Prediction of blood-brain barrier penetrating peptides based on data augmentation with Augur.

BACKGROUND: The blood-brain barrier serves as a critical interface between the bloodstream and brain tissue, mainly composed of pericytes, neurons, endothelial cells, and tightly connected basal membranes. It plays a pivotal role in safeguarding brain from harmful substances, thus protecting the integrity of the nervous system and preserving overall brain homeostasis. However, this remarkable selective transmission also poses a formidable challenge in the realm of central nervous system diseases treatment, hindering the delivery of large-molecule drugs into the brain. In response to this challenge, many researchers have devoted themselves to developing drug delivery systems capable of breaching the blood-brain barrier. Among these, blood-brain barrier penetrating peptides have emerged as promising candidates. These peptides had the advantages of high biosafety, ease of synthesis, and exceptional penetration efficiency, making them an effective drug delivery solution. While previous studies have developed a few prediction models for blood-brain barrier penetrating peptides, their performance has often been hampered by issue of limited positive data. RESULTS: In this study, we present Augur, a novel prediction model using borderline-SMOTE-based data augmentation and machine learning. we extract highly interpretable physicochemical properties of blood-brain barrier penetrating peptides while solving the issues of small sample size and imbalance of positive and negative samples. Experimental results demonstrate the superior prediction performance of Augur with an AUC value of 0.932 on the training set and 0.931 on the independent test set. CONCLUSIONS: This newly developed Augur model demonstrates superior performance in predicting blood-brain barrier penetrating peptides, offering valuable insights for drug development targeting neurological disorders. This breakthrough may enhance the efficiency of peptide-based drug discovery and pave the way for innovative treatment strategies for central nervous system diseases.

[The CD133 polyclonal antibody generation and cancer stem cells identification].

OBJECTIVE: To generate the cancer stem cells (CSCs) specific protein CD133 polyclonal antibody for the study of the biological characteristics of CSCs in tumor tissues and CSCs screening for the mouse model. METHODS: The extracellular peptide of the human CD133 was injected into rabbits to generate polyclonal antibody which was used for glioblastoma(GBM) Western blot and immunohistochemistry. RESULTS: The CD133 antiserum we made could detect both overexpressed myc-CD133 and endogenous CD133 efficiently by Western blot. Immunohistochemistry indicated that the CD133 polyclonal antibody can label CSCs in GBM sections. CONCLUSION: High efficient and specific CD133 antibody was generated successfully and could be used to label CSCs in tumor sections and screen CSCs for the mouse model.

[Preparation and identification of the Syntenin1 polyclonal antibody, a cancer metastasis related gene].

OBJECTIVE: To express the GST fusion protein, GST-Syntenin1 in E. coli, and to prepare the polyclonal antibody of Syntenin1. METHODS: CDS fragment of Syntenin1 was obtained by RT-PCR from normal mouse brain and subcloned into pGEX-4T-2 to generate pGEX-4T-2-Syntenin1 recombinant. The confirmed recombinant was transformed into the BL21 competent cells and induced with IPTG. The recombinant fusion protein was purified with immobilized Glutathione Sepharose and confirmed by SDS-PAGE. The purified fusion protein was mixed with the Freund's adjuvant, and then injected into New Zealand white rabbits by hypodermic injection. The polyclonal antibody titer and specification were identified by Western blot. RESULTS: Syntenin1 polyclonal antibody bind Sytenin1 protein specifically and the antiserum tiger reached to 1 : 20 000. CONCLUSION: The Syntenin1 polyclonal antibody with high titer and high specificity was prepared successfully. This will be very helpful for the further study on Syntenin1 function and molecule mechanism of cancer metastasis.