Computational design and immunoinformatics validation of a T cell multi-epitope vaccine targeting glioblastoma stem cells.
The 1 match
- [1] § Methodology › Modelling, refining, and validation of the tertiary structure of the vaccine construct ↔ colabfold/citations.py, lines 1–60 · score 0.57 · AlphaFold2, protein structure, bioinformatics, acid, interactions, server
Paper
Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC
The paper is loaded when this pane is shown.
The authors' code
Python · 160 lines · 7.1 KB · MIT · 1 match
- import logging
- from pathlib import Path
- logger = logging.getLogger(__name__)
- citations = {
- "Mirdita2021": """@article{Mirdita2022,
- author= {Mirdita, Milot and Schütze, Konstantin and Moriwaki, Yoshitaka and Heo, Lim and Ovchinnikov, Sergey and Steinegger, Martin },
- doi = {10.1038/s41592-022-01488-1},
- journal = {Nature Methods},
- title = {{ColabFold: Making Protein folding accessible to all}},
- year = {2022},
- comment = {ColabFold including MMseqs2 MSA server}
- }""",
- "Mitchell2019": """@article{Mitchell2019,
- author = {Mitchell, Alex L and Almeida, Alexandre and Beracochea, Martin and Boland, Miguel and Burgin, Josephine and Cochrane, Guy and Crusoe, Michael R and Kale, Varsha and Potter, Simon C and Richardson, Lorna J and Sakharova, Ekaterina and Scheremetjew, Maxim and Korobeynikov, Anton and Shlemov, Alex and Kunyavskaya, Olga and Lapidus, Alla and Finn, Robert D},
- doi = {10.1093/nar/gkz1035},
- journal = {Nucleic Acids Res.},
- title = {{MGnify: the microbiome analysis resource in 2020}},
- year = {2019},
- comment = {MGnify database}
- }""",
- "Eastman2017": """@article{Eastman2017,
- author = {Eastman, Peter and Swails, Jason and Chodera, John D. and McGibbon, Robert T. and Zhao, Yutong and Beauchamp, Kyle A. and Wang, Lee-Ping and Simmonett, Andrew C. and Harrigan, Matthew P. and Stern, Chaya D. and Wiewiora, Rafal P. and Brooks, Bernard R. and Pande, Vijay S.},
- doi = {10.1371/journal.pcbi.1005659},
- journal = {PLOS Comput. Biol.},
- number = {7},
- title = {{OpenMM 7: Rapid development of high performance algorithms for molecular dynamics}},
- volume = {13},
- year = {2017},
- comment = {Amber relaxation}
- }""",
- "Jumper2021": """@article{Jumper2021,
- author = {Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and {\v{Z}}{\'{i}}dek, Augustin and Potapenko, Anna and Bridgland, Alex and Meyer, Clemens and Kohl, Simon A. A. and Ballard, Andrew J. and Cowie, Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig and Reiman, David and Clancy, Ellen and Zielinski, Michal and Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol and Senior, Andrew W. and Kavukcuoglu, Koray and Kohli, Pushmeet and Hassabis, Demis},
- doi = {10.1038/s41586-021-03819-2},
- journal = {Nature},
- pmid = {34265844},
- title = {{Highly accurate protein structure prediction with AlphaFold.}},
- year = {2021},
- comment = {AlphaFold2 + BFD Database}
- }""",
- "Evans2021": """@article{Evans2021,
- author = {Evans, Richard and O'Neill, Michael and Pritzel, Alexander and Antropova, Natasha and Senior, Andrew and Green, Tim and Zidek, Augustin and Bates, Russ and Blackwell, Sam and Yim, Jason and Ronneberger, Olaf and Bodenstein, Sebastian and Zielinski, Michal and Bridgland, Alex and Potapenko, Anna and Cowie, Andrew and Tunyasuvunakool, Kathryn and Jain, Rishub and Clancy, Ellen and Kohli, Pushmeet and Jumper, John and Hassabis, Demis},
- doi = {10.1101/2021.10.04.463034v1},
- journal = {bioRxiv},
- title = {{Protein complex prediction with AlphaFold-Multimer}},
- year = {2021},
- comment = {AlphaFold2-multimer}
- }""",
- "Mirdita2019": """@article{Mirdita2019,
- author = {Mirdita, Milot and Steinegger, Martin and S{\"{o}}ding, Johannes},
- doi = {10.1093/bioinformatics/bty1057},
- journal = {Bioinformatics},
- number = {16},
- pages = {2856--2858},
- pmid = {30615063},
- title = {{MMseqs2 desktop and local web server app for fast, interactive sequence searches}},
- volume = {35},
- year = {2019},
- comment = {MMseqs2 search server}
- }""",
- "Steinegger2019": """@article{Steinegger2019,
- author = {Steinegger, Martin and Meier, Markus and Mirdita, Milot and V{\"{o}}hringer, Harald and Haunsberger, Stephan J. and S{\"{o}}ding, Johannes},
- doi = {10.1186/s12859-019-3019-7},
- journal = {BMC Bioinform.},
- number = {1},
- pages = {473},
- pmid = {31521110},
- title = {{HH-suite3 for fast remote homology detection and deep protein annotation}},
- volume = {20},
- year = {2019},
- comment = {PDB70 database}
- }""",
- "VanKempen2023": """@article{VanKempen2023,
- author = {van Kempen, Michel and Kim, Stephanie S and Tumescheit, Charlotte and Mirdita, Milot and Lee, Jeongjae and Gilchrist, Cameron L M and S{\"{o}}ding, Johannes and Steinegger, Martin},
- doi = {10.1038/s41587-023-01773-0},
- journal = {Nature Biotechnology},
- title = {{Fast and accurate protein structure search with Foldseek}},
- year = {2023},
- comment = {PDB100 database}
- }""",
- "Mirdita2017": """@article{Mirdita2017,
- author = {Mirdita, Milot and von den Driesch, Lars and Galiez, Clovis and Martin, Maria J. and S{\"{o}}ding, Johannes and Steinegger, Martin},
- doi = {10.1093/nar/gkw1081},
- journal = {Nucleic Acids Res.},
- number = {D1},
- pages = {D170--D176},
- pmid = {27899574},
- title = {{Uniclust databases of clustered and deeply annotated protein sequences and alignments}},
- volume = {45},
- year = {2017},
- comment = {Uniclust30/UniRef30 database}
- }""",
- "Berman2003": """@misc{Berman2003,
- author = {Berman, Helen and Henrick, Kim and Nakamura, Haruki},
- booktitle = {Nat. Struct. Biol.},
- doi = {10.1038/nsb1203-980},
- number = {12},
- pages = {980},
- pmid = {14634627},
- title = {{Announcing the worldwide Protein Data Bank}},
- volume = {10},
- year = {2003},
- comment = {templates downloaded from wwPDB server}
- }""",
- "Lee2023": """@article{Lee2023,
- author = {Lee, Jae-Won and Won, Jong-Hyun and Jeon, Seonggwang and Choo, Yujin and Yeon, Yubin and Oh, Jin-Seon and Kim, Minsoo and Kim, SeonHwa and Joung, InSuk and Jang, Cheongjae and Lee, Sung Jong and Kim, Tae Hyun and Jin, Kyong Hwan and Song, Giltae and Kim, Eun-Sol and Yoo, Jejoong and Paek, Eunok and Noh, Yung-Kyun and Joo, Keehyoung},
- title = "{DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function}",
- journal = {Bioinformatics},
- volume = {39},
- number = {12},
- pages = {btad712},
- year = {2023},
- month = {11},
- doi = {10.1093/bioinformatics/btad712},
- comment = {DeepFold-v1 Model}
- }
- """,
- }
- def write_bibtex(
- model: str,
- use_msa: bool,
- use_env: bool,
- use_templates: bool,
- use_amber: bool,
- result_dir: Path,
- bibtex_file: str = "cite.bibtex",
- ) -> Path:
- to_cite = ["Mirdita2021"]
- if model == "alphafold2_ptm" or model == "alphafold2":
- to_cite += ["Jumper2021"]
- if model == "deepfold_v1":
- to_cite += ["Lee2023"]
- if model.startswith("alphafold2_multimer"):
- to_cite += ["Evans2021"]
- if use_msa:
- to_cite += ["Mirdita2019"]
- if use_msa:
- to_cite += ["Mirdita2017"]
- if use_env:
- to_cite += ["Mitchell2019"]
- if use_templates:
- to_cite += ["VanKempen2023"]
- if use_templates:
- to_cite += ["Steinegger2019"]
- if use_templates:
- to_cite += ["Berman2003"]
- if use_amber:
- to_cite += ["Eastman2017"]
- bibtex_file = result_dir.joinpath(bibtex_file)
- with bibtex_file.open("w", encoding="utf-8") as writer:
- for i in to_cite:
- writer.write(citations[i])
- writer.write("\n")
- logger.info(f"Found {len(to_cite)} citations for tools or databases")
- return bibtex_file
citations.py at commit efbf31c, under MIT · at the source
Overview
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Infectious and Tropical Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
Abstract
The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.
Repository
Its files are read in the Code ↔ Paper reader above, with 1 match between paragraphs and lines of code.
sokrypton/colabfold
efbf31c37cedb38cd09c69c1b991910a9866480e, 19 September 2026Availability: 1 check, the latest on 27 September 2026: the link answers
- 27 September 2026: the link answers
64 files
- AlphaFold2.ipynb, Jupyter, 498 lines
- AlphaFold3_of3.ipynb, Jupyter, 554 lines
- BioEmu.ipynb, Jupyter, 390 lines
- Boltz1.ipynb, Jupyter, 258 lines
- ColabFold2_preview.ipynb
, Jupyter, 666 lines - ESMFold.ipynb, Jupyter, 265 lines
- MsaServer/
restart-systemd.sh , Shell, 5 lines - MsaServer/
setup-and-start-local.sh , Shell, 111 lines - RoseTTAFold.ipynb, Jupyter, 213 lines
- RoseTTAFold2.ipynb, Jupyter, 411 lines
- batch/
AlphaFold2_batch.ipynb , Jupyter, 180 lines - beta/
AlphaFold2_advanced.ipyn , Jupyter, 615 linesb - beta/
AlphaFold2_advanced_beta , Jupyter, 7 lines.ipynb - beta/
AlphaFold2_advanced_old. , Jupyter, 1,021 linesipynb - beta/
AlphaFold2_complexes.ipy , Jupyter, 514 linesnb - beta/
AlphaFold_wJackhmmer.ipy , Jupyter, 697 linesnb - beta/
Alphafold_single.ipynb , Jupyter, 207 lines - beta/
ESMFold.ipynb , Jupyter, 385 lines - beta/
ESMFold_advanced.ipynb , Jupyter, 496 lines - beta/
ESMFold_api.ipynb , Jupyter, 104 lines - beta/
RoseTTAFold.ipynb , Jupyter, 300 lines - beta/
RoseTTAFold_install.sh , Shell, 5 lines - beta/
RoseTTAFold_run.sh , Shell, 26 lines - beta/
alphafold_output_at_each , Jupyter, 152 lines_recycle.ipynb - beta/
colabfold.py , Python, 711 lines - beta/
colabfold_alphafold.py , Python, 821 lines - beta/
convert_256_to_384_rep.i , Jupyter, 39 linespynb - beta/
omegafold.ipynb , Jupyter, 167 lines - beta/
omegafold_hacks.ipynb , Jupyter, 206 lines - beta/
pairmsa.py , Python, 237 lines - beta/
relax_amber.ipynb , Jupyter, 154 lines - colabfold/
__init__.py , Python, 1 line - colabfold/
alphafold/ , Python, 1 line__init__.py - colabfold/
alphafold/ , Python, 435 linesextra_ptm.py - colabfold/
alphafold/ , Python, 98 linesipsae.py - colabfold/
alphafold/ , Python, 277 linesmodels.py - colabfold/
alphafold/ , Python, 44 linesmsa.py - colabfold/
batch.py , Python, 2,364 lines - colabfold/
citations.py , Python, 160 lines, 1 match - colabfold/
colabfold.py , Python, 831 lines - colabfold/
download.py , Python, 140 lines - colabfold/
input.py , Python, 414 lines - colabfold/
mmseqs/ , Python, 1 line__init__.py - colabfold/
mmseqs/ , Python, 63 linesmerge_and_split_msas.py - colabfold/
mmseqs/ , Python, 640 linessearch.py - colabfold/
mmseqs/ , Python, 55 linessplit_msas.py - colabfold/
pdb.py , Python, 69 lines - colabfold/
plot.py , Python, 158 lines - colabfold/
relax.py , Python, 108 lines - colabfold/
utils.py , Python, 406 lines - colabfold_search.sh, Shell, 68 lines
- setup_databases.sh, Shell, 218 lines
- tests/
__init__.py , Python, 1 line - tests/
mock.py , Python, 230 lines - tests/
reindent_ipynb.py , Python, 8 lines - tests/
test_colabfold.py , Python, 510 lines - tests/
test_msa.py , Python, 40 lines - tests/
test_utils.py , Python, 141 lines - utils/
convert_deepfold_weights , Python, 9 lines.py - utils/
plot_scores.ipynb , Jupyter, 28 lines - verbose/
alphafold_noTemplates_no , Jupyter, 267 linesMD.ipynb - verbose/
alphafold_noTemplates_ye , Jupyter, 323 linessMD.ipynb - LICENSE, License, 21 lines
- README.md, Text, 293 lines
Tracing map
Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.
What the map holds:
- 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
- 62 scripts, each with its path and the digest of its content;
- 1 match between paragraphs of the paper and lines of the code (method lexical-v1);
- neither the text of the paper nor the code itself.
Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.
Data
No dataset and no data link were found in the paper.
Data availability statement
The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:
- no repository, dataset or request procedure was recognized in it
Read it in the paper: doi.org/10.1038/s41598-026-53415-5.
Versions
The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.
Version 1, 28 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 9 keywords, 13 MeSH terms, 1 funder, 125 references.
Cite
This paper
Salahlou, R., Farajnia, S., Bargahi, N., Rahbarnia, L., & Kamalkazemi, E. (2026). Computational design and immunoinformatics validation of a T cell multi-epitope vaccine targeting glioblastoma stem cells. Scientific reports, 16(1), 22423. https://
BibTeX
@article{salahlou2026com
author = {Salahlou, Reza and Farajnia, Safar and Bargahi, Nasrin and Rahbarnia, Leila and Kamalkazemi, Elham},
title = {{Computational design and immunoinformatics validation of a T cell multi-epitope vaccine targeting glioblastoma stem cells}},
journal = {Scientific reports},
year = {2026},
month = may,
volume = {16},
number = {1},
pages = {22423},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/
url = {https://
pmid = {42151414},
pmcid = {PMC13376771}
}
RIS
TY - JOUR
AU - Salahlou, Reza
AU - Farajnia, Safar
AU - Bargahi, Nasrin
AU - Rahbarnia, Leila
AU - Kamalkazemi, Elham
TI - Computational design and immunoinformatics validation of a T cell multi-epitope vaccine targeting glioblastoma stem cells
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/
VL - 16
IS - 1
SP - 22423
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/
UR - https://
LA - en
ER -
CSL-JSON
{
"id": "10.1038/
"type": "article-journal",
"title": "Computational design and immunoinformatics validation of a T cell multi-epitope vaccine targeting glioblastoma stem cells",
"container-title": "Scientific reports",
"author": [
{
"family": "Salahlou",
"given": "Reza"
},
{
"family": "Farajnia",
"given": "Safar"
},
{
"family": "Bargahi",
"given": "Nasrin"
},
{
"family": "Rahbarnia",
"given": "Leila"
},
{
"family": "Kamalkazemi",
"given": "Elham"
}
],
"container-title-short":
"volume": "16",
"issue": "1",
"page": "22423",
"DOI": "10.1038/
"PMID": "42151414",
"PMCID": "PMC13376771",
"ISSN": "2045-2322",
"publisher": "Nature Publishing Group",
"URL": "https://
"language": "en",
"issued": {
"date-parts": [
[
2026,
5,
18
]
]
}
}
The tracing map gets a citation of its own once an author has validated it and it has a DOI.
Similar papers
The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.
- [1] doi:10.1021/acs.biochem.5c00596 [code]
- Cargo Recognition of Nesprin-2 by the Dynein Adapter Bicaudal D2 for a Nuclear Positioning Pathway That Is Important for Brain Development.Journal: BiochemistryIn common: RDKit, JAX, PyTorch Lightning, 9 other tools, cellular / molecular, 2 references
- [2] doi:10.1038/s41586-026-10391-0 [code]
- Cell-type-targeted mitochondrial transplantation rescues cell degeneration.Journal: NatureIn common: RDKit, JAX, PyTorch Lightning, 9 other tools, cellular / molecular, 1 reference
- [3] doi:10.3390/ijms27156614 [code]
- Candidalysin Inhibits &
lt;i& gt;Porphyromonas gingivalis& lt;/ i& gt; Lipoprotein-Induced IL-1β Production in BV-2 Microglia via Hydrophobic Microbial Interactions. Journal: International journal of molecular sciencesIn common: RDKit, JAX, PyTorch Lightning, 9 other tools, cellular / molecular, 1 reference - [4] doi:10.1016/j.molcel.2026.07.006 [code]
- DeorphaNN: Virtual screening of GPCR peptide agonists using AlphaFold-predicted active-state complexes and deep learning embeddings.Journal: Molecular cellIn common: JAX, Biopython, PyTorch Geometric, 7 other tools, cellular / molecular, 2 references
- [5] doi:10.1038/s42003-026-10957-8 [code]
- Brain defence by the extracellular matrix protein Cochlin.Journal: Communications biologyIn common: RDKit, JAX, PyTorch Lightning, 8 other tools, cellular / molecular
- [6] doi:10.1007/s00262-026-04390-3 [code]
- Identification and prioritisation of tumour antigen candidates from 79 glioblastoma transcriptomes.Journal: Cancer immunology, immunotherapy : CIIIn common: scikit-learn, pandas, SciPy, 2 other tools, other condition, cellular / molecular, 6 references
- [7] doi:10.1021/acsomega.5c09368 [code]
- Structure-Based and AI-Assisted Identification of AGPS Inhibitors for Glioma via Integrated Docking, Molecular Dynamics, and Binding Affinity Screening.Journal: ACS omegaIn common: RDKit, Biopython, PyTorch Geometric, 6 other tools, other condition
- [8] doi:10.1038/s41467-026-75444-4 [code]
- Structural insights enable drug discovery for the neuronal NBCn2 carbonate transporter.Journal: Nature communicationsIn common: RDKit, JAX, Biopython, 4 other tools, cellular / molecular, 1 reference
- [9] doi:10.1523/eneuro.0362-25.2026 [code]
- Similarities between &
lt;i& gt;Ciona& lt;/ i& gt; Dorsal Motor Ganglion and Vertebrate Cerebellum: Did a Chordate Ancestor Already Show D/ V Subdivision within a Hindbrain Precursor? Journal: eNeuroIn common: PyTorch Lightning, Biopython, PyTorch Geometric, 6 other tools - [10] doi:10.1093/nar/gkag706 [code]
- scDifformer: diffusion-based post-training for virtual cell modeling across large-scale single-cell data.Journal: Nucleic acids researchIn common: RDKit, PyTorch Geometric, TensorFlow, 6 other tools
Contribute
The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.
Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.
Claim this paper
Correct its record
Say what each link of this record is, remove the ones that are not the paper's, add the ones that are missing. The correction becomes a new version of the record, in its Versions section.
Validate its tracing map
You validate the map as this page shows it: 1 repository of the authors' code, each at its verified commit and with its license, 62 scripts, and 1 match between paragraphs and code (see the Code and Map sections). It then receives a DOI on Zenodo, with you (your ORCID iD) and OSCR as its creators; the code itself is not deposited.
The map's fingerprint: sha256:b0b680057d887f4c…
Add the badge to its README
The badge links the code to this page. Copy one of these into the README of the paper's code: only you decide where it goes, and nothing is changed for you.
Markdown
[, paste the snippet at the top, then “Commit changes…” and, to review it first, “Create a new branch and start a pull request”. You open the pull request; OSCR asks for no permission.
Request its removal
To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).
Discussion, reproductions, activity
Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.
Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.
Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.
