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

De Novo Rational Design of Peptide-Based Protein-Protein Inhibitors (Pep-PPIs) Approach by Mapping the Interaction Motifs of the PP Interface and Physicochemical Filtration: A Case on p25-Cdk5-Mediated Neurodegenerative Diseases

Protein-protein interactions, or PPIs, are a part of every biological activity and have been linked to a number of diseases, including cancer, infectious diseases, and neurological disorders. As such, targeting PPIs is considered a strategic and vital approach in the development of new medications. Nonetheless, the wide and flat contact interface makes it difficult to find small-molecule PP inhibitors. An alternative strategy would be to use the PPI interaction motifs as building blocks for the design of peptide-based inhibitors. Herein, we designed 12-mer peptide inhibitors to target p25-inducing-cyclin-dependent kinase (Cdk5) hyperregulation, a PPI that has been shown to perpetuate neuroinflammation, which is one of the major causal implications of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and frontotemporal dementia. We generated a library of 5 062 500 peptide combination sequences (PCS) derived from the interaction motif of Cdk5/p25 PP interface. The 20 amino acids were differentiated into six groups, namely, hydrophobic (aliphatic), aromatic, basic, acidic, unique, and polar uncharged, on the basis of their physiochemical properties. To preserve the interaction motif necessary for ideal binding, de novo modeling of all possible peptide sequence substitutions was considered. A set of filters, backed by the Support Vector Machine (SVM) algorithm, was then used to create a shortlisted custom peptide library that met specific bioavailability, toxicity, and therapeutic relevance, leading to a refined library of 15 PCS. A greedy algorithm and coarse-grained force field were used to predict peptide structure and folding before subsequent modeling studies. Molecular docking was performed to estimate the relative binding affinities, and out of the top hits, Pep15 was subjected to molecular dynamics simulations and binding free-energy calculations in comparison to a known peptide inhibitor with experimental data (template peptide). Interestingly, the identified peptide through our protocol, Pep15, was found to show a significantly higher binding affinity than the reference template peptide (-48.10 ± 0.23 kcal/mol and -17.53 ± 0.27 kcal/mol, respectively). In comparison to the template peptide, Pep15 was found to possess a more compact and buried surface area, tighter binding landscape, and reduced conformational variability, leading to enhanced structural and kinetic stability of the Cdk5/p25 complex. Notably, both peptide inhibitors were found to have a minimal impact on the architectural integrity of the Cdk5/p25 secondary structure. Herein, we propose Pep15 as a novel and potentially disruptive peptide drug for Cdk5/p25-mediated neurodegenerative phenotypes that require further clinical investigation. The systematic protocol and findings of this report would serve as a valuable tool in the identification of critical PPI interface reactive residues, designing of analogs, and identification of more potent peptide-based PPI inhibitors.

Material-specific binding peptides empower sustainable innovations in plant health, biocatalysis, medicine and microplastic quantification

Material-binding peptides (MBPs) have emerged as a diverse and innovation-enabling class of peptides in applications such as plant-/human health, immobilization of catalysts, bioactive coatings, accelerated polymer degradation and analytics for micro-/nanoplastics quantification. Progress has been fuelled by recent advancements in protein engineering methodologies and advances in computational and analytical methodologies, which allow the design of, for instance, material-specific MBPs with fine-tuned binding strength for numerous demands in material science applications. A genetic or chemical conjugation of second (biological, chemical or physical property-changing) functionality to MBPs empowers the design of advanced (hybrid) materials, bioactive coatings and analytical tools. In this review, we provide a comprehensive overview comprising naturally occurring MBPs and their function in nature, binding properties of short man-made MBPs (<20 amino acids) mainly obtained from phage-display libraries, and medium-sized binding peptides (20-100 amino acids) that have been reported to bind to metals, polymers or other industrially produced materials. The goal of this review is to provide an in-depth understanding of molecular interactions between materials and material-specific binding peptides, and thereby empower the use of MBPs in material science applications. Protein engineering methodologies and selected examples to tailor MBPs toward applications in agriculture with a focus on plant health, biocatalysis, medicine and environmental monitoring serve as examples of the transformative power of MBPs for various industrial applications. An emphasis will be given to MBPs' role in detecting and quantifying microplastics in high throughput, distinguishing microplastics from other environmental particles, and thereby assisting to close an analytical gap in food safety and monitoring of environmental plastic pollution. In essence, this review aims to provide an overview among researchers from diverse disciplines in respect to material-(specific) binding of MBPs, protein engineering methodologies to tailor their properties to application demands, re-engineering for material science applications using MBPs, and thereby inspire researchers to employ MBPs in their research.

Discovery of Antimicrobial Agents Based on Structural and Functional Study of the Klebsiella pneumoniae MazEF Toxin-Antitoxin System

Klebsiella pneumoniae causes severe human diseases, but its resistance to current antibiotics is increasing. Therefore, new antibiotics to eradicate K. pneumoniae are urgently needed. Bacterial toxin-antitoxin (TA) systems are strongly correlated with physiological processes in pathogenic bacteria, such as growth arrest, survival, and apoptosis. By using structural information, we could design the peptides and small-molecule compounds that can disrupt the binding between K. pneumoniae MazE and MazF, which release free MazF toxin. Because the MazEF system is closely implicated in programmed cell death, artificial activation of MazF can promote cell death of K. pneumoniae. The effectiveness of a discovered small-molecule compound in bacterial cell killing was confirmed through flow cytometry analysis. Our findings can contribute to understanding the bacterial MazEF TA system and developing antimicrobial agents for treating drug-resistant K. pneumoniae.

Targeting peptide based therapeutics: Integrated computational and experimental studies of autophagic regulation in host-parasite interaction

Cutaneous leishmaniasis caused by the intracellular parasite Leishmania major, exhibits significant public health challenge worldwide. With limited treatment options available, the identification of novel therapeutic targets is of paramount importance. Present study manifested the crucial role of ATG8 protein as a potential target in combating L. major infection. Using machine learning algorithms, we identified non-conserved motifs within the ATG8 in L. major. Subsequently, a peptide library was generated based on these motifs, and three peptides were selected for further investigation through molecular docking and molecular dynamics simulations. Surface Plasmon Resonance (SPR) experiments confirmed the direct interaction between ATG8 and the identified peptides. Remarkably, these peptides demonstrated the ability to cross the parasite membrane and exert profound effects on L. major. Peptide treatment significantly impacted parasite survival, inducing alterations in the cell cycle and morphology. Furthermore, the peptides were found to modulate autophagosome formation, particularly under starved conditions, indicating their involvement in autophagy regulation within L. major. In vitro studies revealed that the selected peptides effectively decreased the parasite load within the infected host cells. Encouragingly, in vivo experiments corroborated these findings, demonstrating a reduction in parasite burden upon peptide administration. Additionally, the peptides were observed to affect the levels of LC3II, a known autophagy marker within the host cells. Collectively, our findings highlight the efficacy of these novel peptides in targeting L. major ATG8 and disrupting parasite survival, wherein P2 is showing prominent effect on L. major as compared to P1. These results provide valuable insights into the development of innovative therapeutic strategies against leishmaniasis.

Monomeric Far-red and Near-infrared Fluorescent Biliproteins of Ultrahigh Brightness

Far-red and near-infrared fluorescent proteins have regions of maximum transmission in most tissues and can be widely used as fluorescent biomarkers. We report that fluorescent phycobiliproteins originating from the phycobilisome core subunit ApcF2 can covalently bind biliverdin, named BDFPs. To further improve BDFPs, we conducted a series of studies. Firstly, we mutated K53Q and T144A of BDFPs to increase their effective brightness up to 190 % in vivo. Secondly, by homochromatic tandem fusion of high-brightness BDFPs to achieve monomerization, which increases the effective brightness by up to 180 % in vivo, and can effectively improve the labeling effect. By combining the above two approaches, the brightness of the tandem BDFPs was much improved compared with that of the previously reported fluorescent proteins in a similar spectral range. The tandem BDFPs were expressed stably while maintaining fluorescence in mammalian cells and Caenorhabditis elegans. They were also photostable and resistant to high temperature, low pH, and chemical denaturation. The tandem BDFPs advantages were proved in applications as biomarkers for imaging in super-resolution microscopy.

Analysis of Self-Assembled Low- and High-Molecular-Weight Poly-L-Lysine-Ce6 Conjugate-Based Nanoparticles

In cancer therapy, photodynamic therapy (PDT) has attracted significant attention due to its high potential for tumor-selective treatment. However, PDT agents often exhibit poor physicochemical properties, including solubility, necessitating the development of nanoformulations. In this study, we developed two cationic peptide-based self-assembled nanomaterials by using a PDT agent, chlorin e6 (Ce6). To manufacture biocompatible nanoparticles based on peptides, we used the cationic poly-L-lysine peptide, which is rich in primary amines. We prepared low- and high-molecular-weight poly-L-lysine, and then evaluated the formation and performance of nanoparticles after chemical conjugation with Ce6. The results showed that both molecules formed self-assembled nanoparticles by themselves in saline. Interestingly, the high-molecular-weight poly-L-lysine and Ce6 conjugates (HPLCe6) exhibited better self-assembly and PDT performance than low-molecular-weight poly-L-lysine and Ce6 conjugates (LPLCe6). Moreover, the HPLCe6 conjugates showed superior cellular uptake and exhibited stronger cytotoxicity in cell toxicity experiments. Therefore, it is functionally beneficial to use high-molecular-weight poly-L-lysine in the manufacturing of poly-L-lysine-based self-assembling biocompatible PDT nanoconjugates.

Application of Computational Techniques in Antibody Fc-Fused Molecule Design for Therapeutics

Since the advent of hybridoma technology in the year 1975, it took a decade to witness the first approved monoclonal antibody Orthoclone OKT39 (muromonab-CD3) in the year 1986. Since then, continuous strides have been made to engineer antibodies for specific desired effects. The engineering efforts were not confined to only the variable domains of the antibody but also included the fragment crystallizable (Fc) region that influences the immune response and serum half-life. Engineering of the Fc fragment would have a profound effect on the therapeutic dose, antibody-dependent cell-mediated cytotoxicity as well as antibody-dependent cellular phagocytosis. The integration of computational techniques into antibody engineering designs has allowed for the generation of testable hypotheses and guided the rational antibody design framework prior to further experimental evaluations. In this article, we discuss the recent works in the Fc-fused molecule design that involves computational techniques. We also summarize the usefulness of in silico techniques to aid Fc-fused molecule design and analysis for the therapeutics application.

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our exploration encompasses various facets of peptide research, ranging from dataset curation handling to model development. As deep learning technologies become more refined, we channel our efforts into peptide structure prediction and design, aligning with the fundamental principles of structure-activity relationships in drug development. To guide researchers in harnessing the potential of deep learning to advance peptide drug development, our insights comprehensively explore current challenges and future directions of peptide therapeutics.

Bioinformatics and bioactive peptides from foods: Do they work together?

We live in the Big Data Era which affects many aspects of science, including research on bioactive peptides derived from foods, which during the last few decades have been a focus of interest for scientists. These two issues, i.e., the development of computer technologies and progress in the discovery of novel peptides with health-beneficial properties, are closely interrelated. This Chapter presents the example applications of bioinformatics for studying biopeptides, focusing on main aspects of peptide analysis as the starting point, including: (i) the role of peptide databases; (ii) aspects of bioactivity prediction; (iii) simulation of peptide release from proteins. Bioinformatics can also be used for predicting other features of peptides, including ADMET, QSAR, structure, and taste. To answer the question asked "bioinformatics and bioactive peptides from foods: do they work together?", currently it is almost impossible to find examples of peptide research with no bioinformatics involved. However, theoretical predictions are not equivalent to experimental work and always require critical scrutiny. The aspects of compatibility of in silico and in vitro results are also summarized herein.

Insights into the Adsorption Mechanisms of the Antimicrobial Peptide CIDEM-501 on Membrane Models

CIDEM-501 is a hybrid antimicrobial peptide rationally designed based on the structure of panusin and panulirin template peptides. The new peptide exhibits significant antibacterial activity against multidrug-resistant pathogens (MIC = 2-4 μM) while conserving no toxicity in human cell lines. We conducted molecular dynamics (MD) simulations using the CHARMM-36 force field to explore the CIDEM-501 adsorption mechanism with different membrane compositions. Several parameters that characterize these interactions were analyzed to elucidate individual residues' structural and thermodynamic contributions. The membrane models were constructed using CHARMM-GUI, mimicking the bacterial and eukaryotic phospholipid compositions. Molecular dynamics simulations were conducted over 500 ns, showing rapid and highly stable peptide adsorption to bacterial lipids components rather than the zwitterionic eucaryotic model membrane. A predominant peptide orientation was observed in all models dominated by an electric dipole. The peptide remained parallel to the membrane surface with the center loop oriented to the lipids. Our findings shed light on the antibacterial activity of CIDEM-501 on bacterial membranes and yield insights valuable for designing potent antimicrobial peptides targeting multi- and extreme drug-resistant bacteria.

Engraulisin: A novel marine derived cell penetrating peptide with activity against drug resistant bacteria

Cell penetrating peptides (CPP) with their intrinsic ability to penetrate plasma membranes facilitate intracellular uptake of various macromolecules. Although a substantial number of CPPs have been reported over the last three decades, the number is still inadequate when compared to the theoretically feasible peptides with similar physicochemical composition. Marine organisms, due to their hostile environment, are an immense source of several high-valued therapeutically relevant peptides. Various marine derived antibacterial, antimycotic and anticancer peptides have demonstrated improved activity in comparison to peptides of terrestrial origin. While a significant number of marine bioactive peptides exist, cell penetrating peptides from marine organisms remain unravelled. In this study, we report Engraulisin from Engraulis japonicus, a computationally derived novel cell penetrating peptide of marine origin. Engraulisin manifest successful uptake in mammalian cells at 5 μM concentration with negligible cytotoxicity observed through MTT assay. Analysis of its cellular uptake mechanism revealed significant inhibition at 4 °C suggesting endocytosis as the major route of cellular entry. Interestingly, the novel peptide also demonstrated selective antimicrobial activity against Methicillin-resistant Staphylococcus aureus (MRSA). Additionally, molecular dynamics simulation with POPC and POPG bilayer system unveiled significance of positively charged residues in forming a stable membrane interaction. Engraulisin represents a novel marine-derived cell penetrating peptide which can be explored for cellular delivery of pharmaceutically relevant molecules.

DNA Aptamer Binding Octapeptide Repeat Region of Cellular Prion Protein

Cellular prion protein (PrPC) is highly expressed in a variety of tumor cells and plays a crucial role in neurodegenerative diseases. Its N-terminal domain contains a conserved octapeptide (PHGGGWGQ) repeat sequence. The number of repeats has been correlated with the species as well as the development of associated diseases. Herein, PrPC was identified to be the molecular target of a high-affinity DNA aptamer HA5-68 obtained by cell-SELEX. Aptamer HA5-68 was further optimized to two short sequences (HA5-40-1 and HA5-40-2), and its binding site to PrPC was identified to be located in the loop-stem-loop region of the head of its secondary structure. HA5 series aptamers were demonstrated to bind the octapeptide repeat region of PrPC, as well as the synthesized peptides containing different numbers of octapeptide repeats. The PrPC expression on 42 cell lines was measured by using aptamer HA5-68 as a molecular probe. The clear understanding of the molecular structure and binding mechanism of this set of aptamers will provide information for the design of diagnostic methods and therapeutic drugs targeting PrPC.

Dysregulated Autophagy and Sarcomere Dysfunction in Patients With Heart Failure With Co-Occurrence of P63A and P380S BAG3 Variants

BACKGROUND

Mutations to the co-chaperone protein BAG3 (B-cell lymphoma-2-associated athanogene-3) are a leading cause of dilated cardiomyopathy (DCM). These mutations often impact the C-terminal BAG domain (residues 420-499), which regulates heat shock protein 70-dependent protein turnover via autophagy. While mutations in other regions are less common, previous studies in patients with DCM found that co-occurrence of 2 BAG3 variants (P63A, P380S) led to worse prognosis. However, the underlying mechanism for dysfunction is not fully understood.

METHODS AND RESULTS

In this study, we used proteomics, Western blots, and myofilament functional assays on left ventricular tissue from patients with nonfailing, DCM, and DCM with BAG363/380 to determine how these mutations impact protein quality control and cardiomyocyte contractile function. We found dysregulated autophagy and increased protein ubiquitination in patients with BAG363/380 compared with nonfailing and DCM, suggesting impaired protein turnover. Expression and myofilament localization of BAG3-binding proteins were also uniquely altered in the BAG3,63/380 including abolished localization of the small heat shock protein CRYAB (alpha-crystallin B chain) to the sarcomere. To determine whether these variants impacted sarcomere function, we used cardiomyocyte force-calcium assays and found reduced maximal calcium-activated force in DCM and BAG363/380. Interestingly, myofilament calcium sensitivity was increased in DCM but not with BAG363/380, which was not explained by differences in troponin I phosphorylation.

CONCLUSIONS

Together, our data support that the disease-enhancing mechanism for BAG3 variants outside of the BAG domain is through disrupted protein turnover leading to compromised sarcomere function. These findings suggest a shared mechanism of disease among pathogenic BAG3 variants, regardless of location.

Develop a PD-1-blockade peptide to reinvigorate T-cell activity and inhibit tumor progress

Immune checkpoint inhibitors, particularly monoclonal antibodies blocking the programmed cell death 1 (PD-1)/programmed cell death ligand-1 (PD-L1) pathway, have been successfully utilized in the clinic. However, certain drawbacks associated with antibodies, such as high immunogenicity and poor tissue penetration, need to be addressed for their broader clinical application. Peptides, as low molecular weight alternatives, have garnered increasing interest in this field. In this study, we employed bacterial surface display technology to identify a PD-1-binding peptide, PBP. The PBP peptide exhibited moderate affinity for human PD-1 (hPD-1) and displayed cross-reactivity with mouse PD-1 (mPD-1). Molecular docking analysis revealed that the interaction residues of the PBP peptide with PD-1 played crucial roles in the formation of the PD-1/PD-L1 complex. A competing binding assay demonstrated that the peptide could interfere the interaction of PD-1 and PD-L1. Moreover, in vitro experiments showed that the PBP peptide could reinvigorate T cells inhibited by PD-L1. In an in vivo mouse model of CT26, the PBP peptide effectively suppressed tumor growth by enhancing T cell function. In conclusion, our results suggest that the PBP peptide exerts an anti-tumor effect by impeding the interplay between PD-1 and PD-L1, highlighting its potential as an alternative for tumor immunotherapy.

Decoy peptides effectively inhibit the binding of SARS-CoV-2 to ACE2 on oral epithelial cells

The entry of SARS-CoV-2 into host cells involves the interaction between the viral spike protein and the human angiotensin-converting enzyme 2 (ACE2) receptor. Given that the spike protein evolves rapidly to evade host immunity, therapeutics that block ACE2 accessibility, such as spike decoys, could serve as an alternative strategy for attenuating viral infection. Here, we constructed a drug screening platform based on oral epithelial cells to rapidly identify peptides or compounds capable of blocking the spike-ACE2 interaction. We engineered short decoy peptides, 8 to 14 amino acids in length, using the spike protein's receptor-binding motif (RBM) and demonstrated that these peptides can effectively inhibit virus attachment to host cells. Additionally, we discovered that diminazene aceturate (DIZE), an ACE2 activator, similarly inhibited virus binding. Our research thus validates the potential of decoy peptides as a new therapeutic strategy against SARS-CoV-2 infections, opening avenues for further development and study.

An in silico approach for prediction of B cell and T cell epitope candidates against Chikungunya virus

Several outbreaks of Chikungunya virus (CHIKV) had been reported since 1952 when mankind had his first encounter against the virus in Tanzania. Although these reports designate the CHIKV to be rarely fatal, cases of outbreaks in the last decade accompanied by severe complications and death poses a challenge to the development of effective treatment methods. Several attempts to vaccine development against CHIKV still remains unsuccessful. In this study, we aimed at the prediction of B-cell and T cell epitopes against CHIKV by using immunoinformatics. This, in turn, can contribute to development of an epitope based vaccine against CHIKV. Both linear and discontinuous B-cell epitopes, as well as Cytotoxic T-lymphocyte epitopes, were predicted for the CHIKV Envelope (E1 and E2) glycoproteins and (NS2). The antigenic CTL epitopes with highest binding affinities with type-1 MHC were selected and the peptides were docked to them. Docking followed by molecular dynamics simulations were performed to assess the stability of the docked complexes.

Membrane anchoring of the DIRAS3 N-terminal extension permits tumor suppressor function

DIRAS3 is an imprinted tumor suppressor gene encoding a GTPase that has a distinctive N-terminal extension (NTE) not found in other RAS proteins. This NTE and the prenylated C-terminus are required for DIRAS3-mediated inhibition of RAS/MAP signaling and PI3K activity at the plasma membrane. In this study, we applied biochemical, biophysical, and computational methods to characterize the structure and function of the NTE. The NTE peptide recognizes phosphoinositides PI(3,4,5)P3 and PI(4,5)P2 with rapid kinetics and strong affinity. Lipid binding induces NTE structural change from disorder to amphipathic helix. Mass spectrometry identified N-myristoylation of DIRAS3. All-atom molecular dynamic simulations predict DIRAS3 could adhere to the membrane through both termini, suggesting the NTE is involved in targeting and stabilizing DIRAS3 on the membrane by double anchoring. Overall, our results are consistent with DIRAS3's function as a tumor suppressor, whereby the membrane-bound DIRAS3 can effectively target PI3K and KRAS at the membrane.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Therapeutic Potential of Antiviral Peptides against the NS2B/NS3 Protease of Zika Virus

The NS2B/NS3 protease is highly conserved among various proteases of the Zika virus, making it an important therapeutic target for developing broad-spectrum antiviral drugs. The NS2B/NS3 protease is a crucial enzyme in the replication cycle of Zika virus and plays a significant role in viral maturation and assembly. Inhibiting the activity of this protease can potentially prevent viral replication, making it an attractive target for developing therapies against Zika virus infection. This work screens 429 antiviral peptides in comparison with substrate peptide against the NS2B/NS3 of Zika virus using molecular docking and molecular dynamics (MD) simulation. Based on the docking screening, MD simulation conducted for the best four peptides including AVP0239, AVP0642, AVP0660, and AVP2044, could be effective against NS2B/NS3. These results were compared with the control substrate peptide. Further analysis indicates that AVP0642 and AVP2044 are the most promising candidates. The interaction analysis showed that the catalytic site residues including His51, Asp75, Ser135 and other non-catalytic residues such as Asp129, Asp83, and Asp79 contribute substantial interactions. Hydrogen bonds (41%) and hydrophobic interactions (33%) are observed as the prominent non-covalent interaction prompting the peptide-protein complex formation. Furthermore, the structure-activity relationship (SAR) illustrates that positively charged (Lys, Arg) residues in the peptides dominate the interactions. This study provides the basis for developing novel peptide-based protease inhibitors for Zika virus.

The Architect of Neurotransmission in C. elegans : How FLP-3 Neuropeptides' Structures Direct their Function

Neuropeptides direct functions in the nervous, endocrine, and immune systems of all animals by altering the activity at neural synapses. A single neuropeptide gene can be post-translationally modified to create multiple active peptides. These individual active peptides can have unique functions and drive discrete binding partners. We have previously shown that specific peptides encoded by the C. elegans neuropeptide gene, flp- 3, have sex-specific roles in response to a pheromone released by hermaphrodite C. elegans, ascaroside #8 (ascr#8). Using structural predictions of select FLP-3 neuropeptides, we identify individual amino acids within specific neuropeptides that regulate specific behaviors suggesting structure-function relationships of neuropeptides in regulate sex-specific behaviors.

Folding-unfolding asymmetry and a RetroFold computational algorithm

We treat protein folding as molecular self-assembly, while unfolding is viewed as disassembly. Fracture is typically a much faster process than self-assembly. Self-assembly is often an exponentially decaying process, since energy relaxes due to dissipation, while fracture is a constant-rate process as the driving force is opposed by damping. Protein folding takes two orders of magnitude longer than unfolding. We suggest a mathematical transformation of variables, which makes it possible to view self-assembly as time-reversed disassembly, thus folding can be studied as reversed unfolding. We investigate the molecular dynamics modelling of folding and unfolding of the short Trp-cage protein. Folding time constitutes about 800 ns, while unfolding (denaturation) takes only about 5.0 ns and, therefore, fewer computational resources are needed for its simulation. This RetroFold approach can be used for the design of a novel computation algorithm, which, while approximate, is less time-consuming than traditional folding algorithms.

Deciphering anti-biofilm property of Arthrospira platensis-origin peptides against Staphylococcusaureus

Arthrospira platensis is a valuable natural health supplement consisting of various types of vitamins, dietary minerals, and antioxidants. Although different studies have been conducted to explore the hidden benefits of this bacterium, its antimicrobial property has been poorly understood. To decipher this important feature, here, we extended our recently introduced optimization algorithm (Trader) for aligning amino acid sequences associated with the antimicrobial peptides (AMPs) of Staphylococcus aureus and A.platensis. As a result, similar amino acid sequences were identified, and several candidate peptides were generated accordingly. The obtained peptides were then filtered based on their potential biochemical and biophysical properties, and their 3D structures were simulated based on homology modeling techniques. Next, to investigate how the generated peptides can interact with S. aureus proteins (i.e., heptameric state of the hly and homodimeric form of the arsB), molecular docking approaches were used. The results indicated that four peptides included better molecular interactions relative to the other generated ones in terms of the number/average length of hydrogen bonds and hydrophobic interactions. Based on the outcomes, it can be concluded that the antimicrobial property of A.platensis might be associated with its capability in disturbing the membrane of pathogens and their functions.

Molecular Docking, Anti-Biofilm & Antibacterial Activities and Therapeutic Index of mCM11 Peptide on Acinetobacter baumannii Strains

Despite the huge efforts of microbiologists, infectious diseases have yet remained one of the leading causes of death in humans, further highlighting the research priority for controlling opportunistic pathogens. Many researchers have used antibacterial peptides to solve the problem of antibiotic resistance. This research is thus conducted to investigate the antibacterial and anti-biofilm activity of a novel modified cecropin-melittin 11-peptide with improved therapeutic properties and lower side effects. After synthesis and purification of mCM11 (NH2-WRLFRRILRVL-NH2) by solid-phase synthesis and HPLC methods, respectively, the antibacterial and biofilm inhibitory activities were explored in vitro. TMHMM was used to confirm the reaction of mCM11 on the plasma membrane of the prokaryotic cells. The interaction between mCM11 on Acinetobacter baumannii strains was investigated by molecular docking using ClusPro2.0. Hemolysis and therapeutic indexes were also calculated to quantify the relative safety and adverse effects of mCM11. According to the results, mCM11 has a high inhibitory and lethal effect on A. baumannii strains due to its cationic properties and new specific sequence. Molecular docking revealed the release of a significant amount of energy when mCM11 binds to the surface of A. baumannii in an appropriate site. The findings indicated that mCM11 IC50 (4 μg/mL) lysed 2.78% of RBCs; moreover, 8 strains of Acinetobacter baumannii showed a favorable therapeutic index. The mCM11 exhibits strong antibacterial and antibiofilm activities against A. baumannii strains, suggesting its potential therapeutic role in infections caused by these strains. Similar to its impact on A. baumannii, mCM11 could be a suitable alternative to antibiotics in combat against antibiotic-resistant bacteria in the in vivo experiments.

Orthogonal threading-through-β-sheet design of lung cancer EGFR extracellular domain-derived peptidic mimotopes binding to anti-EGFR antibody

Human epidermal growth factor receptor (EGFR) has been established as a therapeutic target of lung cancer and other diverse tumors. The antibody drug Cetuximab has been developed to target the third subdomain III (TSDIII) of EGFR extracellular domain (ECD) by competitively inhibiting epidermal growth factor binding. In this study, we performed systematic investigation on the crystal complex structure of EGFR ECD domain with Cetuximab to create a residue importance profile for the TSDIII subdomain, based on which a number of U-shaped, double-stranded linear peptides were derived and cyclized to orthogonally thread through most hotspot residues and many responsible residues within the TSDIII β-sheet plane; they represent mimotopes of the key antibody-recognition site of TSDIII subdomain. Computational analyses revealed that these linear peptides cannot spontaneously fold to the desired conformation in free state due to their intrinsic flexibility. Cell-free assays confirmed that the stapling can considerably improve the binding affinity of linear peptides to Cetuximab by up to 18-fold. The cOrt1 [3-18] cyclic peptide was measured to have the highest affinity in all designed linear and cyclic peptides.

Explainable Deep Hypergraph Learning Modeling the Peptide Secondary Structure Prediction

Accurately predicting peptide secondary structures remains a challenging task due to the lack of discriminative information in short peptides. In this study, PHAT is proposed, a deep hypergraph learning framework for the prediction of peptide secondary structures and the exploration of downstream tasks. The framework includes a novel interpretable deep hypergraph multi-head attention network that uses residue-based reasoning for structure prediction. The algorithm can incorporate sequential semantic information from large-scale biological corpus and structural semantic information from multi-scale structural segmentation, leading to better accuracy and interpretability even with extremely short peptides. The interpretable models are able to highlight the reasoning of structural feature representations and the classification of secondary substructures. The importance of secondary structures in peptide tertiary structure reconstruction and downstream functional analysis is further demonstrated, highlighting the versatility of our models. To facilitate the use of the model, an online server is established which is accessible via http://inner.wei-group.net/PHAT/. The work is expected to assist in the design of functional peptides and contribute to the advancement of structural biology research.

Mini-αA-Crystallin Stifled Melittin-Induced Haemolysis and Lymphocyte Lysis

Melittin, the most potent pharmacological ingredient of honey bee venom, induces haemolysis, lymphocyte lysis, long-term pain, localised inflammation, and hyperalgesia. In this study, efforts were made to subdue the melittin’s ill effects using a chaperone peptide called ‘mini-αA-crystallin’ (MAC) derived from eye lens αA-crystallin. Haemolytic test on human red blood cells, percentage viability, and DNA diffusion assay on Human peripheral blood lymphocytes (HPBLs) were performed with melittin in the presence or absence of MAC. Propidium iodide and Annexin V-FITC dual staining were performed to analyse quantitative levels of necrotic and apoptotic induction by melittin in the presence or absence of MAC on HPBLs using a flow cytometer. A computational study to find out the interactions between MAC and melittin was undertaken by modelling the structure of MAC using a PEP-FOLD server. The result showed that MAC inhibited melittin-induced lysis in nucleated (lymphocytes) and enucleated (RBC) cells. Flow cytometric analysis revealed a substantial increase in the necrotic and late apoptotic cells after treating HPBLs with melittin (4 µg/ml) for 24 h. Treatment with MAC at a 2:1 molar ratio prevented HPBLs from developing melittin-induced necrosis and late apoptosis. In the docking study, hydrogen, van der Waals, π-π stacking, and salt bridges were observed between the MAC and melittin complex, confirming a strong interaction between them. The MAC-melittin complex was stable during molecular dynamics simulation. These findings may be beneficial in developing a medication for treating severe cases of honeybee stings.

Peptide deregulated in hypertrophic scar-1 alleviates hypertrophic scar fibrosis by targeting focal adhesion kinase and pyruvate kinase M2 and remodeling the metabolic landscape

Hypertrophic scarring is a fibrotic skin disease characterized by excessive deposition of collagens. Emerging evidence has suggested important roles for peptides in fibrosis-related diseases. Here, we demonstrate that a skin-derived endogenous peptide, peptide deregulated in hypertrophic scar-1 (PDHS1), with the sequence IATTTASAATAAAIGATPRAK, inhibits cell proliferation, promotes apoptosis, decreases the proportion of cells in S phase, and decreases collagen synthesis in hypertrophic scar fibroblasts. Additionally, treatment with PDHPS1 alleviates hypertrophic scarring in a rabbit ear model. PDHPS1 was found to bind to focal adhesion kinase (FAK) and to decrease its activity. PDHPS1 was also shown to bind to pyruvate kinase M2 (PKM2) and to decreased its expression. Smad2 phosphorylation is also inhibited by treatment with PDHPS1. Overexpression of FAK rescues the decreased expression of COL3A1 induced by PDHPS1 treatment. Targeted metabolomics revealed that PDHPS1 reprogramed metabolism that related to amino acid synthesis, leading to decreases of the key glycolysis intermediates glucose-6-phosphate and fructose-6-phosphate. These results demonstrated that the endogenous peptide PDHPS1 alleviates hypertrophic scar fibrosis in vitro and in vivo by targeting FAK and PKM2 and remodeling the metabolic landscape. Overall, treatment with PDHPS1 is a potential therapeutic strategy for hypertrophic scarring.

A Novel Peptide-Based Detection of SARS-CoV-2 Antibodies

The need for rapidly developed diagnostic tests has gained significant attention after the recent pandemic. Production of neutralizing antibodies for vaccine development or antibodies to be used in diagnostic tests usually require the usage of recombinant proteins representing the infectious agent. However, peptides that can mimic these recombinant proteins may be rapidly utilized, especially in emergencies such as the recent outbreak. Here, we report two peptides that mimic the receptor binding domain of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and investigate their binding behavior against the corresponding human immunoglobulin G and immunoglobulin M (IgG and IgM) antibodies in a clinical sample using a quartz crystal microbalance (QCM) sensor. These peptides were immobilized on a QCM sensor surface, and their binding behavior was studied against a clinical serum sample that was previously determined to be IgG and IgM-positive. It was determined that designed peptides bind to SARS-CoV-2 antibodies in a clinical sample. These peptides might be useful for the detection of SARS-CoV-2 antibodies using different methods such as enzyme-linked immunosorbent assay (ELISA) or lateral flow assays. A similar platform might prove to be useful for the detection and development of antibodies in other infections.

Structural Characterization, Functional Profiling, and Mechanism Study of Four Antimicrobial Peptides for Antibacterial and Anticancer Applications

Antimicrobial peptides (AMPs) are potent compounds for treating bacterial infection and cancer, drawing ever-increasing interest. However, the function and mechanism of most AMPs remain to be explored. In this research, we focused on investigating the antibacterial and anticancer activities of four AMPs (Dhvar4, Lasioglossin-III, Macropin 1, and Temporin La) and the possible corresponding mechanisms. All four AMPs are cationic α-helical with moderate hydrophobicity and high helicity. They have broad-spectrum antibacterial capacities, among which the antibacterial activities of Dhvar4 and Temporin La are not as effective as Lasioglossin-III and Macropin 1. Macropin 1 exhibited the highest antibacterial effect with a pretty low minimal inhibitory concentration (MIC) of 2-8 μM. Meanwhile, Lasioglossin-III exhibited the strongest anticancer activities, displaying the IC₅₀ of 26.36 μM for A549 and 7.75 μM for HepG2. Although Dhvar4 possessed the highest positive charge and entered the bacterial and animal cells in large amounts, it displayed the lowest bactericidal and anticancer activities which might be ascribed to its lowest hydrophobicity and thus the weakest cell membrane damage capability. It seems that the positive charge and cell internalization play a supporting rather than a determined role in antibacterial and anticancer activities of AMPs. All the four AMPs damaged the bacterial cell membrane with Macropin 1 damaging the cell membrane of Escherichia coli the most and Lasioglossin-III destroying the cell membrane of Staphylococcus aureus the worst. In addition, the animal cellular internalization of the four peptides was temperature-dependent and mainly mediated by caveolae-mediated endocytosis, and they were distributed in lysosomes once inside the cells. These findings expand our knowledge on the function and mechanism of AMPs, laying the fundamental theoretical basis for designing and engineering AMPs for infection and cancer treatment.

In silico approach to design a multi-epitopic vaccine candidate targeting the non-mutational immunogenic regions in envelope protein and surface glycoprotein of SARS-CoV-2

The novel corona virus (COVID-19) is a causative agent for severe acute respiratory syndrome (SARS-CoV-2) and responsible for the current human pandemic situation which has caused global social and economic commotion. The currently available vaccines use whole viruses whereas there is scope for peptide based vaccines. Thus, the global raise in statistics of this infection at an alarming rate evoked us to determine a novel and effective vaccine candidate against SARS-CoV-2. To find the potential vaccine candidate targets, immunoinformatics approaches were used to analyze the mutations in the envelope protein and surface glycoprotein and determine the conserved region; further specific T-cell epitopes VSLVKPSFY, SLVKPSFYV, RVKNLNSSR, SEETGTLIV, LVKPSFYVY, LTDEMIAQY, YLQPRTFLL, RLFRKSNLK, SPRRARSVA, AEIRASANL, TLLALHRSY, YSRVKNLNS and FELLHAPAT and B-cells epitopes TLAILTALRLCAYCCN and AGTITSGWTFGAGAAL were identified. The 3 D structure of epitope was predicted, refined and validated. The molecular docking analysis of multi-epitope vaccine candidates with TLR receptors, predicted effective binding. Overall, using bioinformatics approach this multi-epitopic target facilitates the proof of concept for SARS-CoV-2 conserved epitopic vaccine design.Communicated by Ramaswamy H. Sarma.

Large scale peptide screening against main protease of SARS CoV-2

The COVID-19 pandemic has been a public health emergency, with deadly forms constantly emerging around the world, highlighting the dire need for highly effective antiviral therapeutics. Peptide therapeutics show significant potential for this viral disease due to their efficiency, safety, and specificity. Here, two thousand seven hundred eight antibacterial peptides were screened computationally targeting the Main protease (Mpro) of SARS CoV-2. Six top-ranked peptides according to their binding scores, binding pose were investigated by molecular dynamics to explore the interaction and binding behavior of peptide-Mpro complexes. The structural and energetic characteristics of Mpro-DRAMP01760 and Mpro-DRAMP01808 complexes fluctuated less during a 250 ns MD simulation. In addition, three peptides (DRAMP01760, DRAMP01808, and DRAMP01342) bind strongly to Mpro protein, according to the free energy landscape and principal component analysis. Peptide helicity and secondary structure analysis are in agreement with our findings. Interaction analysis of protein-peptide complexes demonstrated that Mpro's residue CYS145, HIS41, PRO168, GLU166, GLN189, ASN142, MET49, and THR26 play significant contributions in peptide-protein attachment. Binding free energy analysis (MM-PBSA) demonstrated the energy profile of interacting residues of Mpro in peptide-Mpro complexes. To summarize, the peptides DRAMP01808 and DRAMP01760 may be highly Mpro specific, resulting disruption in a viral replication and transcription. The results of this research are expected to assist future research toward the development of antiviral peptide-based therapeutics for Covid-19 treatment.

Toxicological and Safety Pharmacological Profiling of the Anti-Infective and Anti-Inflammatory Peptide Pep19-2.5

Aspidasept (Pep19-2.5) and its derivative Pep19-4LF ("Aspidasept II") are anti-infective and anti-inflammatory synthetic polypeptides currently in development for application against a variety of moderate to severe bacterial infections that could lead to systemic inflammation, as in the case of severe sepsis and septic shock, as well as application to non-systemic diseases in the case of skin and soft tissue infections (SSTI). In the present study, Aspidasept and Aspidasept II and their part structures were analysed with respect to their toxic behavior in different established models against a variety of relevant cells, and in electrophysiological experiments targeting the hERG channel according to ICH S7B. Furthermore, the effects in mouse models of neurobiological behavior and the local lymph node according to OECD test guideline 429 were investigated, as well as a rat model of repeated dose toxicology according to ICH M3. The data provide conclusive information about potential toxic effects, thus specifying a therapeutic window for the application of the peptides. Therefore, these data allow us to define Aspidasept concentrations for their use in clinical studies as parenteral application.

Microbiome-derived antimicrobial peptides offer therapeutic solutions for the treatment of Pseudomonas aeruginosa infections

Microbiomes are rife for biotechnological exploitation, particularly the rumen microbiome, due to their complexicity and diversity. In this study, antimicrobial peptides (AMPs) from the rumen microbiome (Lynronne 1, 2, 3 and P15s) were assessed for their therapeutic potential against seven clinical strains of Pseudomonas aeruginosa. All AMPs exhibited antimicrobial activity against all strains, with minimum inhibitory concentrations (MICs) ranging from 4–512 µg/mL. Time-kill kinetics of all AMPs at 3× MIC values against strains PAO1 and LES431 showed complete kill within 10 min to 4 h, although P15s was not bactericidal against PAO1. All AMPs significantly inhibited biofilm formation by strains PAO1 and LES431, and induction of resistance assays showed no decrease in activity against these strains. AMP cytotoxicity against human lung cells was also minimal. In terms of mechanism of action, the AMPs showed affinity towards PAO1 and LES431 bacterial membrane lipids, efficiently permeabilising the P. aeruginosa membrane. Transcriptome and metabolome analysis revealed increased catalytic activity at the cell membrane and promotion of β-oxidation of fatty acids. Finally, tests performed with the Galleria mellonella infection model showed that Lynronne 1 and 2 were efficacious in vivo, with a 100% survival rate following treatment at 32 mg/kg and 128 mg/kg, respectively. This study illustrates the therapeutic potential of microbiome-derived AMPs against P. aeruginosa infections.

Development of a Multiepitope Vaccine Against SARS-CoV-2: Immunoinformatics Study

Background

Since the first appearance of SARS-CoV-2 in China in December 2019, the world witnessed the emergence of the SARS-CoV-2 outbreak. Due to the high transmissibility rate of the virus, there is an urgent need to design and develop vaccines against SARS-CoV-2 to prevent more cases affected by the virus.

Objective

A computational approach is proposed for vaccine design against the SARS-CoV-2 spike (S) protein, as the key target for neutralizing antibodies, and envelope (E) protein, which contains a conserved sequence feature.

Methods

We used previously reported epitopes of S protein detected experimentally and further identified a collection of predicted B-cell and major histocompatibility (MHC) class II–restricted T-cell epitopes derived from E proteins with an identical match to SARS-CoV-2 E protein.

Results

The in silico design of our candidate vaccine against the S and E proteins of SARS-CoV-2 demonstrated a high affinity to MHC class II molecules and effective results in immune response simulations.

Conclusions

Based on the results of this study, the multiepitope vaccine designed against the S and E proteins of SARS-CoV-2 may be considered as a new, safe, and efficient approach to combatting the COVID-19 pandemic.

In silico identification of two peptides with antibacterial activity against multidrug-resistant Staphylococcus aureus

Here we report two antimicrobial peptides (AMPs), HG2 and HG4 identified from a rumen microbiome metagenomic dataset, with activity against multidrug-resistant (MDR) bacteria, especially methicillin-resistant Staphylococcus aureus (MRSA) strains, a major hospital and community-acquired pathogen. We employed the classifier model design to analyse, visualise, and interpret AMP activities. This approach allowed in silico discrimination of promising lead AMP candidates for experimental evaluation. The lead AMPs, HG2 and HG4, are fast-acting and show anti-biofilm and anti-inflammatory activities in vitro and demonstrated little toxicity to human primary cell lines. The peptides were effective in vivo within a Galleria mellonella model of MRSA USA300 infection. In terms of mechanism of action, HG2 and HG4 appear to interact with the cytoplasmic membrane of target cells and may inhibit other cellular processes, whilst preferentially binding to bacterial lipids over human cell lipids. Therefore, these AMPs may offer additional therapeutic templates for MDR bacterial infections.

Anurans against SARS-CoV-2: A review of the potential antiviral action of anurans cutaneous peptides

At the end of 2019, in China, clinical signs and symptoms of unknown etiology have been reported in several patients whose sample sequencing revealed pneumonia caused by the SARS-CoV-2 virus. COVID-19 is a disease triggered by this virus, and in 2020, the World Health Organization declared it a pandemic. Since then, efforts have been made to find effective therapeutic agents against this disease. Identifying novel natural antiviral drugs can be an alternative to treatment. For this reason, antimicrobial peptides secreted by anurans' skin have gained attention for showing a promissory antiviral effect. Hence, this review aimed to elucidate how and which peptides secreted by anurans' skin can be considered therapeutic agents to treat or prevent human viral infectious diseases. Through a literature review, we attempted to identify potential antiviral frogs' peptides to combat COVID-19. As a result, the Magainin-1 and -2 peptides, from the Magainin family, the Dermaseptin-S9, from the Dermaseptin family, and Caerin 1.6 and 1.10, from the Caerin family, are molecules that already showed antiviral effects against SARS-CoV-2 in silico. In addition to these peptides, this review suggests that future studies should use other families that already have antiviral action against other viruses, such as Brevinins, Maculatins, Esculentins, Temporins, and Urumins. To apply these peptides as therapeutic agents, experimental studies with peptides already tested in silico and new studies with other families not tested yet should be considered.

Topological bio-scaling analysis as a universal measure of protein folding

Scaling relationships for polymeric molecules establish power law dependencies between the number of molecular segments and linear dimensions, such as the radius of gyration. They also establish spatial topological properties of the chains, such as their dimensionality. In the spatial domain, power exponents α = 1 (linear stretched molecule), α = 0.5 (the ideal chain) and α = 0.333 (compact globule) are significant. During folding, the molecule undergoes the transition from the one-dimensional linear to the three-dimensional globular state within a very short time. However, intermediate states with fractional dimensions can be stabilized by modifying the solubility (e.g. by changing the solution temperature). Topological properties, such as dimension, correlate with the interaction energy, and thus by tuning the solubility one can control molecular interaction. We investigate these correlations using the example of a well-studied short model of Trp-cage protein. The radius of gyration is used to estimate the fractal dimension of the chain at different stages of folding. It is expected that the same principle is applicable to much larger molecules and that topological (dimensional) characteristics can provide insights into molecular folding and interactions.

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches

An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was reported to be caused by a novel coronavirus which has infected approximately 220 million people worldwide with a death toll of 4.5 million as of September 2021. This study is focused on finding potential vaccine candidates and designing an in-silico subunit multi-epitope vaccine candidates using a unique computational pipeline, integrating reverse vaccinology, molecular docking and simulation methods. A protein named spike protein of SARS-CoV-2 with the GenBank ID QHD43416.1 was shortlisted as a potential vaccine candidate and was examined for presence of B-cell and T-cell epitopes. We also investigated antigenicity and interaction with distinct polymorphic alleles of the epitopes. High ranking epitopes such as DLCFTNVY (B cell epitope), KIADYNKL (MHC Class-I) and VKNKCVNFN (MHC class-II) were shortlisted for subsequent analysis. Digestion analysis verified the safety and stability of the shortlisted peptides. Docking study reported a strong binding of proposed peptides with HLA-A*02 and HLA-B7 alleles. We used standard methods to construct vaccine model and this construct was evaluated further for its antigenicity, physicochemical properties, 2D and 3D structure prediction and validation. Further, molecular docking followed by molecular dynamics simulation was performed to evaluate the binding affinity and stability of TLR-4 and vaccine complex. Finally, the vaccine construct was reverse transcribed and adapted for E. coli strain K 12 prior to the insertion within the pET-28-a (+) vector for determining translational and microbial expression followed by conservancy analysis. Also, six multi-epitope subunit vaccines were constructed using different strategies containing immunogenic epitopes, appropriate adjuvants and linker sequences. We propose that our vaccine constructs can be used for downstream investigations using in-vitro and in-vivo studies to design effective and safe vaccine against different strains of COVID-19.

New PEPTIR-2.0 Peptide Designed for Use as Recognition Element in Electrochemical Biosensors with Improved Specificity towards E. coli O157:H7

The detection of pathogens through alternative methodologies based on electrochemical biosensors is being studied. These devices exhibit remarkable properties, such as simplicity, specificity, and high sensitivity in monitoring pathogens. However, it is necessary to continue conducting studies that adequately improve these characteristics, especially the recognition molecule. This work aims to design and evaluate a new peptide, named PEPTIR-2.0, as a recognition molecule in electrochemical biosensors to detect E. coli O157:H7 in water. PEPTIR-2.0 was obtained from modifications of the PEPTIR-1.0 peptide sequence, which was previously reported and exhibited excellent properties for detecting and quantifying this pathogenic microorganism. PEPTIR-1.0 is a peptide analogous to the TIR (Translocated Intimin Receptor) protein capable of interacting with the Intimin outer membrane. The basis of this study was to obtain, by using bioinformatics tools, a molecule analogous to PEPTIR-1.0 that maintains its three-dimensional structure but increases the hydrophobic interactions between it and Intimin, since these intermolecular forces are the predominant ones. The designed PEPTIR-2.0 peptide was immobilized on screen-printed electrodes modified with gold nanoparticles. The detection capacity of E. coli O157:H7 in water was evaluated using electrochemical impedance spectroscopy in the presence of other microorganisms, such as P. aeruginosa, S. aureus, and non-pathogenic E. coli. The results showed that PEPTIR-2.0 confers remarkable specificity to the biosensor towards detecting E. coli, even higher than PEPTIR-1.0.

A Generalized Attraction-Repulsion Potential and Revisited Fragment Library Improves PEP-FOLD Peptide Structure Prediction

Fast and accurate structure prediction is essential to the study of peptide function, molecular targets, and interactions and has been the subject of considerable efforts in the past decade. In this work, we present improvements to the popular simplified PEP-FOLD technique for small peptide structure prediction. PEP-FOLD originality is threefold: (i) it uses a predetermined structural alphabet, (ii) it uses a sequential algorithm to reconstruct the tridimensional structures of these peptides in a discrete space using a fragment library, and (iii) it assesses the energy of these structures using a coarse-grained representation in which all of the backbone atoms but the α-hydrogen are present, and the side chain corresponds to a unique bead. In former versions of PEP-FOLD, a van der Waals formulation was used for non-bonded interactions, with each side chain being associated with a fixed radius. Here, we explore the relevance of using instead a generalized formulation in which not only the optimal distance of interaction and the energy at this distance are parameters but also the distance at which the potential is zero. This allows each side chain to be associated with a different radius and potential energy shape, depending on its interaction partner, and in principle to make more effective the coarse-grained representation. In addition, the new PEP-FOLD version is associated with an updated library of fragments. We show that these modifications lead to important improvements for many of the problematic targets identified with the former PEP-FOLD version while maintaining already correct predictions. The improvement is in terms of both model ranking and model accuracy. We also compare the PEP-FOLD enhanced version to state-of-the-art techniques for both peptide and structure predictions: APPTest, RaptorX, and AlphaFold2. We find that the new predictions are superior, in particular with respect to the prediction of small β-targets, to those of APPTest and RaptorX and bring, with its original approach, additional understanding on folded structures, even when less precise than AlphaFold2. With their strong physical influence, the revised structural library and coarse-grained potential offer, however, the means for a deeper understanding of the nature of folding and open a solid basis for studying flexibility and other dynamical properties not accessible to IA structure prediction approaches.

Development of peptide vaccine candidate using highly antigenic PE-PGRS family proteins to stimulate the host immune response against Mycobacterium tuberculosis H37Rv: an immuno-informatics approach

Tuberculosis (TB) is a fast spreading; transmissible disease caused by the Mycobacterium tuberculosis (M. tuberculosis). M. tuberculosis has a high death rate in its endemic regions due to a lack of appropriate treatment and preventative measures. We have used a vaccinomics strategy to create an effective multi-epitope vaccine against M. tuberculosis. The antigenic proteins with the highest antigenicity were utilised to predict cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes. CTL and HTL epitopes were covered in 99.97% of the population. Seven epitopes each of CTL, HTL, and LBL were ultimately selected and utilised to develop a multi-epitope vaccine. A vaccine design was developed by combining these epitopes with suitable linkers and LprG adjuvant. The vaccine chimera was revealed to be highly immunogenic, non-allergenic, and non-toxic. To ensure a better expression within the Escherichia coli K12 (E. coli K12) host system, codon adaptation and in silico cloning were accomplished. Following that, various validation studies were conducted, including molecular docking, molecular dynamics simulation, and immunological simulation, all of which indicated that the designed vaccine would be stable in the biological environment and effective against M. tuberculosis infection. The immune simulation revealed higher levels of T-cell and B-cell activity, which corresponded to the actual immune response. Exposure simulations were repeated several times, resulting in increased clonal selection and faster antigen clearance. These results suggest that, if proposed vaccine chimera would test both in-vitro and in-vivo, it could be a viable treatment and preventive strategy for TB.Communicated by Ramaswamy H. Sarma.

Superior Binding of Proteins on a Silica Surface: Physical Insight into the Synergetic Contribution of Polyhistidine and a Silica-Binding Peptide

Controllable protein attachment onto solid interfaces is essential for the functionality of proteins with broad applications. Silica-binding peptides (SBPs) have emerged as an important tool enabling convenient binding of proteins onto a silica surface. Surprisingly, we found that removal of polyhistidines, a common tag for protein purification, dramatically decrease the binding affinity of a SBP-tagged nanobody onto a silica surface. We hypothesized that polyhistidines and SBPs can be combined to enhance affinity. Through a series of purposely designed SBPs, we identified that the relative orientation of amino acids is a key factor affecting the surface binding strength. One re-engineered SBP, SBP4, exhibits a 4000-fold improvement compared to the original sequence. Guided by physical insights, the work provides a simple strategy that can dramatically improve affinity between a SBP and a silica surface, promising a new way for controllable immobilization of proteins, as demonstrated using nanobodies.

A transcytotic transport mechanism across the tympanic membrane

Drug treatments for middle ear diseases are currently delivered systemically, or locally after opening the impermeable tympanic membrane (TM). We previously used bacteriophage display to discover novel peptides that are actively transported across the intact TM, with a variety of transport rates. Peptide structures were analyzed for evidence regarding the mechanism for this unexpected transport, which was then tested by the application of chemical inhibitors. Primary sequences indicated that trans-TM peptides share one of two amino acid motifs. Secondary structures revealed that linear configurations associate with higher transport rates than coiled structures. Tertiary analysis indicated that the shared sequence motifs are prominently displayed at the free ends of rapidly transported peptide phage. The shared motifs were evaluated for similarity to known motifs. The highest probability matches were for protein motifs involved in transmembrane transport and exosomes. Overall, structural findings suggest that the shared motifs represent binding sequences. They also implicate transcytosis, a polarized cell transport mechanism consisting of endocytosis, transcellular transport, and exocytosis. Inhibitor studies indicated that macropinocytosis, retrograde transport through Golgi and exocytosis participate in transport across the TM, consistent with transcytosis. This process can be harnessed to noninvasively deliver therapeutics to the middle ear.

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.