CycLS: Accurate, whole-library sequencing of cyclic peptides using tandem mass spectrometry

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.

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.

The use of nitrogen-15 in microbial natural product discovery and biosynthetic characterization

This mini-review covers the use of nitrogen-15 in bacterial and fungal natural product discovery and biosynthetic characterization from 1970 to 2022. Nitrogen is an important element in a number of bioactive and structurally intriguing natural products including alkaloids, non-ribosomal peptides, and hybrid natural products. Nitrogen-15 can be detected at natural abundance utilizing two-dimensional nuclear magnetic resonance and mass spectrometry. Additionally, it is a stable isotope that can be added to growth media for both filamentous fungi and bacteria. With stable isotope feeding, additional two-dimensional nuclear magnetic resonance and mass spectrometry strategies have become available, and there is a growing trend to use nitrogen-15 stable isotope feeding for the biosynthetic characterization of natural products. This mini-review will catalog the use of these strategies, analyze the strengths and weaknesses of the different approaches, and suggest future directions for the use of nitrogen-15 in natural product discovery and biosynthetic characterization.

Cyclic Peptide Screening Methods for Preclinical Drug Discovery

Cyclic peptides are among the most diverse architectures for current drug discovery efforts. Their size, stability, and ease of synthesis provide attractive scaffolds to engage and modulate some of the most challenging targets, including protein-protein interactions and those considered to be "undruggable". With a variety of sophisticated screening technologies to produce libraries of cyclic peptides, including phage display, mRNA display, split intein circular ligation of peptides, and in silico screening, a new era of cyclic peptide drug discovery is at the forefront of modern medicine. In this perspective, we begin by discussing cyclic peptides approved for clinical use in the past two decades. Particular focus is placed around synthetic chemistries to generate de novo libraries of cyclic peptides and novel methods to screen them. The perspective culminates with future prospects for generating cyclic peptides as viable therapeutic options and discusses the advantages and disadvantages currently being faced with bringing them to market.

MSPoisDM: A Novel Peptide Identification Algorithm Optimized for Tandem Mass Spectra

Tandem mass spectrometry (MS/MS) plays an extremely important role in proteomics research. Thousands of spectra can be generated in modern experiments, how to interpret the LC-MS/MS is a challenging problem in tandem mass spectra analysis. Our peptide identification algorithm, MSPoisDM, is integrated the intensity information which produced by target-decoy statistics, although intensity information often undervalued. Furthermore, in order to combine the intensity information for better, we propose a novel concept scoring model which based on Poisson distribution. Compared with commonly used commercial software Mascot and Sequest at 1% FDR, the results show MSPoisDM is robust and versatile for various datasets which obtained from different instruments. We expect our algorithm MSPoisDM will be broadly applied in the proteomics studies.

Geometrically Diverse Lariat Peptide Scaffolds Reveal an Untapped Chemical Space of High Membrane Permeability

Constrained, membrane-permeable peptides offer the possibility of engaging challenging intracellular targets. Structure-permeability relationships have been extensively studied in cyclic peptides whose backbones are cyclized from head to tail, like the membrane permeable and orally bioavailable natural product cyclosporine A. In contrast, the physicochemical properties of lariat peptides, which are cyclized from one of the termini onto a side chain, have received little attention. Many lariat peptide natural products exhibit interesting biological activities, and some, such as griselimycin and didemnin B, are membrane permeable and have intracellular targets. To investigate the structure-permeability relationships in the chemical space exemplified by these natural products, we generated a library of scaffolds using stable isotopes to encode stereochemistry and determined the passive membrane permeability of over 1000 novel lariat peptide scaffolds with molecular weights around 1000. Many lariats were surprisingly permeable, comparable to many known orally bioavailable drugs. Passive permeability was strongly dependent on N-methylation, stereochemistry, and ring topology. A variety of structure-permeability trends were observed including a relationship between alternating stereochemistry and high permeability, as well as a set of highly permeable consensus sequences. For the first time, robust structure-permeability relationships are established in synthetic lariat peptides exceeding 1000 compounds.

Genome mining strategies for ribosomally synthesised and post-translationally modified peptides

Genome mining is a computational method for the automatic detection and annotation of biosynthetic gene clusters (BGCs) from genomic data. This approach has been increasingly utilised in natural product (NP) discovery due to the large amount of sequencing data that is now available. Ribosomally synthesised and post-translationally modified peptides (RiPPs) are a class of structurally complex NP with diverse bioactivities. RiPPs have recently been shown to occupy a much larger expanse of genomic and chemical space than previously appreciated, indicating that annotation of RiPP BGCs in genomes may have been overlooked in the past. This review provides an overview of the genome mining tools that have been specifically developed to aid in the discovery of RiPP BGCs, which have been built from an increasing knowledgebase of RiPP structures and biosynthesis. Given these recent advances, the application of targeted genome mining has great potential to accelerate the discovery of important molecules such as antimicrobial and anticancer agents whilst increasing our understanding about how these compounds are biosynthesised in nature.

De Novo Peptide Sequencing Reveals Many Cyclopeptides in the Human Gut and Other Environments

Cyclic and branch cyclic peptides (cyclopeptides) represent a class of bioactive natural products that include many antibiotics and anti-tumor compounds. Despite the recent advances in metabolomics analysis, still little is known about the cyclopeptides in the human gut and their possible interactions due to a lack of computational analysis pipelines that are applicable to such compounds. Here, we introduce CycloNovo, an algorithm for automated de novo cyclopeptide analysis and sequencing that employs de Bruijn graphs, the workhorse of DNA sequencing algorithms, to identify cyclopeptides in spectral datasets. CycloNovo reconstructed 32 previously unreported cyclopeptides (to the best of our knowledge) in the human gut and reported over a hundred cyclopeptides in other environments represented by various spectra on Global Natural Products Social Molecular Network (GNPS). https://github.com/bbehsaz/cyclonovo.