Project description:Display technologies, e.g., phage, ribosome, mRNA, bacterial, and yeast-display, combine high content peptide libraries with appropriate screening strategies to identify functional peptide sequences. Construction of large peptide library and display-screen system in intact mammalian cells will facilitate the development of peptide therapeutics targeting transmembrane proteins. Our previous work established linear-double-stranded DNAs (ldsDNAs) as innovative biological parts to implement AND gate genetic circuits in mammalian cell line. In the current study, we employ ldsDNA with terminal NNK degenerate codons as AND gate input to build highly diverse peptide library in mammalian cells. Only PCR reaction and cell transfection experiments are needed to construct the library. High-throughput sequencing (HTS) results reveal that our new strategy could generate peptide library with both amino acid sequence and peptide length diversities. Our work establishes ldsDNA as biological parts for building highly diverse peptide library in mammalian cells, which shows great application potential in developing therapeutic peptides targeting transmembrane proteins.
Project description:IgNAR exhibits significant promise in the fields of cancer and anti-virus biotherapies. Notably, the variable regions of IgNAR (VNAR) possess comparable antigen binding affinity with much smaller molecular weight (~12 kDa) compared to IgNAR. Antigen specific VNAR screening is a changeling work, which limits its application in medicine and therapy fields. Though phage display is a powerful tool for VNAR screening, it has a lot of drawbacks, such as small library coverage, low expression levels, unstable target protein, complicating and time-consuming procedures. Here we report VNAR screening with next generation sequencing (NGS) could effectively overcome the limitations of phage display, and we successfully identified approximately 3000 BAFF-specific VNARs in Chiloscyllium plagiosum vaccinated with the BAFF antigen. The results of modelling and molecular dynamics simulation and ELISA assay demonstrated that one out of the top five abundant specific VNARs exhibited higher binding affinity to the BAFF antigen than those obtained through phage display screening. Our data indicates NGS would be an alternative way for VNAR screening with plenty of advantages.
Project description:We present a target-unbiased approach for antibody discovery that relies on generating mAbs against native target cell surfaces via phage display. This method combines a previously reported method for improved whole-cell phage display selections with next-generation sequencing analysis to efficiently identify mAbs with the desired target cell reactivity. This approach enabled the identification of three multiple myeloma cell surface antigens, and cognate monoclonal antibody probes.
Project description:This model was developed to support the early efforts in the identification of novel drugs against SARS-CoV2. It predicts the probability that a small molecule inhibits SARS-3CLpro-mediated peptide cleavage. It was developed using a high-throughput screening against the 3CL protease of SARS-CoV1, as no data was yet available for the new virus (SARS-CoV2) causing the COVID-19 pandemic. It uses the ChemProp model.
Model Type: Predictive machine learning model.
Model Relevance: Probability of 3CL protease inhibition.
Model Encoded by: Miquel Duran-frigola (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos9f6t
2024-05-08 | MODEL2405080006 | BioModels
Project description:Phage Display Antibody Library selected against two 24 bases DNA hairpins