State-selective modulation of heterotrimeric Gαs signaling with macrocyclic peptides.

The G protein-coupled receptor cascade leading to production of the second messenger cAMP is replete with pharmacologically targetable proteins, with the exception of the Gα subunit, Gαs. GTPases remain largely undruggable given the difficulty of displacing high-affinity guanine nucleotides and the lack of other drug binding sites. We explored a chemical library of 1012 cyclic peptides to expand the chemical search for inhibitors of this enzyme class. We identified two macrocyclic peptides, GN13 and GD20, that antagonize the active and inactive states of Gαs, respectively. Both macrocyclic peptides fine-tune Gαs activity with high nucleotide-binding-state selectivity and G protein class-specificity. Co-crystal structures reveal that GN13 and GD20 distinguish the conformational differences within the switch II/α3 pocket. Cell-permeable analogs of GN13 and GD20 modulate Gαs/Gßγ signaling in cells through binding to crystallographically defined pockets. The discovery of cyclic peptide inhibitors targeting Gαs provides a path for further development of state-dependent GTPase inhibitors.

Ribosome-Targeting Antibiotics Impair T Cell Effector Function and Ameliorate Autoimmunity by Blocking Mitochondrial Protein Synthesis.

While antibiotics are intended to specifically target bacteria, most are known to affect host cell physiology. In addition, some antibiotic classes are reported as immunosuppressive for reasons that remain unclear. Here, we show that Linezolid, a ribosomal-targeting antibiotic (RAbo), effectively blocked the course of a T cell-mediated autoimmune disease. Linezolid and other RAbos were strong inhibitors of T helper-17 cell effector function in vitro, showing that this effect was independent of their antibiotic activity. Perturbing mitochondrial translation in differentiating T cells, either with RAbos or through the inhibition of mitochondrial elongation factor G1 (mEF-G1) progressively compromised the integrity of the electron transport chain. Ultimately, this led to deficient oxidative phosphorylation, diminishing nicotinamide adenine dinucleotide concentrations and impairing cytokine production in differentiating T cells. In accordance, mice lacking mEF-G1 in T cells were protected from experimental autoimmune encephalomyelitis, demonstrating that this pathway is crucial in maintaining T cell function and pathogenicity.

Discovery, biochemical characterization, and bioengineering of cyanobactin prenyltransferases.

Prenylation is a post-translational modification (PTM) widely found in primary and secondary metabolism. This modification can enhance the lipophilicity of molecules, enabling them to interact with lipid membranes more effectively. The prenylation of peptides is often carried out by cyanobactin prenyltransferases (PTases) from cyanobacteria. These enzymes are of interest due to their ability to add prenyl groups to unmodified peptides, thus making them more effective therapeutics through the subsequent acquisition of increased membrane permeability and bioavailability. Herein we review the current knowledge of cyanobactin PTases, focusing on their discovery, biochemistry, and bioengineering, and highlight the potential application of them as peptide alkylation biocatalysts to generate peptide therapeutics.

Short macrocyclic peptides in sponge genomes.

Sponges (Porifera) contain many peptide-specialized metabolites with potent biological activities and significant roles in shaping marine ecology. It is well established that symbiotic bacteria produce bioactive "sponge" peptides, both on the ribosome (RiPPs) and nonribosomally. Here, we demonstrate that sponges themselves also produce many bioactive macrocyclic peptides, such as phakellistatins and related proline-rich macrocyclic peptides (PRMPs). Using the Stylissa carteri sponge transcriptome, methods were developed to find sequences encoding 46 distinct RiPP-type core peptides, of which ten encoded previously identified PRMP sequences. With this basis set, the genome and transcriptome of the sponge Axinella corrugata was interrogated to find 35 PRMP precursor peptides encoding 31 unique core peptide sequences. At least 11 of these produced cyclic peptides that were present in the sponge and could be characterized by mass spectrometry, including stylissamides A-D and seven previously undescribed compounds. Precursor peptides were encoded in the A. corrugata genome, confirming their animal origin. The peptides contained signal peptide sequences and highly repetitive recognition sequence-core peptide elements with up to 25 PRMP copies in a single precursor. In comparison to sponges without PRMPs, PRMP sponges are incredibly enriched in potentially secreted polypeptides, with >23,000 individual signal peptide encoding genes found in a single transcriptome. The similarities between PRMP biosynthetic genes and neuropeptides in terms of their biosynthetic logic suggest a fundamental biology linked to circular peptides, possibly indicating a widespread and underappreciated diversity of signaling peptide post-translational modifications across the animal kingdom.

Selective ligand recognition and activation of somatostatin receptors SSTR1 and SSTR3.

Somatostatin receptors (SSTRs) exert critical biological functions such as negatively regulating hormone release and cell proliferation, making them popular targets for developing therapeutics to treat endocrine disorders, especially neuroendocrine tumors. Although several panagonists mimicking the endogenous ligand somatostatin are available, the development of more effective and safer somatostatinergic therapies is limited due to a lack of molecular understanding of the ligand recognition and regulation of divergent SSTR subtypes. Here, we report four cryoelectron microscopy structures of Gi-coupled SSTR1 and SSTR3 activated by distinct agonists, including the FDA-approved panagonist pasireotide as well as their selective small molecule agonists L-797591 and L-796778. Our structures reveal a conserved recognition pattern of pasireotide in SSTRs attributed to the binding with a conserved extended binding pocket, distinct from SST14, octreotide, and lanreotide. Together with mutagenesis analyses, our structures further reveal the dynamic feature of ligand binding pockets in SSTR1 and SSTR3 to accommodate divergent agonists, the key determinants of ligand selectivity lying across the orthosteric pocket of different SSTR subtypes, as well as the molecular mechanism underlying diversity and conservation of receptor activation. Our work provides a framework for rational design of subtype-selective SSTR ligands and may facilitate drug development efforts targeting SSTRs with improved therapeutic efficacy and reduced side effects.

Structural basis for activation of somatostatin receptor 5 by cyclic neuropeptide agonists.

Somatostatin receptor 5 (SSTR5) is an important G protein-coupled receptor and drug target for neuroendocrine tumors and pituitary disorders. This study presents two high-resolution cryogenicelectron microscope structures of the SSTR5-Gi complexes bound to the cyclic neuropeptide agonists, cortistatin-17 (CST17) and octreotide, with resolutions of 2.7 Å and 2.9 Å, respectively. The structures reveal that binding of these peptides causes rearrangement of a "hydrophobic lock", consisting of residues from transmembrane helices TM3 and TM6. This rearrangement triggers outward movement of TM6, enabling Gαi protein engagement and receptor activation. In addition to hydrophobic interactions, CST17 forms conserved polar contacts similar to somatostatin-14 binding to SSTR2, while further structural and functional analysis shows that extracellular loops differently recognize CST17 and octreotide. These insights elucidate agonist selectivity and activation mechanisms of SSTR5, providing valuable guidance for structure-based drug development targeting this therapeutically relevant receptor.

Stabilization of interdomain closure by a G protein inhibitor.

Inhibitors of heterotrimeric G proteins are being developed as therapeutic agents. Epitomizing this approach are YM-254890 (YM) and FR900359 (FR), which are efficacious in models of thrombosis, hypertension, obesity, asthma, uveal melanoma, and pain, and under investigation as an FR-antibody conjugate in uveal melanoma clinical trials. YM/FR inhibits the Gq/11/14 subfamily by interfering with GDP (guanosine diphosphate) release, but by an unknown biophysical mechanism. Here, we show that YM inhibits GDP release by stabilizing closure between the Ras-like and α-helical domains of a Gα subunit. Nucleotide-free Gα adopts an ensemble of open and closed configurations, as indicated by single-molecule Förster resonance energy transfer and molecular dynamics simulations, whereas GDP and GTPγS (guanosine 5'-O-[gamma-thio]triphosphate) stabilize distinct closed configurations. YM stabilizes closure in the presence or absence of GDP without requiring an intact interdomain interface. All three classes of mammalian Gα subunits that are insensitive to YM/FR possess homologous but degenerate YM/FR binding sites, yet can be inhibited upon transplantation of the YM/FR binding site of Gq. Novel YM/FR analogs tailored to each class of G protein will provide powerful new tools for therapeutic investigation.

CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides.

Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.

CycPeptMP: enhancing membrane permeability prediction of cyclic peptides with multi-level molecular features and data augmentation.

Cyclic peptides are versatile therapeutic agents that boast high binding affinity, minimal toxicity, and the potential to engage challenging protein targets. However, the pharmaceutical utility of cyclic peptides is limited by their low membrane permeability-an essential indicator of oral bioavailability and intracellular targeting. Current machine learning-based models of cyclic peptide permeability show variable performance owing to the limitations of experimental data. Furthermore, these methods use features derived from the whole molecule that have traditionally been used to predict small molecules and ignore the unique structural properties of cyclic peptides. This study presents CycPeptMP: an accurate and efficient method to predict cyclic peptide membrane permeability. We designed features for cyclic peptides at the atom-, monomer-, and peptide-levels and seamlessly integrated these into a fusion model using deep learning technology. Additionally, we applied various data augmentation techniques to enhance model training efficiency using the latest data. The fusion model exhibited excellent prediction performance for the logarithm of permeability, with a mean absolute error of $0.355$ and correlation coefficient of $0.883$. Ablation studies demonstrated that all feature levels contributed and were relatively essential to predicting membrane permeability, confirming the effectiveness of augmentation to improve prediction accuracy. A comparison with a molecular dynamics-based method showed that CycPeptMP accurately predicted peptide permeability, which is otherwise difficult to predict using simulations.

HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.

In recent years, cyclic peptides have emerged as a promising therapeutic modality due to their diverse biological activities. Understanding the structures of these cyclic peptides and their complexes is crucial for unlocking invaluable insights about protein target-cyclic peptide interaction, which can facilitate the development of novel-related drugs. However, conducting experimental observations is time-consuming and expensive. Computer-aided drug design methods are not practical enough in real-world applications. To tackles this challenge, we introduce HighFold, an AlphaFold-derived model in this study. By integrating specific details about the head-to-tail circle and disulfide bridge structures, the HighFold model can accurately predict the structures of cyclic peptides and their complexes. Our model demonstrates superior predictive performance compared to other existing approaches, representing a significant advancement in structure-activity research. The HighFold model is openly accessible at https://github.com/hongliangduan/HighFold.

Structure prediction of linear and cyclic peptides using CABS-flex.

The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The protocol combines two main stages: coarse-grained simulations using the CABS-flex standalone package and an all-atom reconstruction-optimization process using the Modeller program. We evaluated the protocol on a set of linear peptides and two sets of cyclic peptides, with cyclization through the backbone and disulfide bonds. A comparison with other state-of-the-art tools (APPTEST, PEP-FOLD, ESMFold and AlphaFold implementation in ColabFold) shows that for most cases, AlphaFold offers the highest resolution. However, CABS-flex is competitive, particularly when it comes to short linear peptides. As demonstrated, the protocol performance can be further improved by combination with the residue-residue contact prediction method or more efficient scoring. The protocol is included in the CABS-flex standalone package along with online documentation to aid users in predicting the structure of peptides and mini-proteins.

De novo development of small cyclic peptides that are orally bioavailable.

Cyclic peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, as with biological drugs, most cyclic peptides cannot be applied orally because they are rapidly digested and/or display low absorption in the gastrointestinal tract, hampering their development as therapeutics. In this study, we developed a combinatorial synthesis and screening approach based on sequential cyclization and one-pot peptide acylation and screening, with the possibility of simultaneously interrogating activity and permeability. In a proof of concept, we synthesized a library of 8,448 cyclic peptides and screened them against the disease target thrombin. Our workflow allowed multiple iterative cycles of library synthesis and yielded cyclic peptides with nanomolar affinities, high stabilities and an oral bioavailability (%F) as high as 18% in rats. This method for generating orally available peptides is general and provides a promising push toward unlocking the full potential of peptides as therapeutics.

Biocatalytic cyclization of small macrolactams by a penicillin-binding protein-type thioesterase.

Macrocyclic peptides represent promising scaffolds for chemical tools and potential therapeutics. Synthetic methods for peptide macrocyclization are often hampered by C-terminal epimerization and oligomerization, leading to difficult scalability. While chemical strategies to circumvent this issue exist, they often require specific amino acids to be present in the peptide sequence. Herein, we report the characterization of Ulm16, a peptide cyclase belonging to the penicillin-binding protein-type class of thioesterases that catalyze head-to-tail macrolactamization of nonribosmal peptides. Ulm16 efficiently cyclizes various nonnative peptides ranging from 4 to 6 amino acids with catalytic efficiencies of up to 3 × 106 M-1 s-1. Unlike many previously described homologs, Ulm16 tolerates a variety of C- and N-terminal amino acids. The crystal structure of Ulm16, along with modeling of its substrates and site-directed mutagenesis, allows for rationalization of this wide substrate scope. Overall, Ulm16 represents a promising tool for the biocatalytic production of macrocyclic peptides.

Potent and specific antibiotic combination therapy against Clostridioides difficile.

Keratinicyclins and keratinimicins are recently discovered glycopeptide antibiotics. Keratinimicins show broad-spectrum activity against Gram-positive bacteria, while keratinicyclins form a new chemotype by virtue of an unusual oxazolidinone moiety and exhibit specific antibiosis against Clostridioides difficile. Here we report the mechanism of action of keratinicyclin B (KCB). We find that steric constraints preclude KCB from binding peptidoglycan termini. Instead, KCB inhibits C. difficile growth by binding wall teichoic acids (WTAs) and interfering with cell wall remodeling. A computational model, guided by biochemical studies, provides an image of the interaction of KCB with C. difficile WTAs and shows that the same H-bonding framework used by glycopeptide antibiotics to bind peptidoglycan termini is used by KCB for interacting with WTAs. Analysis of KCB in combination with vancomycin (VAN) shows highly synergistic and specific antimicrobial activity, and that nanomolar combinations of the two drugs are sufficient for complete growth inhibition of C. difficile, while leaving common commensal strains unaffected.

Evolution-guided discovery of antibiotics that inhibit peptidoglycan remodelling.

Addressing the ongoing antibiotic crisis requires the discovery of compounds with novel mechanisms of action that are capable of treating drug-resistant infections1. Many antibiotics are sourced from specialized metabolites produced by bacteria, particularly those of the Actinomycetes family2. Although actinomycete extracts have traditionally been screened using activity-based platforms, this approach has become unfavourable owing to the frequent rediscovery of known compounds. Genome sequencing of actinomycetes reveals an untapped reservoir of biosynthetic gene clusters, but prioritization is required to predict which gene clusters may yield promising new chemical matter2. Here we make use of the phylogeny of biosynthetic genes along with the lack of known resistance determinants to predict divergent members of the glycopeptide family of antibiotics that are likely to possess new biological activities. Using these predictions, we uncovered two members of a new functional class of glycopeptide antibiotics-the known glycopeptide antibiotic complestatin and a newly discovered compound we call corbomycin-that have a novel mode of action. We show that by binding to peptidoglycan, complestatin and corbomycin block the action of autolysins-essential peptidoglycan hydrolases that are required for remodelling of the cell wall during growth. Corbomycin and complestatin have low levels of resistance development and are effective in reducing bacterial burden in a mouse model of skin MRSA infection.

A macrocyclic peptide inhibitor traps MRP1 in a catalytically incompetent conformation.

Adenosine triphosphate-binding cassette (ABC) transporters, such as multidrug resistance protein 1 (MRP1), protect against cellular toxicity by exporting xenobiotic compounds across the plasma membrane. However, constitutive MRP1 function hinders drug delivery across the blood-brain barrier, and MRP1 overexpression in certain cancers leads to acquired multidrug resistance and chemotherapy failure. Small-molecule inhibitors have the potential to block substrate transport, but few show specificity for MRP1. Here we identify a macrocyclic peptide, named CPI1, which inhibits MRP1 with nanomolar potency but shows minimal inhibition of a related multidrug transporter P-glycoprotein. A cryoelectron microscopy (cryo-EM) structure at 3.27 Å resolution shows that CPI1 binds MRP1 at the same location as the physiological substrate leukotriene C4 (LTC4). Residues that interact with both ligands contain large, flexible sidechains that can form a variety of interactions, revealing how MRP1 recognizes multiple structurally unrelated molecules. CPI1 binding prevents the conformational changes necessary for adenosine triphosphate (ATP) hydrolysis and substrate transport, suggesting it may have potential as a therapeutic candidate.

MuCoCP: a priori chemical knowledge-based multimodal contrastive learning pre-trained neural network for the prediction of cyclic peptide membrane penetration ability.

MOTIVATION: There has been a burgeoning interest in cyclic peptide therapeutics due to their various outstanding advantages and strong potential for drug formation. However, it is undoubtedly costly and inefficient to use traditional wet lab methods to clarify their biological activities. Using artificial intelligence instead is a more energy-efficient and faster approach. MuCoCP aims to build a complete pre-trained model for extracting potential features of cyclic peptides, which can be fine-tuned to accurately predict cyclic peptide bioactivity on various downstream tasks. To maximize its effectiveness, we use a novel data augmentation method based on a priori chemical knowledge and multiple unsupervised training objective functions to greatly improve the information-grabbing ability of the model. RESULTS: To assay the efficacy of the model, we conducted validation on the membrane-permeability of cyclic peptides which achieved an accuracy of 0.87 and R-squared of 0.503 on CycPeptMPDB using semi-supervised training and obtained an accuracy of 0.84 and R-squared of 0.384 using a model with frozen parameters on an external dataset. This result has achieved state-of-the-art, which substantiates the stability and generalization capability of MuCoCP. It means that MuCoCP can fully explore the high-dimensional information of cyclic peptides and make accurate predictions on downstream bioactivity tasks, which will serve as a guide for the future de novo design of cyclic peptide drugs and promote the development of cyclic peptide drugs. AVAILABILITY AND IMPLEMENTATION: All code used in our proposed method can be found at https://github.com/lennonyu11234/MuCoCP.

HELM-GPT: de novo macrocyclic peptide design using generative pre-trained transformer.

MOTIVATION: Macrocyclic peptides hold great promise as therapeutics targeting intracellular proteins. This stems from their remarkable ability to bind flat protein surfaces with high affinity and specificity while potentially traversing the cell membrane. Research has already explored their use in developing inhibitors for intracellular proteins, such as KRAS, a well-known driver in various cancers. However, computational approaches for de novo macrocyclic peptide design remain largely unexplored. RESULTS: Here, we introduce HELM-GPT, a novel method that combines the strength of the hierarchical editing language for macromolecules (HELM) representation and generative pre-trained transformer (GPT) for de novo macrocyclic peptide design. Through reinforcement learning (RL), our experiments demonstrate that HELM-GPT has the ability to generate valid macrocyclic peptides and optimize their properties. Furthermore, we introduce a contrastive preference loss during the RL process, further enhanced the optimization performance. Finally, to co-optimize peptide permeability and KRAS binding affinity, we propose a step-by-step optimization strategy, demonstrating its effectiveness in generating molecules fulfilling both criteria. In conclusion, the HELM-GPT method can be used to identify novel macrocyclic peptides to target intracellular proteins. AVAILABILITY AND IMPLEMENTATION: The code and data of HELM-GPT are freely available on GitHub (https://github.com/charlesxu90/helm-gpt).

An anti-biofilm cyclic peptide targets a secreted aminopeptidase from P. aeruginosa.

Pseudomonas aeruginosa is an opportunistic pathogen that causes serious illness, especially in immunocompromised individuals. P. aeruginosa forms biofilms that contribute to growth and persistence in a wide range of environments. Here we investigated the aminopeptidase, P. aeruginosa aminopeptidase (PaAP) from P. aeruginosa, which is highly abundant in the biofilm matrix. PaAP is associated with biofilm development and contributes to nutrient recycling. We confirmed that post-translational processing was required for activation and PaAP is a promiscuous aminopeptidase acting on unstructured regions of peptides and proteins. Crystal structures of wild-type enzymes and variants revealed the mechanism of autoinhibition, whereby the C-terminal propeptide locks the protease-associated domain and the catalytic peptidase domain into a self-inhibited conformation. Inspired by this, we designed a highly potent small cyclic-peptide inhibitor that recapitulates the deleterious phenotype observed with a PaAP deletion variant in biofilm assays and present a path toward targeting secreted proteins in a biofilm context.

Discovery of unusual dimeric piperazyl cyclopeptides encoded by a Lentzea flaviverrucosa DSM 44664 biosynthetic supercluster.

Rare actinomycetes represent an underexploited source of new bioactive compounds. Here, we report the use of a targeted metabologenomic approach to identify piperazyl compounds in the rare actinomycete Lentzea flaviverrucosa DSM 44664. These efforts to identify molecules that incorporate piperazate building blocks resulted in the discovery and structural elucidation of two dimeric biaryl-cyclohexapeptides, petrichorins A and B. Petrichorin B is a symmetric homodimer similar to the known compound chloptosin, but petrichorin A is unique among known piperazyl cyclopeptides because it is an asymmetric heterodimer. Due to the structural complexity of petrichorin A, solving its structure required a combination of several standard chemical methods plus in silico modeling, strain mutagenesis, and solving the structure of its biosynthetic intermediate petrichorin C for confident assignment. Furthermore, we found that the piperazyl cyclopeptides comprising each half of the petrichorin A heterodimer are made via two distinct nonribosomal peptide synthetase (NRPS) assembly lines, and the responsible NRPS enzymes are encoded within a contiguous biosynthetic supercluster on the L. flaviverrucosa chromosome. Requiring promiscuous cytochrome p450 crosslinking events for asymmetric and symmetric biaryl production, petrichorins A and B exhibited potent in vitro activity against A2780 human ovarian cancer, HT1080 fibrosarcoma, PC3 human prostate cancer, and Jurkat human T lymphocyte cell lines with IC50 values at low nM levels. Cyclic piperazyl peptides and their crosslinked derivatives are interesting drug leads, and our findings highlight the potential for heterodimeric bicyclic peptides such as petrichorin A for inclusion in future pharmaceutical design and discovery programs.