A Comprehensive Review on Current Advances in Peptide Drug Development and Design

Rational design of a helical peptide inhibitor targeting c-Myb–KIX interaction

The transcription factor c-Myb promotes the proliferation of hematopoietic cells by interacting with the KIX domain of CREB-binding protein; however, its aberrant expression causes leukemia. Therefore, inhibitors of the c-Myb–KIX interaction are potentially useful as antitumor drugs. Since the intrinsically disordered transactivation domain (TAD) of c-Myb binds KIX via a conformational selection mechanism where helix formation precedes binding, stabilizing the helical structure of c-Myb TAD is expected to increase the KIX-binding affinity. Here, to develop an inhibitor of the c-Myb–KIX interaction, we designed mutants of the c-Myb TAD peptide fragment where the helical structure is stabilized, based on theoretical predictions using AGADIR. Three of the four initially designed peptides each had a different Lys-to-Arg substitution on the helix surface opposite the KIX-binding interface. Furthermore, the triple mutant with three Lys-to-Arg substitutions, named RRR, showed a high helical propensity and achieved three-fold higher affinity to KIX than the wild-type TAD with a dissociation constant of 80 nM. Moreover, the RRR inhibitor efficiently competed out the c-Myb–KIX interaction. These results suggest that stabilizing the helical structure based on theoretical predictions, especially by conservative Lys-to-Arg substitutions, is a simple and useful strategy for designing helical peptide inhibitors of protein–protein interactions.

Marine Depsipeptide Nobilamide I Inhibits Cancer Cell Motility and Tumorigenicity via Suppressing Epithelial-Mesenchymal Transition and MMP2/9 Expression

A cyclic depsipeptide, nobilamide I (1), along with the known peptide A-3302-B/TL-119 (2), was isolated from the saline cultivation of the marine-derived bacterium Saccharomonospora sp., strain CNQ-490. The planar structure of 1 was elucidated by interpretation of 1D and 2D NMR and MS spectroscopic data. The absolute configurations of the amino acids in 1 were assigned by using the C₃ Marfey's analysis and comparing them with those of 2 based on their biosynthetic pathways. Nobilamide I (1) decreased cell motility by inhibiting epithelial-mesenchymal transition markers in A549 (lung cancer), AGS (gastric cancer), and Caco2 (colorectal cancer) cell lines. In addition, 1 modulated the expression of the matrix metalloproteinase (MMP) family (MMP2 and MMP9) in the three cell lines.

Electrochemistry for the Chemoselective Modification of Peptides and Proteins

Although electrochemical strategies for small-molecule synthesis are flourishing, this technology has yet to be fully exploited for the mild and chemoselective modification of peptides and proteins. With the growing number of diverse peptide natural products being identified and the emergence of modified proteins as therapeutic and diagnostic agents, methods for electrochemical modification stand as alluring prospects for harnessing the reactivity of polypeptides to build molecular complexity. As a mild and inherently tunable reaction platform, electrochemistry is arguably well-suited to overcome the chemo- and regioselectivity issues which limit existing bioconjugation strategies. This Perspective will showcase recently developed electrochemical approaches to peptide and protein modification. The article also highlights the wealth of untapped opportunities for the production of homogeneously modified biomolecules, with an eye toward realizing the enormous potential of electrochemistry for chemoselective bioconjugation chemistry.

Insights into post-translational modification enzymes from RiPPs: A toolkit for applications in peptide synthesis

The increasing length and complexity of peptide drug candidates foster the development of novel strategies for their manufacture, which should include sustainable and efficient technologies. In this context, including enzymatic catalysis in the production of peptide molecules has gained interest. Here, several enzymes from ribosomally synthesized and post-translationally modified peptides biosynthesis pathways are reviewed, with attention to their capacity to introduce stability-promoting structural features on peptides, providing an initial framework towards their use in therapeutic peptide production processes.

Harnessing protein folding neural networks for peptide-protein docking

Highly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been developed for the in silico folding of protein monomers, AlphaFold2 also enables quick and accurate modeling of peptide-protein interactions. Our simple implementation of AlphaFold2 generates peptide-protein complex models without requiring multiple sequence alignment information for the peptide partner, and can handle binding-induced conformational changes of the receptor. We explore what AlphaFold2 has memorized and learned, and describe specific examples that highlight differences compared to state-of-the-art peptide docking protocol PIPER-FlexPepDock. These results show that AlphaFold2 holds great promise for providing structural insight into a wide range of peptide-protein complexes, serving as a starting point for the detailed characterization and manipulation of these interactions.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Computational Evolution Protocol for Peptide Design

Computational peptide design is useful for therapeutics, diagnostics, and vaccine development. To select the most promising peptide candidates, the key is describing accurately the peptide-target interactions at the molecular level. We here review a computational peptide design protocol whose key feature is the use of all-atom explicit solvent molecular dynamics for describing the different peptide-target complexes explored during the optimization. We describe the milestones behind the development of this protocol, which is now implemented in an open-source code called PARCE. We provide a basic tutorial to run the code for an antibody fragment design example. Finally, we describe three additional applications of the method to design peptides for different targets, illustrating the broad scope of the proposed approach.

Anticancer peptide Q7 suppresses the growth and migration of human endometrial cancer by inhibiting DHCR24 expression and modulating the AKT-mediated pathway

Endometrial cancer is one of the most common malignancy affecting women in developed countries. Resection uterus or lesion area is usually the first option for a simple and efficient therapy. Therefore, it is necessary to find a new therapeutic drug to reduce surgery areas to preserve fertility. Anticancer peptides (ACP) are bioactive amino acids with lower toxicity and higher specificity than chemical drugs. This study is to address an ACP, herein named Q7, which could downregulate 24-Dehydrocholesterol Reductase (DHCR24) to disrupt lipid rafts formation, and sequentially affect the AKT signal pathway of HEC-1-A cells to suppress their tumorigenicity such as proliferation and migration. Moreover, lipo-PEI-PEG-complex (LPPC) was used to enhance Q7 anticancer activity in vitro and efficiently show its effects on HEC-1-A cells. Furthermore, LPPC-Q7 exhibited a synergistic effect in combination with doxorubicin or paclitaxel. To summarize, Q7 was firstly proved to exhibit an anticancer effect on endometrial cancer cells and combined with LPPC efficiently improved the cytotoxicity of Q7.

Glycopeptide antibiotic drug stability in aqueous solution

Glycopeptide antimicrobials are a class of naturally occurring or semi-synthetic glycosylated products that have shown antibacterial activity against gram-positive organisms by inhibiting cell-wall synthesis. In most cases, these drugs are prepared in dry powder (lyophilized) form due to chemical and physical instability in aqueous solution; however, from an economic and practical point of view, liquid formulations are preferred. Researchers have recently found ways to formulate some glycopeptide antibiotic therapeutic drugs in aqueous solution at refrigerated or room temperature. Chemical degradation can be significantly slowed by formulating them at a defined pH with specific buffers, avoiding oxygen reactive species, and minimizing solvent exposure. Sugars, amino acids, polyols, and surfactants can reduce physical degradation by restricting glycopeptide mobility and reducing solvent interaction. This review focuses on recent studies on glycopeptide antibiotic drug stability in aqueous solution. It is organized into three sections: (i) glycopeptide antibiotic instability due to chemical and physical degradation, (ii) strategies to improve glycopeptide antibiotic stability in aqueous solution, and (iii) a survey of glycopeptide antibiotic drugs currently available in the market and their stability based on published literature and patents. Antimicrobial resistance deaths are expected to increase by 2050, making heat-stable glycopeptides in aqueous solution an important treatment option for multidrug-resistant and extensively drug-resistant pathogens. In conclusion, it should be possible to formulate heat stable glycopeptide drugs in aqueous solution by understanding the degradation mechanisms of this class of therapeutic drugs in greater detail, making them easily accessible to developing countries with a lack of cold chains.

Antitumor Effects of Scorpion Peptide Smp43 through Mitochondrial Dysfunction and Membrane Disruption on Hepatocellular Carcinoma

Smp43, a cationic antimicrobial peptide identified from the venom gland of the Egyptian scorpion Scorpio maurus palmatus, shows cytotoxicity toward hepatoma cell line HepG2 by membrane disruption. However, its underlying detailed mechanisms still remain to be further clarified. In the present study, we evaluated the cellular internalization of Smp43 and explored its effects on cell viability, cell cycle, apoptosis, autophagy, necrosis, and factor expression related to these cellular processes in human HepG2. Smp43 was found to suppress the growth of HepG2, Huh7, and human primary hepatocellular carcinoma cells while showing low toxicity to normal LO2 cells. Furthermore, Smp43 could interact with the cell membrane and be internalized into HepG2 cells via endocytosis and pore formation, which caused a ROS production increase, mitochondrial membrane potential decline, cytoskeleton disorganization, dysregulation of cyclin expression, mitochondrial apoptotic pathway activation, and alteration of MAPK as well as PI3K/Akt/mTOR signaling pathways. Finally, Smp43 showed effective antitumor protection in the HepG2 xenograft mice model. Overall, these findings indicate that Smp43 significantly exerts antitumor effects via induction of apoptosis, autophagy, necrosis, and cell cycle arrest due to its induction of mitochondrial dysfunction and membrane disruption. This discovery will extend the antitumor mechanisms of antimicrobial peptides and contribute to the development of antitumor agents against hepatocellular carcinoma.

Lessons from a Single Amino Acid Substitution: Anticancer and Antibacterial Properties of Two Phospholipase A2-Derived Peptides

The membrane-active nature of phospholipase A₂-derived peptides makes them potential candidates for antineoplastic and antibacterial therapies. Two short 13-mer C-terminal fragments taken from snake venom Lys49-PLA₂ toxins (p-AppK and p-Acl), differing by a leucine/phenylalanine substitution, were synthesized and their bioactivity was evaluated. Their capacity to interfere with the survival of Gram-positive and Gram-negative bacteria as well as with solid and liquid tumors was assessed in vitro. Toxicity to red blood cells was investigated via in silico and in vitro techniques. The mode of action was mainly studied by molecular dynamics simulations and membrane permeabilization assays. Briefly, both peptides have dual activity, i.e., they act against both bacteria, including multidrug-resistant strains and tumor cells. All tested bacteria were susceptible to both peptides, Pseudomonas aeruginosa being the most affected. RAMOS, K562, NB4, and CEM cells were the main leukemic targets of the peptides. In general, p-Acl showed more significant activity, suggesting that phenylalanine confers advantages to the antibacterial and antitumor mechanism, particularly for osteosarcoma lines (HOS and MG63). Peptide-based treatment increased the uptake of a DNA-intercalating dye by bacteria, suggesting membrane damage. Indeed, p-AppK and p-Acl did not disrupt erythrocyte membranes, in agreement with in silico predictions. The latter revealed that the peptides deform the membrane and increase its permeability by facilitating solvent penetration. This phenomenon is expected to catalyze the permeation of solutes that otherwise could not cross the hydrophobic membrane core. In conclusion, the present study highlights the role of a single amino acid substitution present in natural sequences towards the development of dual-action agents. In other words, dissecting and fine-tuning biomembrane remodeling proteins, such as snake venom phospholipase A₂ isoforms, is again demonstrated as a valuable source of therapeutic peptides.

In-Silico Design of a Novel Tridecapeptide Targeting Spike Protein of SARS-CoV-2 Variants of Concern

Several mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased the transmission and mortality rate of coronavirus disease-19 (COVID-19) across the globe. Although many vaccines have been developed, a large proportion of the global population remains at high risk of infection. The current study aims to develop an antiviral peptide capable of inhibiting the interaction of SARS-CoV-2 spike protein and its six major variants with the host cell angiotensin-converting enzyme 2 (ACE2) receptor. An in-silico approach was employed to design a therapeutic peptide inhibitor against the receptor-binding domain (RBD) of the spike (S) protein of SARS-CoV-2 and its variants (B.1.1.7, B.1.351, P.1, B.1.617.1, B.1.617.2 and B.1.617.3). The binding specificity and affinity of our designed peptide inhibitor Mod13AApi (YADKYQKQYKDAY) with wild-type S-RBD and its six variants was confirmed by molecular docking using the HPEPDOCK tool, whereas complex stability was determined by the MD simulation study. The physicochemical and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of inhibitory peptides were determined using the ExPASy tool and pkCSM server. The docking results and its properties from our in-silico analysis present the Mod13AApi, a promising peptide for the rapid development of anti-coronavirus peptide-based antiviral therapy. Blockage of the binding of the spike protein of SARS-CoV-2 variants with ACE2 in the presence of the therapeutic peptide may prevent deadly SARS-CoV-2 variants entry into host cells. Therefore, the designed inhibitory peptide can be utilized as a promising therapeutic strategy to combat COVID-19, as evident from this in-silico study.

MultiPep: a hierarchical deep learning approach for multi-label classification of peptide bioactivities

Peptide-based therapeutics are here to stay and will prosper in the future. A key step in identifying novel peptide-drugs is the determination of their bioactivities. Recent advances in peptidomics screening approaches hold promise as a strategy for identifying novel drug targets. However, these screenings typically generate an immense number of peptides and tools for ranking these peptides prior to planning functional studies are warranted. Whereas a couple of tools in the literature predict multiple classes, these are constructed using multiple binary classifiers. We here aimed to use an innovative deep learning approach to generate an improved peptide bioactivity classifier with capacity of distinguishing between multiple classes. We present MultiPep: a deep learning multi-label classifier that assigns peptides to zero or more of 20 bioactivity classes. We train and test MultiPep on data from several publically available databases. The same data are used for a hierarchical clustering, whose dendrogram shapes the architecture of MultiPep. We test a new loss function that combines a customized version of Matthews correlation coefficient with binary cross entropy (BCE), and show that this is better than using class-weighted BCE as loss function. Further, we show that MultiPep surpasses state-of-the-art peptide bioactivity classifiers and that it predicts known and novel bioactivities of FDA-approved therapeutic peptides. In conclusion, we present innovative machine learning techniques used to produce a peptide prediction tool to aid peptide-based therapy development and hypothesis generation.

Repositioning of Fungal-based Peptides as Modulators of Angiotensin-converting Enzyme-related Carboxypeptidase, SARS-coronavirus HR2 Domain, and Coronavirus Disease 2019 Main Protease

Background and Objectives

Angiotensin-converting enzyme-related carboxypeptidase, SARS-Coronavirus HR2 Domain, and COVID-19 main protease are essential for the cellular entry and replication of coronavirus in the host. This study investigated the putative inhibitory action of peptides form medicinal mushrooms, namely Pseudoplectania nigrella, Russula paludosa, and Clitocybe sinopica, towards selected proteins through computational studies.

Materials and Methods

The respective physicochemical properties of selected peptides were predicted using ProtParam tool, while the binding modes and binding free energy of selected peptides toward proteins were computed through HawkDock server. The structural flexibility and stability of docked protein-peptide complexes were assessed through iMODS server.

Results

The peptides showed an optimum binding afinity with the molecular targets; plectasin from P. nigrella showed the highest binding free energy compared to peptides from R. paludosa and C. sinopica. Besides, molecular dynamic simulations showed all fungal-based peptides could influence the flexibility and stability of selected proteins.

Conclusion

The study revealed fungal-based peptides could be explored as functional modulators of essential proteins that are involved in the cellular entry of coronavirus.

finDr: A web server for in silico D-peptide ligand identification

In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.

Advanced protein drugs and formulations

For a long time, proteins were a subset of molecules rarely applied as therapeutically active molecules. Some of the first applications of proteins as drugs have been insulin and vaccines for supply a physiological deficiency and the prevention of diseases, respectively. Nowadays, proteins have increased their range of application, not only as drugs but also as drug delivery systems to be administered by different routes. Due to their nature, proteins show different behavior while the conditions of the environment are modified. For this reason, it has been necessary to study their behavior for predicting the correct manufacturing, storing, or combination with other possible molecules in a formulation or into the body. The application of techniques for predicting the behavior of proteins in different environments has led to associate this type of behavior into the body with the occurrence of diseases such as celiac disease or Alzheimer's disease. Thus, this work shows an overview of the main types of proteins applied as active therapeutically molecules, proteins-based drug delivery systems, and techniques for predicting their stability into the storing container and the body.

A host-directed macrocyclic peptide therapeutic for MDR gram negative bacterial infections

The emergence of infections by carbapenem resistant Enterobacteriaceae (CRE) pathogens has created an urgent public health threat, as carbapenems are among the drugs of last resort for infections caused by a growing fraction of multi-drug resistant (MDR) bacteria. There is global consensus that new preventive and therapeutic strategies are urgently needed to combat the growing problem of MDR bacterial infections. Here, we report on the efficacy of a novel macrocyclic peptide, minimized theta-defensin (MTD)-12813 in CRE sepsis. MTD12813 is a theta-defensin inspired cyclic peptide that is highly effective against CRE pathogens K. pneumoniae and E. coli in vivo. In mouse septicemia models, single dose administration of MTD12813 significantly enhanced survival by promoting rapid host-mediated bacterial clearance and by modulating pathologic cytokine responses, restoring immune homeostasis, and preventing lethal septic shock. The peptide lacks direct antibacterial activity in the presence of mouse serum or in peritoneal fluid, further evidence for its indirect antibacterial mode of action. MTD12813 is highly stable in biological matrices, resistant to bacterial proteases, and nontoxic to mice at dose levels 100 times the therapeutic dose level, properties which support further development of the peptide as a first in class anti-infective therapeutic.

The Power of Universal Contextualized Protein Embeddings in Cross-species Protein Function Prediction

Computationally annotating proteins with a molecular function is a difficult problem that is made even harder due to the limited amount of available labeled protein training data. Unsupervised protein embeddings partly circumvent this limitation by learning a universal protein representation from many unlabeled sequences. Such embeddings incorporate contextual information of amino acids, thereby modeling the underlying principles of protein sequences insensitive to the context of species. We used an existing pre-trained protein embedding method and subjected its molecular function prediction performance to detailed characterization, first to advance the understanding of protein language models, and second to determine areas of improvement. Then, we applied the model in a transfer learning task by training a function predictor based on the embeddings of annotated protein sequences of one training species and making predictions on the proteins of several test species with varying evolutionary distance. We show that this approach successfully generalizes knowledge about protein function from one eukaryotic species to various other species, outperforming both an alignment-based and a supervised-learning-based baseline. This implies that such a method could be effective for molecular function prediction in inadequately annotated species from understudied taxonomic kingdoms.

The legumain McPAL1 from Momordica cochinchinensis is a highly stable Asx-specific splicing enzyme

Legumains, also known as asparaginyl endopeptidases (AEPs), cleave peptide bonds after Asn/Asp (Asx) residues. In plants, certain legumains also have ligase activity that catalyzes biosynthesis of Asx-containing cyclic peptides. An example is the biosynthesis of MCoTI-I/II, a squash family-derived cyclic trypsin inhibitor, which involves splicing to remove the N-terminal prodomain and then N-to-C-terminal cyclization of the mature domain. To identify plant legumains responsible for the maturation of these cyclic peptides, we have isolated and characterized a legumain involved in splicing, McPAL1, from Momordica cochinchinensis (Cucurbitaceae) seeds. Functional studies show that recombinantly expressed McPAL1 displays a pH-dependent, trimodal enzymatic profile. At pH 4 to 6, McPAL1 selectively catalyzed Asp-ligation and Asn-cleavage, but at pH 6.5 to 8, Asn-ligation predominated. With peptide substrates containing N-terminal Asn and C-terminal Asp, such as is found in precursors of MCoTI-I/II, McPAL1 mediates proteolysis at the Asn site and then ligation at the Asp site at pH 5 to 6. Also, McPAL1 is an unusually stable legumain that is tolerant of heat and high pH. Together, our results support that McPAL1 is a splicing legumain at acidic pH that can mediate biosynthesis of MCoTI-I/II. We purport that the high thermal and pH stability of McPAL1 could have applications for protein engineering.

Broad-Spectrum Antiviral Peptides and Polymers

As the human cost of the pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still being witnessed worldwide, the development of broad-spectrum antiviral agents against emerging and re-emerging viruses is seen as a necessity to hamper the spread of infections. Various targets during the viral life-cycle can be considered to inhibit viral infection, from viral attachment to viral fusion or replication. Macromolecules represent a particularly attractive class of therapeutics due to their multivalency and versatility. Although several antiviral macromolecules hold great promise in clinical applications, the emergence of resistance after prolonged exposure urges the need for improved solutions. In the present article, the recent advancement in the discovery of antiviral peptides and polymers with diverse structural features and antiviral mechanisms is reviewed. Future perspectives, such as, the development of virucidal peptides/polymers and their coatings against SARS-CoV-2 infection, standardization of antiviral testing protocols, and use of artificial intelligence or machine learning as a tool to accelerate the discovery of antiviral macromolecules, are discussed.

Subcellular Dynamic Immunopatterning of Cytosolic Protein Complexes on Microstructured Polymer Substrates

Analysis of protein–protein interactions in living cells by protein micropatterning is currently limited to the spatial arrangement of transmembrane proteins and their corresponding downstream molecules. Here, we present a robust and straightforward method for dynamic immunopatterning of cytosolic protein complexes by use of an artificial transmembrane bait construct in combination with microstructured antibody arrays on cyclic olefin polymer substrates. As a proof, the method was used to characterize Grb2-mediated signaling pathways downstream of the epidermal growth factor receptor (EGFR). Ternary protein complexes (Shc1:Grb2:SOS1 and Grb2:Gab1:PI3K) were identified, and we found that EGFR downstream signaling is based on constitutively bound (Grb2:SOS1 and Grb2:Gab1) as well as on agonist-dependent protein associations with transient interaction properties (Grb2:Shc1 and Grb2:PI3K). Spatiotemporal analysis further revealed significant differences in stability and exchange kinetics of protein interactions. Furthermore, we could show that this approach is well suited to study the efficacy and specificity of SH2 and SH3 protein domain inhibitors in a live cell context. Altogether, this method represents a significant enhancement of quantitative subcellular micropatterning approaches as an alternative to standard biochemical analyses.

Guiding Chemically Synthesized Peptide Drug Lead Optimization by Derisking Mast Cell Degranulation-Related Toxicities of a NaV1.7 Peptide Inhibitor

Studies have shown that some peptides and small molecules can induce non IgE-mediated anaphylactoid reactions through mast cell activation. Upon activation, mast cells degranulate and release vasoactive and proinflammatory mediators, from cytoplasmic granules into the extracellular environment which can induce a cascade of severe adverse reactions. This study describes a lead optimization strategy to select NaV1.7 inhibitor peptides that minimize acute mast cell degranulation (MCD) toxicities. Various in vitro, in vivo, and PKPD models were used to screen candidates and guide peptide chemical modifications to mitigate this risk. Anesthetized rats dosed with peptides demonstrated treatment-related decreases in blood pressure and increases in plasma histamine concentrations which were reversible with a mast cell stabilizer, supporting the MCD mechanism. In vitro testing in rat mast cells with NaV1.7 peptides demonstrated a concentration-dependent increase in histamine. Pharmacodynamic modeling facilitated establishing an in vitro to in vivo correlation for histamine as a biomarker for blood pressure decline via the MCD mechanism. These models enabled assessment of structure-activity relationship (SAR) to identify substructures that contribute to peptide-mediated MCD. Peptides with hydrophobic and cationic characteristics were determined to have an elevated risk for MCD, which could be reduced or avoided by incorporating anionic residues into the protoxin II scaffold. Our analyses support that in vitro MCD assessment in combination with PKPD modeling can guide SAR to improve peptide lead optimization and ensure an acceptable early in vivo tolerability profile with reduced resources, cycle time, and animal use.

Peptide Regulation of Gene Expression: A Systematic Review

Peptides are characterized by their wide range of biological activity: they regulate functions of the endocrine, nervous, and immune systems. The mechanism of such action of peptides involves their ability to regulate gene expression and protein synthesis in plants, microorganisms, insects, birds, rodents, primates, and humans. Short peptides, consisting of 2-7 amino acid residues, can penetrate into the nuclei and nucleoli of cells and interact with the nucleosome, the histone proteins, and both single- and double-stranded DNA. DNA-peptide interactions, including sequence recognition in gene promoters, are important for template-directed synthetic reactions, replication, transcription, and reparation. Peptides can regulate the status of DNA methylation, which is an epigenetic mechanism for the activation or repression of genes in both the normal condition, as well as in cases of pathology and senescence. In this context, one can assume that short peptides were evolutionarily among the first signaling molecules that regulated the reactions of template-directed syntheses. This situation enhances the prospects of developing effective and safe immunoregulatory, neuroprotective, antimicrobial, antiviral, and other drugs based on short peptides.

Antiseptic 9-Meric Peptide with Potency against Carbapenem-Resistant Acinetobacter baumannii Infection

Carbapenem-resistant A. baumannii (CRAB) infection can cause acute host reactions that lead to high-fatality sepsis, making it important to develop new therapeutic options. Previously, we developed a short 9-meric peptide, Pro9-3D, with significant antibacterial and cytotoxic effects. In this study, we attempted to produce safer peptide antibiotics against CRAB by reversing the parent sequence to generate R-Pro9-3 and R-Pro9-3D. Among the tested peptides, R-Pro9-3D had the most rapid and effective antibacterial activity against Gram-negative bacteria, particularly clinical CRAB isolates. Analyses of antimicrobial mechanisms based on lipopolysaccharide (LPS)-neutralization, LPS binding, and membrane depolarization, as well as SEM ultrastructural investigations, revealed that R-Pro9-3D binds strongly to LPS and impairs the membrane integrity of CRAB by effectively permeabilizing its outer membrane. R-Pro9-3D was also less cytotoxic and had better proteolytic stability than Pro9-3D and killed biofilm forming CRAB. As an LPS-neutralizing peptide, R-Pro9-3D effectively reduced LPS-induced pro-inflammatory cytokine levels in RAW 264.7 cells. The antiseptic abilities of R-Pro9-3D were also investigated using a mouse model of CRAB-induced sepsis, which revealed that R-Pro9-3D reduced multiple organ damage and attenuated systemic infection by acting as an antibacterial and immunosuppressive agent. Thus, R-Pro9-3D displays potential as a novel antiseptic peptide for treating Gram-negative CRAB infections.

In Silico Design of Chemically Modified Cell-Penetrating Peptides

In the past few decades, a large number of cell-penetrating peptides (CPPs) have been discovered. These CPPs have a wide range of applications including drug delivery vehicles. Numerous in silico tools have been developed over the years to design and predict the cell-penetrating peptides that contain natural amino acids. The majority of natural cell-penetrating peptides have several limitations including stability, immunogenicity as well as got entrapped in the cell's endosomes. The chemical modification is commonly used to most of these limitations. An in silico tool called CellPPDMod have been developed by our group to predict cell-penetration potential of chemically modified peptides. This chapter is dedicated for designing therapeutically important cell-penetrating peptides using CellPPDMod ( http://webs.iiitd.edu.in/raghava/cellppdmod/ ).

The Use of Peptides in the Treatment of Fragile X Syndrome: Challenges and Opportunities

Fragile X Syndrome (FXS) is the most frequent cause of inherited intellectual disabilities and autism spectrum disorders, characterized by cognitive deficits and autistic behaviors. The silencing of the Fmr1 gene and consequent lack of FMRP protein, is the major contribution to FXS pathophysiology. FMRP is an RNA binding protein involved in the maturation and plasticity of synapses and its absence culminates in a range of morphological, synaptic and behavioral phenotypes. Currently, there are no approved medications for the treatment of FXS, with the approaches under study being fairly specific and unsatisfying in human trials. Here we propose peptides/peptidomimetics as candidates in the pharmacotherapy of FXS; in the last years this class of molecules has catalyzed the attention of pharmaceutical research, being highly selective and well-tolerated. Thanks to their ability to target protein-protein interactions (PPIs), they are already being tested for a wide range of diseases, including cancer, diabetes, inflammation, Alzheimer's disease, but this approach has never been applied to FXS. As FXS is at the forefront of efforts to develop new drugs and approaches, we discuss opportunities, challenges and potential issues of peptides/peptidomimetics in FXS drug design and development.

Thiol Isomerases Orchestrate Thrombosis and Hemostasis

Significance: Since protein disulfide isomerase (PDI) was first described in 1963, researchers have shown conclusively that PDI and sibling proteins are quintessential for thrombus formation. PDI, endoplasmic reticulum protein (ERp)5, ERp57, and ERp72 are released from platelets and vascular cells and interact with integrin αIIbβ3 on the outer surface of platelets. Recent Advances: At the cell surface they influence protein folding and function, propagating thrombosis and maintaining hemostasis. TMX1, which is a transmembrane thiol isomerase, is the first family member shown to negatively regulate platelets. Targets of thiol isomerases have been identified, including integrin α2β1, Von Willebrand Factor, GpIbα, nicotinamide adenine dinucleotide phosphate oxidase (Nox)-1, Nox-2, and tissue factor, all of which are pro-thrombotic, and several of which are on the cell surface. In spite of this, PDI can paradoxically catalyze the delivery of nitric oxide to platelets, which decrease thrombus formation. Critical Issues: Although the overall effect of PDI is to positively regulate platelet activation, it is still unclear how thiol isomerases function in pro-thrombotic states, such as obesity, diabetes, and cancer. In parallel, there has been a surge in the development of novel thiol isomerase inhibitors, which display selectivity, potency and modulate thrombosis and hemostasis. The availability of selective thiol isomerase inhibitors has culminated in clinical trials, with promising outcomes for the prevention of cancer-associated thrombosis. Future Directions: Altogether, thiol isomerases are perceived as an orchestrating force that regulates thrombus development. In the current review, we will explore the history of PDI in cardiovascular biology, detail known mechanisms of action, and summarize known thiol isomerase inhibitors.

Molecular Docking of SP40 Peptide towards Cellular Receptors for Enterovirus 71 (EV-A71)

Enterovirus 71 (EV-A71) is one of the predominant etiological agents of hand, foot and mouth disease (HMFD), which can cause severe central nervous system infections in young children. There is no clinically approved vaccine or antiviral agent against HFMD. The SP40 peptide, derived from the VP1 capsid of EV-A71, was reported to be a promising antiviral peptide that targeted the host receptor(s) involved in viral attachment or entry. So far, the mechanism of action of SP40 peptide is unknown. In this study, interactions between ten reported cell receptors of EV-A71 and the antiviral SP40 peptide were evaluated through molecular docking simulations, followed by in vitro receptor blocking with specific antibodies. The preferable binding region of each receptor to SP40 was predicted by global docking using HPEPDOCK and the cell receptor-SP40 peptide complexes were refined using FlexPepDock. Local molecular docking using GOLD (Genetic Optimization for Ligand Docking) showed that the SP40 peptide had the highest binding score to nucleolin followed by annexin A2, SCARB2 and human tryptophanyl-tRNA synthetase. The average GoldScore for 5 top-scoring models of human cyclophilin, fibronectin, human galectin, DC-SIGN and vimentin were almost similar. Analysis of the nucleolin-SP40 peptide complex showed that SP40 peptide binds to the RNA binding domains (RBDs) of nucleolin. Furthermore, receptor blocking by specific monoclonal antibody was performed for seven cell receptors of EV-A71 and the results showed that the blocking of nucleolin by anti-nucleolin alone conferred a 93% reduction in viral infectivity. Maximum viral inhibition (99.5%) occurred when SCARB2 was concurrently blocked with anti-SCARB2 and the SP40 peptide. This is the first report to reveal the mechanism of action of SP40 peptide in silico through molecular docking analysis. This study provides information on the possible binding site of SP40 peptide to EV-A71 cellular receptors. Such information could be useful to further validate the interaction of the SP40 peptide with nucleolin by site-directed mutagenesis of the nucleolin binding site.

Novel Peptide Therapeutic Approaches for Cancer Treatment

Peptides are increasingly being developed for use as therapeutics to treat many ailments, including cancer. Therapeutic peptides have the advantages of target specificity and low toxicity. The anticancer effects of a peptide can be the direct result of the peptide binding its intended target, or the peptide may be conjugated to a chemotherapy drug or radionuclide and used to target the agent to cancer cells. Peptides can be targeted to proteins on the cell surface, where the peptide–protein interaction can initiate internalization of the complex, or the peptide can be designed to directly cross the cell membrane. Peptides can induce cell death by numerous mechanisms including membrane disruption and subsequent necrosis, apoptosis, tumor angiogenesis inhibition, immune regulation, disruption of cell signaling pathways, cell cycle regulation, DNA repair pathways, or cell death pathways. Although using peptides as therapeutics has many advantages, peptides have the disadvantage of being easily degraded by proteases once administered and, depending on the mode of administration, often have difficulty being adsorbed into the blood stream. In this review, we discuss strategies recently developed to overcome these obstacles of peptide delivery and bioavailability. In addition, we present many examples of peptides developed to fight cancer.

Insights on peptide topology in the computational design of protein ligands: the example of lysozyme binding peptides

Herein, we compared the ability of linear and cyclic peptides generated in silico to target different protein sites: internal pockets and solvent-exposed sites. We selected human lysozyme (HuL) as a model target protein combined with the computational evolution of linear and cyclic peptides. The sequence evolution of these peptides was based on the PARCE algorithm. The generated peptides were screened based on their aqueous solubility and HuL binding affinity. The latter was evaluated by means of scoring functions and atomistic molecular dynamics (MD) trajectories in water, which allowed prediction of the structural features of the protein-peptide complexes. The computational results demonstrated that cyclic peptides constitute the optimal choice for solvent exposed sites, while both linear and cyclic peptides are capable of targeting the HuL pocket effectively. The most promising binders found in silico were investigated experimentally by surface plasmon resonance (SPR), nuclear magnetic resonance (NMR), and electrospray ionization mass spectrometry (ESI-MS) techniques. All tested peptides displayed dissociation constants in the micromolar range, as assessed by SPR; however, both NMR and ESI-MS suggested multiple binding modes, at least for the pocket binding peptides. A detailed NMR analysis confirmed that both linear and cyclic pocket peptides correctly target the binding site they were designed for.

The emergence of the C-H functionalization strategy in medicinal chemistry and drug discovery

Owing to the market competitiveness and urgent societal need, an optimum speed of drug discovery is an important criterion for successful implementation. Despite the rapid ascent of artificial intelligence and computational and bioanalytical techniques to accelerate drug discovery in big pharma, organic synthesis of privileged scaffolds predicted in silico for in vitro and in vivo studies is still considered as the rate-limiting step. C-H activation is the latest technology added into an organic chemist's toolbox for the rapid construction and late-stage modification of functional molecules to achieve the desired chemical and physical properties. Particularly, elimination of prefunctionalization steps, exceptional functional group tolerance, complexity-to-diversity oriented synthesis, and late-stage functionalization of privileged medicinal scaffolds expand the chemical space. It has immense potential for the rapid synthesis of a library of molecules, structural modification to achieve the required pharmacological properties such as absorption, distribution, metabolism, excretion, toxicology (ADMET) and attachment of chemical reporters for proteome profiling, metabolite synthesis, etc. for preclinical studies. Although heterocycle synthesis, late-stage drug modification, ¹⁸F labelling, methylation, etc. via C-H functionalization have been reviewed from the synthetic standpoint, a general overview of these protocols from medicinal and drug discovery aspects has not been reviewed. In this feature article, we will discuss the recent trends of C-H activation methodologies such as synthesis of medicinal scaffolds through C-H activation/annulation cascade; C-H arylation for sp²-sp² and sp²-sp³ cross-coupling; C-H borylation/silylation to introduce a functional linchpin for further manipulation; C-H amination for N-heterocycles and hydrogen bond acceptors; C-H fluorination/fluoroalkylation to tune polarity and lipophilicity; C-H methylation: methyl magic in drug discovery; peptide modification and macrocyclization for therapeutics and biologics; fluorescent labelling and radiolabelling for bioimaging; bioconjugation for chemical biology studies; drug-metabolite synthesis for biodistribution and excretion studies; late-stage diversification of drug-molecules to increase efficacy and safety; cutting-edge DNA encoded library synthesis and improved synthesis of drug molecules via C-H activation in medicinal chemistry and drug discovery.

Tumor vasculature-targeting nanomedicines

Uncontrolled tumor growth and subsequent distant metastasis are highly dependent on an adequate nutrient supply from tumor blood vessels, which have relatively different pathophysiological characteristics from those of normal vasculature. Obviously, strategies targeting tumor vasculature, such as anti-angiogenic drugs and vascular disrupting agents, are attractive methods for cancer therapy. However, the off-target effects and high dose administration of these drug regimens critically restrict their clinical applications. In recent years, nanomedicines focused on tumor vasculature have been shown to be superior to traditional therapeutic methods and do not induce side effects. This review will first highlight the recent development of tumor vasculature-targeting nanomedicines from the following four aspects: 1) angiogenesis-inhibiting nanomedicines (AINs); 2) vasculature-disrupting nanomedicines (VDNs); 3) vasculature infarction nanomedicines (VINs); and 4) vasculature-regulating nanomedicines (VRNs). Furthermore, the design principles, limitations, and future directions are also discussed. STATEMENT OF SIGNIFICANCE: Based on the essential roles of tumor blood vessels, the therapeutic strategies targeting tumor vasculature have exhibited good clinical therapeutic outcomes. However, poor patient adherence to free drug administration limits their clinical usage. Nanomedicines have great potential to overcome the abovementioned obstacle. This review summarizes the tumor-vasculature targeting nanomedicines from four aspects: 1) angiogenesis-inhibiting nanomedicines (AINs); 2) vasculature-disrupting nanomedicines (VDNs); 3) vasculature infarction nanomedicines (VINs); and 4) vasculature regulating nanomedicines (VRNs). In addition, this review provides perspectives on this research field.

Discovery, Optimization, and Clinical Application of Natural Antimicrobial Peptides

Antimicrobial peptides (AMPs) are widespread in multicellular organisms. These structurally diverse molecules are produced as the first line of defense against pathogens such as bacteria, viruses, fungi, and parasites. Also known as host defense peptides in higher eukaryotic organisms, AMPs display immunomodulatory and anticancer activities. During the last 30 years, technological advances have boosted the research on antimicrobial peptides, which have also attracted great interest as an alternative to tackling the antimicrobial resistance scenario mainly provoked by some bacterial and fungal pathogens. However, the introduction of natural AMPs in clinical trials faces challenges such as proteolytic digestion, short half-lives, and cytotoxicity upon systemic and oral application. Therefore, some strategies have been implemented to improve the properties of AMPs aiming to be used as effective therapeutic agents. In the present review, we summarize the discovery path of AMPs, focusing on preclinical development, recent advances in chemical optimization and peptide delivery systems, and their introduction into the market.

Peptide-Based Inhibitors for SARS-CoV-2 and SARS-CoV

The COVID-19 (coronavirus disease) global pandemic, caused by the spread of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus, currently has limited treatment options which include vaccines, anti-virals, and repurposed therapeutics. With their high specificity, tunability, and biocompatibility, small molecules like peptides are positioned to act as key players in combating SARS-CoV-2, and can be readily modified to match viral mutation rate. A recent expansion of the understanding of the viral structure and entry mechanisms has led to the proliferation of therapeutic viral entry inhibitors. In this comprehensive review, inhibitors of SARS and SARS-CoV-2 are investigated and discussed based on therapeutic design, inhibitory mechanistic approaches, and common targets. Peptide therapeutics are highlighted, which have demonstrated in vitro or in vivo efficacy, discuss advantages of peptide therapeutics, and common strategies in identifying targets for viral inhibition.

Systematic Development of Peptide Inhibitors Targeting the CXCL12/HMGB1 Interaction

During inflammatory reactions, the production and release of chemotactic factors guide the recruitment of selective leukocyte subpopulations. The alarmin HMGB1 and the chemokine CXCL12, both released in the microenvironment, can form a heterocomplex, which exclusively acts on the chemokine receptor CXCR4, enhancing cell migration, and in some pathological conditions such as rheumatoid arthritis exacerbates the immune response. An excessive cell influx at the inflammatory site can be diminished by disrupting the heterocomplex. Here, we report the computationally driven identification of the first peptide (HBP08) binding HMGB1 and selectively inhibiting the activity of the CXCL12/HMGB1 heterocomplex. Furthermore, HBP08 binds HMGB1 with the highest affinity reported so far (K_d of 0.8 ± 0.4 μM). The identification of this peptide represents an important step toward the development of innovative pharmacological tools for the treatment of severe chronic inflammatory conditions characterized by an uncontrolled immune response.

A deep-learning framework for multi-level peptide-protein interaction prediction

Peptide-protein interactions are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. Recently, a number of computational methods have been developed to predict peptide-protein interactions. However, most of the existing prediction approaches heavily depend on high-resolution structure data. Here, we present a deep learning framework for multi-level peptide-protein interaction prediction, called CAMP, including binary peptide-protein interaction prediction and corresponding peptide binding residue identification. Comprehensive evaluation demonstrated that CAMP can successfully capture the binary interactions between peptides and proteins and identify the binding residues along the peptides involved in the interactions. In addition, CAMP outperformed other state-of-the-art methods on binary peptide-protein interaction prediction. CAMP can serve as a useful tool in peptide-protein interaction prediction and identification of important binding residues in the peptides, which can thus facilitate the peptide drug discovery process.

Delivery of Various Cargos into Cancer Cells and Tissues via Cell-Penetrating Peptides: A Review of the Last Decade

Cell-penetrating peptides (CPPs), also known as protein transduction domains, are a class of diverse amino acid sequences with the ability to cross cellular membranes. CPPs can deliver several bioactive cargos, including proteins, peptides, nucleic acids and chemotherapeutics, into cells. Ever since their discovery, synthetic and natural CPPs have been utilized in therapeutics delivery, gene editing and cell imaging in fundamental research and clinical experiments. Over the years, CPPs have gained significant attention due to their low cytotoxicity and high transduction efficacy. In the last decade, multiple investigations demonstrated the potential of CPPs as carriers for the delivery of therapeutics to treat various types of cancer. Besides their remarkable efficacy owing to fast and efficient delivery, a crucial benefit of CPP-based cancer treatments is delivering anticancer agents selectively, rather than mediating toxicities toward normal tissues. To obtain a higher therapeutic index and to improve cell and tissue selectivity, CPP-cargo constructions can also be complexed with other agents such as nanocarriers and liposomes to obtain encouraging outcomes. This review summarizes various types of CPPs conjugated to anticancer cargos. Furthermore, we present a brief history of CPP utilization as delivery systems for anticancer agents in the last decade and evaluate several reports on the applications of CPPs in basic research and preclinical studies.

Peptide Platform as a Powerful Tool in the Fight against COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a global pandemic causing over 195 million infections and more than 4 million fatalities as of July 2021.To date, it has been demonstrated that a number of mutations in the spike glycoprotein (S protein) of SARS-CoV-2 variants of concern abrogate or reduce the neutralization potency of several therapeutic antibodies and vaccine-elicited antibodies. Therefore, the development of additional vaccine platforms with improved supply and logistic profile remains a pressing need. In this work, we have validated the applicability of a peptide-based strategy focused on a preventive as well as a therapeutic purpose. On the basis of the involvement of the dipeptidyl peptidase 4 (DPP4), in addition to the angiotensin converting enzyme 2 (ACE2) receptor in the mechanism of virus entry, we analyzed peptides bearing DPP4 sequences by protein-protein docking and assessed their ability to block pseudovirus infection in vitro. In parallel, we have selected and synthetized peptide sequences located within the highly conserved receptor-binding domain (RBD) of the S protein, and we found that RBD-based vaccines could better promote elicitation of high titers of neutralizing antibodies specific against the regions of interest, as confirmed by immunoinformatic methodologies and in vivo studies. These findings unveil a key antigenic site targeted by broadly neutralizing antibodies and pave the way to the design of pan-coronavirus vaccines.

Peptide-Assisted Nucleic Acid Delivery Systems on the Rise

Concerns associated with nanocarriers' therapeutic efficacy and side effects have led to the development of strategies to advance them into targeted and responsive delivery systems. Owing to their bioactivity and biocompatibility, peptides play a key role in these strategies and, thus, have been extensively studied in nanomedicine. Peptide-based nanocarriers, in particular, have burgeoned with advances in purely peptidic structures and in combinations of peptides, both native and modified, with polymers, lipids, and inorganic nanoparticles. In this review, we summarize advances on peptides promoting gene delivery systems. The efficacy of nucleic acid therapies largely depends on cell internalization and the delivery to subcellular organelles. Hence, the review focuses on nanocarriers where peptides are pivotal in ferrying nucleic acids to their site of action, with a special emphasis on peptides that assist anionic, water-soluble nucleic acids in crossing the membrane barriers they encounter on their way to efficient function. In a second part, we address how peptides advance nanoassembly delivery tools, such that they navigate delivery barriers and release their nucleic acid cargo at specific sites in a controlled fashion.

Contribution of the Commensal Microflora to the Immunological Homeostasis and the Importance of Immune-Related Drug Development for Clinical Applications

Not long ago, self-reactive immune activity was considered as pathological trait. A paradigm shift has now led to the recognition of autoimmune processes as part of natural maintenance of molecular homeostasis. The immune system is assigned further roles beneath the defense against pathogenic organisms. Regarding the humoral immune system, the investigation of natural autoantibodies that are frequently found in healthy individuals has led to further hypotheses involving natural autoimmunity in other processes as the clearing of cellular debris or decrease in inflammatory processes. However, their role and origin have not been entirely clarified, but accumulating evidence links their formation to immune reactions against the gut microbiome. Antibodies targeting highly conserved proteins of the commensal microflora are suggested to show self-reactive properties, following the paradigm of the molecular mimicry. Here, we discuss recent findings, which demonstrate potential links of the commensal microflora to the immunological homeostasis and highlight the possible implications for various diseases. Furthermore, specific components of the immune system, especially antibodies, have become a focus of attention for the medical management of various diseases and provide attractive treatment options in the future. Nevertheless, the development and optimization of such macromolecules still represents a very time-consuming task, shifting the need to more medical agents with simple structural properties and low manufacturing costs. Synthesizing only the biologically active sites of antibodies has become of great interest for the pharmaceutical industry and offers a wide range of therapeutic application areas as it will be discussed in the present review article.

Rational design of thioamide peptides as selective inhibitors of cysteine protease cathepsin L

Aberrant levels of cathepsin L (Cts L), a ubiquitously expressed endosomal cysteine protease, have been implicated in many diseases such as cancer and diabetes. Significantly, Cts L has been identified as a potential target for the treatment of COVID-19 due to its recently unveiled critical role in SARS-CoV-2 entry into the host cells. However, there are currently no clinically approved specific inhibitors of Cts L, as it is often challenging to obtain specificity against the many highly homologous cathepsin family cysteine proteases. Peptide-based agents are often promising protease inhibitors as they offer high selectivity and potency, but unfortunately are subject to degradation in vivo. Thioamide substitution, a single-atom O-to-S modification in the peptide backbone, has been shown to improve the proteolytic stability of peptides addressing this issue. Utilizing this approach, we demonstrate herein that good peptidyl substrates can be converted into sub-micromolar inhibitors of Cts L by a single thioamide substitution in the peptide backbone. We have designed and scanned several thioamide stabilized peptide scaffolds, in which one peptide, RS 1A, was stabilized against proteolysis by all five cathepsins (Cts L, Cts V, Cts K, Cts S, and Cts B) while inhibiting Cts L with >25-fold specificity against the other cathepsins. We further showed that this stabilized RS 1A peptide could inhibit Cts L in human liver carcinoma lysates (IC50 = 19 μM). Our study demonstrates that one can rationally design a stabilized, specific peptidyl protease inhibitor by strategic placement of a thioamide and reaffirms the place of this single-atom modification in the toolbox of peptide-based rational drug design.

Recent Applications of Retro-Inverso Peptides

Natural and de novo designed peptides are gaining an ever-growing interest as drugs against several diseases. Their use is however limited by the intrinsic low bioavailability and poor stability. To overcome these issues retro-inverso analogues have been investigated for decades as more stable surrogates of peptides composed of natural amino acids. Retro-inverso peptides possess reversed sequences and chirality compared to the parent molecules maintaining at the same time an identical array of side chains and in some cases similar structure. The inverted chirality renders them less prone to degradation by endogenous proteases conferring enhanced half-lives and an increased potential as new drugs. However, given their general incapability to adopt the 3D structure of the parent peptides their application should be careful evaluated and investigated case by case. Here, we review the application of retro-inverso peptides in anticancer therapies, in immunology, in neurodegenerative diseases, and as antimicrobials, analyzing pros and cons of this interesting subclass of molecules.

Affinity-Directed Dynamics of Host-Guest Motifs for Pharmacokinetic Modulation via Supramolecular PEGylation

Proteins are an impactful class of therapeutics but can exhibit suboptimal therapeutic performance, arising from poor control over the timescale of clearance. Covalent PEGylation is one established strategy to extend circulation time but often at the cost of reduced activity and increased immunogenicity. Supramolecular PEGylation may afford similar benefits without necessitating that the protein be permanently modified with a polymer. Here, we show that insulin pharmacokinetics can be modulated by tuning the affinity-directed dynamics of a host-guest motif used to non-covalently endow insulin with a poly(ethylene glycol) (PEG) chain. When administered subcutaneously, supramolecular PEGylation with higher binding affinities extends the time of total insulin exposure systemically. Pharmacokinetic modeling reveals that the extension in the duration of exposure arises specifically from decreased absorption from the subcutaneous depot governed directly by the affinity and dynamics of host-guest exchange. The lifetime of the supramolecular interaction thus dictates the rate of absorption, with negligible impact attributed to association of the PEG upon rapid dilution of the supramolecular complex in circulation. This modular approach to supramolecular PEGylation offers a powerful tool to tune protein pharmacokinetics in response to the needs of different disease applications.

Inhibition of cancer-cell migration by tetraspanin CD9-binding peptide

A CD9-binding peptide (RSHRLRLH), screened from EWI-2, was characterized, and its effect on cellular migration and invasion was evaluated. As CD9 protein is overexpressed in cancer cells and plays an important role in cellular migration, the CD9-binding peptide preferentially inhibited the migration of cancer cells. Unlike conventional antiproliferative drugs, this CD9-binding peptide is promising as a novel precision antimigratory agent for cancer therapeutics.

In vitro antiviral activity of peptide-rich extracts from seven Nigerian plants against three non-polio enterovirus species C serotypes

Background

As frequent viral outbreaks continue to pose threat to public health, the unavailability of antiviral drugs and challenges associated with vaccine development underscore the need for antiviral drugs discovery in emergent moments (endemic or pandemic). Plants in response to microbial and pest attacks are able to produce defence molecules such as antimicrobial peptides as components of their innate immunity, which can be explored for viral therapeutics.

Methods

In this study, partially purified peptide-rich fraction (P-PPf) were obtained from aqueous extracts of seven plants by reverse-phase solid-phase extraction and cysteine-rich peptides detected by a modified TLC method. The peptide-enriched fractions and the aqueous (crude polar) were screened for antiviral effect against three non-polio enterovirus species C members using cytopathic effect reduction assay.

Results

In this study, peptide fraction obtained from Euphorbia hirta leaf showed most potent antiviral effect against Coxsackievirus A13, Coxsackievirus A20, and Enterovirus C99 (EV-C99) with IC₅₀ < 2.0 µg/mL and selective index ≥ 81. EV-C99 was susceptible to all partially purified peptide fractions except Allamanda blanchetii leaf.

Conclusion

These findings establish the antiviral potentials of plants antimicrobial peptides and provides evidence for the anti-infective use of E. hirta in ethnomedicine. This study provides basis for further scientific investigation geared towards the isolation, characterization and mechanistic pharmacological study of the detected cysteine-rich peptides.

How can artificial intelligence be used for peptidomics?

INTRODUCTION

Peptidomics is an emerging field of omics sciences using advanced isolation, analysis, and computational techniques that enable qualitative and quantitative analyses of various peptides in biological samples. Peptides can act as useful biomarkers and as therapeutic molecules for diseases.

AREAS COVERED

The use of therapeutic peptides can be predicted quickly and efficiently using data-driven computational methods, particularly artificial intelligence (AI) approach. Various AI approaches are useful for peptide-based drug discovery, such as support vector machine, random forest, extremely randomized trees, and other more recently developed deep learning methods. AI methods are relatively new to the development of peptide-based therapies, but these techniques already become essential tools in protein science by dissecting novel therapeutic peptides and their functions (Figure 1).[Figure: see text].

EXPERT OPINION

Researchers have shown that AI models can facilitate the development of peptidomics and selective peptide therapies in the field of peptide science. Biopeptide prediction is important for the discovery and development of successful peptide-based drugs. Due to their ability to predict therapeutic roles based on sequence details, many AI-dependent prediction tools have been developed (Figure 1).

Exploring peptide studies related to SARS-CoV to accelerate the development of novel therapeutic and prophylactic solutions against COVID-19

Recent advances in peptide research revolutionized therapeutic discoveries for various infectious diseases. In view of the ongoing threat of the COVID-19 pandemic, there is an urgent need to develop potential therapeutic options. Intense and accomplishing research is being carried out to develop broad-spectrum vaccines and treatment options for corona viruses, due to the risk of recurrent infection by the existing strains or pandemic outbreaks by new mutant strains. Developing a novel medicine is costly and time consuming, which increases the value of repurposing existing therapies. Since, SARS-CoV-2 shares significant genomic homology with SARS-CoV, we have summarized various peptides identified against SARS-CoV using in silico and molecular studies and also the peptides effective against SARS-CoV-2. Dissecting the molecular mechanisms underlying viral infection could yield fundamental insights in the discovery of new antiviral agents, targeting viral proteins or host factors. We postulate that these peptides can serve as effective components for therapeutic options against SARS-CoV-2, supporting clinical scientists globally in selectively identifying and testing the therapeutic and prophylactic agents for COVID-19 treatment. In addition, we also summarized the latest updates on peptide therapeutics against SARS-CoV-2.