pepsickle rapidly and accurately predicts proteasomal cleavage sites for improved neoantigen identification

Motivation Proteasomal cleavage is a key component in protein turnover, as well as antigen processing and presentation. Although tools for proteasomal cleavage prediction are available, they vary widely in their performance, options, and availability. Results Herein we present pepsickle, an open-source tool for proteasomal cleavage prediction with better in vivo prediction performance (AUC) and computational speed than current models available in the field and with the ability to predict sites based on both constitutive and immunoproteasome profiles. Post-hoc filtering of predicted patient neoepitopes using pepsickle significantly enriches for immune-responsive epitopes and may improve current epitope prediction and vaccine development pipelines. Availability pepsickle is open source and available at https://github.com/pdxgx/pepsickle Supplementary information Supplementary data are available at Bioinformatics online.

Pepsickle rapidly and accurately predicts proteasomal cleavage sites for improved neoantigen identification

Proteasomal cleavage is a key component in protein turnover, as well as antigen presentation and subsequent immune response. Herein we present pepsickle, an open-source tool for proteasomal cleavage prediction with better in vivo prediction performance (AUC) and computational speed than current models available in the field, and with the ability to predict sites based on both constitutive and immunoproteasome profiles. Post-hoc filtering of predicted patient neoepitopes using pepsickle significantly enriches for immune-responsive epitopes and may represent a significant opportunity to improve current epitope prediction and vaccine development pipelines.

In-silico Immunomodelling of 2019-nCoV

Background: Novel Corona Virus 2019 (2019-nCoV) is a positive-sense single-strand RNA virus form coronaviridae family, responsible for corona virus infectious disease 2019 (COVID-19) with rapid transmission. The aim of this study is characterization of major viral proteins, prediction of antigen proteasomal cleavage pattern, MHC class I processing and presentation, B- and T-cell epitopes, and anti-inflammatory epitopes of 2019-nCoV, compared with SARS-CoV. Methods: The aminoacid sequence of spike surface (S) glycoprotein, membrane (M) glycoprotein, envelop (E) protein and nucleocapsid (N) phosphoprotein were obtained from NCBI. The sequences were aligned by MEGA 7.0 and modeled by SWISS-MODEL. The proteasomal cleavage pattern, MHC class I processing and T-cells epitopes were predicted via IEDB analysis and EPISOFT. The B-cell epitopes were predicted by BepiPred 2.0. Also, prediction of anti-inflammatory epitopes was performed by AntiFlam. Results: Two major antigen proteins, S glycoprotein and M glycoprotein of 2019-nCoV, respectively, have 26.57% and 20.59% less efficiency in proteasomal cleavage and presentation to MHC class I, comparing SARS-CoV. There are less B-cell predicted epitopes in 2019-nCoV, comparing SARS-CoV. The anti-inflammatory properties of 2019-nCoV S glycoprotein and N protein is higher than SARS-CoV. Discussion: It seems that the evolution of 2019-nCoV is on the way of deficiency in antigen presenting to MHC class I and escaping from cellular immunity. Also, the predicted hotspot epitopes potentially can be used to induction of adaptive cellular immunity against 2019-nCoV. In addition, 2019-nCoV appears to be less immunopathogenic than SARS-CoV due to its higher anti-inflammatory proteins.

Dephosphorylation of YB-1 is Required for Nuclear Localisation During G2 Phase of the Cell Cycle

Elevated levels of nuclear Y-box binding protein 1 (YB-1) are linked to poor prognosis in cancer. It has been proposed that entry into the nucleus requires specific proteasomal cleavage. However, evidence for cleavage is contradictory and high YB-1 levels are prognostic regardless of cellular location. Here, using confocal microscopy and mass spectrometry, we find no evidence of specific proteolytic cleavage. Doxorubicin treatment, and the resultant G2 arrest, leads to a significant increase in the number of cells where YB-1 is not found in the cytoplasm, suggesting that its cellular localisation is variable during the cell cycle. Live cell imaging reveals that the location of YB-1 is linked to progression through the cell cycle. Primarily perinuclear during G1 and S phases, YB-1 enters the nucleus as cells transition through late G2/M and exits at the completion of mitosis. Atomistic modelling and molecular dynamics simulations show that dephosphorylation of YB-1 at serine residues 102, 165 and 176 increases the accessibility of the nuclear localisation signal (NLS). We propose that this conformational change facilitates nuclear entry during late G2/M. Thus, the phosphorylation status of YB-1 determines its cellular location.