Current Protein and Peptide Science - Online First

Proteomics holds immense significance in fundamental and applied research in various fields, including life sciences, medicinal sciences, and pharmaceutical sciences. The rapid development of mass spectrometry (MS) technologies has facilitated MS-based proteomics research, which has emerged as one of the primary methods for determining the composition, structures, and functions of proteins. The necessity of processing these complex datasets has increased significantly owing to the growing volume and diversity of MS data pertaining to proteins. Artificial intelligence (AI) possesses powerful data processing abilities, and is being increasingly employed for handling these challenges. In particular, deep learning has been extensively employed in MS-based proteomics research. This review discusses and compares the different AI algorithms developed for various tasks, including the prediction of protein spectra, retention times, peptide sequences, and MS-based protein structure prediction, and highlights their respective strengths and weaknesses. The limitations and future prospects of AI in MS-based proteomics research are additionally discussed herein.

Neurodegenerative diseases are brought on by the loss of function of nerve cells in the brain or peripheral nervous system and afflict millions of people worldwide. Parkinson's disease and Alzheimer's disease are the two most common neurodegenerative diseases. These neurodegenerative diseases are multi-factorial, progressive, age-related, and influenced by two factors: genetic and environmental. Successful treatment of neurodegenerative diseases is yet a challenging task due to lack of selectivity, toxicity, and the growth of multi-drug-resistant cells to the currently available drugs. Plant-derived, natural secondary metabolites have a significant impact on the research and development of novel medications against neurodegenerative disease. Plant-derived natural products are frequently regarded as safe and relatively safer substitutes for synthetic drugs. The present review deals with the elucidation of plant-derived secondary metabolites, namely alkaloids, flavonoids, and terpenoids, as anti-neurological therapeutics with special reference to various enzymatic targets, such as β-secretase, γ-secretase, α-Secretase, acetylcholinesterase, monoamine oxidase, and phosphodiesterase-4.

Circular RNAs (circRNAs) have emerged as promising candidates for neoantigen vaccine development due to their unique structural stability, enhanced translational efficiency, and immunostimulatory properties. Unlike linear RNAs, circRNAs exhibit exonuclease resistance, prolonged antigen expression, and increased activation of innate immune receptors such as RIG-I and MDA5, thereby enhancing anti-tumor immune responses. Preclinical studies have demonstrated that circRNA-based vaccines encoding tumor-specific neoantigens effectively stimulate Antigen-Presenting Cells (APCs), particularly Dendritic Cells (DCs), leading to robust CD8⁺ Cytotoxic T Lymphocyte (CTL) activation. This results in increased cytokine production, T-cell proliferation, and durable anti-tumor immunity. Compared to conventional neoantigen vaccine platforms, circRNA vaccines offer distinct advantages, including higher immunogenicity, improved cytosolic delivery, and minimal risk of genomic integration. CircRNA vaccines have demonstrated efficacy in preclinical tumor models, with studies highlighting their ability to induce long-term memory T-cell responses and enhance the efficacy of immune checkpoint blockade therapies. However, challenges remain in optimizing circRNA delivery, mitigating unintended immune activation, and scaling up manufacturing processes. The translational potential of circRNA vaccines in tumor immunotherapy is significant, offering a novel and scalable approach to personalized cancer treatment. Further research and clinical validation are needed to optimize their design, improve manufacturing efficiency, and assess their efficacy in human trials. CircRNA vaccines represent a next-generation platform with the potential to revolutionize cancer immunotherapy by harnessing durable and targeted anti-tumor immune responses.

COVID-19 is a respiratory disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), but because the receptor protein of this virus can appear not only in the lungs and throat but also in various parts of the host's body, it causes different diseases. Recent observations have suggested that SARS-CoV-2 damages the central nervous system of patients in a manner similar to amyloid-associated neurodegenerative diseases such as Alzheimer's and Parkinson's. Neurodegenerative diseases are believed to be associated with the self-assembly of amyloid proteins and peptides. On the other hand, whole proteins or parts of them encoded by SARS-CoV-2 can form amyloid fibrils, which may play an important role in amyloid-related diseases. Motivated by this evidence, this mini-review discusses experimental and computational studies of SARS-CoV-2 proteins that can form amyloid aggregates. Liquid-Liquid Phase Separation (LLPS) is a dynamic and reversible process leading to the creation of membrane-less organelles within the cytoplasm, which is not bound by a membrane that concentrates specific types of biomolecules. These organelles play pivotal roles in cellular signaling, stress response, and the regulation of biomolecular condensates. Recently, LLPS of the Nucleocapsid (N) protein and SARS-CoV-2 RNA has been disclosed, but many questions about the phase separation mechanism and the formation of the virion core are still unclear. We summarize the results of this phenomenon and suggest potentially intriguing issues for future research.

Gastric cancer remains one of the leading cancer-related deaths worldwide. Despite the research advances, many challenges persist because the diseases are usually diagnosed at an advanced stage and have a complex treatment protocol. Conventional treatments such as chemotherapy, radiation, and surgery pose several side effects and low efficiency. The growing worldwide interest in herbal products, particularly, their bioactive ingredients, presents a promising prospect for auxiliary or alternative therapies for gastric cancer. In vivo experiments show that the given compounds increase the effectiveness and decrease the cumulative harmful impact of conventional anticancer treatments, which may have additive effects. Furthermore, clinical trials have revealed that phytoconstituents have possible anti-gastric cancer properties in humans. Nonetheless, these encouraging preclinical observations have not progressed into clinical practice all that much due to the absence of adequately powered Phase III trials for GC. Therefore, this review stresses the need for well-controlled human interventions to confirm the effectiveness and safety of herb-based therapies. In the long run, the incorporation of these herbal products could present a new approach to constructing the gastric cancer prevention and treatment outlook while minimizing the side effects of conventional treatments and opening up arenas of functional foods and pharmaceuticals.

Recently, a new type of cow’s milk has been commercialized in the markets, called A2 milk. It is derived from a specific allelic composition on chromosome 6. The only difference between A1 and A2 milk results from the polymorphism at the 67 amino acid chain. In this position, A2 milk has a proline amino acid, while A1 milk has a histidine amino acid. Proteins are one of the most important components of milk, especially casein, and have received significant attention as they are the source of bioactive >opioid peptides called beta-casomorphin-7. Peptides are released through enzymatic digestion of casein and whey proteins. More precisely, this bioactive peptide is produced by sequential gastrointestinal digestion of bovine A1 variants proteins, while this phenomenon is not present in variant A2. Studies have reported that A1 milk can be harmful to health not only for adults but also for infants and that β-casein A2 becomes a safer choice following the relationship between disease risk and consumption of the beta-casomorphin-7 peptide. Indeed, epidemiological studies suggest that the released beta-casomorphin-7 peptide is a risk factor for the development of diseases in humans, but this has not yet been validated by other studies. In contrast, A2 milk has been suggested as an appropriate substitute for A1 milk since populations consuming milk containing high levels of the A2 beta-casein variant have lower rates of diseases, such as diabetes, coronary heart disease, autism, and schizophrenia.

Schizophrenia is now diagnosed mostly based on symptoms and physical signs rather than the patient's pathological and physiological markers. While oncologists once felt satisfied when their patients experienced a long remission, today, they are leading research into innovative treatments with molecularly targeted drugs, as well as strategies to enhance diagnostic accuracy and alleviate symptoms as the disease advances.Because biomarkers reflect an organism's physiological, physical, and biochemical state, they are very beneficial and have a wide range of real-world uses. The identification of blood biomarkers may open up new avenues for studying schizophrenia. MicroRNAs (miRNAs) may serve as diagnostic indicators for schizophrenia as their abnormal expression has recently been linked to the disease's pathophysiology. The precise etiological process of schizophrenia remains largely unknown despite the general agreement that developmental and genetic factors play a critical role in the pathophysiology of the disorder. miRNAs have gained recognition as an essential post-transcriptional regulator in the regulation of gene expression in recent decades. The importance of miRNAs for brain development and neuroplasticity is well established.