In-solution enrichment identifies peptide inhibitors of protein-protein interactions

Reversibly Reactive Affinity Selection-Mass Spectrometry Enables Identification of Covalent Peptide Binders

Covalent peptide binders have found applications as activity-based probes and as irreversible therapeutic inhibitors. Currently, there is no rapid, label-free, and tunable affinity selection platform to enrich covalent reactive peptide binders from synthetic libraries. We address this challenge by developing a reversibly reactive affinity selection platform termed ReAct-ASMS enabled by tandem high-resolution mass spectrometry (MS/MS) to identify covalent peptide binders to native protein targets. It uses mixed disulfide-containing peptides to build reversible peptide-protein conjugates that can enrich for covalent variants, which can be sequenced by MS/MS after reduction. Using this platform, we identified covalent peptide binders against two oncoproteins, human papillomavirus 16 early protein 6 (HPV16 E6) and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 protein (Pin1). The resulting peptide binders efficiently and selectively cross-link Cys58 of E6 at 37 °C and Cys113 of Pin1 at room temperature, respectively. ReAct-ASMS enables the identification of highly selective covalent peptide binders for diverse molecular targets, introducing an applicable platform to assist preclinical therapeutic development pipelines.

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.

Development of an α-Klotho Recognizing High-Affinity Peptide Probe from In-Solution Enrichment

The kidney, parathyroid gland, and choroid plexus express the aging-related transmembrane protein α-Klotho, a coreceptor of the fibroblast growth factor 23 (FGF23) receptor complex. Reduced α-Klotho levels are correlated with chronic kidney disease and other age-related diseases, wherein they are released from membranes into circulation. Klotho's potential physiological action as a hormone is of current scientific interest. Part of the challenges associated with advancing these studies, however, has been the long-standing difficulty in detecting soluble α-Klotho in biofluids. Here, we describe the discovery of peptides that recognize α-Klotho with high affinity and selectivity by applying in-solution size-exclusion-based affinity selection-mass spectrometry (AS-MS). After two rounds of AS-MS and subsequent N-terminal modifications, the peptides improved their binding affinity to α-Klotho by approximately 2300-fold compared to the reported starting peptide Pep-10, previously designed based on the C-terminal region of FGF23. The lead peptide binders were shown to enrich α-Klotho from cell lysates and to label α-Klotho in kidney cells. Our results further support the utility of in-solution, label-free AS-MS protocols to discover peptide-based binders to target proteins of interest with high affinity and selectivity, resulting in functional probes for biological studies.

Cyclic Peptides for Drug Development

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years through improved methods for synthesis and drug development have resulted in a steady stream of new drugs, with an average of around one cyclic peptide drug approved per year. Powerful technologies for screening random peptide libraries, and de novo generating ligands, have enabled the development of cyclic peptide drugs independent of naturally derived molecules and now offer virtually unlimited development opportunities. In this review, we feature therapeutically relevant cyclic peptides derived from nature and discuss the unique properties of cyclic peptides, the enormous technological advances in peptide ligand development in recent years, and current challenges and opportunities for developing cyclic peptides that address unmet medical needs.

An Update on Protein Kinases as Therapeutic Targets-Part II: Peptides as Allosteric Protein Kinase C Modulators Targeting Protein-Protein Interactions

Human protein kinases are highly-sought-after drug targets, historically harnessed for treating cancer, cardiovascular disease, and an increasing number of autoimmune and inflammatory conditions. Most current treatments involve small molecule protein kinase inhibitors that interact orthosterically with the protein kinase ATP-binding pocket. As a result, these compounds are often poorly selective and highly toxic. Part I of this series reviews the role of PKC isoforms in various human diseases, featuring cancer and cardiovascular disease, as well as translational examples of PKC modulation applied to human health and disease. In the present Part II, we discuss alternative allosteric binding mechanisms for targeting PKC, as well as novel drug platforms, such as modified peptides. A major goal is to design protein kinase modulators with enhanced selectivity and improved pharmacological properties. To this end, we use molecular docking analysis to predict the mechanisms of action for inhibitor-kinase interactions that can facilitate the development of next-generation PKC modulators.

De Novo Sequencing of Synthetic Bis-cysteine Peptide Macrocycles Enabled by "Chemical Linearization" of Compound Mixtures

A "chemical linearization" approach was applied to synthetic peptide macrocycles to enable their de novo sequencing from mixtures using nanoliquid chromatography-tandem mass spectrometry (nLC-MS/MS). This approach─previously applied to individual macrocycles but not to mixtures─involves cleavage of the peptide backbone at a defined position to give a product capable of generating sequence-determining fragment ions. Here, we first established the compatibility of "chemical linearization" by Edman degradation with a prominent macrocycle scaffold based on bis-Cys peptides cross-linked with the m-xylene linker, which are of major significance in therapeutics discovery. Then, using macrocycle libraries of known sequence composition, the ability to recover accurate de novo assignments to linearized products was critically tested using performance metrics unique to mixtures. Significantly, we show that linearized macrocycles can be sequenced with lower recall compared to linear peptides but with similar accuracy, which establishes the potential of using "chemical linearization" with synthetic libraries and selection procedures that yield compound mixtures. Sodiated precursor ions were identified as a significant source of high-scoring but inaccurate assignments, with potential implications for improving automated de novo sequencing more generally.

Advances in Ultrahigh Throughput Hit Discovery with Tandem Mass Spectrometry Encoded Libraries

Discovering new bioactive molecules is crucial for drug development. Finding a hit compound for a new drug target usually requires screening of millions of molecules. Affinity selection based technologies have revolutionized early hit discovery by enabling the rapid screening of libraries with millions or billions of compounds in short timeframes. In this Perspective, we describe recent technology breakthroughs that enable the screening of ultralarge synthetic peptidomimetic libraries with a barcode-free tandem mass spectrometry decoding strategy. A combination of combinatorial synthesis, affinity selection, automated de novo peptide sequencing algorithms, and advances in mass spectrometry instrumentation now enables hit discovery from synthetic libraries with over 100 million members. We provide a perspective on this powerful technology and showcase success stories featuring the discovery of high affinity binders for a number of drug targets including proteins, nucleic acids, and specific cell types. Further, we show the usage of the technology to discover synthetic peptidomimetics with specific functions and reactivity. We predict that affinity selection coupled with tandem mass spectrometry and automated de novo decoding will rapidly evolve further and become a broadly used drug discovery technology.

Emerging Pharmacotherapeutic Strategies to Overcome Undruggable Proteins in Cancer

Targeted therapies in cancer treatment can improve in vivo efficacy and reduce adverse effects by altering the tissue exposure of specific biomolecules. However, there are still large number of target proteins in cancer are still undruggable, owing to the following factors including (1) lack of ligand-binding pockets, (2) function based on protein-protein interactions (PPIs), (3) the highly specific conserved active sites among protein family members, and (4) the variability of tertiary docking structures. The current status of undruggable targets proteins such as KRAS, TP53, C-MYC, PTP, are carefully introduced in this review. Some novel techniques and drug designing strategies have been applicated for overcoming these undruggable proteins, and the most classic and well-known technology is proteolysis targeting chimeras (PROTACs). In this review, the novel drug development strategies including targeting protein degradation, targeting PPI, targeting intrinsically disordered regions, as well as targeting protein-DNA binding are described, and we also discuss the potential of these strategies for overcoming the undruggable targets. Besides, intelligence-assisted technologies like Alpha-Fold help us a lot to predict the protein structure, which is beneficial for drug development. The discovery of new targets and the development of drugs targeting them, especially those undruggable targets, remain a huge challenge. New drug development strategies, better extraction processes that do not disrupt protein-protein interactions, and more precise artificial intelligence technologies may provide significant assistance in overcoming these undruggable targets.

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.

An antibody that neutralizes SARS-CoV-1 and SARS-CoV-2 by binding to a conserved spike epitope outside the receptor binding motif

The rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), such as the Omicron variants that are highly transmissible and immune evasive, underscores the need to develop therapeutic antibodies with broad neutralizing activities. Here, we used the LIBRA-seq technology, which identified SARS-CoV-2-specific B cells via DNA barcoding and subsequently single-cell sequenced BCRs, to identify an antibody, SW186, which could neutralize major SARS-CoV-2 variants of concern, including Beta, Delta, and Omicron, as well as SARS-CoV-1. The cryo-EM structure of SW186 bound to the receptor binding domain (RBD) of the viral spike protein showed that SW186 interacted with an epitope of the RBD that is not at the interface of its binding to the ACE2 receptor but is highly conserved among SARS coronaviruses. This epitope encompasses a glycosylation site (N343) of the viral spike protein. Administration of SW186 in mice after they were infected with SARS-CoV-2 Alpha, Beta, or Delta variants reduced the viral loads in the lung. These results demonstrated that SW186 neutralizes diverse SARS coronaviruses by binding to a conserved RBD epitope, which could serve as a target for further antibody development.

Binary combinatorial scanning reveals potent poly-alanine-substituted inhibitors of protein-protein interactions

Establishing structure-activity relationships is crucial to understand and optimize the activity of peptide-based inhibitors of protein-protein interactions. Single alanine substitutions provide limited information on the residues that tolerate simultaneous modifications with retention of biological activity. To guide optimization of peptide binders, we use combinatorial peptide libraries of over 4,000 variants-in which each position is varied with either the wild-type residue or alanine-with a label-free affinity selection platform to study protein-ligand interactions. Applying this platform to a peptide binder to the oncogenic protein MDM2, several multi-alanine-substituted analogs with picomolar binding affinity were discovered. We reveal a non-additive substitution pattern in the selected sequences. The alanine substitution tolerances for peptide ligands of the 12ca5 antibody and 14-3-3 regulatory protein are also characterized, demonstrating the general applicability of this new platform. We envision that binary combinatorial alanine scanning will be a powerful tool for investigating structure-activity relationships.

Identification of a binding site on soluble RANKL that can be targeted to inhibit soluble RANK-RANKL interactions and treat osteoporosis

One of the major challenges for discovering protein-protein interaction inhibitors is identifying selective and druggable binding sites at the protein surface. Here, we report an approach to identify a small molecular binding site to selectively inhibit the interaction of soluble RANKL and RANK for designing anti-osteoporosis drugs without undesirable immunosuppressive effects. Through molecular dynamic simulations, we discovered a binding site that allows a small molecule to selectively interrupt soluble RANKL-RANK interaction and without interfering with the membrane RANKL-RANK interaction. We describe a highly potent inhibitor, S3-15, and demonstrate its specificity to inhibit the soluble RANKL-RANK interaction with in vitro and in vivo studies. S3-15 exhibits anti-osteoporotic effects without causing immunosuppression. Through in silico and in vitro experiments we further confirm the binding model of S3-15 and soluble RANKL. This work might inspire structure-based drug discovery for targeting protein-protein interactions.

Development of an RHEB-Targeting Peptide To Inhibit mTORC1 Kinase Activity

In cancer, the mechanistic/mammalian target of rapamycin complex-1 (mTORC1) is hyperactivated to promote survival under adverse conditions. The kinase activity of mTORC1 is activated by small-GTPase RHEB-GTP. Therefore, a new modality to inhibit mTORC1 activity has emerged, through intercepting RHEB. However, due to the relatively large contact area involved in the interaction between RHEB and mTORC1, facilitating this inhibition through small molecules has been challenging. Here, we report the development of a peptide that can inhibit the RHEB-mTORC1 interaction. The peptide, P1_WT, was designed based on the α-helix (aa 101-115) of the N-heat domain of mTOR to interact with switch II of RHEB. P1_WT bound to RHEB (K _D = 0.14 μM) and inhibited RHEB-mTOR^N-heat interaction (IC₅₀ = 0.33 μM) in vitro. Consequently, P1_WT inhibited mTORC1 activity at a sub-micromolar level (IC₅₀ ∼ 0.3 μM). P1_WT was predicted to be cell-permeable due to the rich content of arginine (23%), enhancing the intracellular translocation. These results show that P1_WT is a potential compound to further develop inhibitors for mTORC1 by intercepting RHEB from mTORC1.

Accelerated Identification of Cell Active KRAS Inhibitory Macrocyclic Peptides using Mixture Libraries and Automated Ligand Identification System (ALIS) Technology

Macrocyclic peptides can disrupt previously intractable protein–protein interactions (PPIs) relevant to oncology targets such as KRAS. Early hits often lack cellular activity and require meticulous improvement of affinity, permeability, and metabolic stability to become viable leads. We have validated the use of the Automated Ligand Identification System (ALIS) to screen oncogenic KRAS^G12D (GDP) against mass-encoded mini-libraries of macrocyclic peptides and accelerate our structure–activity relationship (SAR) exploration. These mixture libraries were generated by premixing various unnatural amino acids without the need for the laborious purification of individual peptides. The affinity ranking of the peptide sequences provided SAR-rich data sets that led to the selection of novel potency-enhancing substitutions in our subsequent designs. Additional stability and permeability optimization resulted in the identification of peptide 7 that inhibited pERK activity in a pancreatic cancer cell line. More broadly, this methodology offers an efficient alternative to accelerate the fastidious hit-to-lead optimization of PPI peptide inhibitors.

Integrated Design of a Membrane-Lytic Peptide-Based Intravenous Nanotherapeutic Suppresses Triple-Negative Breast Cancer

Membrane-lytic peptides offer broad synthetic flexibilities and design potential to the arsenal of anticancer therapeutics, which can be limited by cytotoxicity to noncancerous cells and induction of drug resistance via stress-induced mutagenesis. Despite continued research efforts on membrane-perforating peptides for antimicrobial applications, success in anticancer peptide therapeutics remains elusive given the muted distinction between cancerous and normal cell membranes and the challenge of peptide degradation and neutralization upon intravenous delivery. Using triple-negative breast cancer as a model, the authors report the development of a new class of anticancer peptides. Through function-conserving mutations, the authors achieved cancer cell selective membrane perforation, with leads exhibiting a 200-fold selectivity over non-cancerogenic cells and superior cytotoxicity over doxorubicin against breast cancer tumorspheres. Upon continuous exposure to the anticancer peptides at growth-arresting concentrations, cancer cells do not exhibit resistance phenotype, frequently observed under chemotherapeutic treatment. The authors further demonstrate efficient encapsulation of the anticancer peptides in 20 nm polymeric nanocarriers, which possess high tolerability and lead to effective tumor growth inhibition in a mouse model of MDA-MB-231 triple-negative breast cancer. This work demonstrates a multidisciplinary approach for enabling translationally relevant membrane-lytic peptides in oncology, opening up a vast chemical repertoire to the arms race against cancer.

Synthetic molecular evolution of antimicrobial peptides

As we learn more about how peptide structure and activity are related, we anticipate that antimicrobial peptides will be engineered to have strong potency and distinct functions and that synthetic peptides will have new biomedical applications, such as treatments for emerging infectious diseases. As a result of the enormous number of possible amino acid sequences and the low-throughput nature of antimicrobial peptide assays, computational tools for peptide design and optimization are needed for direct experimentation toward obtaining functional sequences. Recent developments in computational tools have improved peptide design, saving labor, reagents, costs, and time. At the same time, improvements in peptide synthesis and experimental platforms continue to reduce the cost and increase the throughput of peptide-drug screening. In this review, we discuss the current methods of peptide design and engineering, including in silico methods and peptide synthesis and screening, and highlight areas of potential improvement.

Oligo(N-methylalanine) as a Peptide-Based Molecular Scaffold with a Minimal Structure and High Density of Functionalizable Sites

Functionalizable synthetic molecules with nanometer sizes and defined shapes in water are useful as molecular scaffolds to mimic the functions of biomacromolecules and develop chemical tools for manipulating biomacromolecules. Herein, we propose oligo(N-methylalanine) (oligo-NMA) as a peptide-based molecular scaffold with a minimal structure and a high density of functionalizable sites. Oligo-NMA forms a defined shape in water without hydrogen-bonding networks or ring constraints, which enables the molecule to act as a scaffold with minimal atomic composition. Furthermore, functional groups can be readily introduced on the nitrogens and α-carbons of oligo-NMA. Computational and NMR spectroscopic analysis suggested that the backbone structure of oligo-NMA is not largely affected by functionalization. Moreover, the usefulness of oligo-NMA was demonstrated by the design of protein ligands. The ease of synthesis, minimal structure, and high functionalization flexibility makes oligo-NMA a useful scaffold for chemical and biological applications.

Targeting intracellular protein-protein interactions with macrocyclic peptides

Intracellular protein-protein interactions (PPIs) are challenging targets for traditional drug modalities. Macrocyclic peptides (MPs) prove highly effective PPI inhibitors in vitro and can be rapidly discovered against PPI targets by rational design or screening combinatorial libraries but are generally impermeable to the cell membrane. Recent advances in MP science and technology are allowing for the development of 'drug-like' MPs that potently and specifically modulate intracellular PPI targets in cell culture and animal models. In this review, we highlight recent progress in generating cell-permeable MPs that enter the mammalian cell by passive diffusion, endocytosis followed by endosomal escape, or as-yet unknown mechanisms.

High-throughput glycolytic inhibitor discovery targeting glioblastoma by graphite dots-assisted LDI mass spectrometry

Malignant tumors will become vulnerable if their uncontrolled biosynthesis and energy consumption engaged in metabolic reprogramming can be cut off. Here, we report finding a glycolytic inhibitor targeting glioblastoma with graphite dots-assisted laser desorption/ionization mass spectrometry as an integrated drug screening and pharmacokinetic platform (GLMSD). We have performed high-throughput virtual screening to narrow an initial library of 240,000 compounds down to the docking of 40 compounds and identified five previously unknown chemical scaffolds as promising hexokinase-2 inhibitors. The best inhibitor (Compd 27) can regulate the reprogrammed metabolic pathway in U87 glioma cells (median inhibitory concentration ~ 11.3 μM) for tumor suppression. Highly effective therapy against glioblastoma has been demonstrated in both subcutaneous and orthotopic brain tumors by synergizing Compd 27 and temozolomide. Our glycolytic inhibitor discovery can inspire personalized medicine targeting reprogrammed metabolisms of malignant tumors. GLMSD enables large, high-quality data for next-generation artificial intelligence-aided drug development.

Affinity Selection from Synthetic Peptide Libraries Enabled by De Novo MS/MS Sequencing

Recently, de novo MS/MS peptide sequencing has enabled the application of affinity selections to synthetic peptide mixtures that approach the diversity of phage libraries (> 108 random peptides). In conjunction with ‘split-mix’ solid phase synthesis to access equimolar peptide mixtures, this approach provides a straightforward means to examine synthetic peptide libraries of considerably higher diversity than has been feasible historically. Here, we offer a critical perspective on this work, report emerging data, and highlight opportunities for further methods refinement. With continued development, ‘affinity selection–mass spectrometry’ may become a complimentary approach to phage display, in vitro selection, and DNA-encoded libraries for the discovery of synthetic ligands that modulate protein function.

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.

Rapid de novo discovery of peptidomimetic affinity reagents for human angiotensin converting enzyme 2

Rapid discovery and development of serum-stable, selective, and high affinity peptide-based binders to protein targets are challenging. Angiotensin converting enzyme 2 (ACE2) has recently been identified as a cardiovascular disease biomarker and the primary receptor utilized by the severe acute respiratory syndrome coronavirus 2. In this study, we report the discovery of high affinity peptidomimetic binders to ACE2 via affinity selection-mass spectrometry (AS-MS). Multiple high affinity ACE2-binding peptides (ABP) were identified by selection from canonical and noncanonical peptidomimetic libraries containing 200 million members (dissociation constant, K_D = 19-123 nM). The most potent noncanonical ACE2 peptide binder, ABP N1 (K_D = 19 nM), showed enhanced serum stability in comparison with the most potent canonical binder, ABP C7 (K_D = 26 nM). Picomolar to low nanomolar ACE2 concentrations in human serum were detected selectively using ABP N1 in an enzyme-linked immunosorbent assay. The discovery of serum-stable noncanonical peptidomimetics like ABP N1 from a single-pass selection demonstrates the utility of advanced AS-MS for accelerated development of affinity reagents to protein targets.

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.

Peptoid-based reprogrammable template for cell-permeable inhibitors of protein-protein interactions

The development of inhibitors of intracellular protein–protein interactions (PPIs) is of great significance for drug discovery, but the generation of a cell-permeable molecule with high affinity to protein is challenging. Oligo(N-substituted glycines) (oligo-NSGs), referred to as peptoids, are attractive as potential intracellular PPI inhibitors owing to their high membrane permeability. However, their intrinsically flexible backbones make the rational design of inhibitors difficult. Here, we propose a peptoid-based rational approach to develop cell-permeable PPI inhibitors using oligo(N-substituted alanines) (oligo-NSAs). The rigid structures of oligo-NSAs enable independent optimization of each N-substituent to improve binding affinity and membrane permeability, while preserving the backbone shape. A molecule with optimized N-substituents inhibited a target PPI in cells, which demonstrated the utility of oligo-NSA as a reprogrammable template to develop intracellular PPI inhibitors.

A peptoid-based modular approach using oligo(N-substituted alanine) as a reprogrammable template enables independent optimization of N-substituents and facile development of cell-permeable inhibitors of protein–protein interactions.

Computational Design of Structured and Functional Peptide Macrocycles

Structure-based computational design methods have been developed to create proteins in silico with diverse shapes and sizes that accurately fold in vitro, from 7-residue macrocycles to megadalton-scale self-assembling nanomaterials. Precise control over protein shape has further enabled design and optimization of functional therapeutic proteins, including agonists, antagonists, enzymes, and vaccines. Computational design of functional peptides of smaller size presents a persistent challenge, with few successful examples to date. Herein we describe validated general methods for computational design of peptides using the Rosetta molecular modeling suite and discuss outstanding challenges and future directions.

Allosteric Inhibition of the Tumor-Promoting Interaction between AIMP2-DX2 and HSP70

Although protein-protein interactions (PPIs) have emerged as an attractive therapeutic target space, the identification of chemicals that effectively inhibit PPIs remains challenging. Here, we identified through library screening a chemical probe, compound 1 that can inhibit the tumor-promoting interaction between the oncogenic factor AIMP2-DX2 and HSP70. We found that compound 1 binds to the N-terminal subdomain of glutathione S transferase (GST-N) of AIMP2-DX2, causing a direct steric clash with HSP70 and an intramolecular interaction between the N-terminal flexible region (NFR) and the GST-N of AIMP2-DX2, which induces masking of the HSP70 binding region during molecular dynamics and mutation studies. Compound 1 thus interferes with the AIMP2-DX2 and HSP70 interaction and suppresses the growth of cancer cells that express high levels of AIMP2-DX2 in vitro and in preliminary in vivo experiment. This work provides an example showing that allosteric conformational changes induced by chemicals can be a way to control pathologic PPIs. Significance Statement Compound 1 is a promising protein-protein interaction inhibitor between AIMP2-DX2 and HSP70 for cancer therapy by the mechanism with allosteric modulation as well as competitive binding. It seems to induce allosteric conformational change of AIMP2-DX2 proteins and direct binding clash between AIMP2-DX2 and HSP70. The compound reduced the level of AIMP2-DX2 in ubiquitin-dependent manner via suppression of binding between AIMP2-DX2 and HSP70, and suppressed the growth of cancer cells highly expressing AIMP2-DX2 in vitro and in preliminary in vivo experiment.

An in vivo selection-derived d-peptide for engineering erythrocyte-binding antigens that promote immune tolerance

When displayed on erythrocytes, peptides and proteins can drive antigen-specific immune tolerance. Here, we investigated a straightforward approach based on erythrocyte binding to promote antigen-specific tolerance to both peptides and proteins. We first identified a robust erythrocyte-binding ligand. A pool of one million fully d-chiral peptides was injected into mice, blood cells were isolated, and ligands enriched on these cells were identified using nano-liquid chromatography-tandem mass spectrometry. One round of selection yielded a murine erythrocyte-binding ligand with an 80 nM apparent dissociation constant, K _d We modified an 83-kDa bacterial protein and a peptide antigen derived from ovalbumin (OVA) with the identified erythrocyte-binding ligand. An administration of the engineered bacterial protein led to decreased protein-specific antibodies in mice. Similarly, mice given the engineered OVA-derived peptide had decreased inflammatory anti-OVA CD8⁺ T cell responses. These findings suggest that our tolerance-induction strategy is applicable to both peptide and protein antigens and that our in vivo selection strategy can be used for de novo discovery of robust erythrocyte-binding ligands.

Automated affinity selection for rapid discovery of peptide binders

In-solution affinity selection (AS) of large synthetic peptide libraries affords identification of binders to protein targets through access to an expanded chemical space. Standard affinity selection methods, however, can be time-consuming, low-throughput, or provide hits that display low selectivity to the target. Here we report an automated bio-layer interferometry (BLI)-assisted affinity selection platform. When coupled with tandem mass spectrometry (MS), this method enables both rapid de novo discovery and affinity maturation of known peptide binders with high selectivity. The BLI-assisted AS-MS technology also features real-time monitoring of the peptide binding during the library selection process, a feature unattainable by current selection approaches. We show the utility of the BLI AS-MS platform toward rapid identification of novel nanomolar (dissociation constant, K_D < 50 nM) non-canonical binders to the leukemia-associated oncogenic protein menin. To our knowledge, this is the first application of BLI to the affinity selection of synthetic peptide libraries. We believe our approach can significantly accelerate the use of synthetic peptidomimetic libraries in drug discovery.

This work reports an automated affinity selection-mass spectrometry (AS-MS) approach amenable to both de novo peptide binder discovery and affinity maturation of known binders in a high-throughput and selective manner.

Denaturing and Native Mass Spectrometric Analytics for Biotherapeutic Drug Discovery Research: Historical, Current, and Future Personal Perspectives

Mass spectrometry (MS) plays a key role throughout all stages of drug development and is now as ubiquitous as other analytical techniques such as surface plasmon resonance, nuclear magnetic resonance, and supercritical fluid chromatography, among others. Herein, we aim to discuss the history of MS, both electrospray and matrix-assisted laser desorption ionization, specifically for the analysis of antibodies, evolving through to denaturing and native-MS analysis of newer biologic moieties such as antibody-drug conjugates, multispecific antibodies, and interfering nucleic acid-based therapies. We discuss challenging therapeutic target characterization such as membrane protein receptors. Importantly, we compare and contrast the MS and hyphenated analytical chromatographic methods used to characterize these therapeutic modalities and targets within biopharmaceutical research and highlight the importance of appropriate MS deconvolution software and its essential contribution to project progression. Finally, we describe emerging applications and MS technologies that are still predominantly within either a development or academic stage of use but are poised to have significant impact on future drug development within the biopharmaceutic industry once matured. The views reflected herein are personal and are not meant to be an exhaustive list of all relevant MS performed within biopharmaceutical research but are what we feel have been historically, are currently, and will be in the future the most impactful for the drug development process.

Targeting therapy-resistant lung cancer stem cells via disruption of the AKT/TSPYL5/PTEN positive-feedback loop

Cancer stem cells (CSCs) are regarded as essential targets to overcome tumor progression and therapeutic resistance; however, practical targeting approaches are limited. Here, we identify testis-specific Y-like protein 5 (TSPYL5) as an upstream regulator of CSC-associated genes in non-small cell lung cancer cells, and suggest as a therapeutic target for CSC elimination. TSPYL5 elevation is driven by AKT-dependent TSPYL5 phosphorylation at threonine-120 and stabilization via inhibiting its ubiquitination. TSPYL5-pT120 also induces nuclear translocation and functions as a transcriptional activator of CSC-associated genes, ALDH1 and CD44. Also, nuclear TSPYL5 suppresses the transcription of PTEN, a negative regulator of PI3K signaling. TSPYL5-pT120 maintains persistent CSC-like characteristics via transcriptional activation of CSC-associated genes and a positive feedback loop consisting of AKT/TSPYL5/PTEN signaling pathway. Accordingly, elimination of TSPYL5 by inhibiting TSPYL5-pT120 can block aberrant AKT/TSPYL5/PTEN cyclic signaling and TSPYL5-mediated cancer stemness regulation. Our study suggests TSPYL5 be an effective target for therapy-resistant cancer.

In order to assist the development of cancer stem cell (CSC) therapy, Kim et al identified testis-specific Y-like protein 5 (TSPYL5) as an upstream regulator of CSC-associated genes in non-small cell lung cancer cells. They demonstrated in cancer cell lines and in vivo that TSPYL5 activity is dependent on AKT signalling and that disruption of TSPYL5 signalling could serve as a potential strategy to tackle therapy-resistant cancers.

Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites

Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational "anchor extension" methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC₅₀ values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.

Computational designing of a peptide that potentially blocks the entry of SARS-CoV, SARS-CoV-2 and MERS-CoV

Last decade has witnessed three major pandemics caused by SARS-CoV, SARS-CoV-2 and MERS-CoV that belong to Coronavirus family. Currently, there are no effective therapies available for corona virus infections. Since the three viruses belong to the same family and share many common features, we can theoretically design a drug that can be effective on all the three of them. In this study, using computational approach, we designed a peptide (Peptide 7) that can bind to the Receptor Binding Domain (RBD) of SARS-CoV, SARS-CoV-2 and MERS-CoV thereby preventing the entry of the viruses into the host cell. The peptide inhibitor was designed as a consensus peptide from three different peptides that might individually bind to the RBD of the three viruses. Docking studies and molecular dynamic simulations using Peptide 7 has shown that it binds with higher affinity than the native receptors of the RBD and forms a stable complex thereby preventing further viral-receptor interaction and inhibiting their cellular entry. This effective binding is observed for the three RBDs, despite the Peptide 7 interactions being slightly different. Hence; this peptide inhibitor can be used as a potential candidate for the development of peptide based anti-viral therapy against Corona viruses.

Rational Design of Peptide-Based Inhibitors Disrupting Protein-Protein Interactions

Protein-protein interactions (PPIs) are well-established as a class of promising drug targets for their implications in a wide range of biological processes. However, drug development toward PPIs is inevitably hampered by their flat and wide interfaces, which generally lack suitable pockets for ligand binding, rendering most PPI systems "undruggable." Here, we summarized drug design strategies for developing peptide-based PPI inhibitors. Importantly, several quintessential examples toward well-established PPI targets such as Bcl-2 family members, p53-MDM2, as well as APC-Asef are presented to illustrate the detailed schemes for peptide-based PPI inhibitor development and optimizations. This review supplies a comprehensive overview of recent progresses in drug discovery targeting PPIs through peptides or peptidomimetics, and will shed light on future therapeutic agent development toward the historically "intractable" PPI systems.

CYP1A2, 2A13, and 3A4 network and interaction with aflatoxin B1

Aspergillus fungi are known to produce aflatoxins, among which aflatoxin B1 (AFB1) is the most potent carcinogen that is metabolised by cytochrome P450 (CYP450). In the liver, AFB1 is metabolised into exo-8,9-epoxide by the CYP1A2 enzymes. The resulting epoxide can react with guanine to cause DNA damage. Natural inhibitors are being identified. However, the modes of action are poorly understood. In the current study, we have investigated the mode of action of AFB1 with CYP1A2, CYP3A4 and CYP2A13 using molecular dynamic simulation (MD simulation) approaches. The interaction network and paths among CYP1A2, CYP3A4, and CYP2A13 have been investigated using the STRING database and PathLinker plugin of Cytoscape. CYP3A4 is the most active protein involved in interactions with AFB1 during its metabolism. Residues 362ARG, 445SER, 450LEU and 451PHE of CYP1A2 are important, interacting with AFB1 and converting it to toxic exo-AFB1-8,9-epoxide (AFBEX). The pathway shows that microsomal epoxide hydrolase (EPHX1) may acts as initiator in the signalling pathway where CYP1A2, CYP3A4 and CYP2A13 interact in a sequential order. The interaction network shows there to be a strong association in expression among CYP1A2, CYP3A4 and CYP2A13 along with other metabolising enzymes. The complex of AFB1 and CYP1A2 was found to be stable during the MD simulation. This study provides a better understanding of the mode of action between AFB1 and CYP1A2, CYP3A4 and CYP2A13 which relates to the effective management of AFB1 toxicity. EPHX1 in the protein network may be an ideal target when designing inhibitors to prevent the toxin’s activation. Peptide inhibitors may be designed to block the substrate site residues of CYP1A2 in order to prevent the conversion from AFB1 into AFBEX. This would either neutralise or reduce its toxicity.

Designed β-Hairpins Inhibit LDH5 Oligomerization and Enzymatic Activity

Lactate dehydrogenase 5 (LDH5) is overexpressed in metastatic tumors and is an attractive target for anticancer therapy. Small-molecule drugs have been developed to target the substrate/cofactor sites of LDH5, but none has reached the clinic to date, and alternative strategies remain almost unexplored. Combining rational and computer-based approaches, we identified peptidic sequences with high affinity toward a β-sheet region that is involved in protein-protein interactions (PPIs) required for the activity of LDH5. To improve stability and potency, these sequences were grafted into a cyclic cell-penetrating β-hairpin peptide scaffold. The lead grafted peptide, cGmC9, inhibited LDH5 activity in vitro in low micromolar range and more efficiently than the small-molecule inhibitor GNE-140. cGmC9 inhibits LDH5 by targeting an interface unlikely to be inhibited by small-molecule drugs. This lead will guide the development of new LDH5 inhibitors and challenges the landscape of drug discovery programs exclusively dedicated to small molecules.

A reactive peptide interface for site-selective cysteine bioconjugation

We report aqueous, site-selective modification of proteins using a reactive peptide interface comprising a nine-residue sequence. This interface is the fastest (second-order rate constant of 152 M-1 s-1) catalyst-free, cysteine-based method for modifying proteins available to date, and enables near-quantitative labeling of antibodies in cell lysate.

Expanding GABAAR pharmacology via receptor-associated proteins

Drugs directly targeting γ-aminobutyric acid type A receptors (GABA_ARs), the major mediators of fast synaptic inhibition, contribute significantly to today's neuropharmacology. Emerging evidence establishes intracellularly GABA_AR-associated proteins as the central players in determining cellular and subcellular GABAergic input sites, thereby providing pharmacological opportunities to affect distinct receptor populations and address discrete neuronal dysfunctions. Here, we report on recently studied GABA_AR-associated proteins and highlight challenges and newly available methods for their functional and physical mapping. We anticipate these efforts to contribute to decipher the complexity of GABAergic signalling in the brain and eventually enable therapeutic avenues for, so far, untreatable neuronal disorders and diseases.

Harnessing molecular recognition for localized drug delivery

A grand challenge in drug delivery is providing the right dose, at the right anatomic location, for the right duration of time to maximize therapeutic efficacy while minimizing off-target toxicity and other deleterious side-effects. Two general modalities are receiving broad attention for localized drug delivery. In the first, referred to as "targeted accumulation", drugs or drug carriers are engineered to have targeting moieties that promote their accumulation at a specific tissue site from circulation. In the second, referred to as "local anchoring", drugs or drug carriers are inserted directly into the tissue site of interest where they persist for a specified duration of time. This review surveys recent advances in harnessing molecular recognition between proteins, peptides, nucleic acids, lipids, and carbohydrates to mediate targeted accumulation and local anchoring of drugs and drug carriers.

De Novo Discovery of High-Affinity Peptide Binders for the SARS-CoV-2 Spike Protein

The β-coronavirus SARS-CoV-2 has caused a global pandemic. Affinity reagents targeting the SARS-CoV-2 spike protein are of interest for the development of therapeutics and diagnostics. We used affinity selection-mass spectrometry for the rapid discovery of synthetic high-affinity peptide binders for the receptor binding domain (RBD) of the SARS-CoV-2 spike protein. From library screening with 800 million synthetic peptides, we identified three sequences with nanomolar affinities (dissociation constants K d = 80-970 nM) for RBD and selectivity over human serum proteins. Nanomolar RBD concentrations in a biological matrix could be detected using the biotinylated lead peptide in ELISA format. These peptides do not compete for ACE2 binding, and their site of interaction on the SARS-CoV-2-spike-RBD might be unrelated to the ACE2 binding site, making them potential orthogonal reagents for sandwich immunoassays. These findings serve as a starting point for the development of SARS-CoV-2 diagnostics or conjugates for virus-directed delivery of therapeutics.

Affinity selection-mass spectrometry for the discovery of pharmacologically active compounds from combinatorial libraries and natural products

Invented to address the high-throughput screening (HTS) demands of combinatorial chemistry, affinity selection-mass spectrometry (AS-MS) utilizes binding interactions between ligands and receptors to isolate pharmacologically active compounds from mixtures of small molecules and then relies on the selectivity, sensitivity, and speed of mass spectrometry to identify them. No radiolabels, fluorophores, or chromophores are required. Although many variations of AS-MS have been devised, three approaches have emerged as the most flexible, productive, and popular, and they differ primarily in how ligand-receptor complexes are separated from nonbinding compounds in the mixture. These are pulsed ultrafiltration (PUF) AS-MS, size exclusion chromatography (SEC) AS-MS, and magnetic microbead affinity selection screening (MagMASS). PUF and SEC AS-MS are solution-phase screening approaches, and MagMASS uses receptors immobilized on magnetic microbeads. Because pools of compounds are screened using AS-MS, each containing hundreds to thousands of potential ligands, hundreds of thousands of compounds can be screened per day. AS-MS is also compatible with complex mixtures of chemically diverse natural products in extracts of botanicals and fungi and microbial cultures, which often contain fluorophores and chromophores that can interfere with convention HTS. Unlike conventional HTS, AS-MS may be used to discover ligands binding to allosteric as well as orthosteric receptor sites, and AS-MS has been useful for discovering ligands to targets that are not easily incorporated into conventional HTS such as membrane-bound receptors.

Optimizing synthetic nucleic acid and protein nanocarriers: The chemical evolution approach

Optimizing synthetic nanocarriers is like searching for a needle in a haystack. How to find the most suitable carrier for intracellular delivery of a specified macromolecular nanoagent for a given disease target location? Here, we review different synthetic 'chemical evolution' strategies that have been pursued. Libraries of nanocarriers have been generated either by unbiased combinatorial chemistry or by variation and novel combination of known functional delivery elements. As in natural evolution, definition of nanocarriers as sequences, as barcode or design principle, may fuel chemical evolution. Screening in appropriate test system may not only provide delivery candidates, but also a refined understanding of cellular delivery including novel, unpredictable mechanisms. Combined with rational design and computational algorithms, candidates can be further optimized in subsequent evolution cycles into nanocarriers with improved safety and efficacy. Optimization of nanocarriers differs for various cargos, as illustrated for plasmid DNA, siRNA, mRNA, proteins, or genome-editing nucleases.

Bioactive Cyclization Optimizes the Affinity of a Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Peptide Inhibitor

Peptides are regarded as promising next-generation therapeutics. However, an analysis of over 1000 bioactive peptide candidates suggests that many have underdeveloped affinities and could benefit from cyclization using a bridging linker sequence. Until now, the primary focus has been on the use of inert peptide linkers. Here, we show that affinity can be significantly improved by enriching the linker with functional amino acids. We engineered a peptide inhibitor of PCSK9, a target for clinical management of hypercholesterolemia, to demonstrate this concept. Cyclization linker optimization from library screening produced a cyclic peptide with ∼100-fold improved activity over the parent peptide and efficiently restored low-density lipoprotein (LDL) receptor levels and cleared extracellular LDL. The linker forms favorable interactions with PCSK9 as evidenced by thermodynamics, structure-activity relationship (SAR), NMR, and molecular dynamics (MD) studies. This PCSK9 inhibitor is one of many peptides that could benefit from bioactive cyclization, a strategy that is amenable to broad application in pharmaceutical design.

Development of a High-Throughput Affinity Mass Spectrometry (AMS) Platform Using Laser Diode Thermal Desorption Ionization Coupled to Mass Spectrometry (LDTD-MS)

Affinity selection mass spectrometry (MS) or, simply, affinity mass spectrometry (AMS) is a label-free technology that has been used to identify high-affinity ligands of target proteins of interest by screening against small-molecule compound libraries and identifying molecules that are enriched in the presence of the target protein. We have previously applied Agilent Technology's (Santa Clara, CA) RapidFire solid-phase extraction (SPE)-based high-throughput MS technology to screen small-molecule libraries using AMS. However, SPE-based technologies rely on fluidics for desalting and separation prior to mass analysis with attendant high solvent consumption, relatively high sample volume requirements, risk of sample carryover, and frequent maintenance. To address these challenges, we have established an AMS platform using a laser diode thermal desorption-atmospheric pressure chemical ionization (LDTD-APCI) ionization source (Phytronix, Quebec, Canada) coupled with a SCIEX 5600+ TripleTOF MS (Framingham, MA). We also validated a data-independent acquisition (DIA) Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) method for the robust detection and analysis of small-molecule affinity hits. An informatics platform developed in-house has resulted in a streamlined data analysis workflow for high-throughput AMS screening campaigns and reduced data processing time without compromising data quality. Finally, 68,000 compounds were screened in a single plate and affinity selected hits were confirmed in an orthogonal enzyme activity assay.

Discovery of Nucleic Acid Binding Molecules from Combinatorial Biohybrid Nucleobase Peptide Libraries

Nature has three biopolymers: oligonucleotides, polypeptides, and oligosaccharides. Each biopolymer has independent functions, but when needed, they form mixed assemblies for higher-order purposes, as in the case of ribosomal protein synthesis. Rather than forming large complexes to coordinate the role of different biopolymers, we dovetail protein amino acids and nucleobases into a single low molecular weight precision polyamide polymer. We established efficient chemical synthesis and de novo sequencing procedures and prepared combinatorial libraries with up to 100 million biohybrid molecules. This biohybrid material has a higher bulk affinity to oligonucleotides than peptides composed exclusively of canonical amino acids. Using affinity selection mass spectrometry, we discovered variants with a high affinity for pre-microRNA hairpins. Our platform points toward the development of high throughput discovery of sequence defined polymers with designer properties, such as oligonucleotide binding.

Ultra-large chemical libraries for the discovery of high-affinity peptide binders

High-diversity genetically-encoded combinatorial libraries (108-1013 members) are a rich source of peptide-based binding molecules, identified by affinity selection. Synthetic libraries can access broader chemical space, but typically examine only ~ 106 compounds by screening. Here we show that in-solution affinity selection can be interfaced with nano-liquid chromatography-tandem mass spectrometry peptide sequencing to identify binders from fully randomized synthetic libraries of 108 members-a 100-fold gain in diversity over standard practice. To validate this approach, we show that binders to a monoclonal antibody are identified in proportion to library diversity, as diversity is increased from 106-108. These results are then applied to the discovery of p53-like binders to MDM2, and to a family of 3-19 nM-affinity, α/β-peptide-based binders to 14-3-3. An X-ray structure of one of these binders in complex with 14-3-3σ is determined, illustrating the role of β-amino acids in facilitating a key binding contact.

Synthesis of proteins by automated flow chemistry

Ribosomes can produce proteins in minutes and are largely constrained to proteinogenic amino acids. Here, we report highly efficient chemistry matched with an automated fast-flow instrument for the direct manufacturing of peptide chains up to 164 amino acids long over 327 consecutive reactions. The machine is rapid: Peptide chain elongation is complete in hours. We demonstrate the utility of this approach by the chemical synthesis of nine different protein chains that represent enzymes, structural units, and regulatory factors. After purification and folding, the synthetic materials display biophysical and enzymatic properties comparable to the biologically expressed proteins. High-fidelity automated flow chemistry is an alternative for producing single-domain proteins without the ribosome.

Secondary Amino Alcohols: Traceless Cleavable Linkers for Use in Affinity Capture and Release

Capture and release of peptides is often a critical operation in the pathway to discovering materials with novel functions. However, the best methods for efficient capture impede facile release. To overcome this challenge, we report linkers based on secondary amino alcohols for the release of peptides after capture. These amino alcohols are based on serine (seramox) or isoserine (isoseramox) and can be incorporated into peptides during solid-phase peptide synthesis through reductive amination. Both linkers are quantitatively cleaved within minutes under NaIO₄ treatment. Cleavage of isoseramox produced a native peptide N-terminus. This linker also showed broad substrate compatibility; incorporation into a synthetic peptide library resulted in the identification of all sequences by nanoLC-MS/MS. The linkers are cell compatible; a cell-penetrating peptide that contained this linker was efficiently captured and identified after uptake into cells. These findings suggest that such secondary amino alcohol based linkers might be suitable tools for peptide-discovery platforms.