Interfering peptides targeting protein-protein interactions: the next generation of drugs?

A Transdermal Prion-Bionics Supermolecule as a RAB3A Antagonist for Enhancing Facial Youthfulness

The mechanism research of skin wrinkles, conducted on volunteers underwent high-intensity desk work and mice subjected to partial sleep deprivation, revealed a significant reduction in dermal thickness associated with the presence of wrinkles. This can be attributed to the activation of facial nerves in a state of hysteria due to an abnormally elevated interaction between SNAP25 and RAB3A proteins involved in the synaptic vesicle cycle (SVC). Facilitated by AI-assisted structural design, a refined peptide called RSIpep is developed to modulate this interaction and normalize SVC. Drawing inspiration from prions, which possess the ability to protect themselves against proteolysis and invade neighboring nerve cells through macropinocytosis, RSIpep is engineered to demonstrate a GSH-responsive reversible self-assembly into a prion-like supermolecule (RSIprion). RSIprion showcases protease resistance, micropinocytosis-dependent cellular internalization, and low adhesion with constituent molecules in the cuticle, thereby endowing it with the transdermic absorption and subsequent biofunction in redressing the frenzied SVC. As a facial mud mask, it effectively reduces periorbital and perinasal wrinkles in the human face. Collectively, RSIprion not only presents a clinical potential as an anti-wrinkle prion-like supermolecule, but also exemplifies a reproducible instance of bionic strategy-guided drug development that bestows transdermal ability upon the pharmaceutical molecule.

PRDX1 Interfering Peptide Disrupts Amino Acids 70-90 of PRDX1 to Inhibit the TLR4/NF-κB Signaling Pathway and Attenuate Neuroinflammation and Ischemic Brain Injury

Ischemic stroke ranks among the leading causes of death and disability in humans and is accompanied by motor and cognitive impairment. However, the precise mechanisms underlying injury after stroke and effective treatment strategies require further investigation. Peroxiredoxin-1 (PRDX1) triggers an extensive inflammatory cascade that plays a pivotal role in the pathology of ischemic stroke, resulting in severe brain damage from activated microglia. In the present study, we used molecular dynamics simulation and nuclear magnetic resonance to detect the interaction between PRDX1 and a specific interfering peptide. We used behavioral, morphological, and molecular experimental methods to demonstrate the effect of PRDX1-peptide on cerebral ischemia-reperfusion (I/R) in mice and to investigate the related mechanism. We found that PRDX1-peptide bound specifically to PRDX1 and improved motor and cognitive functions in I/R mice. In addition, pretreatment with PRDX1-peptide reduced the infarct area and decreased the number of apoptotic cells in the penumbra. Furthermore, PRDX1-peptide inhibited microglial activation and downregulated proinflammatory cytokines including IL-1β, IL-6, and TNF-α through inhibition of the TLR4/NF-κB signaling pathway, thereby attenuating ischemic brain injury. Our findings clarify the precise mechanism underlying PRDX1-induced inflammation after ischemic stroke and suggest that the PRDX1-peptide can significantly alleviate the postischemic inflammatory response by interfering with PRDX1 amino acids 70-90 and thereby inhibiting the TLR4/NF-κB signaling pathway. Our study provides a theoretical basis for a new therapeutic strategy to treat ischemic stroke.

A Tag-Free Platform for Synthesis and Screening of Cyclic Peptide Libraries

In the realm of high-throughput screening (HTS), macrocyclic peptide libraries traditionally necessitate decoding tags, essential for both library synthesis and identifying hit peptide sequences post-screening. Our innovation introduces a tag-free technology platform for synthesizing cyclic peptide libraries in solution and facilitates screening against biological targets to identify peptide binders through unconventional intramolecular CyClick and DeClick chemistries (CCDC) discovered through our research. This combination allows for the synthesis of diverse cyclic peptide libraries, the incorporation of various amino acids, and facile linearization and decoding of cyclic peptide binder sequences. Our sensitivity-enhancing derivatization method, utilized in tandem with nano LC-MS/MS, enables the sequencing of peptides even at exceedingly low picomolar concentrations. Employing our technology platform, we have successfully unearthed novel cyclic peptide binders against a monoclonal antibody and the first cyclic peptide binder of HIV capsid protein responsible for viral infections as validated by microscale thermal shift assays (TSA), biolayer interferometry (BLI) and functional assays.

In Silico Discovery of Stapled Peptide Inhibitor Targeting the Nur77-PPARγ Interaction and Its Anti-Breast-Cancer Efficacy

The binding of peroxisome proliferator-activated receptor γ (PPARγ) to the orphan nuclear receptor Nur77 facilitates the ubiquitination and degradation of Nur77, and leads to aberrant fatty acid uptake for breast cancer progression. Because of its crucial role in clinical prognosis, the interaction between Nur77 and PPARγ is an attractive target for anti-breast-cancer therapy. However, developing an inhibitor of the Nur77-PPARγ interaction poses a technical challenge due to the absence of the crystal structure of PPARγ and its corresponding interactive model with Nur77. Here, ST-CY14, a stapled peptide, is identified as a potent modulator of Nur77 with a KD value of 3.247 × 10-8 M by in silico analysis, rational design, and structural modification. ST-CY14 effectively increases Nur77 protein levels by blocking the Nur77-PPARγ interaction, thereby inhibiting lipid metabolism in breast tumor cells. Notably, ST-CY14 significantly suppresses breast cancer growth and bone metastasis in mice. The findings demonstrate the feasibility of exploiting directly Nur77-PPARγ interaction in breast cancer, and generate what to the best knowledge is the first direct inhibitor of the Nur77-PPARγ interaction available for impeding fatty acid uptake and therapeutic development.

Interaction between Yersinia pestis Ail Outer Membrane Protein and the C-Terminal Domain of Human Vitronectin

Yersinia pestis, the causative agent of plague, is capable of evading the human immune system response by recruiting the plasma circulating vitronectin proteins, which act as a shield and avoid its lysis. Vitronectin recruitment is mediated by its interaction with the bacterial transmembrane protein Ail, protruding from the Y. pestis outer membrane. By using all-atom long-scale molecular dynamic simulations of Ail embedded in a realistic model of the bacterial membrane, we have shown that vitronectin forms a stable complex, mediated by interactions between the disordered moieties of the two proteins. The main amino acids driving the complexation have also been evidenced, thus favoring the possible rational design of specific peptides which, by inhibiting vitronectin recruitment, could act as original antibacterial agents.

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein-protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the conformational plasticity of peptides. The discovery of bioactive peptides, working against disease-relevant protein targets, generally requires the high-throughput screening of large libraries, and in silico approaches are highly exploited for their low-cost incidence and efficiency. The present review reports on the potential challenges linked to the employment of peptides as therapeutics and describes computational approaches, mainly structure-based virtual screening (SBVS), to support the identification of novel peptides for therapeutic implementations. Cutting-edge SBVS strategies are reviewed along with examples of applications focused on diverse classes of bioactive peptides (i.e., anticancer, antimicrobial/antiviral peptides, peptides blocking amyloid fiber formation).

DeepProSite: structure-aware protein binding site prediction using ESMFold and pretrained language model

MOTIVATION

Identifying the functional sites of a protein, such as the binding sites of proteins, peptides, or other biological components, is crucial for understanding related biological processes and drug design. However, existing sequence-based methods have limited predictive accuracy, as they only consider sequence-adjacent contextual features and lack structural information.

RESULTS

In this study, DeepProSite is presented as a new framework for identifying protein binding site that utilizes protein structure and sequence information. DeepProSite first generates protein structures from ESMFold and sequence representations from pretrained language models. It then uses Graph Transformer and formulates binding site predictions as graph node classifications. In predicting protein-protein/peptide binding sites, DeepProSite outperforms state-of-the-art sequence- and structure-based methods on most metrics. Moreover, DeepProSite maintains its performance when predicting unbound structures, in contrast to competing structure-based prediction methods. DeepProSite is also extended to the prediction of binding sites for nucleic acids and other ligands, verifying its generalization capability. Finally, an online server for predicting multiple types of residue is established as the implementation of the proposed DeepProSite.

AVAILABILITY AND IMPLEMENTATION

The datasets and source codes can be accessed at https://github.com/WeiLab-Biology/DeepProSite. The proposed DeepProSite can be accessed at https://inner.wei-group.net/DeepProSite/.

Rapid Formation of Intramolecular Disulfide Bridges using Light: An Efficient Method to Control the Conformation and Function of Bioactive Peptides

Disulfide bonds are widely found in natural peptides and play a pivotal role in stabilizing their secondary structures, which are highly associated with their biological functions. Herein, we introduce a light-mediated strategy to effectively control the formation of disulfides. Our strategy is based on 2-nitroveratryl (oNv), a widely used photolabile motif, which serves both as a photocaging group and an oxidant (after photolysis). We demonstrated that irradiation of oNv-caged thiols with UV light could release free thiols that are rapidly oxidized by locally released byproduct nitrosoarene, leading to a "break-to-bond" fashion. This strategy is highlighted by the in situ restoration of the antimicrobial peptide tachyplesin I (TPI) from its external disulfide-caged analogue TPI-1. TPI-1 exhibits a distorted structure and a diminished function. However, upon irradiation, the β-hairpin structure and membrane activity of TPI were largely restored via rapid intramolecular disulfide formation. Our study proposes a powerful method to regulate the conformation and function of peptides in a spatiotemporal manner, which has significant potential for the design of disulfide-centered light-responsive systems.

Small molecules targeting protein-protein interactions for cancer therapy

Protein-protein interactions (PPIs) are fundamental to many biological processes that play an important role in the occurrence and development of a variety of diseases. Targeting the interaction between tumour-related proteins with emerging small molecule drugs has become an attractive approach for treatment of human diseases, especially tumours. Encouragingly, selective PPI-based therapeutic agents have been rapidly advancing over the past decade, providing promising perspectives for novel therapies for patients with cancer. In this review we comprehensively clarify the discovery and development of small molecule modulators of PPIs from multiple aspects, focusing on PPIs in disease, drug design and discovery strategies, structure-activity relationships, inherent dilemmas, and future directions.

Developing a peptide to disrupt cohesin head domain interactions

Cohesin mediates the 3-D structure of chromatin and is involved in maintaining genome stability and function. The cohesin core comprises Smc1 and Smc3, elongated-shaped proteins that dimerize through globular domains at their edges, called head and hinge. ATP binding to the Smc heads induces their dimerization and the formation of two active sites, while ATP hydrolysis results in head disengagement. This ATPase cycle is essential for driving cohesin activity. We report on the development of the first cohesin-inhibiting peptide (CIP). The CIP binds Smc3 in vitro and inhibits the ATPase activity of the holocomplex. Treating yeast cells with the CIP prevents cohesin's tethering activity and, interestingly, leads to the accumulation of cohesin on chromatin. CIP3 also affects cohesin activity in human cells. Altogether, we demonstrate the power of peptides to inhibit cohesin in cells and discuss the potential application of CIPs as a therapeutic approach.

Molecular Design of Cyclic Peptides with Cell Membrane Permeability and Development of MDMX-p53 Inhibitor

Cyclic peptides have been expected to be one of the modalities of intracellular protein-protein interaction (PPI) inhibitors, but they are generally known to have low cell membrane permeability. In this study, we focused on the conformation of cyclic peptides in the cell membrane to determine the requirement for their cell membrane permeability through passive diffusion. Utilizing the requirement, we searched for structures with high affinity for MDMX via computational chemistry and acquired cyclic peptide 19 (Papp = 0.80 × 10-6 cm s-1, IC50 = 0.07 μM).

Proteolytically Stable Diaza-Peptide Foldamers Mimic Helical Hot Spots of Protein-Protein Interactions and Act as Natural Chaperones

A novel class of peptidomimetic foldamers based on diaza-peptide units are reported. Circular dichroism, attenuated total reflection -Fourier transform infrared, NMR, and molecular dynamics studies demonstrate that unlike the natural parent nonapeptide, the specific incorporation of one diaza-peptide unit at the N-terminus allows helical folding in water, which is further reinforced by the introduction of a second unit at the C-terminus. The ability of these foldamers to resist proteolysis, to mimic the small helical hot spot of transthyretin-amyloid β (Aβ) cross-interaction, and to decrease pathological Aβ aggregation demonstrates that the introduction of diaza-peptide units is a valid approach for designing mimics or inhibitors of protein-protein interaction and other therapeutic peptidomimetics. This study also reveals that small peptide foldamers can play the same role as physiological chaperone proteins and opens a new way to design inhibitors of amyloid protein aggregation, a hallmark of more than 20 serious human diseases such as Alzheimer's disease.

STAP-2-Derived Peptide Suppresses TCR-Mediated Signals to Initiate Immune Responses

Signal-transducing adaptor protein-2 (STAP-2) is an adaptor protein that contains pleckstrin and Src homology 2-like domains, as well as a proline-rich region in its C-terminal region. Our previous study demonstrated that STAP-2 positively regulates TCR signaling by associating with TCR-proximal CD3ζ ITAMs and the lymphocyte-specific protein tyrosine kinase. In this study, we identify the STAP-2 interacting regions of CD3ζ ITAMs and show that the STAP-2-derived synthetic peptide (iSP2) directly interacts with the ITAM sequence and blocks the interactions between STAP-2 and CD3ζ ITAMs. Cell-penetrating iSP2 was delivered into human and murine T cells. iSP2 suppressed cell proliferation and TCR-induced IL-2 production. Importantly, iSP2 treatment suppressed TCR-mediated activation of naive CD4+ T cells and decreased immune responses in CD4+ T cell-mediated experimental autoimmune encephalomyelitis. It is likely that iSP2 is a novel immunomodulatory tool that modulates STAP-2-mediated activation of TCR signaling and represses the progression of autoimmune diseases.

Development of an interfering peptide M1-20 with potent anti-cancer effects by targeting FOXM1

Disrupting protein-protein interactions (PPIs) has emerged as a promising strategy for cancer drug development. Interfering peptides disrupting PPIs can be rationally designed based on the structures of natural sequences mediating these interactions. Transcription factor FOXM1 overexpresses in multiple cancers and is considered an effective target for cancer therapeutic drug development. Using a rational design approach, we have generated a peptide library from the FOXM1 C-terminal sequence and screened FOXM1-binding peptides. Combining FOXM1 binding and cell inhibitory results, we have obtained a FOXM1-targeting interfering peptide M1-20 that is optimized from the natural parent peptide to the D-retro-inverso peptide. With improved stability characteristics, M1-20 inhibits proliferation and migration, and induces apoptosis of cancer cells. Mechanistically, M1-20 inhibits FOXM1 transcriptional activities by disrupting its interaction between the MuvB complex and the transcriptional co-activator CBP. These are consistent with the results that M1-20 suppresses cancer progression and metastasis without noticeable toxic and side effects in wild-type mice. These findings reveal that M1-20 has the potential to be developed as an anti-cancer drug candidate targeting FOXM1.

The development of an anti-cancer peptide M1-21 targeting transcription factor FOXM1

BACKGROUND

Transcription factor FOXM1 is a potential target for anti-cancer drug development. An interfering peptide M1-21, targeting FOXM1 and FOXM1-interacting proteins, is developed and its anti-cancer efficacy is evaluated.

METHODS

FOXM1 C-terminus-binding peptides are screened by in silico protocols from the peptide library of FOXM1 (1-138aa) and confirmed by cellular experiments. The selected peptide is synthesized into its D-retro-inverso (DRI) form by fusing a TAT cell-penetrating sequence. Anti-cancer activities are evaluated in vitro and in vivo with tumor-grafted nude mice, spontaneous breast cancer mice, and wild-type metastasis-tracing mice. Anti-cancer mechanisms are analyzed. Distribution and safety profiles in mice are evaluated.

RESULTS

With improved stability and cell inhibitory activity compared to the parent peptide, M1-21 binds to multiple regions of FOXM1 and interferes with protein-protein interactions between FOXM1 and its various known partner proteins, including PLK1, LIN9 and B-MYB of the MuvB complex, and β-catenin. Consequently, M1-21 inhibits FOXM1-related transcriptional activities and FOXM1-mediated nuclear importation of β-catenin and β-catenin transcriptional activities. M1-21 inhibits multiple types of cancer (20 µM in vitro or 30 mg/kg in vivo) by preventing proliferation, migration, and WNT signaling. Distribution and safety profiles of M1-21 are favorable (broad distribution and > 15 h stability in mice) and the tested non-severely toxic dose reaches 200 mg/kg in mice. M1-21 also has low hemolytic toxicity and immunogenicity in mice.

CONCLUSIONS

M1-21 is a promising interfering peptide targeting FOXM1 for the development of anti-cancer drugs.

The WW domain of IQGAP1 binds directly to the p110α catalytic subunit of PI 3-kinase

IQGAP1 is a multi-domain cancer-associated protein that serves as a scaffold protein for multiple signaling pathways. Numerous binding partners have been found for the calponin homology, IQ and GAP-related domains in IQGAP1. Identification of a binding partner for its WW domain has proven elusive, however, even though a cell-penetrating peptide derived from this domain has marked anti-tumor activity. Here, using in vitro binding assays with human proteins and co-precipitation from human cells, we show that the WW domain of human IQGAP1 binds directly to the p110α catalytic subunit of phosphoinositide 3-kinase (PI3K). In contrast, the WW domain does not bind to ERK1/2, MEK1/2, or the p85α regulatory subunit of PI3K when p85α is expressed alone. However, the WW domain is able to bind to the p110α/p85α heterodimer when both subunits are co-expressed, as well as to the mutationally activated p110α/p65α heterodimer. We present a model of the structure of the IQGAP1 WW domain, and experimentally identify key residues in the hydrophobic core and beta strands of the WW domain that are required for binding to p110α. These findings contribute to a more precise understanding of IQGAP1-mediated scaffolding, and of how IQGAP1-derived therapeutic peptides might inhibit tumorigenesis.

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

Analysis of critical protein-protein interactions of SARS-CoV-2 capping and proofreading molecular machineries towards designing dual target inhibitory peptides

In recent years, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as the cause of the coronavirus disease (COVID-19) global pandemic, and its variants, especially those with higher transmissibility and substantial immune evasion, have highlighted the imperative for developing novel therapeutics as sustainable solutions other than vaccination to combat coronaviruses (CoVs). Beside receptor recognition and virus entry, members of the SARS-CoV-2 replication/transcription complex are promising targets for designing antivirals. Here, the interacting residues that mediate protein-protein interactions (PPIs) of nsp10 with nsp16 and nsp14 were comprehensively analyzed, and the key residues' interaction maps, interaction energies, structural networks, and dynamics were investigated. Nsp10 stimulates both nsp14's exoribonuclease (ExoN) and nsp16's 2'O-methyltransferase (2'O-MTase). Nsp14 ExoN is an RNA proofreading enzyme that supports replication fidelity. Nsp16 2'O-MTase is responsible for the completion of RNA capping to ensure efficient replication and translation and escape from the host cell's innate immune system. The results of the PPIs analysis proposed crucial information with implications for designing SARS-CoV-2 antiviral drugs. Based on the predicted shared protein-protein interfaces of the nsp16-nsp10 and nsp14-nsp10 interactions, a set of dual-target peptide inhibitors was designed. The designed peptides were evaluated by molecular docking, peptide-protein interaction analysis, and free energy calculations, and then further optimized by in silico saturation mutagenesis. Based on the predicted evolutionary conservation of the interacted target residues among CoVs, the designed peptides have the potential to be developed as dual target pan-coronavirus inhibitors.

Customized Reversible Stapling for Selective Delivery of Bioactive Peptides

We have developed a new concept for reversible peptide stapling that involves macrocyclization between two amino groups and decyclization promoted via dual 1,4-elimination. Depending on the trigger moiety, this strategy could be employed to selectively deliver peptides to either intracellular or extracellular targets. As a proof of concept, a peptide inhibitor targeting a lysine-specific demethylase 1 (LSD1) was temporarily cyclized to enhance its stability and ability to cross the cell membrane. Once inside the cells, the biologically active linear peptide was released under reducing environment. Moreover, we have developed reversibly stapled peptides using antimicrobial peptides (RStAMPs) whose bioactive helical conformation can be temporarily destabilized by stapling the peptide backbone. The resulting helix-distorted RStAMPs are nontoxic and highly resistant to protease hydrolysis, while at the infection site, RStAMPs can be rapidly activated by the overproduced H₂O₂ through the dual 1,4-elimination. The latter restored the helical structure of the native peptide and its antimicrobial activity. This work illustrates a highly valuable macrocyclization strategy for the peptide community and should greatly benefit the field of peptide delivery.

Chemical Wastes in the Peptide Synthesis Process and Ways to Reduce Them

In recent decades, a growing interest has been observed among pharmaceutical companies in producing and selling 80 FDA-approved therapeutic peptides. However, there are many drawbacks to peptide synthesis at the academic and industrial scales, involving the use of large amounts of highly hazardous coupling reagents and solvents. This review focuses on hideous and observant wastes produced before, during, and after peptide synthesis and proposes some solutions to reduce them.

Binding and Kinetic Analysis of Human Protein Phosphatase PP2A Interactions with Caspase 9 Protein and the Interfering Peptide C9h

The serine/threonine phosphatase PP2A and the cysteine protease Caspase 9 are two proteins involved in physiological and pathological processes, including cancer and apoptosis. We previously demonstrated the interaction between Caspase 9 and PP2A and identified the C9h peptide, corresponding to the binding site of Caspase 9 to PP2A. This interfering peptide can modulate Caspase 9/PP2A interaction leading to a strong therapeutic effect in vitro and in vivo in mouse models of tumor progression. In this manuscript, we investigate (I) the peptide binding to PP2A combining docking with molecular dynamics and (II) the secondary structure of the peptide using CD spectroscopy. Additionally, we compare the binding affinity, using biolayer interferometry, of the wild-type protein PP2A with Caspase 9 and vice versa to that observed between the PP2A protein and the interfering peptide C9h. This result strongly encourages the use of peptides as new therapeutics against cancer, as shown for the C9h peptide already in clinical trial.

Accurate Prediction for Protein-Peptide Binding Based on High-Temperature Molecular Dynamics Simulations

The structural characterization of protein-peptide interactions is fundamental to elucidating biological processes and designing peptide drugs. Molecular dynamics (MD) simulations are extensively used to study biomolecular systems. However, simulating the protein-peptide binding process is usually quite expensive. Based on our previous studies, herein, we propose a simple and effective method to predict the binding site and pose of the peptide simultaneously using high-temperature (high-T) MD simulations with the RSFF2C force field. Thousands of binding events (nonspecific or specific) can be sampled during microseconds of high-T MD. From density-based clustering analysis, the structures of all of the 12 complexes (nine with linear peptides and three with cyclic peptides) can be successfully predicted with root-mean-square deviation (RMSD) < 2.5 Å. By directly simulating the process of the ligand binding onto the receptor, our method approaches experimental precision for the first time, significantly surpassing previous protein-peptide docking methods in terms of accuracy.

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.

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.

Cell-Penetrating Peptide TAT-HuR-HNS3 Suppresses Proinflammatory Gene Expression via Competitively Blocking Interaction of HuR with Its Partners

Proinflammatory cytokines/chemokines are commonly regulated by RNA-binding proteins at posttranscriptional levels. Human Ag R (HuR)/embryonic lethal abnormal vision-like 1 (ELAVL1) is one of the well-characterized RNA-binding proteins that increases the stability of short-lived mRNAs, which encode proinflammatory mediators. HuR employs its nucleocytoplasmic shuttling sequence (HNS) domain, interacting with poly(ADP-ribose) polymerase 1 (PARP1), which accounts for the enhanced poly-ADP-ribosylation and cytoplasmic shuttling of HuR. Also by using its HNS domain, HuR undergoes dimerization/oligomerization, underlying the increased binding of HuR with proinflammatory cytokine/chemokine mRNAs and the disassociation of the miRNA-induced silencing complex from the targets. Therefore, competitively blocking the interactions of HuR with its partners may suppress proinflammatory mediator production. In this study, peptides derived from the sequence of the HuR-HNS domain were synthesized, and their effects on interfering HuR interacting with PARP1 and HuR itself were analyzed. Moreover, cell-penetrating TAT-HuR-HNS3 was delivered into human and mouse cells or administered into mouse lungs with or without exposure of TNF-α or LPS. mRNA levels of proinflammatory mediators as well as neutrophil infiltration were evaluated. We showed that TAT-HuR-HNS3 interrupts HuR-PARP1 interaction and therefore results in a lowered poly-ADP-ribosylation level and decreased cytoplasmic distribution of HuR. TAT-HuR-HNS3 also blocks HuR dimerization and promotes Argonaute 2-based miRNA-induced silencing complex binding to the targets. Moreover, TAT-HuR-HNS3 lowers mRNA stability of proinflammatory mediators in TNF-α-treated epithelial cells and macrophages, and it decreases TNF-α-induced inflammatory responses in lungs of experimental animals. Thus, TAT-HuR-HNS3 is a promising lead peptide for the development of inhibitors to treat inflammation-related diseases.

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

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

PepSeA: Peptide Sequence Alignment and Visualization Tools to Enable Lead Optimization

Therapeutic peptides offer potential advantages over small molecules in terms of selectivity, affinity, and their ability to target "undruggable" proteins that are associated with a wide range of pathologies. Despite their importance, current molecular design capabilities that inform medicinal chemistry decisions on peptide programs are limited. More specifically, there are unmet needs for structure-activity relationship (SAR) analysis and visualization of linear, cyclic, and cross-linked peptides containing non-natural motifs, which are widely used in drug discovery. To bridge this gap, we developed PepSeA (Peptide Sequence Alignment and Visualization), an open-source, freely available package of sequence-based tools (https://github.com/Merck/PepSeA). PepSeA enables multiple sequence alignment of non-natural amino acids and enhanced visualization with the hierarchical editing language for macromolecules (HELM). Via stepwise SAR analysis of a ChEMBL peptide data set, we demonstrate the utility of PepSeA to accelerate decision making in lead optimization campaigns in pharmaceutical setting. PepSeA represents an initial attempt to expand cheminformatics capabilities for therapeutic peptides and to enable rapid and more efficient design-make-test cycles.

PEPscan: A Broad Spectrum Approach for the Characterization of Protein-Binder Interactions?

In a previous study, we have shown that PEPscan can provide a cheap and rapid means to identify candidate interfering peptides (IPs), i.e., peptides able to disrupt a target protein-protein interaction. PEPscan was shown to be effective in identifying a limited number of candidate IPs specific to the target interaction. Here, we investigate the results of 14 new PEPscan experiments for protein complexes of known 3D structures. We show that for almost all complexes, PEPscan is able to identify candidate IPs that are located at the protein-protein interface. The information it provides about the binding site seems, however, too ambiguous to be exploited in a simple manner to assist the modeling of protein complexes. Moreover, these candidates are associated with false positives. For these, we suggest they could correspond to non-specific binders, which leaves room for further optimization of the PEPscan protocol. Another unexpected advance comes from the observation of the applicability of PEPscan for polysaccharides and labeled peptides, suggesting that PEPscan could become a large spectrum approach to investigate protein-binder interactions, the binder not necessarily being a protein.

Predicting Protein-Peptide Complex Structures by Accounting for Peptide Flexibility and the Physicochemical Environment

Predicting protein-peptide complex structures is crucial to the understanding of a vast variety of peptide-mediated cellular processes and to peptide-based drug development. Peptide flexibility and binding mode ranking are the two major challenges for protein-peptide complex structure prediction. Peptides are highly flexible molecules, and therefore, brute-force modeling of peptide conformations of interest in protein-peptide docking is beyond current computing power. Inspired by the fact that the protein-peptide binding process is like protein folding, we developed a novel strategy, named MDockPeP2, which tries to address these challenges using physicochemical information embedded in abundant monomeric proteins with an exhaustive search strategy, in combination with an integrated global search and a local flexible minimization method. Only the peptide sequence and the protein crystal structure are required. The method was systemically assessed using a newly constructed structural database of 89 nonredundant protein-peptide complexes with the peptide sequence length ranging from 5 to 29 in which about half of the peptides are longer than 15 residues. MDockPeP2 yielded a total success rate of 58.4% (70.8, 79.8%) for the bound docking (i.e., with the bound receptor and fully flexible peptides) and 19.0% (44.8, 70.7%) for the challenging unbound docking when top 10 (100, 1000) models were considered for each prediction. MDockPeP2 achieved significantly higher success rates on two other datasets, peptiDB and LEADS-PEP, which contain only short- and medium-size peptides (≤ 15 residues). For peptiDB, our method obtained a success rate of 62.0% for the bound docking and 35.9% for the unbound docking when the top 10 models were considered. For LEADS-PEP, MDockPeP2 achieved a success rate of 69.8% when the top 10 models were considered. The program is available at https://zougrouptoolkit.missouri.edu/mdockpep2/download.html.

Peptide OPTX-1 From Ornithodoros papillipes Tick Inhibits the pS273R Protease of African Swine Fever Virus

African swine fever virus (ASFV) is a large double-stranded DNA virus and causes high mortality in swine. ASFV can be transmitted by biological vectors, including soft ticks in genus Ornithodoros but not hard ticks. However, the underlying mechanisms evolved in the vectorial capacity of soft ticks are not well-understood. Here, we found that a defensin-like peptide toxin OPTX-1 identified from Ornithodoros papillipes inhibits the enzyme activity of the ASFV pS273R protease with a Ki =0.821±0.526μM and shows inhibitory activity on the replication of ASFV. The analogs of OPTX-1 from hard ticks show more inhibitory efficient on pS273R protease. Considering that ticks are blood-sucking animals, we tested the effects of OPTX-1 and its analogs on the coagulation system. At last, top 3D structures represented surface analyses of the binding sites of pS273R with different inhibitors that were obtained by molecular docking based on known structural information. In summary, our study provides evidence that different inhibitory efficiencies between soft tick-derived OPTX-1 and hard tick-derived defensin-like peptides may determine the vector and reservoir competence of ticks.

Penta-peptide ATN-161 based neutralization mechanism of SARS-CoV-2 spike protein

SARS-CoV-2 has become a big challenge for the scientific community worldwide. SARS-CoV-2 enters into the host cell by the spike protein binding with an ACE2 receptor present on the host cell. Developing safe and effective inhibitor appears an urgent need to interrupt the binding of SARS-CoV-2 spike protein with ACE2 receptor in order to reduce the SARS-CoV-2 infection. We have examined the penta-peptide ATN-161 as potential inhibitor of ACE2 and SARS-CoV-2 spike protein binding, where ATN-161 has been commercially approved for the safety and possess high affinity and specificity towards the receptor binding domain (RBD) of S1 subunit in SARS-CoV-2 spike protein. We carried out experiments and confirmed these phenomena that the virus bindings were indeed minimized. ATN-161 peptide can be used as an inhibitor of protein-protein interaction (PPI) stands as a crucial interaction in biological systems. The molecular docking finding suggests that the binding energy of the ACE2-spike protein complex is reduced in the presence of ATN-161. Protein-protein docking binding energy (-40.50 kcal/mol) of the spike glycoprotein toward the human ACE2 and binding of ATN-161 at their binding interface reduced the biding energy (-26.25 kcal/mol). The finding of this study suggests that ATN-161 peptide can mask the RBD of the spike protein and be considered as a neutralizing candidate by binding with the ACE2 receptor. Peptide-based masking of spike S1 protein (RBD) and its neutralization is a highly promising strategy to prevent virus penetration into the host cell. Thus masking of the RBD leads to the loss of receptor recognition property which can reduce the chance of infection host cells.

Wandering beyond small molecules: peptides as allosteric protein modulators

Recent years have seen the rise of allosteric modulation as an innovative approach for drug design and discovery, efforts which culminated in the development of several clinical candidates. Allosteric modulation of many drug targets, including mainly membrane-embedded receptors, have been vastly explored through small molecule screening campaigns, but much less attention has been paid to peptide-based allosteric modulators. However, peptides have a significant impact on the pharmaceutical industry due to the typically higher potency and selectivity for their targets, as compared with small molecule therapeutics. Therefore, peptides represent one of the most promising classes of molecules that can modulate key biological pathways. Here, we report on the allosteric modulation of proteins (ranging from G protein-coupled receptors to specific protein-protein interactions) by peptides for applications in drug discovery.

Peptides derived from the SARS-CoV-2 receptor binding motif bind to ACE2 but do not block ACE2-mediated host cell entry or pro-inflammatory cytokine induction

SARS-CoV-2 viral attachment and entry into host cells is mediated by a direct interaction between viral spike glycoproteins and membrane bound angiotensin-converting enzyme 2 (ACE2). The receptor binding motif (RBM), located within the S1 subunit of the spike protein, incorporates the majority of known ACE2 contact residues responsible for high affinity binding and associated virulence. Observation of existing crystal structures of the SARS-CoV-2 receptor binding domain (SRBD)-ACE2 interface, combined with peptide array screening, allowed us to define a series of linear native RBM-derived peptides that were selected as potential antiviral decoy sequences with the aim of directly binding ACE2 and attenuating viral cell entry. RBM1 (16mer): S443KVGGNYNYLYRLFRK458, RBM2A (25mer): E484GFNCYFPLQSYGFQPTNGVGYQPY508, RBM2B (20mer): F456NCYFPLQSYGFQPTNGVGY505 and RBM2A-Sc (25mer): NYGLQGSPFGYQETPYPFCNFVQYG. Data from fluorescence polarisation experiments suggested direct binding between RBM peptides and ACE2, with binding affinities ranging from the high nM to low μM range (Kd = 0.207-1.206 μM). However, the RBM peptides demonstrated only modest effects in preventing SRBD internalisation and showed no antiviral activity in a spike protein trimer neutralisation assay. The RBM peptides also failed to suppress S1-protein mediated inflammation in an endogenously expressing ACE2 human cell line. We conclude that linear native RBM-derived peptides are unable to outcompete viral spike protein for binding to ACE2 and therefore represent a suboptimal approach to inhibiting SARS-CoV-2 viral cell entry. These findings reinforce the notion that larger biologics (such as soluble ACE2, 'miniproteins', nanobodies and antibodies) are likely better suited as SARS-CoV-2 cell-entry inhibitors than short-sequence linear peptides.

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.

Modulation of serine/threonine-protein phosphatase 1 (PP1) complexes: A promising approach in cancer treatment

Cancer is the second leading cause of death worldwide. Despite the availability of numerous therapeutic options, tumor heterogeneity and chemoresistance have limited the success of these treatments, and the development of effective anticancer therapies remains a major focus in oncology research. The serine/threonine-protein phosphatase 1 (PP1) and its complexes have been recognized as potential drug targets. Research on the modulation of PP1 complexes is currently at an early stage, but has immense potential. Chemically diverse compounds have been developed to disrupt or stabilize different PP1 complexes in various cancer types, with the objective of inhibiting disease progression. Beneficial results obtained in vitro now require further pre-clinical and clinical validation. In conclusion, the modulation of PP1 complexes seems to be a promising, albeit challenging, therapeutic strategy for cancer.

Concise solid-phase synthesis enables derivatisation of YEATS domain cyclopeptide inhibitors for improved cellular uptake

YEATS domains, which are newly identified epigenetic readers of histone lysine acetylation and crotonylation, have emerged as promising anti-cancer drug targets. We recently developed AF9 YEATS domain-selective cyclopeptide inhibitors. However, the cumbersome and time-consuming synthesis of the cyclopeptides limited further structural derivatisation and applications. Here, we reported a concise method for the solid-phase synthesis of the cyclopeptides, which substantially reduced the amount of time required for the preparation of the cyclopeptides and led to a higher overall yield. Moreover, this new synthetic route also allowed further derivatisation of the cyclopeptides with various functional modules, including fluorescent dye and cell-penetrating peptide. We demonstrated that the conjugation of the cyclopeptide with cell-penetrating peptide TAT led to a significantly increased cellular uptake.

Development of oxetane modified building blocks for peptide synthesis

The synthesis and use of oxetane modified dipeptide building blocks in solution and solid-phase peptide synthesis (SPPS) is reported. The preparation of building blocks containing non-glycine residues at the N-terminus in a stereochemically controlled manner is challenging. Here, a practical 4-step route to such building blocks is demonstrated, through the synthesis of dipeptides containing contiguous alanine residues. The incorporation of these new derivatives at specific sites along the backbone of an alanine-rich peptide sequence containing eighteen amino acids is demonstrated via solid-phase peptide synthesis. Additionally, new methods to enable the incorporation of all 20 of the proteinogenic amino acids into such dipeptide building blocks are reported through modifications of the synthetic route (for Cys and Met) and by changes to the protecting group strategy (for His, Ser and Thr).

Protein-Protein Interface Topology as a Predictor of Secondary Structure and Molecular Function Using Convolutional Deep Learning

To power the specific recognition and binding of protein partners into functional complexes, a wealth of information about the structure and function of the partners is necessarily encoded into the global shape of protein-protein interfaces and their local topological features. To identify whether this is the case, this study uses convolutional deep learning methods (typically leveraged for 2D image recognition) on 3D voxel representations of protein-protein interfaces colored by burial depth. A novel two-stage network fed with voxelizations of each interface at two distinct resolutions achieves balance between performance and computational cost. From the shape of the interfaces, the network tries to predict the presence of secondary structure motifs at the interface and the molecular function of the corresponding complex. Secondary structure and certain classes of function are found to be very well predicted, validating the hypothesis that interface shape is a conveyor of higher-level information. Interface patterns triggering the recognition of specific classes are also identified and described.

Photoreceptor Phosphodiesterase (PDE6): Structure, Regulatory Mechanisms, and Implications for Treatment of Retinal Diseases

The photoreceptor phosphodiesterase (PDE6) is a member of large family of Class I phosphodiesterases responsible for hydrolyzing the second messengers cAMP and cGMP. PDE6 consists of two catalytic subunits and two inhibitory subunits that form a tetrameric protein. PDE6 is a peripheral membrane protein that is localized to the signal-transducing compartment of rod and cone photoreceptors. As the central effector enzyme of the G-protein coupled visual transduction pathway, activation of PDE6 catalysis causes a rapid decrease in cGMP levels that results in closure of cGMP-gated ion channels in the photoreceptor plasma membrane. Because of its importance in the phototransduction pathway, mutations in PDE6 genes result in various retinal diseases that currently lack therapeutic treatment strategies due to inadequate knowledge of the structure, function, and regulation of this enzyme. This review focuses on recent progress in understanding the structure of the regulatory and catalytic domains of the PDE6 holoenzyme, the central role of the multi-functional inhibitory γ-subunit, the mechanism of activation by the heterotrimeric G protein, transducin, and future directions for pharmacological interventions to treat retinal degenerative diseases arising from mutations in the PDE6 genes.

Pepscan Approach for the Identification of Protein-Protein Interfaces: Lessons from Experiment

PEPscan is an old approach that has recently gained renewed interest for the identification of interfering peptides (IPs), i.e., peptides able to interfere with protein-protein interactions (PPIs). Its principle is to slice a protein sequence as a series of short overlapping peptides that are synthesized on a peptide array and tested for their ability to bind a partner, with positive spots corresponding to candidate IPs. PEPscan has been applied with a rather large success in various contexts, but the structural determinants underlying this success remain obscure. Here, we analyze the results of 14 PEPscan experiments, and confront the in vitro results with the available structural information. PEPscan identifies candidate IPs in limited numbers that in all cases correspond to solvent-accessible regions of the structures, their location at the protein-protein interface remaining to be further demonstrated. A strong point of PEPscan seems to be its ability to identify specific IPs. IPs identified from the same protein differ depending on the target PPI, and correspond to patches not frequently involved in the interactions seen in the 3D structures available. Overall, PEPscan seems to provide a cheap and rapid manner to identify candidate IPs, that also comes with room for improvement.

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.

Deconvoluting complex protein interaction networks through reductionist strategies in peptide biochemistry: Modern approaches and research questions

Following the decoding of the first human genome, researchers have vastly improved their understanding of cell biology and its regulation. As a result, it has become clear that it is not merely genetic information, but the aberrant changes in the functionality and connectivity of its encoded proteins that drive cell response to periods of stress and external cues. Therefore, proper utilization of refined methods that help to describe protein signalling or regulatory networks (i.e., functional connectivity), can help us understand how change in the signalling landscape effects the cell. However, given the vast complexity in 'how and when' proteins communicate or interact with each other, it is extremely difficult to define, characterize, and understand these interaction networks in a tangible manner. Herein lies the challenge of tackling the functional proteome; its regulation is encoded in multiple layers of interaction, chemical modification and cell compartmentalization. To address and refine simple research questions, modern reductionist strategies in protein biochemistry have successfully used peptide-based experiments; their summation helping to simplify the overall complexity of these protein interaction networks. In this way, peptides are powerful tools used in fundamental research that can be readily applied to comparative biochemical research. Understanding and defining how proteins interact is one of the key aspects towards understanding how the proteome functions. To date, reductionist peptide-based research has helped to address a wide range of proteome-related research questions, including the prediction of enzymes substrates, identification of posttranslational modifications, and the annotation of protein interaction partners. Peptide arrays have been used to identify the binding specificity of reader domains, which are able to recognise the posttranslational modifications; forming dynamic protein interactions that are dependent on modification state. Finally, representing one of the fastest growing classes of inhibitor molecules, peptides are now begin explored as "disruptors" of protein-protein interactions or enzyme activity. Collectively, this review will discuss the use of peptides, peptide arrays, peptide-oriented computational biochemistry as modern reductionist strategies in deconvoluting the functional proteome.

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

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

Photoreceptor phosphodiesterase (PDE6): activation and inactivation mechanisms during visual transduction in rods and cones

Rod and cone photoreceptors of the vertebrate retina utilize cGMP as the primary intracellular messenger for the visual signaling pathway that converts a light stimulus into an electrical response. cGMP metabolism in the signal-transducing photoreceptor outer segment reflects the balance of cGMP synthesis (catalyzed by guanylyl cyclase) and degradation (catalyzed by the photoreceptor phosphodiesterase, PDE6). Upon light stimulation, rapid activation of PDE6 by the heterotrimeric G-protein (transducin) triggers a dramatic drop in cGMP levels that lead to cell hyperpolarization. Following cessation of the light stimulus, the lifetime of activated PDE6 is also precisely regulated by additional processes. This review summarizes recent advances in the structural characterization of the rod and cone PDE6 catalytic and regulatory subunits in the context of previous biochemical studies of the enzymological properties and allosteric regulation of PDE6. Emphasis is given to recent advances in understanding the structural and conformational changes underlying the mechanism by which the activated transducin α-subunit binds to-and relieves inhibition of-PDE6 catalysis that is controlled by its intrinsically disordered, inhibitory γ-subunit. The role of the regulator of G-protein signaling 9-1 (RGS9-1) in regulating the lifetime of the transducin-PDE6 is also briefly covered. The therapeutic potential of pharmacological compounds acting as inhibitors or activators targeting PDE6 is discussed in the context of inherited retinal diseases resulting from mutations in rod and cone PDE6 genes as well as other inherited defects that arise from excessive cGMP accumulation in retinal photoreceptor cells.

Modulators of protein-protein interactions as antimicrobial agents

Protein-Protein interactions (PPIs) are involved in a myriad of cellular processes in all living organisms and the modulation of PPIs is already under investigation for the development of new drugs targeting cancers, autoimmune diseases and viruses. PPIs are also involved in the regulation of vital functions in bacteria and, therefore, targeting bacterial PPIs offers an attractive strategy for the development of antibiotics with novel modes of action. The latter are urgently needed to tackle multidrug-resistant and multidrug-tolerant bacteria. In this review, we describe recent developments in the modulation of PPIs in pathogenic bacteria for antibiotic development, including advanced small molecule and peptide inhibitors acting on bacterial PPIs involved in division, replication and transcription, outer membrane protein biogenesis, with an additional focus on toxin-antitoxin systems as upcoming drug targets.

Structural Characterization of Receptor-Receptor Interactions in the Allosteric Modulation of G Protein-Coupled Receptor (GPCR) Dimers

G protein-coupled receptor (GPCR) oligomerization, while contentious, continues to attract the attention of researchers. Numerous experimental investigations have validated the presence of GPCR dimers, and the relevance of dimerization in the effectuation of physiological functions intensifies the attractiveness of this concept as a potential therapeutic target. GPCRs, as a single entity, have been the main source of scrutiny for drug design objectives for multiple diseases such as cancer, inflammation, cardiac, and respiratory diseases. The existence of dimers broadens the research scope of GPCR functions, revealing new signaling pathways that can be targeted for disease pathogenesis that have not previously been reported when GPCRs were only viewed in their monomeric form. This review will highlight several aspects of GPCR dimerization, which include a summary of the structural elucidation of the allosteric modulation of class C GPCR activation offered through recent solutions to the three-dimensional, full-length structures of metabotropic glutamate receptor and γ-aminobutyric acid B receptor as well as the role of dimerization in the modification of GPCR function and allostery. With the growing influence of computational methods in the study of GPCRs, we will also be reviewing recent computational tools that have been utilized to map protein-protein interactions (PPI).

LncRNA SPOCD1-AS from ovarian cancer extracellular vesicles remodels mesothelial cells to promote peritoneal metastasis via interacting with G3BP1

Background

Metastasis is the key cause of death in ovarian cancer patients. To figure out the biological nature of cancer metastasis is essential for developing effective targeted therapy. Here we investigate how long non-coding RNA (lncRNA) SPOCD1-AS from ovarian cancer extracellular vesicles (EVs) remodel mesothelial cells through a mesothelial-to-mesenchymal transition (MMT) manner and facilitate peritoneal metastasis.

Methods

EVs purified from ovarian cancer cells and ascites of patients were applied to mesothelial cells. The MMT process of mesothelial cells was assessed by morphology observation, western blot analysis, migration assay and adhesion assay. Altered lncRNAs of EV-treated mesothelial cells were screened by RNA sequencing and identified by qRT-PCR. SPOCD1-AS was overexpressed or silenced by overexpression lentivirus or shRNA, respectively. RNA pull-down and RNA immunoprecipitation assays were conducted to reveal the mechanism by which SPOCD1-AS remodeled mesothelial cells. Interfering peptides were synthesized and applied. Ovarian cancer orthotopic implantation mouse model was established in vivo.

Results

We found that ovarian cancer-secreted EVs could be taken into recipient mesothelial cells, induce the MMT phenotype and enhance cancer cell adhesion to mesothelial cells. Furthermore, SPOCD1-AS embedded in ovarian cancer-secreted EVs was transmitted to mesothelial cells to induce the MMT process and facilitate peritoneal colonization in vitro and in vivo. SPOCD1-AS induced the MMT process of mesothelial cells via interacting with G3BP1 protein. Additionally, G3BP1 interfering peptide based on the F380/F382 residues was able to block SPOCD1-AS/G3BP1 interaction, inhibit the MMT phenotype of mesothelial cells, and diminish peritoneal metastasis in vivo.

Conclusions

Our findings elucidate the mechanism associated with EVs and their cargos in ovarian cancer peritoneal metastasis and may provide a potential approach for metastatic ovarian cancer therapeutics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01899-6.

Exploring and exploiting plant cyclic peptides for drug discovery and development

Ever since the discovery of insulin, natural peptides have become an important resource for therapeutic development. Decades of research has led to the discovery of a long list of peptide drugs with broad applications in clinics, from antibiotics to hypertension treatment to pain management. Many of these US FDA-approved peptide drugs are derived from microorganisms and animals. By contrast, the great potential of plant cyclic peptides as therapeutics remains largely unexplored. These macrocyclic peptides typically have rigid structures, good bioavailability and membrane permeability, making them appealing candidates for drug development and engineering. In this review, we introduce the three major classes of plant cyclic peptides and summarize their potential medical applications. We discuss how we can leverage the genome information of many different plants to quickly search for new cyclic peptides and how we can take advantage of the insights gained from their biosynthetic pathways to transform the process of production and drug development. These recent developments have provided a new angle for exploring and exploiting plant cyclic peptides, and we believe that many more peptide drugs derived from plants are about to come.