Directed Evolution Using Stabilized Bacterial Peptide Display

Late-Stage Reshaping of Phage-Displayed Libraries to Macrocyclic and Bicyclic Landscapes using a Multipurpose Linchpin

Genetically encoded libraries (GEL) are increasingly being used for the discovery of ligands for "undruggable" targets that cannot be addressed with small molecules. Foundational GEL platforms like phage-, yeast-, ribosome-, and mRNA-display have enabled the display of libraries composed of 20 natural amino acids (20AA). Unnatural amino acids (UAA) and chemical post-translational modification (cPTM) expanded GEL beyond the 20AA space to yield unnatural linear, cyclic, and bicyclic peptides. The standard operating procedure incorporates UAA and cPTM into a "naive" library with 108-1012 compounds and uses a chemically upgraded library in multiple rounds of selection to discover target-binding hits. However, such an approach uses zero knowledge of natural peptide-receptor interactions that might have been discovered in selections performed with 20AA libraries. There is currently no consensus regarding whether "zero-knowledge" naive libraries or libraries with pre-existing knowledge can offer a more effective path to discovery of molecular interactions. In this manuscript, we evaluated the feasibility of discovery of macrocyclic and bicyclic peptides from "nonzero-knowledge" libraries. We approach this problem by late-stage chemical reshaping of a preselected phage-displayed landscape of 20AA binders to NS3aH1 protease. The reshaping is performed using a novel multifunctional C2-symmetric linchpin, 3,5-bis(bromomethyl)benzaldehyde (termed KYL), that combines two electrophiles that react with thiols and an aldehyde group that reacts with N-terminal amine. KYL diversified phage-displayed peptides into bicyclic architectures and delineated 2 distinct sequence populations: (i) peptides with the HXDMT motif that retained binding upon bicyclization and (ii) peptides without the HXDMT motif that lost binding once chemically modified. The same HXDMT family can be found in traditional selections starting from the naive KYL-modified library. Our report provides a case study for discovering advanced, chemically upgraded macrocycles and bicycles from libraries with pre-existing knowledge. The results imply that other selection campaigns completed in 20AA space, potentially, can serve for late-stage reshaping and as a starting point for the discovery of advanced peptide-derived ligands.

Selection of Nucleotide-Encoded Mass Libraries of Macrocyclic Peptides for Inaccessible Drug Targets

Technological advances and breakthrough developments in the pharmaceutical field are knocking at the door of the "undruggable" fortress with increasing insistence. Notably, the 21st century has seen the emergence of macrocyclic compounds, among which cyclic peptides are of particular interest. This new class of potential drug candidates occupies the vast chemical space between classic small-molecule drugs and larger protein-based therapeutics, such as antibodies. As research advances toward clinical targets that have long been considered inaccessible, macrocyclic peptides are well-suited to tackle these challenges in a post-rule of 5 pharmaceutical landscape. Facilitating their discovery is an arsenal of high-throughput screening methods that exploit massive randomized libraries of genetically encoded compounds. These techniques benefit from the incorporation of non-natural moieties, such as non- proteinogenic amino acids or stabilizing hydrocarbon staples. Exploiting these features for the strategic architectural design of macrocyclic peptides has the potential to tackle challenging targets such as protein-protein interactions, which have long resisted research efforts. This Review summarizes the basic principles and recent developments of the main high-throughput techniques for the discovery of macrocyclic peptides and focuses on their specific deployment for targeting undruggable space. A particular focus is placed on the development of new design guidelines and principles for the cyclization and structural stabilization of cyclic peptides and the resulting success stories achieved against well-known inaccessible drug targets.

Reaching New Heights in Genetic Code Manipulation with High Throughput Screening

The chemical and physical properties of proteins are limited by the 20 canonical amino acids. Genetic code manipulation allows for the incorporation of noncanonical amino acids (ncAAs) that enhance or alter protein functionality. This review explores advances in the three main strategies for introducing ncAAs into biosynthesized proteins, focusing on the role of high throughput screening in these advancements. The first section discusses engineering aminoacyl-tRNA synthetases (aaRSs) and tRNAs, emphasizing how novel selection methods improve characteristics including ncAA incorporation efficiency and selectivity. The second section examines high-throughput techniques for improving protein translation machinery, enabling accommodation of alternative genetic codes. This includes opportunities to enhance ncAA incorporation through engineering cellular components unrelated to translation. The final section highlights various discovery platforms for high-throughput screening of ncAA-containing proteins, showcasing innovative binding ligands and enzymes that are challenging to create with only canonical amino acids. These advances have led to promising drug leads and biocatalysts. Overall, the ability to discover unexpected functionalities through high-throughput methods significantly influences ncAA incorporation and its applications. Future innovations in experimental techniques, along with advancements in computational protein design and machine learning, are poised to further elevate this field.

Engineered Proteins and Materials Utilizing Residue-Specific Noncanonical Amino Acid Incorporation

The incorporation of noncanonical amino acids into proteins and protein-based materials has significantly expanded the repertoire of available protein structures and chemistries. Through residue-specific incorporation, protein properties can be globally modified, resulting in the creation of novel proteins and materials with diverse and tailored characteristics. In this review, we highlight recent advancements in residue-specific incorporation techniques as well as the applications of the engineered proteins and materials. Specifically, we discuss their utility in bio-orthogonal noncanonical amino acid tagging (BONCAT), fluorescent noncanonical amino acid tagging (FUNCAT), threonine-derived noncanonical amino acid tagging (THRONCAT), cross-linking, fluorination, and enzyme engineering. This review underscores the importance of noncanonical amino acid incorporation as a tool for the development of tailored protein properties to meet diverse research and industrial needs.

Employing unnatural promiscuity of sortase to construct peptide macrocycle libraries for ligand discovery

With the increasing attention paid to macrocyclic scaffolds in peptide drug development, genetically encoded peptide macrocycle libraries have become invaluable sources for the discovery of high-affinity peptide ligands targeting disease-associated proteins. The traditional phage display technique of constructing disulfide-tethered macrocycles by cysteine oxidation has the inherent drawback of reduction instability of the disulfide bond. Chemical macrocyclization solves the problem of disulfide bond instability, but the involved highly electrophilic reagents are usually toxic to phages and may bring undesirable side reactions. Here, we report a unique Sortase-mediated Peptide Ligation and One-pot Cyclization strategy (SPLOC) to generate peptide macrocycle libraries, avoiding the undesired reactions of electrophiles with phages. The key to this platform is to mine the unnatural promiscuity of sortase on the X residue of the pentapeptide recognition sequence (LPXTG). Low reactive electrophiles are incorporated into the X-residue side chain, enabling intramolecular cyclization with the cysteine residue of the phage-displayed peptide library. Utilizing the genetically encoded peptide macrocycle library constructed by the SPLOC platform, we found a high-affinity bicyclic peptide binding TEAD4 with a nanomolar KD value (63.9 nM). Importantly, the binding affinity of the bicyclic peptide ligand is 102-fold lower than that of the acyclic analogue. To our knowledge, this is the first time to mine the unnatural promiscuity of ligases to generate peptide macrocycles, providing a new avenue for the construction of genetically encoded cyclic peptide libraries.

Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space

Proteins are a diverse class of biomolecules responsible for wide-ranging cellular functions, from catalyzing reactions to recognizing pathogens. The ability to evolve proteins rapidly and inexpensively toward improved properties is a common objective for protein engineers. Powerful high-throughput methods like fluorescent activated cell sorting and next-generation sequencing have dramatically improved directed evolution experiments. However, it is unclear how to best leverage these data to characterize protein fitness landscapes more completely and identify lead candidates. In this work, we develop a simple yet powerful framework to improve protein optimization by predicting continuous protein properties from simple directed evolution experiments using interpretable, linear machine learning models. Importantly, we find that these models, which use data from simple but imprecise experimental estimates of protein fitness, have predictive capabilities that approach more precise but expensive data. Evaluated across five diverse protein engineering tasks, continuous properties are consistently predicted from readily available deep sequencing data, demonstrating that protein fitness space can be reasonably well modeled by linear relationships among sequence mutations. To prospectively test the utility of this approach, we generated a library of stapled peptides and applied the framework to predict affinity and specificity from simple cell sorting data. We then coupled integer linear programming, a method to optimize protein fitness from linear weights, with mutation scores from machine learning to identify variants in unseen sequence space that have improved and co-optimal properties. This approach represents a versatile tool for improved analysis and identification of protein variants across many domains of protein engineering.

Review of phage display: A jack-of-all-trades and master of most biomolecule display

Phage display was first described by George P. Smith when it was shown that virus particles were capable of presenting foreign proteins on their surface. The technology has paved the way for the evolution of various biomolecules presentation and diverse selection strategies. This unique feature has been applied as a versatile platform for numerous applications in drug discovery, protein engineering, diagnostics, and vaccine development. Over the decades, the limits of biomolecules displayed on phage particles have expanded from peptides to proteomes and even alternative scaffolds. This has allowed phage display to be viewed as a versatile display platform to accommodate various biomolecules ranging from small peptides to larger proteomes which has significantly impacted advancements in the biomedical industry. This review will explore the vast array of biomolecules that have been successfully employed in phage display technology in biomedical research.

Rapid Evaluation of Staple Placement in Stabilized α Helices Using Bacterial Surface Display

There are a wealth of proteins involved in disease that cannot be targeted by current therapeutics because they are inside cells, inaccessible to most macromolecules, and lack small-molecule binding pockets. Stapled peptides, where two amino acids are covalently linked, form a class of macrocycles that have the potential to penetrate cell membranes and disrupt intracellular protein-protein interactions. However, their discovery relies on solid-phase synthesis, greatly limiting queries into their complex design space involving amino acid sequence, staple location, and staple chemistry. Here, we use stabilized peptide engineering by Escherichia coli display (SPEED), which utilizes noncanonical amino acids and click chemistry for stabilization, to rapidly screen staple location and linker structure to accelerate peptide design. After using SPEED to confirm hotspots in the mdm2-p53 interaction, we evaluated different staple locations and staple chemistry to identify several novel nanomolar and sub-nanomolar antagonists. Next, we evaluated SPEED in the B cell lymphoma 2 (Bcl-2) protein family, which is responsible for regulating apoptosis. We report that novel staple locations modified in the context of BIM, a high affinity but nonspecific naturally occurring peptide, improve its specificity against the highly homologous proteins in the Bcl-2 family. These compounds demonstrate the importance of screening linker location and chemistry in identifying high affinity and specific peptide antagonists. Therefore, SPEED can be used as a versatile platform to evaluate multiple design criteria for stabilized peptide engineering.

DNA-Encoded Libraries: Towards Harnessing their Full Power with Darwinian Evolution

DNA-encoded library (DEL) technologies are transforming the drug discovery process, enabling the identification of ligands at unprecedented speed and scale. DEL makes use of libraries that are orders of magnitude larger than traditional high-throughput screens. While a DNA tag alludes to a genotype-phenotype connection that is exploitable for molecular evolution, most of the work in the field is performed with libraries where the tag serves as an amplifiable barcode but does not allow "translation" into the synthetic product it is linked to. In this Review, we cover technologies that enable the "translation" of the genetic tag into synthetic molecules, both biochemically and chemically, and explore how it can be used to harness Darwinian evolutionary pressure.

Strategies for enriching and characterizing proteins with inhibitory properties on the yeast surface

Display technologies are powerful tools for discovering binding proteins against a broad range of biological targets. However, it remains challenging to adapt display technologies for the discovery of proteins that inhibit the enzymatic activities of targets. Here, we investigate approaches for discovering and characterizing inhibitory antibodies in yeast display format using a well-defined series of constructs and the target matrix metalloproteinase-9. Three previously reported antibodies were used to create model libraries consisting of inhibitory, non-inhibitory, and non-binding constructs. Conditions that preferentially enrich for inhibitory clones were identified for both magnetic bead-based enrichments and fluorescence-activated cell sorting. Half maximal inhibitory concentration (IC50) was obtained through yeast titration assays. The IC50 of the inhibitory antibody obtained in yeast display format falls within the confidence interval of the IC50 value determined in soluble form. Overall, this study identifies strategies for the discovery and characterization of inhibitory clones directly in yeast display format.

High-Throughput Screening of Stapled Helical Peptides in Drug Discovery

Therapeutic peptides have revolutionized treatment for a number of human diseases. In particular, the past two decades have witnessed rapid progress of stapled helical peptides in drug discovery. Stapled helical peptides are chemically modified and constrained in their bioactive α-helical conformation. Compared to unstabilized linear peptides, stapled helical peptides exhibit superior binding affinity and selectivity, enhanced membrane permeability, and improved metabolic stability, presenting exciting promise for targeting otherwise challenging protein-protein interfaces. In this Perspective, we summarize recent applications of high-throughput screening technologies for identification of potent stapled helical peptides with optimized binding properties. We expect to provide a broad reference to accelerate the development of stapled helical peptides as the next generation of therapeutic peptides for various human diseases.

Methods for the directed evolution of biomolecular interactions

Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.

Engineered protein-small molecule conjugates empower selective enzyme inhibition

Potent, specific ligands drive precision medicine and fundamental biology. Proteins, peptides, and small molecules constitute effective ligand classes. Yet greater molecular diversity would aid the pursuit of ligands to elicit precise biological activity against challenging targets. We demonstrate a platform to discover protein-small molecule (PriSM) hybrids to combine unique pharmacophore activities and shapes with constrained, efficiently engineerable proteins. In this platform, a fibronectin protein library is displayed on yeast with a single cysteine coupled to acetazolamide via a maleimide-poly(ethylene glycol) linker. Magnetic and flow cytometric sorts enrich specific binders to carbonic anhydrase isoforms. Isolated PriSMs exhibit potent, specific inhibition of carbonic anhydrase isoforms with efficacy superior to that of acetazolamide or protein alone, including an 80-fold specificity increase and 9-fold potency gain. PriSMs are engineered with multiple linker lengths, protein conjugation sites, and sequences against two different isoforms, which reveal platform flexibility and impacts of molecular designs. PriSMs advance the molecular diversity of efficiently engineerable ligands.

A mating mechanism to generate diversity for the Darwinian selection of DNA-encoded synthetic molecules

DNA-encoded library technologies enable the screening of synthetic molecules but have thus far not tapped into the power of Darwinian selection with iterative cycles of selection, amplification and diversification. Here we report a simple strategy to rapidly assemble libraries of conformationally constrained peptides that are paired in a combinatorial fashion (suprabodies). We demonstrate that the pairing can be shuffled after each amplification cycle in a process similar to DNA shuffling or mating to regenerate diversity. Using simulations, we show the benefits of this recombination in yielding a more accurate correlation of selection fitness with affinity after multiple rounds of selection, particularly if the starting library is heterogeneous in the concentration of its members. The method was validated with selections against streptavidin and applied to the discovery of PD-L1 binders. We further demonstrate that the binding of self-assembled suprabodies can be recapitulated by smaller (∼7 kDa) synthetic products that maintain the conformational constraint of the peptides.

GPCR-FEX: A Fluoride-Based Selection System for Rapid GPCR Screening and Engineering

The directed evolution of proteins comprises a search of sequence space for variants that improve a target phenotype, yet identification of desirable variants is inherently limited by library size and screening ability. Selections that couple protein phenotype to cell viability accelerate identification of promising variants by depleting libraries of undesirable variants en masse. Here, we introduce GPCR-FEX, a stringent selection platform that couples G-protein coupled receptor (GPCR) signaling to expression of a fluoride ion exporter (FEX)-GFP fusion gene and concomitant cellular fluoride tolerance in yeast. The GPCR-FEX platform works to deplete inactive GPCR variants from the library prior to high-throughput fluorescence-based cell sorting for rapid, inexpensive screening of receptor libraries that sample an expanded sequence space. Using this system, FEX1 was placed under the control of either P_FUS1 or P_FIG1, promoters activated upon agonist binding by the native yeast GPCRs, Ste2p or Ste3p. Addition of a C-terminal degron to FEX1p enhanced the dynamic range of cell growth between agonist-treated and untreated cells. Using deep sequencing to enumerate population members, we show rapid selection of a previously engineered Ste2p receptor mutant strain over wild-type Ste2p in a model library enrichment experiment. Overall, the GPCR-FEX platform provides a mechanism to rapidly engineer GPCRs, which are important cellular sensors for synthetic biology.

Suprastapled Peptides: Hybridization-Enhanced Peptide Ligation and Enforced α-Helical Conformation for Affinity Selection of Combinatorial Libraries

Stapled peptides with an enforced α-helical conformation have been shown to overcome major limitations in the development of short peptides targeting protein-protein interactions (PPIs). While the growing arsenal of methodologies to staple peptides facilitates their preparation, stapling methodologies are not broadly embraced in synthetic library screening. Herein, we report a strategy leveraged on hybridization of short PNA-peptide conjugates wherein nucleobase driven assembly facilitates ligation of peptide fragments and constrains the peptide's conformation into an α-helix. Using native chemical ligation, we show that a mixture of peptide fragments can be combinatorially ligated and used directly in affinity selection against a target of interest. This approach was exemplified with a focused library targeting the p-53/MDM2 interaction. One hundred peptides were obtained in a one-pot ligation reaction, selected by affinity against MDM2 immobilized on beads, and the best binders were identified by mass spectrometry.

Strategies and Tactics for the Development of Selective Glycan-Binding Proteins

The influences of glycans impact all biological processes, disease states, and pathogenic interactions. Glycan-binding proteins (GBPs), such as lectins, are decisive tools for interrogating glycan structure and function because of their ease of use and ability to selectively bind defined carbohydrate epitopes and glycosidic linkages. GBP reagents are prominent tools for basic research, clinical diagnostics, therapeutics, and biotechnological applications. However, the study of glycans is hindered by the lack of specific and selective protein reagents to cover the massive diversity of carbohydrate structures that exist in nature. In addition, existing GBP reagents often suffer from low affinity or broad specificity, complicating data interpretation. There have been numerous efforts to expand the GBP toolkit beyond those identified from natural sources through protein engineering, to improve the properties of existing GBPs or to engineer novel specificities and potential applications. This review details the current scope of proteins that bind carbohydrates and the engineering methods that have been applied to enhance the affinity, selectivity, and specificity of binders.

Machine learning screening of bile acid-binding peptides in a peptide database derived from food proteins

Bioactive peptides (BPs) are protein fragments that exhibit a wide variety of physicochemical properties, such as basic, acidic, hydrophobic, and hydrophilic properties; thus, they have the potential to interact with a variety of biomolecules, whereas neither carbohydrates nor fatty acids have such diverse properties. Therefore, BP is considered to be a new generation of biologically active regulators. Recently, some BPs that have shown positive benefits in humans have been screened from edible proteins. In the present study, a new BP screening method was developed using BIOPEP-UWM and machine learning. Training data were initially obtained using high-throughput techniques, and positive and negative datasets were generated. The predictive model was generated by calculating the explanatory variables of the peptides. To understand both site-specific and global characteristics, amino acid features (for site-specific characteristics) and peptide global features (for global characteristics) were generated. The constructed models were applied to the peptide database generated using BIOPEP-UWM, and bioactivity was predicted to explore candidate bile acid-binding peptides. Using this strategy, seven novel bile acid-binding peptides (VFWM, QRIFW, RVWVQ, LIRYTK, NGDEPL, PTFTRKL, and KISQRYQ) were identified. Our novel screening method can be easily applied to industrial applications using whole edible proteins. The proposed approach would be useful for identifying bile acid-binding peptides, as well as other BPs, as long as a large amount of training data can be obtained.

Highly paralleled emulsion droplets for efficient isolation, amplification, and screening of cancer biomarker binding phages

Based on the linkage of genotype and phenotype, display technology has been widely used to generate specific ligands for profiling, imaging, diagnosis and therapy applications. However, due to the lack of effective monoclonal manipulation and affinity evaluation methods, traditional display technology has to undergo tedious steps of selection, clone isolation, amplification, sequencing, synthesis and characterization to obtain the binding sequences. To directly acquire high-affinity clones, we propose a double monoclonal display approach (dm-Display) for peptide screening based on highly paralleled monoclonal manipulation in emulsion droplets. dm-Display can monoclonally link the genotype, phenotype and affinity to realize integrated monoclonal separation, amplification, recognition and staining in one droplet so that discrete high-affinity clones can be quickly extracted. Monoclonal manipulations highly-parallelly occur in millions of droplets so that molecular screening of a highly diverse phage library is achieved. We have screened specific peptide ligands against CD71 and GPC1, proving the feasibility and generality of dm-Display. As a highly efficient ligand screening platform, dm-Display will promote the further development of molecular screening.

Library and post-translational modifications of peptide-based display systems

Innovative biotechnological methods empower the successful identification of new drug candidates. Phage, ribosome and mRNA display represent high throughput screenings, allowing fast and efficient progress in the field of targeted drug discovery. The identification range comprises low molecular weight peptides up to whole antibodies. However, a major challenge poses the stability and affinity in particular of peptides. Chemical modifications e.g. the introduction of unnatural amino acids or cyclization, have been proven to be essential tools to overcome these limitations. This review article particularly focuses on available methods for the targeted chemical modification of peptides and peptide libraries in selected display approaches.

Expanding the Chemical Diversity of Genetically Encoded Libraries

The power of ribosomes has increasingly been harnessed for the synthesis and selection of molecular libraries. Technologies, such as phage display, yeast display, and mRNA display, effectively couple genotype to phenotype for the molecular evolution of high affinity epitopes for many therapeutic targets. Genetic code expansion is central to the success of these technologies, allowing researchers to surpass the intrinsic capabilities of the ribosome and access new, genetically encoded materials for these selections. Here, we review techniques for the chemical expansion of genetically encoded libraries, their abilities and limits, and opportunities for further development. Importantly, we also discuss methods and metrics used to assess the efficiency of modification and library diversity with these new techniques.

Proapoptotic Peptide Brush Polymer Nanoparticles via Photoinitiated Polymerization-Induced Self-Assembly

Herein, we report the photoinitiated polymerization-induced self-assembly (photo-PISA) of spherical micelles consisting of proapoptotic peptide-polymer amphiphiles. The one-pot synthetic approach yielded micellar nanoparticles at high concentrations and at scale (150 mg mL-1 ) with tunable peptide loadings up to 48 wt. %. The size of the micellar nanoparticles was tuned by varying the lengths of hydrophobic and hydrophilic building blocks. Critically, the peptide-functionalized nanoparticles imbued the proapoptotic "KLA" peptides (amino acid sequence: KLAKLAKKLAKLAK) with two key properties otherwise not inherent to the sequence: 1) proteolytic resistance compared to the oligopeptide alone; 2) significantly enhanced cell uptake by multivalent display of KLA peptide brushes. The result was demonstrated improved apoptosis efficiency in HeLa cells. These results highlight the potential of photo-PISA in the large-scale synthesis of functional, proteolytically resistant peptide-polymer conjugates for intracellular delivery.

Isolation of Chemically Cyclized Peptide Binders Using Yeast Surface Display

Cyclic peptides with engineered protein-binding activity have gained increasing attention for use in therapeutic and biotechnology applications. We describe the efficient isolation and characterization of cyclic peptide binders from genetically encoded combinatorial libraries using yeast surface display. Here, peptide cyclization is achieved by disuccinimidyl glutarate-mediated cross-linking of amine groups within a linear peptide sequence that is expressed as a yeast cell surface fusion. Using this approach, we first screened a library of cyclic heptapeptides using magnetic selection, followed by fluorescence activated cell sorting (FACS) to isolate binders for a model target (lysozyme) with low micromolar binding affinity (KD ∼ 1.2-3.7 μM). The isolated peptides bind lysozyme selectively and only when cyclized. Importantly, we showed that yeast surface displayed cyclic peptides can be used to efficiently obtain quantitative estimates of binding affinity, circumventing the need for chemical synthesis of the selected peptides. Subsequently, to demonstrate broader applicability of our approach, we isolated cyclic heptapeptides that bind human interleukin-17 (IL-17) using yeast-displayed IL-17 as a target for magnetic selection, followed by FACS using recombinant IL-17. Molecular docking simulations and follow-up experimental analyses identified a candidate cyclic peptide that likely binds IL-17 in its receptor binding region with moderate apparent affinity (KD ∼ 300 nM). Taken together, our results show that yeast surface display can be used to efficiently isolate and characterize cyclic peptides generated by chemical modification from combinatorial libraries.

Micropeptide MIAC Inhibits HNSCC Progression by Interacting with Aquaporin 2

Several important micropeptides encoded by noncoding RNAs have been identified in recent years; however, there have never been any reports of micropeptides in head and neck squamous cell carcinoma (HNSCC). Here we report the discovery and characterization of a human endogenous peptide named micropeptide inhibiting actin cytoskeleton (MIAC). Comprehensive analysis of the TCGA (The Cancer Genome Atlas) database (n = 500), clinical fresh samples (n = 94), and tissue microarrays (n = 60) revealed that lower MIAC expression is correlated with poor overall survival of HNSCC patients. Meanwhile, RNA-sequencing analysis of 9657 human tissues across 32 cancer types from TCGA cohorts found that MIAC is significantly associated with the progression of 5 other different tumors. Mechanistically, MIAC directly interacts with AQP2 (Aquaporin 2) to inhibit the actin cytoskeleton by regulating SEPT2 (Septin 2)/ITGB4 (Integrin Beta 4) and ultimately suppressing the tumor growth and metastasis of HNSCC. Collectively, the mechanism investigation and evaluation of MIAC activity in vivo and in vitro highlights that MIAC plays an important role in HNSCC tumorigenesis.