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

Prediction of Aggregation of Biologically-Active Peptides with the UNRES Coarse-Grained Model

The UNited RESidue (UNRES) model of polypeptide chains was applied to study the association of 20 peptides with sizes ranging from 6 to 32 amino-acid residues. Twelve of those were potentially aggregating hexa- or heptapeptides excised from larger proteins, while the remaining eight contained potentially aggregating sequences, functionalized by attaching larger ends rich in charged residues. For 13 peptides, the experimental data of aggregation were used. The remaining seven were synthesized, and their properties were measured in this work. Multiplexed replica-exchange simulations of eight-chain systems were conducted at 12 temperatures from 260 to 370 K at concentrations from 0.421 to 5.78 mM, corresponding to the experimental conditions. The temperature profiles of the fractions of monomers and octamers showed a clear transition corresponding to aggregate dissociation. Low simulated transition temperatures were obtained for the peptides, which did not precipitate after incubation, as well as for the H-GNNQQNY-NH2 prion-protein fragment, which forms small fibrils. A substantial amount of inter-strand β-sheets was found in most of the systems. The results suggest that UNRES simulations can be used to assess peptide aggregation except for glutamine- and asparagine-rich peptides, for which a revision of the UNRES sidechain-sidechain interaction potentials appears necessary.

Non-competitive fluorescence polarization immunosensing for CD9 detection using a peptide as a tracer

This paper is the first report of a non-competitive fluorescence polarization immunoassay (NC-FPIA) using a peptide as a tracer. The NC-FPIA can easily and quickly quantify the target after simply mixing them together. This feature is desirable for point-of-need applications such as clinical diagnostics, infectious disease screening, on-site analysis for food safety, etc. In this study, the NC-FPIA was applied to detect CD9, which is one of the exosome markers. We succeeded in detecting not only CD9 but also CD9 expressing exosomes derived from HeLa cells. This method can be applied to various targets if a tracer for the target can be prepared, and expectations are high for its future uses.

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

Therapeutic Potential of Marine Peptides in Prostate Cancer: Mechanistic Insights

Prostate cancer (PCa) is the leading cause of cancer death in men, and its treatment is commonly associated with severe adverse effects. Thus, new treatment modalities are required. In this context, natural compounds have been widely explored for their anti-PCa properties. Aquatic organisms contain numerous potential medications. Anticancer peptides are less toxic to normal cells and provide an efficacious treatment approach via multiple mechanisms, including altered cell viability, apoptosis, cell migration/invasion, suppression of angiogenesis and microtubule balance disturbances. This review sheds light on marine peptides as efficacious and safe therapeutic agents for PCa.

Photocatalytic Reductive Olefin Hydrodifluoroalkylation Enabled by Tertiary Amine Reductants Compatible with Complex Systems

Noncanonical amino acids (NCAAs) are imperative to many facets of chemistry and biology. Herein, we report a method for the reductive hydrodifluoroalkylation of olefins that utilizes triethylamine base as the terminal reductant. The alkene acceptors include a range of electronically diverse alkenes, chief among them, dehydroalanine in variously protected forms, which provides access to synthetically relevant NCAA scaffolds under mild and general reaction conditions. We have demonstrated that a chiral auxiliary may be incorporated to provide diastereocontrol for pro-stereogenic substrates. Mechanistically motivated experiments provide some insight into the reaction mechanism, which supports a terminal step involving proton transfer for electron-poor olefins, while H atom transfer assisted by a thiol cocatalyst may complete the catalytic cycle for electron-rich olefins. The protocol is found to be compatible with additions to complex molecules, including the natural product thiostrepton.

Structural analysis of the basal state of the Artemis:DNA-PKcs complex

Artemis nuclease and DNA-dependent protein kinase catalytic subunit (DNA-PKcs) are key components in nonhomologous DNA end joining (NHEJ), the major repair mechanism for double-strand DNA breaks. Artemis activation by DNA-PKcs resolves hairpin DNA ends formed during V(D)J recombination. Artemis deficiency disrupts development of adaptive immunity and leads to radiosensitive T- B- severe combined immunodeficiency (RS-SCID). An activated state of Artemis in complex with DNA-PK was solved by cryo-EM recently, which showed Artemis bound to the DNA. Here, we report that the pre-activated form (basal state) of the Artemis:DNA-PKcs complex is stable on an agarose-acrylamide gel system, and suitable for cryo-EM structural analysis. Structures show that the Artemis catalytic domain is dynamically positioned externally to DNA-PKcs prior to ABCDE autophosphorylation and show how both the catalytic and regulatory domains of Artemis interact with the N-HEAT and FAT domains of DNA-PKcs. We define a mutually exclusive binding site for Artemis and XRCC4 on DNA-PKcs and show that an XRCC4 peptide disrupts the Artemis:DNA-PKcs complex. All of the findings are useful in explaining how a hypomorphic L3062R missense mutation of DNA-PKcs could lead to insufficient Artemis activation, hence RS-SCID. Our results provide various target site candidates to design disruptors for Artemis:DNA-PKcs complex formation.

Multipotential Role of Growth Factor Mimetic Peptides for Osteochondral Tissue Engineering

Articular cartilage is characterized by a poor self-healing capacity due to its aneural and avascular nature. Once injured, it undergoes a series of catabolic processes which lead to its progressive degeneration and the onset of a severe chronic disease called osteoarthritis (OA). In OA, important alterations of the morpho-functional organization occur in the cartilage extracellular matrix, involving all the nearby tissues, including the subchondral bone. Osteochondral engineering, based on a perfect combination of cells, biomaterials and biomolecules, is becoming increasingly successful for the regeneration of injured cartilage and underlying subchondral bone tissue. To this end, recently, several peptides have been explored as active molecules and enrichment motifs for the functionalization of biomaterials due to their ability to be easily chemically synthesized, as well as their tunable physico-chemical features, low immunogenicity issues and functional group modeling properties. In addition, they have shown a good aptitude to penetrate into the tissue due to their small size and stability at room temperature. In particular, growth-factor-derived peptides can play multiple functions in bone and cartilage repair, exhibiting chondrogenic/osteogenic differentiation properties. Among the most studied peptides, great attention has been paid to transforming growth factor-β and bone morphogenetic protein mimetic peptides, cell-penetrating peptides, cell-binding peptides, self-assembling peptides and extracellular matrix-derived peptides. Moreover, recently, phage display technology is emerging as a powerful selection technique for obtaining functional peptides on a large scale and at a low cost. In particular, these peptides have demonstrated advantages such as high biocompatibility; the ability to be immobilized directly on chondro- and osteoinductive nanomaterials; and improving the cell attachment, differentiation, development and regeneration of osteochondral tissue. In this context, the aim of the present review was to go through the recent literature underlining the importance of studying novel functional motifs related to growth factor mimetic peptides that could be a useful tool in osteochondral repair strategies. Moreover, the review summarizes the current knowledge of the use of phage display peptides in osteochondral tissue regeneration.

PD1 CD44 antiviral peptide as an inhibitor of the protein-protein interaction in dengue virus invasion

Dengue virus (DENV) infection is mediated by the interaction between the virus envelope protein and cellular receptors of the host cells. In this study, we designed peptides to inhibit protein-protein interaction between dengue virus and CD44 receptor, which is one of the receptors used by DENV for entry. In silico model complexes were designed between domain III of the viral envelope protein of dengue virus 2 and the domain of human CD44 receptor using ClusPro 2.0, (https://cluspro.bu.edu/login.php), and inhibition peptides were designed with Rosetta Online-Server(http://rosie.rosettacommons.org/peptiderive). We identified one linear antiviral peptide of 18 amino acids derived from the human CD44 receptor, PD1 CD44. It did not show hemolysis or toxicity in HepG2 or BHK cell lines, nor did it stimulate the release of IL-1β, IL-6, TNF-α, and IFN-γ, below 100 µM. It had an IC50 of 13.8 µM and maximum effective dose of 54.9 µM evaluated in BHK cells. The decrease in plaque-forming units/mL for DENV1, DENV2, DENV3, and DENV4 was 99.60%, 99.40%, 97.80%, and 70.50%, respectively, and similar results were obtained by RT-qPCR. Non-structural protein 1 release was decreased in pre- and co-treatment but not in post-treatment. Competition assays between the DN59 peptide, envelope protein, and the fragment of domain III "MDKLQLKGMSYSMCTGKF" of the viral envelope of DENV2 and PD1 CD44 showed that our peptide lost its antiviral activity. We demonstrated that our peptide decreased endosome formation, and we propose that it binds to the envelope protein of DENV, inhibiting viral invasion/fusion.

Non-small molecule PROTACs (NSM-PROTACs): Protein degradation kaleidoscope

The proteolysis targeting chimeras (PROTACs) technology has been rapidly developed since its birth in 2001, attracting rapidly growing attention of scientific institutes and pharmaceutical companies. At present, a variety of small molecule PROTACs have entered the clinical trial. However, as small molecule PROTACs flourish, non-small molecule PROTACs (NSM-PROTACs) such as peptide PROTACs, nucleic acid PROTACs and antibody PROTACs have also advanced considerably over recent years, exhibiting the unique characters beyond the small molecule PROTACs. Here, we briefly introduce the types of NSM-PROTACs, describe the advantages of NSM-PROTACs, and summarize the development of NSM-PROTACs so far in detail. We hope this article could not only provide useful insights into NSM-PROTACs, but also expand the research interest of NSM-PROTACs.

Will Peptides Help to Stop COVID-19?

Peptides are widely used for the diagnostics, prevention, and therapy of certain human diseases. How useful can they be for the disease caused by the SARS-CoV-2 coronavirus? In this review, we discuss the possibility of using synthetic and recombinant peptides and polypeptides for prevention of COVID-19 via blocking the interaction between the virus and its main receptor ACE2, as well as components of antiviral vaccines, in particular, against new emerging virus variants.

A story of peptides, lipophilicity and chromatography - back and forth in time

Peptides, as part of the beyond the rule of 5 (bRo5) chemical space, represent a unique class of pharmaceutical compounds. Because of their exceptional position in the chemical space between traditional small molecules (molecular weight (MW) < 500 Da) and large therapeutic proteins (MW > 5000 Da), peptides became promising candidates for targeting challenging binding sites, including even targets traditionally considered as undruggable - e.g. intracellular protein-protein interactions. However, basic knowledge about physicochemical properties that are important for a drug to be membrane permeable is missing but would enhance the drug discovery process of bRo5 molecules. Consequently, there is a demand for quick and simple lipophilicity determination methods for peptides. In comparison to the traditional lipophilicity determination methods via shake flask and in silico prediction, chromatography-based methods could have multiple benefits such as the requirement of low analyte amount, insensitivity to impurities and high throughput. Herein we elucidate the role of peptide lipophilicity and different lipophilicity values. Further, we summarize peptide analysis via common chromatographic techniques, in specific reversed phase liquid chromatography, hydrophilic interaction liquid chromatography and supercritical fluid chromatography and their role in drug discovery and development process.

Targeting the interaction of GABAB receptors with CaMKII with an interfering peptide restores receptor expression after cerebral ischemia and inhibits progressive neuronal death in mouse brain cells and slices

Cerebral ischemia is the leading cause for long-term disability and mortality in adults due to massive neuronal death. Currently, there is no pharmacological treatment available to limit progressive neuronal death after stroke. A major mechanism causing ischemia-induced neuronal death is the excessive release of glutamate and the associated overexcitation of neurons (excitotoxicity). Normally, GABA_B receptors control neuronal excitability in the brain via prolonged inhibition. However, excitotoxic conditions rapidly downregulate GABA_B receptors via a CaMKII-mediated mechanism and thereby diminish adequate inhibition that could counteract neuronal overexcitation and neuronal death. To prevent the deleterious downregulation of GABA_B receptors, we developed a cell-penetrating synthetic peptide (R1-Pep) that inhibits the interaction of GABA_B receptors with CaMKII. Administration of this peptide to cultured cortical neurons exposed to excitotoxic conditions restored cell surface expression and function of GABA_B receptors. R1-Pep did not affect CaMKII expression or activity but prevented its T286 autophosphorylation that renders it autonomously and persistently active. Moreover, R1-Pep counteracted the aberrant downregulation of G protein-coupled inwardly rectifying K⁺ channels and the upregulation of N-type voltage-gated Ca²⁺ channels, the main effectors of GABA_B receptors. The restoration of GABA_B receptors activated the Akt survival pathway and inhibited excitotoxic neuronal death with a wide time window in cultured neurons. Restoration of GABA_B receptors and neuroprotective activity of R1-Pep was verified by using brain slices prepared from mice after middle cerebral artery occlusion (MCAO). Treatment with R1-Pep restored normal GABA_B receptor expression and GABA receptor-mediated K⁺ channel currents. This reduced MCAO-induced neuronal excitability and inhibited neuronal death. These results support the hypothesis that restoration of GABA_B receptor expression under excitatory conditions provides neuroprotection and might be the basis for the development of a selective intervention to inhibit progressive neuronal death after ischemic stroke.

Amyloid-β Inspired Short Peptide Amphiphile Facilitates Synthesis of Silver Nanoparticles as Potential Antibacterial Agents

An amyloid-β inspired biocompatible short peptide amphiphile (sPA) molecule was used for controlled and targeted delivery of bioactive silver nanoparticles via transforming sPA nanostructures. Such sPA-AgNPs hybrid structures can be further used to develop antibacterial materials to combat emerging bacterial resistance. Due to the excellent antibacterial activity of silver, the growth of clinically relevant bacteria was inhibited in the presence of AgNPs-sPA hybrids. Bacterial tests demonstrated that the high biocompatibility and low cytotoxicity of the designed sPA allow it to work as a model drug delivery agent. It therefore shows great potential in locally addressing bacterial infections. The results of our study suggest that these nanodevices have the potential to trap and then engage in the facile delivery of their chemical payload at the target site, thereby working as potential delivery materials. This system has potential therapeutic value for the treatment of microbiota triggered progression of neurodegenerative diseases.

A novel mRNA decay inhibitor abolishes pathophysiological cellular transition

In cells, mRNA synthesis and decay are influenced by each other, and their balance is altered by either external or internal cues, resulting in changes in cell dynamics. We previously reported that it is important that an array of mRNAs that shape a phenotype are degraded before cellular transitions, such as cellular reprogramming and differentiation. In adipogenesis, the interaction between DDX6 and 4E-T had a definitive impact on the pathway in the processing body (PB). We screened a library of α-helix analogs with an alkaloid-like backbone to identify compounds that inhibit the binding between DDX6 and 4E-T proteins, which occurs between the α-helix of structured and internally disordered proteins. IAMC-00192 was identified as a lead compound. This compound directly inhibited the interaction between DDX6 and 4E-T. IAMC-00192 inhibited the temporal increase in PB formation that occurs during adipogenesis and epithelial-mesenchymal transition (EMT) and significantly suppressed these cellular transitions. In the EMT model, the half-life of preexisting mRNAs in PBs was extended twofold by the compound. The novel inhibitor of RNA decay not only represents a potentially useful tool to analyze in detail the pathological conditions affected by RNA decay and how it regulates the pathological state. The identification of this inhibitor may lead to the discovery of a first-in-class RNA decay inhibitor drug.

PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

Background

Computational methods based on initial screening and prediction of peptides for desired functions have proven to be effective alternatives to lengthy and expensive biochemical experimental methods traditionally utilized in peptide research, thus saving time and effort. However, for many researchers, the lack of expertise in utilizing programming libraries, access to computational resources, and flexible pipelines are big hurdles to adopting these advanced methods.

Results

To address the above mentioned barriers, we have implemented the peptide design and analysis under Galaxy (PDAUG) package, a Galaxy-based Python powered collection of tools, workflows, and datasets for rapid in-silico peptide library analysis. In contrast to existing methods like standard programming libraries or rigid single-function web-based tools, PDAUG offers an integrated GUI-based toolset, providing flexibility to build and distribute reproducible pipelines and workflows without programming expertise. Finally, we demonstrate the usability of PDAUG in predicting anticancer properties of peptides using four different feature sets and assess the suitability of various ML algorithms.

Conclusion

PDAUG offers tools for peptide library generation, data visualization, built-in and public database peptide sequence retrieval, peptide feature calculation, and machine learning (ML) modeling. Additionally, this toolset facilitates researchers to combine PDAUG with hundreds of compatible existing Galaxy tools for limitless analytic strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04727-6.

Synthetic antiviral peptides: a new way to develop targeted antiviral drugs

The global concern over emerging and re-emerging viral infections has spurred the search for novel antiviral agents. Peptides with antiviral activity stand out, by overcoming limitations of the current drugs utilized, due to their biocompatibility, specificity and effectiveness. Synthetic peptides have been shown to be viable alternatives to natural peptides due to several difficulties of using of the latter in clinical trials. Various platforms have been utilized by researchers to predict the most effective peptide sequences against HIV, influenza, dengue, MERS and SARS. Synthetic peptides are already employed in the treatment of HIV infection. The novelty of this study is to discuss, for the first time, the potential of synthetic peptides as antiviral molecules. We conclude that synthetic peptides can act as new weapons against viral threats to humans.

Inhibiting UCH-L5: Rational Design of a Cyclic Ubiquitin-Based Peptide Inhibitor

The ubiquitin-proteasome system is an essential regulator of many cellular processes including controlling protein homeostasis. The degradation of proteins by the multi-subunit proteasome complex is tightly regulated through a series of checkpoints, amongst which are a set of deubiquitinating proteases (DUBs). The proteasome-associated DUBs, UCH-L5 (Ubiquitin carboxyl-terminal hydrolase isozyme L5) and USP14 (Ubiquitin-specific protease 14), and the integral-DUB in the proteasome, Rpn11, is known to regulate proteasomal degradation by deubiquitination of distinct substrates. Although selective inhibitors for USP14 and Rpn11 have been recently developed, there are no known inhibitors that selectively bind to UCH-L5. The X-ray structure of the Ubiquitin (Ub) bound to UCH-L5 shows a β-sheet hairpin in Ub that contains a crucial hydrophobic patch involved in the interaction with UCH-L5. Herein, we designed and developed both a Ub sequence-based linear- and cyclic- β-sheet hairpin peptide that was found to preferably inhibit UCH-L5. We show that these peptides have low micromolar IC₅₀ values and the cyclic peptide competes with the activity-based UbVME (Ubiquitin-Vinyl-Methyl-Ester) probe for UCH-L5, binding in a concentration-dependent manner. We further establish the selectivity profile of the cyclic peptide for UCH-L5 compared to other members of the UCH-DUB family and other cysteine DUBs in cell lysate. Furthermore, the cyclic peptide infiltrated cells resulting in the accumulation of polyUb chains, and was found to be non-toxic at the concentrations used here. Taken together, our data suggest that the cyclic peptide permeates the cell membrane, inhibits UCH-L5 by possibly blocking its deubiquitinating function, and contributes to the accumulation of polyubiquitinated substrates. The implications of inhibiting UCH-L5 in the context of the 26S proteasome render it an attractive candidate for further development as a potential selective inhibitor for therapeutic purposes.

Development of Anticancer Peptides Using Artificial Intelligence and Combinational Therapy for Cancer Therapeutics

Cancer is a group of diseases causing abnormal cell growth, altering the genome, and invading or spreading to other parts of the body. Among therapeutic peptide drugs, anticancer peptides (ACPs) have been considered to target and kill cancer cells because cancer cells have unique characteristics such as a high negative charge and abundance of microvilli in the cell membrane when compared to a normal cell. ACPs have several advantages, such as high specificity, cost-effectiveness, low immunogenicity, minimal toxicity, and high tolerance under normal physiological conditions. However, the development and identification of ACPs are time-consuming and expensive in traditional wet-lab-based approaches. Thus, the application of artificial intelligence on the approaches can save time and reduce the cost to identify candidate ACPs. Recently, machine learning (ML), deep learning (DL), and hybrid learning (ML combined DL) have emerged into the development of ACPs without experimental analysis, owing to advances in computer power and big data from the power system. Additionally, we suggest that combination therapy with classical approaches and ACPs might be one of the impactful approaches to increase the efficiency of cancer therapy.

Computational assessment of pigment epithelium-derived factor as an anti-cancer protein during its interaction with the receptors

Pigment epithelium-derived factor (PEDF) is a member of the serine proteinase inhibitor (serpin) with antiangiogenic, anti-tumorigenic, antioxidant, anti-atherosclerosis, antithrombotic, anti-inflammatory, and neuroprotective properties. The PEDF can bind to low-density lipoprotein receptor-related protein 6 (LRP6), laminin (LR), vascular endothelial growth factor receptor 1 (VEGFR1), vascular endothelial growth factor receptor 2 (VEGFR2), and ATP synthase β-subunit receptors. In this study, we aimed to investigate the structural basis of the interaction between PEDF and its receptors using bioinformatics approaches to identify the critical amino acids for designing anticancer peptides. The human ATP synthase β-subunit was predicted by homology modeling. The molecular docking, molecular dynamics (MD) simulation, and Molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) were used to study this protein-receptor complex. The molecular docking showed PEDF could bind to the Laminin and VEGFR2 much stronger than ATP synthase β-subunit, VEGFR1, and LRP6. The PEDF could effectively interact with various receptors during the simulation. The N-terminal of PEDF has an important role in the interaction with the receptors. The MM/PBSA showed the electrostatic (ΔE_Elec) and van der Waals interactions (ΔE_VdW) contributed positively to the binding process of the complexes. The critical amino acids in the binding interaction of PEDF to its receptors in the MD simulation were determined. The interaction mode of 34-mer PEDF to laminin, VEGFR2, and LRP6 were different from VEGFR1, ATP synthase β-subunit. The 34-mer PEDF has an important role in the interaction with different receptors and these critical amino acids can be used for designing peptides for future therapeutic aims.Communicated by Ramaswamy H. Sarma.

Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond

Cyclic peptides formed by disulfide bonds have been one large group of common drug candidates in drug development. Structural information of a peptide is essential to understand its interaction with its target. However, due to the high flexibility of peptides, it is difficult to sample the near-native conformations of a peptide. Here, we have developed an extended version of our MODPEP approach, named MODPEP2.0, to fast generate the conformations of cyclic peptides formed by a disulfide bond. MODPEP2.0 builds the three-dimensional (3D) structures of a cyclic peptide from scratch by assembling amino acids one by one onto the cyclic fragment based on the constructed rotamer and cyclic backbone libraries. Being tested on a data set of 193 diverse cyclic peptides, MODPEP2.0 obtained a considerable advantage in both accuracy and computational efficiency, compared with other sampling algorithms including PEP-FOLD, ETKDG, and modified ETKDG (mETKDG). MODPEP2.0 achieved a high sampling accuracy with an average C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha$$\end{document}α RMSD of 2.20 Å and 1.66 Å when 10 and 100 conformations were considered, respectively, compared with 3.41 Å and 2.62 Å for PEP-FOLD, 3.44 Å and 3.16 Å for ETKDG, 3.09 Å and 2.72 Å for mETKDG. MODPEP2.0 also reproduced experimental peptide structures for 81.35% of the test cases when an ensemble of 100 conformations were considered, compared with 54.95%, 37.50% and 50.00% for PEP-FOLD, ETKDG, and mETKDG. MODPEP2.0 is computationally efficient and can generate 100 peptide conformations in one second. MODPEP2.0 will be useful in sampling cyclic peptide structures and modeling related protein-peptide interactions, facilitating the development of cyclic peptide drugs.

Antimicrobial peptides: A plausible approach for COVID-19 treatment

INTRODUCTION

Coronavirus disease 2019 (COVID-19), which emerged as a major public health threat, has affected >400 million people globally leading to >5 million mortalities to date. Treatments of COVID-19 are still to be developed as the available therapeutic approaches are not able to combat the virus causing the disease (severe acute respiratory syndrome coronavirus-2; SARS-CoV-2) satisfactorily. However, antiviral peptides (AVPs) have demonstrated prophylactic and therapeutic effects against many coronaviruses (CoVs).

AREAS COVERED

This review critically discusses various types of AVPs evaluated for the treatment of COVID-19 along with their mechanisms of action. Furthermore, the peptides inhibiting the entry of the virus by targeting its binding to angiotensin-converting enzyme 2 (ACE2) or integrins, fusion mechanism as well as activation of proteolytic enzymes (cathepsin L, transmembrane serine protease 2 (TMPRSS2), or furin) are also discussed.

EXPERT OPINION

Although extensively investigated, successful treatment of COVID-19 is still a challenge due to emergence of virus mutants. Antiviral peptides are anticipated to be blockbuster drugs for the management of this serious infection because of their formulation and therapeutic advantages. Although they may act on different pathways, AVPs having a multi-targeted approach are considered to have the upper hand in the management of this infection.

Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking

We present a combined computational approach to protein-ligand binding, which consists of two steps: (1) a deep neural network is used to locate a binding region on a target protein, and (2) molecular docking of a ligand is performed within the specified region to obtain the best pose using Autodock Vina. Our in-house designed neural network was trained using the PepBDB dataset. Although the training dataset consisted of protein-peptide complexes, we show that the approach is not limited to peptides, but also works remarkably well for a large class of non-peptide ligands. The results are compared with those in which the binding region (first step) was provided by Accluster. In cases where no prior experimental data on the binding region are available, our deep neural network provides a fast and effective alternative to classical software for its localization. Our code is available at https://github.com/mksmd/NNforDocking.

Design, Synthesis and Evaluation of Fused Bicyclo[2.2.2]octene as a Potential Core Scaffold for the Non-Covalent Inhibitors of SARS-CoV-2 3CLpro Main Protease

The emergence of SARS-CoV-2, responsible for the global COVID-19 pandemic, requires the rapid development of novel antiviral drugs that would contribute to an effective treatment alongside vaccines. Drug repurposing and development of new molecules targeting numerous viral targets have already led to promising drug candidates. To this end, versatile molecular scaffolds with high functionalization capabilities play a key role. Starting with the clinically used conformationally flexible HIV-1 protease inhibitors that inhibit replication of SARS-CoV-2 and bind major protease 3CL^pro, we designed and synthesized a series of rigid bicyclo[2.2.2]octenes fused to N-substituted succinimides to test whether this core scaffold could support the development of non-covalent 3CL^pro inhibitors. Inhibition assays confirmed that some compounds can inhibit the SARS-CoV-2 main protease; the most promising compound 11a inhibited 3CL^pro in micromolar range (IC₅₀ = 102.2 μM). Molecular simulations of the target-ligand complex in conjunction with dynophore analyses and endpoint free energy calculations provide additional insight and first recommendations for future optimization. The fused bicyclo[2.2.2]octenes can be used as a new potential starting point in the development of non-covalent SARS-CoV-2 3CL^pro protease inhibitors and the study also substantiates the potential of this versatile scaffold for the development of biologically active molecules.

Marine Migrastatics: A Comprehensive 2022 Update

Metastasis is responsible for the bad prognosis in cancer patients. Advances in research on metastasis prevention focus attention on the molecular mechanisms underlying cancer cell motility and invasion to improve therapies for long-term survival in cancer patients. The so-called "migrastatics" could help block cancer cell invasion and lead to the rapid development of antimetastatic therapies, improving conventional cancer therapies. In the relentless search for migrastatics, the marine environment represents an important source of natural compounds due to its enormous biodiversity. Thus, this review is a selection of scientific research that has pointed out in a broad spectrum of in vitro and in vivo models the anti-cancer power of marine-derived products against cancer cell migration and invasion over the past five years. Overall, this review might provide a useful up-to-date guide about marine-derived compounds with potential interest for pharmaceutical and scientific research on antimetastatic drug endpoints.

Propagation of seminal toxins through binary expression gene drives could suppress populations

Gene drives can be highly effective in controlling a target population by disrupting a female fertility gene. To spread across a population, these drives require that disrupted alleles be largely recessive so as not to impose too high of a fitness penalty. We argue that this restriction may be relaxed by using a double gene drive design to spread a split binary expression system. One drive carries a dominant lethal/toxic effector alone and the other a transactivator factor, without which the effector will not act. Only after the drives reach sufficiently high frequencies would individuals have the chance to inherit both system components and the effector be expressed. We explore through mathematical modeling the potential of this design to spread dominant lethal/toxic alleles and suppress populations. We show that this system could be implemented to spread engineered seminal proteins designed to kill females, making it highly effective against polyandrous populations.

Novel Antimicrobial Peptides Designed Using a Recurrent Neural Network Reduce Mortality in Experimental Sepsis

The search and development of new antibiotics is relevant due to widespread antibiotic resistance. One of the promising strategies is the de novo design of novel antimicrobial peptides. The amino acid sequences of 198 novel peptides were obtained using a generative long short-term memory recurrent neural network (LSTM RNN). To assess their antimicrobial effect, we synthesized five out of 198 generated peptides. The PEP-38 and PEP-137 peptides were active in vitro against carbapenem-resistant isolates of Klebsiella aerogenes and K. pneumoniae. PEP-137 was also active against Pseudomonas aeruginosa. The remaining three peptides (PEP-36, PEP-136 and PEP-174) showed no antibacterial effect. Then the effect of PEP-38 and PEP-137 (a single intraperitoneal administration of a 100 μg dose 30 min after infection) on animal survival in an experimental murine model of K. pneumoniae-induced sepsis was investigated. As a control, two groups of mice were used: one received sterile saline, and the other received inactive in vitro PEP-36 (a single 100 μg dose). The PEP-36 peptide was shown to provide the highest survival rate (66.7%). PEP-137 showed a survival rate of 50%. PEP-38 was found to be ineffective. The data obtained can be used to develop new antibacterial peptide drugs to combat antibiotic resistance.

Vasopressin and Its Analogues: From Natural Hormones to Multitasking Peptides

Human neurohormone vasopressin (AVP) is synthesized in overlapping regions in the hypothalamus. It is mainly known for its vasoconstricting abilities, and it is responsible for the regulation of plasma osmolality by maintaining fluid homeostasis. Over years, many attempts have been made to modify this hormone and find AVP analogues with different pharmacological profiles that could overcome its limitations. Non-peptide AVP analogues with low molecular weight presented good affinity to AVP receptors. Natural peptide counterparts, found in animals, are successfully applied as therapeutics; for instance, lypressin used in treatment of diabetes insipidus. Synthetic peptide analogues compensate for the shortcomings of AVP. Desmopressin is more resistant to proteolysis and presents mainly antidiuretic effects, while terlipressin is a long-acting AVP analogue and a drug recommended in the treatment of varicose bleeding in patients with liver cirrhosis. Recently published results on diverse applications of AVP analogues in medicinal practice, including potential lypressin, terlipressin and ornipressin in the treatment of SARS-CoV-2, are discussed.

Bioinspired Polydopamine Coatings Facilitate Attachment of Antimicrobial Peptidomimetics with Broad-Spectrum Antibacterial Activity

The prevention and treatment of biofilm-mediated infections remains an unmet clinical need for medical devices. With the increasing prevalence of antibiotic-resistant infections, it is important that novel approaches are developed to prevent biofilms forming on implantable medical devices. This study presents a versatile and simple polydopamine surface coating technique for medical devices, using a new class of antibiotics—antimicrobial peptidomimetics. Their unique mechanism of action primes them for activity against antibiotic-resistant bacteria and makes them suitable for covalent attachment to medical devices. This study assesses the anti-biofilm activity of peptidomimetics, characterises the surface chemistry of peptidomimetic coatings, quantifies the antibacterial activity of coated surfaces and assesses the biocompatibility of these coated materials. X-ray photoelectron spectroscopy and water contact angle measurements were used to confirm the chemical modification of coated surfaces. The antibacterial activity of surfaces was quantified for S. aureus, E. coli and P. aeruginosa, with all peptidomimetic coatings showing the complete eradication of S. aureus on surfaces and variable activity for Gram-negative bacteria. Scanning electron microscopy confirmed the membrane disruption mechanism of peptidomimetic coatings against E. coli. Furthermore, peptidomimetic surfaces did not lyse red blood cells, which suggests these surfaces may be biocompatible with biological fluids such as blood. Overall, this study provides a simple and effective antibacterial coating strategy that can be applied to biomaterials to reduce biofilm-mediated infections.

Novel Strategies to Inhibit Pertussis Toxin

Pertussis, also known as whooping cough, is a respiratory disease caused by infection with Bordetella pertussis, which releases several virulence factors, including the AB-type pertussis toxin (PT). The characteristic symptom is severe, long-lasting paroxysmal coughing. Especially in newborns and infants, pertussis symptoms, such as leukocytosis, can become life-threatening. Despite an available vaccination, increasing case numbers have been reported worldwide, including Western countries such as Germany and the USA. Antibiotic treatment is available and important to prevent further transmission. However, antibiotics only reduce symptoms if administered in early stages, which rarely occurs due to a late diagnosis. Thus, no causative treatments against symptoms of whooping cough are currently available. The AB-type protein toxin PT is a main virulence factor and consists of a binding subunit that facilitates transport of an enzyme subunit into the cytosol of target cells. There, the enzyme subunit ADP-ribosylates inhibitory α-subunits of G-protein coupled receptors resulting in disturbed cAMP signaling. As an important virulence factor associated with severe symptoms, such as leukocytosis, and poor outcomes, PT represents an attractive drug target to develop novel therapeutic strategies. In this review, chaperone inhibitors, human peptides, small molecule inhibitors, and humanized antibodies are discussed as novel strategies to inhibit PT.

Chondroinductive/chondroconductive peptides and their-functionalized biomaterials for cartilage tissue engineering

The repair of articular cartilage defects is still challenging in the fields of orthopedics and maxillofacial surgery due to the avascular structure of articular cartilage and the limited regenerative capacity of mature chondrocytes. To provide viable treatment options, tremendous efforts have been made to develop various chondrogenically-functionalized biomaterials for cartilage tissue engineering. Peptides that are derived from and mimic the functions of chondroconductive cartilage extracellular matrix and chondroinductive growth factors, represent a unique group of bioactive agents for chondrogenic functionalization. Since they can be chemically synthesized, peptides bear better reproducibility, more stable efficacy, higher modifiability and yielding efficiency in comparison with naturally derived biomaterials and recombinant growth factors. In this review, we summarize the current knowledge in the designs of the chondroinductive/chondroconductive peptides, the underlying molecular mechanisms and their-functionalized biomaterials for cartilage tissue engineering. We also systematically compare their in-vitro and in-vivo efficacies in inducing chondrogenesis. Our vision is to stimulate the development of novel peptides and their-functionalized biomaterials for cartilage tissue engineering.

Leveraging the multivalent p53 peptide-MdmX interaction to guide the improvement of small molecule inhibitors

Overexpressed Mdm2 and its 7homolog MdmX impair p53 activity in many cancers. Small molecules mimicking a p53 peptide can effectively inhibit Mdm2 but not MdmX. Here, we show a strategy for improving lead compounds for Mdm2 and MdmX inhibition based on the multivalency of the p53 peptide. Crystal structures of MdmX complexed with nutlin-3a, a strong Mdm2 inhibitor but a weak one for MdmX, reveal that nutlin-3a fits into the ligand binding pocket of MdmX mimicking the p53 peptide. However, due to distinct flexibility around the MdmX ligand binding pocket, the structures are missing many important intermolecular interactions that exist in the MdmX/p53 peptide and Mdm2/nultin-3a complexes. By targeting these flexible regions, we identify allosteric and additive fragments that enhance the binding affinity of nutlin-3a for MdmX, leading to potent Mdm2/MdmX inhibitors with anticancer activity. Our work provides a practical approach to drug design for signal transduction therapy.

Peptide fragments derived from the interfaces of protein-protein interactions (PPIs) provide useful templates for designing small molecule PPI inhibitors. Here, the authors utilize the multivalency of an MdmX-binding p53 peptide to develop a weak inhibitor of MdmX into potent Mdm2/MdmX inhibitors.

Therapeutic Peptides to Treat Myocardial Ischemia-Reperfusion Injury

Cardiovascular diseases (CVD) including acute myocardial infarction (AMI) rank first in worldwide mortality and according to the World Health Organization (WHO), they will stay at this rank until 2030. Prompt revascularization of the occluded artery to reperfuse the myocardium is the only recommended treatment (by angioplasty or thrombolysis) to decrease infarct size (IS). However, despite beneficial effects on ischemic lesions, reperfusion leads to ischemia-reperfusion (IR) injury related mainly to apoptosis. Improvement of revascularization techniques and patient care has decreased myocardial infarction (MI) mortality however heart failure (HF) morbidity is increasing, contributing to the cost-intense worldwide HF epidemic. Currently, there is no treatment for reperfusion injury despite promising results in animal models. There is now an obvious need to develop new cardioprotective strategies to decrease morbidity/mortality of CVD, which is increasing due to the aging of the population and the rising prevalence rates of diabetes and obesity. In this review, we will summarize the different therapeutic peptides developed or used focused on the treatment of myocardial IR injury (MIRI). Therapeutic peptides will be presented depending on their interacting mechanisms (apoptosis, necroptosis, and inflammation) reported as playing an important role in reperfusion injury following myocardial ischemia. The search and development of therapeutic peptides have become very active, with increasing numbers of candidates entering clinical trials. Their optimization and their potential application in the treatment of patients with AMI will be discussed.

Therapeutic peptides: current applications and future directions

Peptide drug development has made great progress in the last decade thanks to new production, modification, and analytic technologies. Peptides have been produced and modified using both chemical and biological methods, together with novel design and delivery strategies, which have helped to overcome the inherent drawbacks of peptides and have allowed the continued advancement of this field. A wide variety of natural and modified peptides have been obtained and studied, covering multiple therapeutic areas. This review summarizes the efforts and achievements in peptide drug discovery, production, and modification, and their current applications. We also discuss the value and challenges associated with future developments in therapeutic peptides.

Uncovering a Hub Signaling Pathway of Antimicrobial-Antifungal-Anticancer Peptides’ Axis on Short Cationic Peptides via Network Pharmacology Study

Short cationic peptides (SCPs) with therapeutic efficacy of antimicrobial peptides (AMPs), antifungal peptides (AFPs), and anticancer peptides (ACPs) are known as an enhancement of the host defense system. Here, we investigated the uppermost peptide(s), hub signaling pathway(s), and their associated target(s) through network pharmacology. Firstly, we selected SCPs with positive amino acid residues on N- and C- terminals under 500 Dalton via RStudio. Secondly, the overlapping targets between the bacteria-responsive targets (TTD and OMIM) and AMPs’ targets were visualized by VENNY 2.1. Thirdly, the overlapping targets between AFPs’ targets and fungal-responsive targets were exhibited by VENNY 2.1. Fourthly, the overlapping targets between cancer-related targets (TTD and OMIM) and fungal-responsive targets were displayed by VENNY 2.1. Finally, a molecular docking study (MDS) was carried out to discover the most potent peptides on a hub signaling pathway. A total of 1833 SCPs were identified, and AMPs’, AFPs’, and ACPs’ filtration suggested that 197 peptides (30 targets), 81 peptides (6 targets), and 59 peptides (4 targets) were connected, respectively. The AMPs―AFPs―ACPs’ axis indicated that 27 peptides (2 targets) were associated. Each hub signaling pathway for the enhancement of the host defense system was “Inactivation of Rap1 signaling pathway on AMPs”, “Activation of Notch signaling pathway on AMPs―AFPs’ axis”, and “Inactivation of HIF-1 signaling pathway on AMPs―AFPs―ACPs’ axis”. The most potent peptides were assessed via MDS; finally, HPIK on STAT3 and HVTK on NOS2 and on HIF-1 signaling pathway were the most stable complexes. Furthermore, the two peptides had better affinity scores than standard inhibitors (Stattic, 1400 W). Overall, the most potent SCPs for the human defense system were HPIK on STAT3 and HVTK on NOS2, which might inactivate the HIF-1 signaling pathway.

Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions

Peptide-protein interactions play a key role for many cellular and metabolic processes involved in the onset of largely spread diseases such as cancer and neurodegenerative pathologies. Despite the progress in the structural characterization of peptide-protein interfaces, the in-depth knowledge of the molecular details behind their interactions is still a daunting task. Here, we present the first comprehensive in silico morphological and energetic study of peptide binding sites by focusing on both peptide and protein standpoints. Starting from the PixelDB database, a nonredundant benchmark collection of high-quality 3D crystallographic structures of peptide-protein complexes, a classification analysis of the most representative categories based on the nature of each cocrystallized peptide has been carried out. Several interpretable geometrical and energetic descriptors have been computed both from peptide and target protein sides in the attempt to unveil physicochemical and structural causative correlations. Finally, we investigated the most frequent peptide-protein residue pairs at the binding interface and made extensive energetic analyses, based on GRID MIFs, with the aim to study the peptide affinity-enhancing interactions to be further exploited in rational drug design strategies.

An albumin scaffold grafted with an alpha-helical motif delivers therapeutic payloads by modular coiled-coil assembly

A short in vivo half-life of protein-based therapeutics often restricts successful clinical translation despite their promising efficacy in vitro. As a biocompatible half-life extender, human serum albumin (HSA) has proven effective in some cases. While genetic fusion is well-established for interlinking HSA and a protein payload, it is limited to structurally simple proteins, necessitating new strategies to expand the utility of HSA for delivery of therapeutic proteins. Here, we report a novel HSA variant (eHSA) as a modular and long-acting carrier compatible with any protein payload of interest. The assembly between eHSA and a payload was driven by a heterodimeric coiled-coil interaction in which a short α-helix grafted onto HSA specifically bound to a complementary α-helix genetically fused to a payload. We showed various proteins including tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), single-chain TRAIL, or green fluorescent protein could piggyback onto eHSA via simple mixing without losing native activity. Additionally, either in presence or absence of a payload, eHSA was found to retain the pH-dependent FcRn-binding behavior - a critical attribute for prolonged survival in the systemic circulation. These results demonstrate eHSA would serve as a modular platform capable of delivering various therapeutic proteins with potentially long in vivo half-lives.

Mapping oncogenic protein interactions for precision medicine

Normal protein‐protein interactions (normPPIs) occur with high fidelity to regulate almost every physiological process. In cancer, this highly organised and precisely regulated network is disrupted, hijacked or reprogrammed resulting in oncogenic protein‐protein interactions (oncoPPIs). OncoPPIs, which can result from genomic alterations, are a hallmark of many types of cancers. Recent technological advances in the field of mass spectrometry (MS)‐based interactomics, structural biology and drug discovery have prompted scientists to identify and characterise oncoPPIs. Disruption of oncoPPI interfaces has become a major focus of drug discovery programs and has resulted in the use of PPI‐specific drugs clinically. However, due to several technical hurdles, studies to build a reference oncoPPI map for various cancer types have not been undertaken. Therefore, there is an urgent need for experimental workflows to overcome the existing challenges in studying oncoPPIs in various cancers and to build comprehensive reference maps. Here, we discuss the important hurdles for characterising oncoPPIs and propose a three‐phase multidisciplinary workflow to identify and characterise oncoPPIs. Systematic identification of cancer‐type‐specific oncogenic interactions will spur new opportunities for PPI‐focused drug discovery projects and precision medicine.

Integration of Molecular Docking Analysis and Molecular Dynamics Simulations for Studying Food Proteins and Bioactive Peptides

In silico tools, such as molecular docking, are widely applied to study interactions and binding affinity of biological activity of proteins and peptides. However, restricted sampling of both ligand and receptor conformations and use of approximated scoring functions can produce results that do not correlate with actual experimental binding affinities. Molecular dynamics simulations (MDS) can provide valuable information in deciphering functional mechanisms of proteins/peptides and other biomolecules, overcoming the rigid sampling limitations in docking analysis. This review will discuss the information related to the traditional use of in silico models, such as molecular docking, and its application for studying food proteins and bioactive peptides, followed by an in-depth introduction to the theory of MDS and description of why these molecular simulation techniques are important in the theoretical prediction of structural and functional dynamics of food proteins and bioactive peptides. Applications, limitations, and future prospects of MDS will also be discussed.

The Arsenal of Bioactive Molecules in the Skin Secretion of Urodele Amphibians

Urodele amphibians (∼768 spp.), salamanders and newts, are a rich source of molecules with bioactive properties, especially those isolated from their skin secretions. These include pharmacological attributes, such as antimicrobial, antioxidant, vasoactive, immune system modulation, and dermal wound healing activities. Considering the high demand for new compounds to guide the discovery of new drugs to treat conventional and novel diseases, this review summarizes the characteristics of molecules identified in the skin of urodele amphibians. We describe urodele-derived peptides and alkaloids, with emphasis on their biological activities, which can be considered new scaffolds for the pharmaceutical industry. Although much more attention has been given to anurans, bioactive molecules produced by urodeles have the potential to be used for biotechnological purposes and stand as viable alternatives for the development of therapeutic agents.

Therapeutic potential of marine peptides in cervical and ovarian cancers

Cervical and ovarian cancers contribute significantly to female morbidity and mortality worldwide. The current standard of treatment, including surgical removal, radiation therapy, and chemotherapy, offers poor outcomes. There are many side effects to traditional chemotherapeutic agents and treatment-resistant types, and often the immune response is depressed. As a result, traditional approaches have evolved to include new alternative remedies, such as natural compounds. Aquatic species provide a rich supply of possible drugs. The potential anti-cancer peptides are less toxic to normal cells and can attenuate multiple drug resistance by providing an efficacious treatment approach. The physiological effects of marine peptides are described in this review focusing on various pathways, such as apoptosis, microtubule balance disturbances, suppression of angiogenesis, cell migration/invasion, and cell viability. The review also highlights the potential role of marine peptides as safe and efficacious therapeutic agent for the treatment of cervical and ovarian cancers.

Modeling the MreB-CbtA Interaction to Facilitate the Prediction and Design of Candidate Antibacterial Peptides

Protein-protein interactions (PPIs) have emerged as promising targets for PPI modulators as alternative drugs because they are essential for most biochemical processes in living organisms. In recent years, a spotlight has been put on the development of peptide-based PPI inhibitors as the next-generation therapeutics to combat antimicrobial resistance taking cognizance of protein-based PPI-modulators that interact with target proteins to inhibit function. Although protein-based PPI inhibitors are not effective therapeutic agents because of their high molecular weights, they could serve as sources for peptide-based pharmaceutics if the target-inhibitor complex is accessible and well characterized. The Escherichia coli (E. coli) toxin protein, CbtA, has been identified as a protein-based PPI modulator that binds to the bacterial actin homolog MreB leading to the perturbation of its polymerization dynamics; and consequently has been suggested to have antibacterial properties. Unfortunately, however, the three-dimensional structures of CbtA and the MreB-CbtA complex are currently not available to facilitate the optimization process of the pharmacological properties of CbtA. In this study, computer modeling strategies were used to predict key MreB-CbtA interactions to facilitate the design of antiMreB peptide candidates. A model of the E. coli CbtA was built using the trRosetta software and its stability was assessed through molecular dynamics (MD) simulations. The modeling and simulations data pointed to a model with reasonable quality and stability. Also, the HADDOCK software was used to predict a possible MreB-CbtA complex, which was characterized through MD simulations and compared with MreB-MreB dimmer. The results suggest that CbtA inhibits MreB through the competitive mechanism whereby CbtA competes with MreB monomers for the interprotofilament interface leading to interference with double protofilament formation. Additionally, by using the antiBP software to predict antibacterial peptides in CbtA, and the MreB-CbtA complex as the reference structure to determine important interactions and contacts, candidate antiMreB peptides were suggested. The peptide sequences could be useful in a rational antimicrobial peptide hybridization strategy to design novel antibiotics. All-inclusive, the data reveal the molecular basis of MreB inhibition by CbtA and can be incorporated in the design/development of the next-generation antibacterial peptides targeting MreB.

Tuning protein half-life in mouse using sequence-defined biopolymers functionalized with lipids

The use of biologics in the treatment of numerous diseases has increased steadily over the past decade due to their high specificities, low toxicity, and limited side effects. Despite this success, peptide- and protein-based drugs are limited by short half-lives and immunogenicity. To address these challenges, we use a genomically recoded organism to produce genetically encoded elastin-like polypeptide-protein fusions containing multiple instances of para-azidophenylalanine (pAzF). Precise lipidation of these pAzF residues generated a set of sequence-defined synthetic biopolymers with programmable binding affinity to albumin without ablating the activity of model fusion proteins, and with tunable blood serum half-lives spanning 5 to 94% of albumin's half-life in a mouse model. Our findings present a proof of concept for the use of genetically encoded bioorthogonal conjugation sites for multisite lipidation to tune protein stability in mouse serum. This work establishes a programmable approach to extend and tune the half-life of protein or peptide therapeutics and a technical foundation to produce functionalized biopolymers endowed with programmable chemical and biophysical properties with broad applications in medicine, materials science, and biotechnology.

Strategic Decoy Peptides Interfere with MSI1/AGO2 Interaction to Elicit Tumor Suppression Effects

Simple Summary

Peptide drugs that can specifically target undesirable protein–protein interactions that lead to oncogenic developments have emerged as the next era of future medicine for cancers. To combat GBM tumor progression, our study offers an alternative therapeutic strategy via targeting the protein–protein interaction between MSI1 and AGO2 with synthetic peptides identified from the C-terminus of MSI1 in peptide arrays. Our present data revealed for the first time that peptidic disruption to the MSI1/AGO2 complex known for promoting cancer stemness and progression could lead to encouraging therapeutic efficacy at both in vitro and in vivo levels. The significantly suppressed tumor growth and prolonged survival rates in PDX tumor models by decoy peptides evidently provided a new rationale for stratifying patients with MSI1/AGO2-targeted therapeutics.

Abstract

Peptide drugs that target protein–protein interactions have attracted mounting research efforts towards clinical developments over the past decades. Increasing reports have indicated that expression of Musashi 1 (MSI1) is tightly correlated to high grade of cancers as well as enrichment of cancer stem cells. Treatment failure in malignant tumors glioblastoma multiform (GBM) had also been correlated to CSC-regulating properties of MSI1. It is thus imperative to develop new therapeutics that could effectively improve current regimens used in clinics. MSI1 and AGO2 are two emerging oncogenic molecules that both contribute to GBM tumorigenesis through mRNA regulation of targets involved in apoptosis and cell cycle. In this study, we designed peptide arrays covering the C-terminus of MSI1 and identified two peptides (Pep#11 and Pep#26) that could specifically interfere with the binding with AGO2. Our Biacore analyses ascertained binding between the identified peptides and AGO2. Recombinant reporter system Gaussian luciferase and fluorescent bioconjugate techniques were employed to determine biological functions and pharmacokinetic characteristics of these two peptides. Our data suggested that Pep#11 and Pep#26 could function as decoy peptides by mimicking the interaction function of MSI1 with its binding partner AGO2 in vitro and in vivo. Further experiments using GMB animal models corroborated the ability of Pep#11 and Pep#26 in disrupting MSI1/AGO2 interaction and consequently anti-tumorigenicity and prolonged survival rates. These striking therapeutic efficacies orchestrated by the synthetic peptides were attributed to the decoy function to C-terminal MSI1, especially in malignant brain tumors and glioblastoma.