–liquid phase separation. Although the PLD evolves three times as rapidly as the remainder of FUS, it harbors absolutely conserved tyrosine residues that are crucial for phase separation. Ancestral reconstruction shows that the phosphorylation sites within the PLD are subject to stabilizing selection. They toggle among a small number of amino acid states. One exception to this pattern is primates, where the number of such phosphosites has increased through positive selection. In addition, we find frequent glutamine to proline changes that help maintain the unstructured state of FUS that is necessary for phase separation. Our work provides evidence that natural selection has stabilized the liquid forming potential of FUS and minimized the propensity of cytotoxic liquid-to-solid phase transitions during 160 My of mammalian evolution.

BING, a novel antimicrobial peptide isolated from Japanese medaka plasma, targets bacterial envelope stress response by suppressing cpxR expression

Antimicrobial peptides (AMPs) have emerged as a promising alternative to small molecule antibiotics. Although AMPs have previously been isolated in many organisms, efforts on the systematic identification of AMPs in fish have been lagging. Here, we collected peptides from the plasma of medaka (Oryzias latipes) fish. By using mass spectrometry, 6399 unique sequences were identified from the isolated peptides, among which 430 peptides were bioinformatically predicted to be potential AMPs. One of them, a thermostable 13-residue peptide named BING, shows a broad-spectrum toxicity against pathogenic bacteria including drug-resistant strains, at concentrations that presented relatively low toxicity to mammalian cell lines and medaka. Proteomic analysis indicated that BING treatment induced a deregulation of periplasmic peptidyl-prolyl isomerases in gram-negative bacteria. We observed that BING reduced the RNA level of cpxR, an upstream regulator of envelope stress responses. cpxR is known to play a crucial role in the development of antimicrobial resistance, including the regulation of genes involved in drug efflux. BING downregulated the expression of efflux pump components mexB, mexY and oprM in P. aeruginosa and significantly synergised the toxicity of antibiotics towards these bacteria. In addition, exposure to sublethal doses of BING delayed the development of antibiotic resistance. To our knowledge, BING is the first AMP shown to suppress cpxR expression in Gram-negative bacteria. This discovery highlights the cpxR pathway as a potential antimicrobial target.

Immunoinformatics-guided design of a multi-epitope vaccine based on the structural proteins of severe acute respiratory syndrome coronavirus 2

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in a contagious respiratory tract infection that has become a global burden since the end of 2019. Notably, fewer patients infected with SARS-CoV-2 progress from acute disease onset to death compared with the progression rate associated with two other coronaviruses, SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Several research organizations and pharmaceutical industries have attempted to develop successful vaccine candidates for the prevention of COVID-19. However, increasing evidence indicates that the SARS-CoV-2 genome undergoes frequent mutation; thus, an adequate analysis of the viral strain remains necessary to construct effective vaccines. The current study attempted to design a multi-epitope vaccine by utilizing an approach based on the SARS-CoV-2 structural proteins. We predicted the antigenic T- and B-lymphocyte responses to four structural proteins after screening all structural proteins according to specific characteristics. The predicted epitopes were combined using suitable adjuvants and linkers, and a secondary structure profile indicated that the vaccine shared similar properties with the native protein. Importantly, the molecular docking analysis and molecular dynamics simulations revealed that the constructed vaccine possessed a high affinity for toll-like receptor 4 (TLR4). In addition, multiple descriptors were obtained from the simulation trajectories, including the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (R g), demonstrating the rigid nature and inflexibility of the vaccine and receptor molecules. In addition, codon optimization, based on Escherichia coli K12, was used to determine the GC content and the codon adaptation index (CAI) value, which further followed for the incorporation into the cloning vector pET28+(a). Collectively, these findings suggested that the constructed vaccine could be used to modulate the immune reaction against SARS-CoV-2.

Prospective Role of Peptide-Based Antiviral Therapy Against the Main Protease of SARS-CoV-2

The recently emerged coronavirus (SARS-CoV-2) has created a crisis in world health, and economic sectors as an effective treatment or vaccine candidates are still developing. Besides, negative results in clinical trials and effective cheap solution against this deadly virus have brought new challenges. The viral protein, the main protease from SARS-CoV-2, can be effectively targeted due to its viral replication and pathogenesis role. In this study, we have enlisted 88 peptides from the AVPdb database. The peptide molecules were modeled to carry out the docking interactions. The four peptides molecules, P14, P39, P41, and P74, had more binding energy than the rest of the peptides in multiple docking programs. Interestingly, the active points of the main protease from SARS-CoV-2, Cys145, Leu141, Ser139, Phe140, Leu167, and Gln189, showed nonbonded interaction with the peptide molecules. The molecular dynamics simulation study was carried out for 200 ns to find out the docked complex’s stability where their stability index was proved to be positive compared to the apo and control complex. Our computational works based on peptide molecules may aid the future development of therapeutic options against SARS-CoV-2.

A Peptides Prediction Methodology for Tertiary Structure Based on Simulated Annealing

The Protein Folding Problem (PFP) is a big challenge that has remained unsolved for more than fifty years. This problem consists of obtaining the tertiary structure or Native Structure (NS) of a protein knowing its amino acid sequence. The computational methodologies applied to this problem are classified into two groups, known as Template-Based Modeling (TBM) and ab initio models. In the latter methodology, only information from the primary structure of the target protein is used. In the literature, Hybrid Simulated Annealing (HSA) algorithms are among the best ab initio algorithms for PFP; Golden Ratio Simulated Annealing (GRSA) is a PFP family of these algorithms designed for peptides. Moreover, for the algorithms designed with TBM, they use information from a target protein’s primary structure and information from similar or analog proteins. This paper presents GRSA-SSP methodology that implements a secondary structure prediction to build an initial model and refine it with HSA algorithms. Additionally, we compare the performance of the GRSAX-SSP algorithms versus its corresponding GRSAX. Finally, our best algorithm GRSAX-SSP is compared with PEP-FOLD3, I-TASSER, QUARK, and Rosetta, showing that it competes in small peptides except when predicting the largest peptides.

A Bioinspired Peptide in TIR Protein as Recognition Molecule on Electrochemical Biosensors for the Detection of E. coli O157:H7 in an Aqueous Matrix

Currently, the detection of pathogens such as Escherichia coli through instrumental alternatives with fast response and excellent sensitivity and selectivity are being studied. Biosensors are systems consisting of nanomaterials and biomolecules that exhibit remarkable properties such as simplicity, portable, affordable, user‑friendly, and deliverable to end‑users. For this, in this work we report for the first time, to our knowledge, the bioinformatic design of a new peptide based on TIR protein, a receptor of Intimin membrane protein which is characteristic of E. coli. This peptide (named PEPTIR‑1.0) was used as recognition element in a biosensor based on AuNPs‑modified screen‑printed electrodes for the detection of E. coli. The morphological and electrochemical characteristics of the biosensor obtained were studied. Results show that the biosensor can detect the bacteria with limits of detection and quantification of 2 and 6 CFU/mL, respectively. Moreover, the selectivity of the system is statistically significant towards the detection of the pathogen in the presence of other microorganisms such as P. aeruginosa and S. aureus. This makes this new PEPTIR‑1.0 based biosensor can be used in the rapid, sensitive, and selective detection of E. coli in aqueous matrices.

In silico Approaches for the Design and Optimization of Interfering Peptides Against Protein-Protein Interactions

Large contact surfaces of protein-protein interactions (PPIs) remain to be an ongoing issue in the discovery and design of small molecule modulators. Peptides are intrinsically capable of exploring larger surfaces, stable, and bioavailable, and therefore bear a high therapeutic value in the treatment of various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Given these promising properties, a long way has been covered in the field of targeting PPIs via peptide design strategies. In silico tools have recently become an inevitable approach for the design and optimization of these interfering peptides. Various algorithms have been developed to scrutinize the PPI interfaces. Moreover, different databases and software tools have been created to predict the peptide structures and their interactions with target protein complexes. High-throughput screening of large peptide libraries against PPIs; "hotspot" identification; structure-based and off-structure approaches of peptide design; 3D peptide modeling; peptide optimization strategies like cyclization; and peptide binding energy evaluation are among the capabilities of in silico tools. In the present study, the most recent advances in the field of in silico approaches for the design of interfering peptides against PPIs will be reviewed. The future perspective of the field and its advantages and limitations will also be pinpointed.

The rumen eukaryotome is a source of novel antimicrobial peptides with therapeutic potential

BACKGROUND

The rise of microbial antibiotic resistance is a leading threat to the health of the human population. As such, finding new approaches to tackle these microbes, including development of novel antibiotics is vital.

RESULTS

In this study, we mined a rumen eukaryotic metatranscriptomic library for novel Antimicrobial peptides (AMPs) using computational approaches and thereafter characterised the therapeutic potential of the AMPs. We identified a total of 208 potentially novel AMPs from the ruminal eukaryotome, and characterised one of those, namely Lubelisin. Lubelisin (GIVAWFWRLAR) is an α-helical peptide, 11 amino acid long with theoretical molecular weight of 1373.76 D. In the presence of Lubelisin, strains of methicillin-resistant Staphylococcus aureus (MRSA) USA300 and EMRSA-15 were killed within 30 min of exposure with ≥103 and 104 CFU/mL reduction in viable cells respectively. Cytotoxicity of Lubelisin against both human and sheep erythrocytes was low resulting in a therapeutic index of 0.43. Membrane permeabilisation assays using propidium iodide alongside transmission electron microscopy revealed that cytoplasmic membrane damage may contribute to the antimicrobial activities of Lubelisin.

CONCLUSIONS

We demonstrate that the rumen eukaryotome is a viable source for the discovery of antimicrobial molecules for the treatment of bacterial infections and further development of these may provide part of the potential solution to the ongoing problem of antimicrobial resistance. The role of these AMPs in the ecological warfare within the rumen is also currently unknown.

Epitope-based universal vaccine for Human T-lymphotropic virus-1 (HTLV-1)

Human T-cell leukemia virus type 1 (HTLV-1) was the first oncogenic human retrovirus identified in humans which infects at least 10-15 million people worldwide. Large HTLV-1 endemic areas exist in Southern Japan, the Caribbean, Central and South America, the Middle East, Melanesia, and equatorial regions of Africa. HTLV-1 TAX viral protein is thought to play a critical role in HTLV-1 associated diseases. We have used numerous bio-informatics and immuno-informatics implements comprising sequence and construction tools for the construction of a 3D model and epitope prediction for HTLV-1 Tax viral protein. The conformational linear B-cell and T-cell epitopes for HTLV-1 TAX viral protein have been predicted for their possible collective use as vaccine candidates. Based on in silico investigation two B cell epitopes, KEADDNDHEPQISPGGLEPPSEKHFR and DGTPMISGPCPKDGQPS spanning from 324-349 and 252-268 respectively; and T cell epitopes, LLFGYPVYV, ITWPLLPHV and GLLPFHSTL ranging from 11-19, 163-171 and 233-241 were found most antigenic and immunogenic epitopes. Among different vaccine constructs generated by different combinations of these epitopes our predicted vaccine construct was found to be most antigenic with a score of 0.57. T cell epitopes interacted strongly with HLA-A*0201 suggesting a significant immune response evoked by these epitopes. Molecular docking study also showed a high binding affinity of the vaccine construct for TLR4. The study was carried out to predict antigenic determinants of the Tax protein along with the 3D protein modeling. The study revealed a potential multi epitope vaccine that can raise the desired immune response against HTLV-1 and be useful in developing effective vaccines against Human T-lymphotropic virus.

Immuno-informatics design of a multimeric epitope peptide based vaccine targeting SARS-CoV-2 spike glycoprotein

Developing an efficacious vaccine for SARS-CoV-2 infection is critical to stemming COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in designing an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers and 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC I and II alleles, respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. With our In silico test, the vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was also characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We, therefore, propose that potential vaccine designs consider this approach.

Role of nuclear localization signals in the DNA delivery function of Chikungunya virus capsid protein

Capsids of several RNA viruses are reported to have unconventional roles attributed to their subcellular trafficking property. The capsid of CHIKV is also found to localize in the nucleus, but the rationale is not yet clear. To understand the role of the nuclear-localized capsid, we examined the nucleic acid binding and cargo delivery activity of the CHIKV capsid. We used bacterially purified capsid protein to probe the binding affinity with CHIKV genome-specific and non-specific nucleic acids. We found that the capsid was able to bind non-specifically to different forms of nucleic acids. The successful transfection of GFP-tagged plasmid DNA by CHIKV capsid protein shows the DNA delivery ability of the protein. Further, we selected and investigated the DNA binding and cargo delivery activity of commercially synthesized Nuclear Localization Signal sequences (NLS 1 and NLS2) of capsid protein. Both peptides showed comparable DNA binding affinity, however, only the NLS1 peptide was capable of delivering plasmid DNA inside the cell. Furthermore, the cellular uptake study using the FITC-labelled NLS1 peptide was performed to highlight the membrane penetrating ability. Structural analysis was performed using circular dichroism and NMR spectroscopy to elucidate the transfection ability of the NLS1 peptides. Our findings suggest that the capsid of CHIKV might influence cellular trafficking in the infected cell via non-specific interactions. Our study also indicates the significance of NLS sequences in the multifunctionality of CHIKV capsid protein.

An immunoprophylactic evaluation of Ld-ODC derived HLA-A0201 restricted peptides against visceral leishmaniasis

Five (5) HLA-A 0201 restricted epitopes of ornithine decarboxylase derived from Leishmania donovani (Ld-ODC) were examined by reverse vaccinology to develop prophylactics against visceral leishmaniasis (VL). These consensus epitopes comprising (P1: RLMPSAHAI, P2: LLDQYQIHL, P3: GLYHSFNCI, P4: AVLEVLSAL and P5: RLPASPAAL) were observed and presented by diverse HLA alleles screened by immune-informatics tools. These epitopes were also observed for strong stability for appropriate immune response in in silico screening and molecular dynamics. Top five selected epitopes filtered from population coverage analysis and TAP binding affinity were identified and evaluated against treated cases of VL subjects. Experiments were run individually with synthetic peptides or as the cocktail of peptides. A major population of CD8+ T cells were predominantly IFN-γ producers but not the IL-10 cytokines and shown with granzyme-B activity. Therefore, it can be concluded that the screened HLA-A0201 restricted epitope hotspots derived from Leishmania ODC can trigger CD8+ T cells, which can skew other immune cells functions toward protection. However, a detailed analysis can explore its potentiality as a vaccine candidate.Communicated by Ramaswamy H. Sarma.

Scouting the receptor-binding domain of SARS coronavirus 2: a comprehensive immunoinformatics inquisition

Aim: December 2019 witnessed the emergence of a worldwide outbreak of a novel strain of coronavirus (CoV) termed SARS-CoV-2. Several preventive strategies are being developed, such as vaccines, to stop the spread of infection. Materials & methods: A comprehensive immunoinformatics approach was used to map conserved peptide sequences on the receptor binding domain of SARS-CoV-2 for their B-cell, T-helper & T-cytotoxic cell epitope profiles. Results & conclusion: The antigenic B-cell epitopes were LFRKSN and SYGFQPT. Among T-cell epitopes, CVADYSVLY and FTNVYADSF exhibited affinity for MHC class I, while YRLFRKSNL and VYAWNRKRI exhibited affinity for of MHC class II alleles. The overlapping epitope between B- and T-cells was YRLFRKSNL. The deployment of these epitopes in potential vaccine development against COVID-19 may help in slowing down the SARS-CoV-2 spread.

Immuno-informatics approach for B-cell and T-cell epitope based peptide vaccine design against novel COVID-19 virus

COVID-19 has brought the world to a standstill with a wave of destruction in country after country with tremendous loss of lives and livelihood in advanced to developing nations. Whole world is staring at the prospect of repeated lockdowns with another wave of COVID-19 predicted to hit the world in September of 2020. The second wave is assumed to be even more destructive with severe impact across much of the world. The only way to defeat this pandemic is to quickly develop a safe and effective vaccine against this raging menace and initiate a global vaccination drive. Our study is an attempt to deploy various computational methods to identify B-cell and T-cell epitopes from the spike surface glycoprotein of SARS-COV-2 which have the novel potential for vaccine development against COVID-19. For this we have taken 8 unique strains with one each from India, China, France, USA, Italy, Australia, Iran and Pakistan. The strain data was extracted from NCBI Database. By analyzing the immune parameters like surface accessibility, antigenicity, variability, conservancy, flexibility, hydrophilicity, allergenicity and toxicity of the conserved sequences of spike glycoprotein using various databases and bioinformatics tools, we identified two potential novel linear (SGTNGTKRFDN and ASVYAWNRK) and one structural B-cell epitope as well as two T-cell epitopes (RLFRKSNLK and IPTNFTISV) which can be used as epitope-based peptide vaccines. Docking simulation assay revealed that above T-cell epitopes have minimum free binding energy and showed strong hydrogen bond interaction which strengthened its potential as being a T-cell epitope for the epitope-based novel vaccine against SARS-CoV-2. This study allows us to claim that B-cell and T-cell epitopes mentioned above provide potential pathways for developing an exploratory vaccine against spike surface glycoprotein of SARS-CoV-2 with high confidence for the identified strains. We will need to confirm our findings with biological assays.

T and B cell Epitope analysis of SARS-CoV-2 S protein based on immunoinformatics and experimental research

COVID-19 caused by SARS-CoV-2 is pandemic with a severe morbidity and mortality rate across the world. Despite the race for effective vaccine and drug against further expansion and fatality rate of this novel coronavirus, there is still lack of effective antiviral therapy. To this effect, we deemed it necessary to identify potential B and T cell epitopes from the envelope S protein. This can be used as potential targets to develop anti-SARS-CoV-2 vaccine preparations. In this study, we used immunoinformatics to identify conservative B and T cell epitopes for S proteins of SARS-CoV-2, which might play roles in the initiation of SARS-CoV-2 infection. We identified the B cell and T cell peptide epitopes of S protein and their antigenicity, as well as the interaction between the peptide epitopes and human leucocyte antigen (HLA). Among the B cell epitopes, 'EILDITPCSFGGVS' has the highest score of antigenicity and great immunogenicity. In T cell epitopes, MHC-I peptide 'KIADYNYKL' and MHC-II peptide 'LEILDITPC' were identified as high antigens. Besides, docking analysis showed that the predicted peptide 'KIADYNYKL' was closely bound to the HLA-A*0201. The results of molecular dynamics simulation through GROMACS software showed that 'HLA-A*0201~peptide' complex was very stable. And the peptide we selected could induce the T cell response similar to that of SARS-CoV-2 infection. Moreover, the predicted peptides were highly conserved in different isolates from different countries. The antigenic epitopes presumed in this study were effective new vaccine targets to prevent SARS-CoV-2 infection.

Molecular Screening Strategy to Identify a Non-invasive Delivery Mechanism for the Treatment of Middle Ear Disorders

Middle ear ailments include a broad range of pathological conditions. Otitis media is the leading middle ear disease of childhood, which incurs significant health care resources in developed countries and, in developing countries, causes significant mortality and morbidity. Recurrent and chronic infections of the middle ear lead to the prolonged presence of inflammatory factors and cellular infiltrates resulting in temporary hearing loss. However, long-term alteration of the middle ear space can pose the risk of permanent damage to the delicate ear structures and cause tissue remodeling. While the etiopathogenesis of middle ear diseases is multifactorial, targeting the biological mechanisms and molecular networks that drive disease development is critical. Yet, a pivotal step in realizing the potential of molecular therapies is the development of methods for local drug delivery, since systemic application risks side effects. Utilizing bacteriophage display in the rat, we discovered rare peptides that are able to transit the intact tympanic membrane from the external canal to the middle ear cavity by an active process. An in vitro assay demonstrated that transport occurs across the tympanic membranes of humans and that the peptides cross the membrane independent of phage. Transport of phage, which is ~900 nm in length, suggests that these peptides could non-invasively deliver drug packages or gene therapy vectors into the middle ear.

Synthetic Peptide Libraries Designed From a Minimal Alpha-Helical Domain of AS-48-Bacteriocin Homologs Exhibit Potent Antibacterial Activity

The circularized bacteriocin enterocin AS-48 produced by Enterococcus sp. exhibits antibacterial activity through membrane disruption. The membrane-penetrating activity of enterocin AS-48 has been attributed to a specific alpha-helical region on the circular peptide. Truncated, linearized forms containing these domains have been shown to preserve limited bactericidal activity. We utilized the amino acid sequence of the active helical domain of enterocin AS-48 to perform a homology-based search of similar sequences in other bacterial genomes. We identified similar domains in three previously uncharacterized AS-48-like bacteriocin genes in Clostridium sordellii, Paenibacillus larvae, and Bacillus xiamenensis. Enterocin AS-48 and homologs from these bacterial species were used as scaffolds for the design of a minimal peptide library based on the active helical domain of each bacteriocin sequence. 95 synthetic peptide variants of each scaffold peptide, designated Syn-enterocin, Syn-sordellicin, Syn-larvacin, and Syn-xiamensin, were designed and synthesized from each scaffold sequence based on defined biophysical parameters. A total of 384 total peptides were assessed for antibacterial activity against Gram-negative and Gram-positive bacteria. Minimal Inhibitory Concentrations (MICs) as low as 15.6 nM could be observed for the most potent peptide candidate tested, with no significant cytotoxicity to eukaryotic cells. Our work demonstrates for the first time a general workflow of using minimal domains of natural bacteriocin sequences as scaffolds to design and rapidly synthesize a library of bacteriocin-based antimicrobial peptide variants for evaluation.

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019), as a global pandemic. Additionally, the positive cases are still following an upward trend worldwide and as a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication and interferes with host immune responses. We comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we predicted the most immunogenic epitope for the T-cell and B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.

Harnessing the PD-L1 interface peptide for positron emission tomography imaging of the PD-1 immune checkpoint

Interface peptides that mediate protein–protein interactions (PPI) are a class of important lead compounds for designing PPI inhibitors. However, their potential as precursors for radiotracers has never been exploited. Here we report that the interface peptides from programmed death-ligand 1 (PD-L1) can be used in positron emission tomography (PET) imaging of programmed cell death 1 (PD-1) with high accuracy and sensitivity. Moreover, the performance differentiation between murine PD-L1 derived interface peptide (mPep-1) and human PD-L1 derived interface peptide (hPep-1) as PET tracers for PD-1 unveiled an unprecedented role of a non-critical residue in target binding, highlighting the significance of PET imaging as a companion diagnostic in drug development. Collectively, this study not only provided a first-of-its-kind peptide-based PET tracer for PD-1 but also conveyed a unique paradigm for developing imaging agents for highly challenging protein targets, which could be used to identify other protein biomarkers involved in the PPI networks.

Leveraging interface peptides in PD-L1 for PET imaging of PD-1, providing a new paradigm for radiotracer development.

Computational approaches in epitope design using DNA binding proteins as vaccine candidate in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is a successful pathogen in the history of mankind. A high rate of mortality and morbidity raises the need for vaccine development. Mechanism of pathogenesis, survival strategy and virulence determinant are needed to be explored well for this pathogen. The involvement of DNA binding proteins in the regulation of virulence genes, transcription, DNA replication, repair make them more significant. In present work, we have identified 1453 DNA binding proteins (DBPs) in the 4173 genes of Mtb through the DNABIND tool and they were subjected for further screening by incorporating different bioinformatics tools. The eighteen DBPs were selected for the B-cell epitope prediction by using ABCpred server. Moreover, the B-cell epitope bearing the antigenic and non- allergenic property were selected for T-cell epitope prediction using ProPredI, and ProPred server. Finally, DGIGSAVSV (Rv1088), IRALPSSRH (Rv3923c), LTISPIANS (Rv3235), VQPSGKGGL (Rv2871) VPRPGPRPG (Rv2731) and VGQKINPHG (Rv0707) were identified as T-cell epitopes. The structural modelling of these epitopes and DBPs was performed to ensure the localization of these epitopes on the respective proteins. The interaction studies of these epitopes with human HLA confirmed their validation to be used as potential vaccine candidates. Collectively, these results revealed that the DBPs- Rv2731, Rv3235, Rv1088, Rv0707, Rv3923c and Rv2871 are the most appropriate vaccine candidates. In our knowledge, it is the first report of using the DBPs of Mtb for epitope prediction. Significantly, this study also provides evidence to be useful for designing a peptide-based vaccine against tuberculosis.

Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein

AIMS

With a large number of fatalities, coronavirus disease-2019 (COVID-19) has greatly affected human health worldwide. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19. The World Health Organization has declared a global pandemic of this contagious disease. Researchers across the world are collaborating in a quest for remedies to combat this deadly virus. It has recently been demonstrated that the spike glycoprotein (SGP) of SARS-CoV-2 is the mediator by which the virus enters host cells.

MAIN METHODS

Our group comprehensibly analyzed the SGP of SARS-CoV-2 through multiple sequence analysis and a phylogenetic analysis. We predicted the strongest immunogenic epitopes of the SGP for both B cells and T cells.

KEY FINDINGS

We focused on predicting peptides that would bind major histocompatibility complex class I. Two optimal epitopes were identified, WTAGAAAYY and GAAAYYVGY. They interact with the HLA-B*15:01 allele, which was further validated by molecular docking simulation. This study also found that the selected epitopes are able to be recognized in a large percentage of the world's population. Furthermore, we predicted CD4+ T-cell epitopes and B-cell epitopes.

SIGNIFICANCE

Our study provides a strong basis for designing vaccine candidates against SARS-CoV-2. However, laboratory work is required to validate our theoretical results, which would lay the foundation for the appropriate vaccine manufacturing and testing processes.

The anti-ageing effects of a natural peptide discovered by artificial intelligence

OBJECTIVE

As skin ages, impaired extracellular matrix (ECM) protein synthesis and increased action of degradative enzymes manifest as atrophy, wrinkling and laxity. There is mounting evidence for the functional role of exogenous peptides across many areas, including in offsetting the effects of cutaneous ageing. Here, using an artificial intelligence (AI) approach, we identified peptide RTE62G (pep_RTE62G), a naturally occurring, unmodified peptide with ECM stimulatory properties. The AI-predicted anti-ageing properties of pep_RTE62G were then validated through in vitro, ex vivo and proof of concept clinical testing.

METHODS

A deep learning approach was applied to unlock pep_RTE62G from a plant source, Pisum sativum (pea). Cell culture assays of human dermal fibroblasts (HDFs) and keratinocytes (HaCaTs) were subsequently used to evaluate the in vitro effect of pep_RTE62G. Distinct activities such as cell proliferation and ECM protein production properties were determined by ELISA assays. Cell migration was assessed using a wound healing assay, while ECM protein synthesis and gene expression were analysed, respectively, by immunofluorescence microscopy and PCR. Immunohistochemistry of human skin explants was employed to further investigate the induction of ECM proteins by pep_RTE62G ex vivo. Finally, the clinical effect of pep_RTE626 was evaluated in a proof of concept 28-day pilot study.

RESULTS

In vitro testing confirmed that pep_RTE62G is an effective multi-functional anti-ageing ingredient. In HaCaTs, pep_RTE62G treatment significantly increases both cellular proliferation and migration. Similarly, in HDFs, pep_RTE62G consistently induced the neosynthesis of ECM protein elastin and collagen, effects that are upheld in human skin explants. Lastly, in our proof of concept clinical study, application of pep_RTE626 over 28 days demonstrated anti-wrinkle and collagen stimulatory potential.

CONCLUSION

pep_RTE62G represents a natural, unmodified peptide with AI-predicted and experimentally validated anti-ageing properties. Our results affirm the utility of AI in the discovery of novel, functional topical ingredients.

Norepinephrine transporter-derived homing peptides enable rapid endocytosis of drug delivery nanovehicles into neuroblastoma cells

BACKGROUND

Currently, the diagnosis and treatment of neuroblastomas-the most frequent solid tumors in children-exploit the norepinephrine transporter (hNET) via radiolabeled norepinephrine analogs. We aim to develop a nanomedicine-based strategy towards precision therapy by targeting hNET cell-surface protein with hNET-derived homing peptides.

RESULTS

The peptides (seq. GASNGINAYL and SLWERLAYGI) were shown to bind high-resolution homology models of hNET in silico. In particular, one unique binding site has marked the sequence and structural similarities of both peptides, while most of the contribution to the interaction was attributed to the electrostatic energy of Asn and Arg (< - 228 kJ/mol). The peptides were comprehensively characterized by computational and spectroscopic methods showing ~ 21% β-sheets/aggregation for GASNGINAYL and ~ 27% α-helix for SLWERLAYGI. After decorating 12-nm ferritin-based nanovehicles with cysteinated peptides, both peptides exhibited high potential for use in actively targeted neuroblastoma nanotherapy with exceptional in vitro biocompatibility and stability, showing minor yet distinct influences of the peptides on the global expression profiles. Upon binding to hNET with fast binding kinetics, GASNGINAYLC peptides enabled rapid endocytosis of ferritins into neuroblastoma cells, leading to apoptosis due to increased selective cytotoxicity of transported payload ellipticine. Peptide-coated nanovehicles significantly showed higher levels of early apoptosis after 6 h than non-coated nanovehicles (11% and 7.3%, respectively). Furthermore, targeting with the GASNGINAYLC peptide led to significantly higher degree of late apoptosis compared to the SLWERLAYGIC peptide (9.3% and 4.4%, respectively). These findings were supported by increased formation of reactive oxygen species, down-regulation of survivin and Bcl-2 and up-regulated p53.

CONCLUSION

This novel homing nanovehicle employing GASNGINAYLC peptide was shown to induce rapid endocytosis of ellipticine-loaded ferritins into neuroblastoma cells in selective fashion and with successful payload. Future homing peptide development via lead optimization and functional analysis can pave the way towards efficient peptide-based active delivery of nanomedicines to neuroblastoma cells.

Structure-based drug designing and immunoinformatics approach for SARS-CoV-2

The prevalence of respiratory illness caused by the novel SARS-CoV-2 virus associated with multiple organ failures is spreading rapidly because of its contagious human-to-human transmission and inadequate globalhealth care systems. Pharmaceutical repurposing, an effective drug development technique using existing drugs, could shorten development time and reduce costs compared to those of de novo drug discovery. We carried out virtual screening of antiviral compounds targeting the spike glycoprotein (S), main protease (Mpro), and the SARS-CoV-2 receptor binding domain (RBD)-angiotensin-converting enzyme 2 (ACE2) complex of SARS-CoV-2. PC786, an antiviral polymerase inhibitor, showed enhanced binding affinity to all the targets. Furthermore, the postfusion conformation of the trimeric S protein RBD with ACE2 revealed conformational changes associated with PC786 drug binding. Exploiting immunoinformatics to identify T cell and B cell epitopes could guide future experimental studies with a higher probability of discovering appropriate vaccine candidates with fewer experiments and higher reliability.

Structures of the intrinsically disordered Aβ, tau and α-synuclein proteins in aqueous solution from computer simulations

Intrinsically disordered proteins (IDPs) play many biological roles in the human proteome ranging from vesicular transport, signal transduction to neurodegenerative diseases. The Aβ and tau proteins, and the α-synuclein protein, key players in Alzheimer's and Parkinson's diseases, respectively are fully disordered at the monomer level. The structural heterogeneity of the monomeric and oligomeric states and the high self-assembly propensity of these three IDPs have precluded experimental structural determination. Simulations have been used to determine the atomic structures of these IDPs. In this article, we review recent computer models to capture the equilibrium ensemble of Aβ, tau and α-synuclein proteins at different association steps in aqueous solution and present new results of the PEP-FOLD framework on α-synuclein monomer.

An in-silico approach to develop of a multi-epitope vaccine candidate against SARS-CoV-2 envelope (E) protein

Since the first appearance of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) in China on December 2019, the world has now witnessed the emergence of the SARS- CoV-2 outbreak. Therefore, due to the high transmissibility rate of virus, there is an urgent need to design and develop vaccines against SARS-CoV-2 to prevent more cases affected by the virus. In this study, a computational approach is proposed for vaccine design against the envelope (E) protein of SARS-CoV-2, which contains a conserved sequence feature. First, we sought to gain potential B-cell and T-cell epitopes for vaccine designing against SARS-CoV-2. Second, we attempted to develop a multi-epitope vaccine. Immune targeting of such epitopes could theoretically provide defense against SARS-CoV-2. Finally, we evaluated the affinity of the vaccine to major histocompatibility complex (MHC) molecules to stimulate the immune system response to this vaccine. We also identified a collection of B-cell and T-cell epitopes derived from E proteins that correspond identically to SARS-CoV-2 E proteins. The in-silico design of our potential vaccine against E protein of SARS-CoV-2 demonstrated a high affinity to MHC molecules, and it can be a candidate to make a protection against this pandemic event.

Epitope-Based Peptide Vaccine Against Severe Acute Respiratory Syndrome-Coronavirus-2 Nucleocapsid Protein: An in silico Approach.. [DOI: 10.1101/2020.05.16.100206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. SARS-CoV-2 is a member of the Coronaviridae family, which is transmitted from animal to human and because of being contagious, further it transmitted human to human. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019) as a global pandemic. But, no specific medications are available for the treatment of COVID-19 so far. As a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication as well as interferes with host immune responses. We have comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we have predicted the most immunogenic epitope for T-cell as well as B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.

Secretory Expression of a Chimeric Peptide in Lactococcus lactis: Assessment of its Cytotoxic Activity and a Deep View on Its Interaction with Cell-Surface Glycosaminoglycans by Molecular Modeling

Nowadays, cancer remains a major cause of death affecting millions of people. Currently, the antimicrobial peptides (AMPs) as potent anticancer therapeutic agents offer specificity and low levels of side effects in cancer therapy. In the present study, a cationic chimeric peptide (cLFchimera), derived from camel lactoferrin, was expressed as a secretory peptide using P170 expression system in L. lactis. Peptide purification was carried out using Ni-NTA agarose column from culture medium with 21 μ/mL concentration. The recombinant peptide was investigated for its activity against four tumor and one normal cell line. The cLFchimera was more active against two tumor cell lines (chondrosarcoma and colorectal cancer cells), but the activity against two other tumor cell lines (hepatoma and breast cancer cell line) and normal cells was low. Finally, to have better insight into the mode of action of the peptide on cytotoxic activity, we examined the interaction of cationic peptide with two glycosaminoglycans (GAGs), heparan sulfate (HS) and chondroitin sulfate (CS), as the two most anionic molecules on the cell surface by molecular dynamic simulation. The results of in silico analysis showed that the cLFchimera interacted with HS and CS with a totally different amino acid profile. Hydrogen bonding screening in GAGs-peptide complexes revealed K²¹, V²³ and I³, R¹⁶ are the dominant amino acids involved in peptide-HS and CS interaction, respectively. Overall, the results of this investigation showed the P170 expression system successfully expressed a cationic peptide with potent anticancer activity. Moreover, molecular docking analysis revealed the pattern of peptide interaction with negatively charged membrane molecules.

Phage display-identified PD-L1-binding peptides reinvigorate T-cell activity and inhibit tumor progression

Blockade of programmed cell death ligand-1 (PD-L1) restores T-cell activity and enhances anti-tumor immunity. Screening a phage-displayed peptide library for peptides that selectively bind to PD-L1-overexpressing cells identified two peptides, CLQKTPKQC and CVRARTR (PD-L1Pep-1 and PD-L1Pep-2, respectively) that appeared to block PD-L1. PD-L1Pep-1 and PD-L1Pep-2 preferentially bound to high PD-L1-expressing cells over low PD-L1-expressing cells; binding was further enhanced by interferon-γ, an inducer of PD-L1 expression. Binding affinities of PD-L1Pep-1 and PD-L1Pep-2 were approximately 373 and 281 nM, respectively. Cellular binding of the PD-L1-binding peptides was reduced by silencing PD-L1 gene expression or competition with anti-PD-L1 antibody. PD-L1Pep-1 and PD-L1Pep-2 induced the internalization and downregulated cell surface levels of PD-L1. The PD-L1-binding peptides restored cytokine secretion and T-cell proliferation to cells inhibited by co-culture with tumor cells or culture on PD-L1-coated plates. Intravenously injected PD-L1Pep-1 and PD-L1Pep-2 efficiently homed to tumor tissues, inhibited tumor growth, and increased CD8+/FoxP3+ ratio in mice. The PD-L1-binding peptides in combination with doxorubicin or PD-L1-targeted liposomal doxorubicin inhibited tumor growth and increased CD8+/FoxP3+ ratio more efficiently than doxorubicin alone and untargeted liposomal doxorubicin, respectively. These results suggest that PD-L1Pep-1 and PD-L1Pep-2 block PD-L1 and reinvigorate T-cell activity, inhibiting tumor growth by enhancing anti-tumor immunity.

Interaction of camel Lactoferrin derived peptides with DNA: a molecular dynamics study

Background

Lactoferrampin (LFampin), Lactoferricin (LFcin), and LFchimera are three well-known antimicrobial peptides derived from Lactoferrin and proposed as alternatives for antibiotics. Although the intracellular activity of these peptides has been previously demonstrated, their mode of action is not yet fully understood. Here, we performed a molecular dynamics simulation study to understand the molecular interactions between camel Lactoferrin derived peptides, including CLFampin, CLFcin, and CLFchimera, and DNA as an important intracellular target.

Results

Our results indicate that all three peptides bind to DNA, albeit with different propensities, with CLFchimera showing the highest binding affinity. The secondary structures of the peptides, modeled on Lactoferrin, did not undergo significant changes during simulation, supporting their functional relevance. Main residues involved in the peptide-DNA interaction were identified based on binding free energy estimates calculated over 200 ns, which, as expected, confirmed strong electrostatic interactions between DNA phosphate groups and positively charged peptide side chains. Interaction between the different concentrations of CLFchimera and DNA revealed that after binding of four copies of CLFchimera to DNA, hydrogen bonds between the two strands of DNA start to break from one of the termini.

Conclusions

Importantly, our results revealed that there is no DNA-sequence preference for peptide binding, in line with a broad antimicrobial activity. Moreover, the results showed that the strength of the interaction between DNA and CLFchimera is concentration dependent. The insight provided by these results can be used for the rational redesign of natural antimicrobial peptides targeting the bacterial DNA.

Coarse-grained and atomic resolution biomolecular docking with the ATTRACT approach

The ATTRACT protein-protein docking program has been employed to predict protein-protein complex structures in CAPRI rounds 38-45. For 11 out of 16 targets acceptable or better quality solutions have been submitted (~70%). It includes also several cases of peptide-protein docking and the successful prediction of the geometry of carbohydrate-protein interactions. The option of combining rigid body minimization and simultaneous optimization in collective degrees of freedom based on elastic network modes was employed and systematically evaluated. Application to a large benchmark set indicates a modest improvement in docking performance compared to rigid docking. Possible further improvements of the docking approach in particular at the scoring and the flexible refinement steps are discussed.

Specific metallo-protein interactions and antimicrobial activity in Histatin-5, an intrinsically disordered salivary peptide

Histatin-5 (Hst-5) is an antimicrobial, salivary protein that is involved in the host defense system. Hst-5 has been proposed to bind functionally relevant zinc and copper but presents challenges in structural studies due to its disordered conformation in aqueous solution. Here, we used circular dichroism (CD) and UV resonance Raman (UVRR) spectroscopy to define metallo-Hst-5 interactions in aqueous solution. A zinc-containing Hst-5 sample exhibits shifted Raman bands, relative to bands observed in the absence of zinc. Based on comparison to model compounds and to a family of designed, zinc-binding beta hairpins, the alterations in the Hst-5 UVRR spectrum are attributed to zinc coordination by imidazole side chains. Zinc addition also shifted a tyrosine aromatic ring UVRR band through an electrostatic interaction. Copper addition did not have these effects. A sequence variant, H18A/H19A, was employed; this mutant has less potent antifungal activity, when compared to Hst-5. Zinc addition had only a small effect on the thermal stability of this mutant. Interestingly, both zinc and copper addition shifted histidine UVRR bands in a manner diagnostic for metal coordination. Results obtained with a K13E/R22G mutant were similar to those obtained with wildtype. These experiments show that H18 and H19 contribute to a zinc binding site. In the H18A/H19A mutant the specificity of the copper/zinc binding sites is lost. The experiments implicate specific zinc binding to be important in the antimicrobial activity of Hst-5.

Epitope-based peptide vaccine design and target site depiction against Middle East Respiratory Syndrome Coronavirus: an immune-informatics study

Background

Middle East Respiratory Syndrome Coronavirus (MERS-COV) is the main cause of lung and kidney infections in developing countries such as Saudi Arabia and South Korea. This infectious single-stranded, positive (+) sense RNA virus enters the host by binding to dipeptidyl-peptide receptors. Since no vaccine is yet available for MERS-COV, rapid case identification, isolation, and infection prevention strategies must be used to combat the spreading of MERS-COV infection. Additionally, there is a desperate need for vaccines and antiviral strategies.

Methods

The present study used immuno-informatics and computational approaches to identify conserved B- and T cell epitopes for the MERS-COV spike (S) protein that may perform a significant role in eliciting the resistance response to MERS-COV infection.

Results

Many conserved cytotoxic T-lymphocyte epitopes and discontinuous and linear B-cell epitopes were predicted for the MERS-COV S protein, and their antigenicity and interactions with the human leukocyte antigen (HLA) B7 allele were estimated. Among B-cell epitopes, QLQMGFGITVQYGT displayed the highest antigenicity-score, and was immensely immunogenic. Among T-cell epitopes, MHC class-I peptide YKLQPLTFL and MHC class-II peptide YCILEPRSG were identified as highly antigenic. Furthermore, docking analyses revealed that the predicted peptides engaged in strong bonding with the HLA-B7 allele.

Conclusion

The present study identified several MERS-COV S protein epitopes that are conserved among various isolates from different countries. The putative antigenic epitopes may prove effective as novel vaccines for eradication and combating of MERS-COV infection.

In Silico Design of Novel Mutant Anti-MUC1 Aptamers for Targeted Cancer Therapy

The transmembrane glycoprotein mucin 1 (MUC1) is an attractive tumor marker for cancer therapy and diagnosis. The nine amino acid extracellular epitope APDTRPAPG of this protein is selectively recognized by the S2.2 single-stranded DNA anti-MUC1 aptamer, which has emerged as a promising template for designing novel targeting agents for MUC1-directed therapy. In this work, 100 ns molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, and conformational analysis were employed to propose a novel prospective anti-MUC1 aptamer with increased affinity toward the MUC1 epitope resulting from the double mutation of the T11 and T12 residues with PSU and U nucleosides, respectively. The double mutant aptamer exhibits a tight interaction with the MUC1 epitope and adopts a groove conformation that structurally favors the intermolecular contact with the epitope through the intermediate T11-A18 region leaving the 3' and 5' ends free for further chemical conjugation with a nanocarrier or pharmaceutical. These results are valuable to gain understanding about the molecular features governing aptamer-epitope interactions and constitute a first key step for the design of novel aptamer-based nanocarriers for MUC1-targeted cancer therapy.

Mitigation of peri-implantitis by rational design of bifunctional peptides with antimicrobial properties

The integration of molecular and cell biology with materials science has led to strategies to improve the interface between dental implants with the surrounding soft and hard tissues in order to replace missing teeth and restore mastication. More than 3 million implants have been placed in the US alone and this number is rising by 500,000/year. Peri-implantitis, an inflammatory response to oral pathogens growing on the implant surface threatens to reduce service life leading to eventual implant failure, and such an outcome will have adverse impact on public health and create significant health care costs. Here we report a predictive approach to peptide design, which enabled us to engineer a bifunctional peptide to combat bacterial colonization and biofilm formation, reducing the adverse host inflammatory immune response that destroys the tissue surrounding implants and shortens their lifespans. This bifunctional peptide contains a titanium-binding domain that recognizes and binds with high affinity to titanium implant surfaces, fused through a rigid spacer domain with an antimicrobial domain. By varying the antimicrobial peptide domain, we were able to predict the properties of the resulting bifunctional peptides in their entirety by analyzing the sequence-structure-function relationship. These bifunctional peptides achieve: 1) nearly 100% surface coverage within minutes, a timeframe suitable for their clinical application to existing implants; 2) nearly 100% binding to a titanium surface even in the presence of contaminating serum protein; 3) durability to brushing with a commercially available electric toothbrush; and 4) retention of antimicrobial activity on the implant surface following bacterial challenge. A bifunctional peptide film can be applied to both new implants and/or repeatedly applied to previously placed implants to control bacterial colonization mitigating peri-implant disease that threatens dental implant longevity.