Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions.

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

GhHAM regulates GoPGF-dependent gland development and contributes to broad-spectrum pest resistance in cotton.

Cotton is a globally cultivated crop, producing 87% of the natural fiber used in the global textile industry. The pigment glands, unique to cotton and its relatives, serve as a defense structure against pests and pathogens. However, the molecular mechanism underlying gland formation and the specific role of pigment glands in cotton's pest defense are still not well understood. In this study, we cloned a gland-related transcription factor GhHAM and generated the GhHAM knockout mutant using CRISPR/Cas9. Phenotypic observations, transcriptome analysis, and promoter-binding experiments revealed that GhHAM binds to the promoter of GoPGF, regulating pigment gland formation in cotton's multiple organs via the GoPGF-GhJUB1 module. The knockout of GhHAM significantly reduced gossypol production and increased cotton's susceptibility to pests in the field. Feeding assays demonstrated that more than 80% of the cotton bollworm larvae preferred ghham over the wild type. Furthermore, the ghham mutants displayed shorter cell length and decreased gibberellins (GA) production in the stem. Exogenous application of GA3 restored stem cell elongation but not gland formation, thereby indicating that GhHAM controls gland morphogenesis independently of GA. Our study sheds light on the functional differentiation of HAM proteins among plant species, highlights the significant role of pigment glands in influencing pest feeding preference, and provides a theoretical basis for breeding pest-resistant cotton varieties to address the challenges posed by frequent outbreaks of pests.

Bioinformatics toolbox for exploring target mutation-induced drug resistance.

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way. However, these resources are scattered and underutilized, and their strengths and limitations have not been systematically analyzed and compared. Here, we systematically surveyed 59 freely available bioinformatics tools for exploring target mutation-induced drug resistance. We analyzed and summarized these resources based on their functionality, data volume, data source, operating principle, performance, etc. And we concisely discussed the strengths, limitations and application examples of these tools. Specifically, we tested some predictive tools and offered some thoughts from the clinician's perspective. Hopefully, this work will provide a useful toolbox for researchers working in the biomedical, pesticide, bioinformatics and pharmaceutical engineering fields, and a good platform for non-specialists to quickly understand drug resistance prediction.

Human-virus protein-protein interactions maps assist in revealing the pathogenesis of viral infection.

Many significant viral infections have been recorded in human history, which have caused enormous negative impacts worldwide. Human-virus protein-protein interactions (PPIs) mediate viral infection and immune processes in the host. The identification, quantification, localization, and construction of human-virus PPIs maps are critical prerequisites for understanding the biophysical basis of the viral invasion process and characterising the framework for all protein functions. With the technological revolution and the introduction of artificial intelligence, the human-virus PPIs maps have been expanded rapidly in the past decade and shed light on solving complicated biomedical problems. However, there is still a lack of prospective insight into the field. In this work, we comprehensively review and compare the effectiveness, potential, and limitations of diverse approaches for constructing large-scale PPIs maps in human-virus, including experimental methods based on biophysics and biochemistry, databases of human-virus PPIs, computational methods based on artificial intelligence, and tools for visualising PPIs maps. The work aims to provide a toolbox for researchers, hoping to better assist in deciphering the relationship between humans and viruses.

ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner. The Auto Core Fragment in silico Screening (ACFIS) server is a well-established and effective online tool for FBDD. However, the accurate prediction of protein-fragment binding mode and affinity is still a major challenge for FBDD due to weak binding affinity. Here, we present an updated version (ACFIS 2.0), that incorporates a dynamic fragment growing strategy to consider protein flexibility. The major improvements of ACFIS 2.0 include (i) increased accuracy of hit compound identification (from 75.4% to 88.5% using the same test set), (ii) improved rationality of the protein-fragment binding mode, (iii) increased structural diversity due to expanded fragment libraries and (iv) inclusion of more comprehensive functionality for predicting molecular properties. Three successful cases of drug lead discovery using ACFIS 2.0 are described, including drugs leads to treat Parkinson's disease, cancer, and major depressive disorder. These cases demonstrate the utility of this web-based server. ACFIS 2.0 is freely available at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS2/.

Unraveling the secrets: Evolution of resistance mediated by membrane proteins.

Membrane protein-mediated resistance is a multidisciplinary challenge that spans fields such as medicine, agriculture, and environmental science. Understanding its complexity and devising innovative strategies are crucial for treating diseases like cancer and managing resistant pests in agriculture. This paper explores the dual nature of resistance mechanisms across different organisms: On one hand, animals, bacteria, fungi, plants, and insects exhibit convergent evolution, leading to the development of similar resistance mechanisms. On the other hand, influenced by diverse environmental pressures and structural differences among organisms, they also demonstrate divergent resistance characteristics. Membrane protein-mediated resistance mechanisms are prevalent across animals, bacteria, fungi, plants, and insects, reflecting their shared survival strategies evolved through convergent evolution to address similar survival challenges. However, variations in ecological environments and biological characteristics result in differing responses to resistance. Therefore, examining these differences not only enhances our understanding of adaptive resistance mechanisms but also provides crucial theoretical support and insights for addressing drug resistance and advancing pharmaceutical development.

Fluorescent chemosensors facilitate the visualization of plant health and their living environment in sustainable agriculture.

Globally, 91% of plant production encounters diverse environmental stresses that adversely affect their growth, leading to severe yield losses of 50-60%. In this case, monitoring the connection between the environment and plant health can balance population demands with environmental protection and resource distribution. Fluorescent chemosensors have shown great progress in monitoring the health and environment of plants due to their high sensitivity and biocompatibility. However, to date, no comprehensive analysis and systematic summary of fluorescent chemosensors used in monitoring the correlation between plant health and their environment have been reported. Thus, herein, we summarize the current fluorescent chemosensors ranging from their design strategies to applications in monitoring plant-environment interaction processes. First, we highlight the types of fluorescent chemosensors with design strategies to resolve the bottlenecks encountered in monitoring the health and living environment of plants. In addition, the applications of fluorescent small-molecule, nano and supramolecular chemosensors in the visualization of the health and living environment of plants are discussed. Finally, the major challenges and perspectives in this field are presented. This work will provide guidance for the design of efficient fluorescent chemosensors to monitor plant health, and then promote sustainable agricultural development.

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era.

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations.

Protein kinases play crucial roles in many cellular signaling processes, making them become important targets for drug discovery. But drug resistance mediated by mutation puts a barrier to the therapeutic effect of kinase inhibitors. Fragment-based drug discovery has been successfully applied to overcome such resistance. However, the complicate kinase-inhibitor fragment interaction and fragment-to-lead process seriously limit the efficiency of kinase inhibitor discovery against resistance caused by mutation. Here, we constructed a comprehensive web platform KinaFrag for the fragment-based kinase inhibitor discovery to overcome resistance. The kinase-inhibitor fragment space was investigated from 7783 crystal kinase-inhibitor fragment complexes, and the structural requirements of kinase subpockets were analyzed. The core fragment-based virtual screening workflow towards specific subpockets was developed to generate new kinase inhibitors. A series of tropomyosin receptor kinase (TRK) inhibitors were designed, and the most potent compound YT9 exhibits up to 70-fold activity improvement than marketed drugs larotrectinib and selitrectinib against G595R, G667C and F589L mutations of TRKA. YT9 shows promising antiproliferative against tumor cells in vitro and effectively inhibits tumor growth in vivo for wild type TRK and TRK mutants. Our results illustrate the great potential of KinaFrag in the kinase inhibitor discovery to combat resistance mediated by mutation. KinaFrag is freely available at http://chemyang.ccnu.edu.cn/ccb/database/KinaFrag/.

PTMdyna: exploring the influence of post-translation modifications on protein conformational dynamics.

Protein post-translational modifications (PTM) play vital roles in cellular regulation, modulating functions by driving changes in protein structure and dynamics. Exploring comprehensively the influence of PTM on conformational dynamics can facilitate the understanding of the related biological function and molecular mechanism. Currently, a series of excellent computation tools have been designed to analyze the time-dependent structural properties of proteins. However, the protocol aimed to explore conformational dynamics of post-translational modified protein is still a blank. To fill this gap, we present PTMdyna to visually predict the conformational dynamics differences between unmodified and modified proteins, thus indicating the influence of specific PTM. PTMdyna exhibits an AUC of 0.884 tested on 220 protein-protein complex structures. The case of heterochromatin protein 1α complexed with lysine 9-methylated histone H3, which is critical for genomic stability and cell differentiation, was used to demonstrate its applicability. PTMdyna provides a reliable platform to predict the influence of PTM on protein dynamics, making it easier to interpret PTM functionality at the structure level. The web server is freely available at http://ccbportal.com/PTMdyna.

Preliminary evaluation of the protective effect of rEi-SAG19 on Eimeria intestinalis infection in rabbits.

Eimeria intestinalis is one of the most pathogenic coccidia species in rabbits. Anticoccidial treaments are the main measures to control rabbit coccidiosis now, but there are drug resistance and residues concerns. Therefore, vaccine has been used as an alternative strategy. The surface antigens (SAGs) of apicomplexan protozoa play a role in adhesion and invasion of host intestinal cells, and are considered to be potential candidate antigens for vaccines. In this study, transcriptional analysis of 5 Ei-SAGs genes at four developmental stages was conducted, then the Ei-SAG19 gene were screened out for prokaryotic expression and the reactogenicity of recombinant SAG19 (rEi-SAG19) was investigated by immunoblotting. To assessment the protective effects of rEi-SAG19, rabbits (n = 40) were randomly divided into four groups (Blank control, PBS-infected, Trx-His-S-Quil-A-infected and rEi-SAG19 immunized groups), the rEi-SAG19 immunized group was subcutaneously immunized with 100 µg rEi-SAG19 in the neck with an interval of two weeks, and challenged with 5×104 homologous oocysts two weeks after the second immunization. Two weeks after the challenge, all rabbits were sacrificed. After that, the level of serum specific IgG antibody was detected weekly and the level of cytokines in serum before the challenge were determined. At the end of the experiment, the weight gain, oocyst reduction rate, lesion score and anticoccidial index (ACI) were calculated. The results showed that rEi-SAG19 has a good reactogenicity. The relative weight gain rate, oocyst reduction rate and ACI of the rabbits in rEi-SAG19 immunized group were 80.51%, 72.6%, and 165.1, respectively, which has a moderate protective effect. The level of serum specific IgG antibody and IL-4 rised significantly (P < 0.05), but the levels of IL-2, IFN-γ and IL-10 had no significant difference (P > 0.05). Our results indicated that rEi-SAG19 could provides moderate protective effect against E. intestinalis infection in rabbits (ACI = 165.1). Therefore, rEi-SAG19 could be used as a vaccine candidate antigen for E. intestinalis.

Evaluation of the immunoprotective effect of the recombinant Eimeria intestinalis rhoptry protein 25 and rhoptry protein 30 on New Zealand rabbits.

BACKGROUND: Rabbit coccidiosis is a parasitism caused by either one or multiple co-infections of Eimeria species. Among them, Eimeria intestinalis is the primary pathogen responsible for diarrhea, growth retardation, and potential mortality in rabbits. Concerns regarding drug resistance and drug residues have led to the development of recombinant subunit vaccines targeting Eimeria species as a promising preventive measure. The aim of this study was to assess the immunoprotective efficacy of recombinant subunit vaccines comprising EiROP25 and EiROP30 (rhoptry proteins (ROPs)) against E. intestinalis infection in rabbits. METHODS: Cloning, prokaryotic expression, and protein purification were performed to obtain EiROP25 and EiROP30. Five groups of fifty 35-day-old Eimeria-free rabbits were created (unchallenged control group, challenged control group, vector protein control group, rEiROP25 group, and rEiROP30 group), with 10 rabbits in each group. Rabbits in the rEiROP25 and rEiROP30 groups were immunized with the recombinant proteins (100 µg per rabbit) for primary and booster immunization (100 µg per rabbit) at a two-week intervals, and challenged with 7 × 104 oocysts per rabbit after an additional two-week interval. Two weeks after the challenge, the rabbits were euthanized for analysis. Weekly collections of rabbit sera were made to measure changes in specific IgG and cytokine level. Clinical symptoms and pathological changes after challenge were observed and recorded. At the conclusion of the animal experiment, lesion scores, the relative weight increase ratio, the oocyst reduction rate, and the anticoccidial index were computed. RESULTS: Rabbits immunized with rEiROP25 and rEiROP30 exhibited relative weight gain ratios of 56.57% and 72.36%, respectively. Oocysts decreased by 78.14% and 84.06% for the rEiROP25 and rEiROP30 groups, respectively. The anticoccidial indexes were 140 and 155. Furthermore, there was a noticeable drop in intestinal lesions. After the primary immunization with rEiROP25 and rEiROP30, a week later, there was a notable rise in specific IgG levels, which remained elevated for two weeks following challenge (P < 0.05). Interleukin (IL)-2 levels increased markedly in the rEiROP25 group, whereas IL-2, interferon gamma (IFN-γ), and IL-4 levels increased substantially in the rEiROP30 group (P < 0.05). CONCLUSION: Immunization of rabbits indicated that both rEiROP25 and rEiROP30 are capable of inducing an increase in specific antibody levels. rEiROP25 triggered a Th1-type immune protection response, while rEiROP30 elicited a Th1/Th2 mixed response. EiROP25 and EiROP30 can generate a moderate level of immune protection, with better efficacy observed for EiROP30. This study provides valuable insights for the promotion of recombinant subunit vaccines targeting rabbit E. intestinalis infection.

Mapping cryptic binding sites of drug targets to overcome drug resistance.

The emergence of drug resistance is a primary obstacle for successful chemotherapy. Drugs that target cryptic binding sites (CBSs) represent a novel strategy for overcoming drug resistance. In this short communication, we explain and discuss how the discovery of CBSs and their inhibitors can overcome drug resistance.

Protection against Eimeria intestinalis infection in rabbits immunized with the recombinant elongation factors EF1α and EFG.

Eimeria intestinalis is the most pathogenic species of rabbit coccidiosis, causing weight loss, diarrhea, and even acute death. The currently used anticoccidial drugs against E. intestinalis in rabbits are associated with drug resistance and residues. Immunological control might be a potential alternative. We cloned and expressed the E. intestinalis recombinant EF1α and EFG (rEi-EF1α and rEi-EFG, respectively). Rabbits were immunized subcutaneously every 14 days with 100 µg of rEi-EF1α and rEi-EFG and followed by 5 × 104 E. intestinalis sporulated oocysts orally challenge. Serum samples were collected every 7 days to measure the levels of specific antibodies and cytokines. On post-challenge day 14, rabbits were sacrificed and the anticoccidial index was evaluated. The rabbits of PBS challenged groups exhibited anorexia, diarrhea, marked intestinal wall thickening, and white nodules that formed patches, while rabbits from the rEi-EF1α or rEi-EFG challenged group exhibited milder symptoms. The rEi-EF1α group showed a 75.18% oocyst reduction and 89.01%wt gain; the rEi-EFG group had a 60.58% oocyst reduction and 56.04%wt gain. After vaccination, specific IgG levels increased and stayed high (P < 0.05). The IL-4 and IL-2 levels of rEi-EF1α immunized groups showed a significant increase after immunization (P < 0.05). Both rEi-EF1α and rEi-EFG could induce humoral and cellular immune responses. In contrast, rabbits immunized with rEi-EF1α were better protected from challenge by E. intestinalis than rEi-EFG.

Web repositories of natural agents promote pests and pathogenic microbes management.

The grand challenge to meet the increasing demands for food by a rapidly growing global population requires protecting crops from pests. Natural active substances play a significant role in the sustainable pests and pathogenic microbes management. In recent years, natural products- (NPs), antimicrobial peptides- (AMPs), medicinal plant- and plant essential oils (EOs)-related online resources have greatly facilitated the development of pests and pathogenic microbes control agents in an efficient and economical manner. However, a comprehensive comparison, analysis and summary of these existing web resources are still lacking. Here, we surveyed these databases of NPs, AMPs, medicinal plants and plant EOs with insecticidal, antibacterial, antiviral and antifungal activity, and we compared their functionality, data volume, data sources and applicability. We comprehensively discussed the limitation of these web resources. This study provides a toolbox for bench scientists working in the pesticide, botany, biomedical and pharmaceutical engineering fields. The aim of the review is to hope that these web resources will facilitate the discovery and development of potential active ingredients of pests and pathogenic microbes control agents.

HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.

Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http://chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http://agroda.gzu.edu.cn:9999/ccb/server/HISNAPI/.

Bioinformatics toolbox for exploring protein phosphorylation network.

A clear systematic delineation of the interactions between phosphorylation sites on substrates and their effector kinases plays a fundamental role in revealing cellular activities, understanding signaling modulation mechanisms and proposing novel hypotheses. The emergence of bioinformatics tools contributes to studying phosphorylation network. Some of them feature the visualization of network, enabling more effective trace of the underlying biological problems in a clear and succinct way. In this review, we aimed to provide a toolbox for exploring phosphorylation network. We first systematically surveyed 19 tools that are available for exploring phosphorylation networks, and subsequently comparatively analyzed and summarized these tools to guide tool selection in terms of functionality, data sources, performance, network visualization and implementation, and finally briefly discussed the application cases of these tools. In different scenarios, the conclusion on the suitability of a tool for a specific user may vary. Nevertheless, easily accessible bioinformatics tools are proved to facilitate biological findings. Hopefully, this work might also assist non-specialists, students, as well as computational scientists who aim at developing novel tools in the field of phosphorylation modification.

Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery.

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure-Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery. To meet the needs of researchers to utilize this technology, numerous QSAR-related web servers, such as Web-4D-QSAR and DPubChem, have been developed in recent years. However, none of the servers mentioned above can perform a complete QSAR modeling and supply activity prediction functions. We introduce Cloud 3D-QSAR by integrating the functions of molecular structure generation, alignment, molecular interaction field (MIF) computing and results analysis to provide a one-stop solution. We rigidly validated this server, and the activity prediction correlation was R2 = 0.934 in 834 test molecules. The sensitivity, specificity and accuracy were 86.9%, 94.5% and 91.5%, respectively, with AUC = 0.981, AUCPR = 0.971. The Cloud 3D-QSAR server may facilitate the development of good QSAR models in drug discovery. Our server is free and now available at http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/ and http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/.

Assessment of the Immunoprotective Efficacy of Recombinant 14-3-3 Protein and Dense Granule Protein 10 (GRA10) as Candidate Antigens for Rabbit Vaccines against Eimeria intestinalis.

Eimeria intestinalis infects rabbits, causing severe intestinal coccidiosis. Prolonged anticoccidial drug use might lead to coccidia resistance and drug residues in food. Thus, vaccines are required to control rabbit coccidiosis. In this study, recombinant E. intestinalis 14-3-3 and GRA10 proteins (rEi-14-3-3 and rEi-GRA10) were obtained via prokaryotic expression and used as recombinant subunit vaccines. Fifty 30-day-old rabbits were randomly grouped as follows: PBS-uninfected group, PBS-infected group, Trx-His-S control group, and rEi-14-3-3 and rEi-GRA10 immunized groups. The rabbits were subcutaneously immunized twice at 2-week intervals, challenged with 7 × 104 sporulated oocysts, and sacrificed 14 days later. The protective effects were assessed via clinical signs, relative weight gain, oocyst reduction, mean intestinal lesion score, ACI (anticoccidial index), cytokine, and specific antibody levels in sera. The rEi-14-3-3 and rEi-GRA10 groups had higher relative weight gain rates of 81.94% and 73.61% (p < 0.05), and higher oocyst reduction rates of 86.13% and 84.87% (p < 0.05), respectively. The two immunized groups had fewer intestinal lesions (p < 0.05) and higher IgG levels (p < 0.05). Higher levels of IL-2, IL-4, and IFN-γ cytokines in the rEi-14-3-3 group (p < 0.05) and a higher level of IFN-γ in the rEi-GRA10 group (p < 0.05) were observed. The ACI values of the rEi-14-3-3 and rEi-GRA10 groups were 168.24 and 159.91, with good and moderate protective effects, respectively. Both rEi-14-3-3 and rEi-GRA10 induced humoral immunity in the rabbits. In addition, rEi-14-3-3 induced Th1- and Th2-type immune responses. Both recombinant proteins were protective against E. intestinalis infection in rabbits, with rEi-14-3-3 showing a better protective effect.

Copper-Catalyzed Oxygenative Skeletal Rearrangement of Tetrahydro-ß-carbolines Using H2 O and O2 as Oxygen Sources.

Herein, we report an unprecedented skeletal rearrangement reaction of tetrahydro-ß-carbolines enabled by copper-catalyzed single-electron oxidative oxygenation, in which H2 O and O2 act as oxygen sources to generate a unique 2-hydroxyl-3-peroxide indoline intermediate. The synthetic reactivity of 2-hydroxyl-3-peroxide indoline species was demonstrated by a unique multi-step bond cleavage and formation cascade. Using a readily available copper catalyst under open-air conditions, highly important yet synthetically difficult spiro[pyrrolidone-(3,1-benzoxazine)] products were obtained in a single operation. The synthetic utility of this methodology is demonstrated by the efficient synthesis of the natural products donaxanine and chimonamidine, as well as the 3-hydroxyl-pyrroloindoline scaffold, in just one or two steps.