15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Modified recombinant human erythropoietin with potentially reduced immunogenicity

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Recombinant human erythropoietin (rHuEPO) is a biopharmaceutical drug given to patients who have a low hemoglobin related to chronic kidney disease, cancer or anemia. However, some patients repeatedly receiving rHuEPO develop anti-rHuEPO neutralizing antibodies leading to the development of pure red cell aplasia (PRCA). The immunogenic antibody response activated by rHuEPO is believed to be triggered by T-cells recognizing EPO epitopes bound to MHC molecules displayed on the cell surface of APCs. Previous studies have reported an association between the development of anti-rHuEpo-associated PRCA and the HLA-DRB1*09 gene, which is reported to be entrenched in the Thai population. In this study, we used computational design to screen for immunogenic hotspots recognized by HLA-DRB1*09, and predicted seventeen mutants having anywhere between one through four mutations that reduce affinity for the allele, without disrupting the structural integrity and bioactivity. Five out of seventeen mutants were less immunogenic in vitro while retaining similar or slightly reduced bioactivity than rHuEPO. These engineered proteins could be the potential candidates to treat patients who are rHuEpo-dependent and express the HLA-DRB1*09 allele.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: found
          • Article: not found

          NIH Image to ImageJ: 25 years of image analysis

          For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Improved methods for predicting peptide binding affinity to MHC class II molecules

            Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools

              Abstract The Allele Frequency Net Database (AFND, www.allelefrequencies.net) provides the scientific community with a freely available repository for the storage of frequency data (alleles, genes, haplotypes and genotypes) related to human leukocyte antigens (HLA), killer-cell immunoglobulin-like receptors (KIR), major histocompatibility complex Class I chain related genes (MIC) and a number of cytokine gene polymorphisms in worldwide populations. In the last five years, AFND has become more popular in terms of clinical and scientific usage, with a recent increase in genotyping data as a necessary component of Short Population Report article submissions to another scientific journal. In addition, we have developed a user-friendly desktop application for HLA and KIR genotype/population data submissions. We have also focused on classification of existing and new data into ‘gold–silver–bronze’ criteria, allowing users to filter and query depending on their needs. Moreover, we have also continued to expand other features, for example focussed on HLA associations with adverse drug reactions. At present, AFND contains >1600 populations from >10 million healthy individuals, making AFND a valuable resource for the analysis of some of the most polymorphic regions in the human genome.
                Bookmark

                Author and article information

                Contributors
                mathuros@cri.or.th
                rams@mit.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 January 2021
                15 January 2021
                2021
                : 11
                : 1491
                Affiliations
                [1 ]GRID grid.452298.0, ISNI 0000 0004 0482 1383, Program in Environmental Toxicology, , Chulabhorn Graduate Institute, ; Bangkok, 10210 Thailand
                [2 ]GRID grid.418595.4, ISNI 0000 0004 0617 2559, Translational Research Unit, , Chulabhorn Research Institute, ; Bangkok, 10210 Thailand
                [3 ]GRID grid.116068.8, ISNI 0000 0001 2341 2786, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, ; Cambridge, MA 02139 USA
                [4 ]GRID grid.116068.8, ISNI 0000 0001 2341 2786, Department of Biological Engineering, , Massachusetts Institute of Technology, ; Cambridge, MA 02139 USA
                Article
                80402
                10.1038/s41598-020-80402-1
                7810742
                33452310
                f9e709a2-b473-4643-b7ec-1dcb44fe9a8b
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 June 2020
                : 15 December 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100007959, Chulabhorn Research Institute;
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                molecular modelling,biologics
                Uncategorized
                molecular modelling, biologics

                Comments

                Comment on this article