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TCRep 3D specifications

Information


Unique identifier OMICS_34129
Name TCRep 3D

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Publication for TCRep 3D

TCRep 3D citations

 (6)
library_books

Sensitive and frequent identification of high avidity neo epitope specific CD8+ T cells in immunotherapy naive ovarian cancer

2018
Nat Commun
PMCID: 5854609
PMID: 29545564
DOI: 10.1038/s41467-018-03301-0

[…] The protocol used to model the TCR-p-MHC complexes was adapted from our TCRep 3D approach. Starting from V and J segment identifiers and from the CDR3 sequences, the full sequence of the constant and variable domains of TCRα and TCRβ were reconstituted based on IMGT/GENE- […]

library_books

DynaDom: structure based prediction of T cell receptor inter domain and T cell receptor peptide MHC (class I) association angles

2017
BMC Struct Biol
PMCID: 5289058
PMID: 28148269
DOI: 10.1186/s12900-016-0071-7

[…] ELLER program with simulated annealing techniques [], and suggested a rational homology model, which was refined based on previous mutation studies []. Further developments of the approach led to the TCRep 3D method [], which was recently applied in the context of rational TCR design []. In addition, Haidar et al. enhanced the affinity of the A6 TCR to TAX:HLA-A2 for about 100-fold using a structu […]

library_books

Quantitative Analysis of the Association Angle between T cell Receptor Vα/Vβ Domains Reveals Important Features for Epitope Recognition

2015
PLoS Comput Biol
PMCID: 4505886
PMID: 26185983
DOI: 10.1371/journal.pcbi.1004244

[…] or free energy calculations to study the influence of single mutations in the TCR or in the ligand, or to study differences of similar systems [–], and since recently, the automated modeling approach TCRep 3D is available to predict arbitrary TCR:pMHCI complex structures []. Recently Knapp et al. applied the ABangle methodology to a broad range of MD simulations of the LC13 TCR bound to 172 differ […]

library_books

Structure Based, Rational Design of T Cell Receptors

2013
Front Immunol
PMCID: 3770923
PMID: 24062738
DOI: 10.3389/fimmu.2013.00268

[…] The first study described above () led to the development of TCRep 3D, as a generalization of the TCR-pMHC modeling approach (). TCRep 3D is an approach dedicated to the prediction of high-quality 3D-structures that can provide a functional insight on the inter […]

library_books

T Cell Receptors Binding Orientation over Peptide/MHC Class I Is Driven by Long Range Interactions

2012
PLoS One
PMCID: 3522592
PMID: 23251658
DOI: 10.1371/journal.pone.0051943

[…] 500 models of the A6 TCR were built using the homology module of the TCRep 3D approach, as described elsewhere . TCRep 3D makes use of state of the art homology modeling using the Modeller 9v5 software , complemented by the use of additional dihedral restraints applied […]

library_books

TCRep 3D: An Automated In Silico Approach to Study the Structural Properties of TCR Repertoires

2011
PLoS One
PMCID: 3203878
PMID: 22053188
DOI: 10.1371/journal.pone.0026301

[…] owed clustering the candidates () . The RMSD cutoff of the algorithm was automatically adjusted to ensure that the biggest cluster contained at least 20 conformers. To select the final conformer, the TCRep 3D scoring function was computed for each conformer within the best mean Modeller pseudo-energy cluster as the sum of the occurrence of each of its potential hydrogen bonds between the TCR and t […]

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TCRep 3D institution(s)
Multidisciplinary Oncology Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Ludwig Institute for Cancer Research, Lausanne Branch, Epalinges, Lausanne, Switzerland; The National Centre of Competence in Research (NCCR), Lausanne, Switzerland; Department of Research, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Urology Research Unit, Department of Urology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
TCRep 3D funding source(s)
Supported by the Swiss National Science Foundation (Grant Number: SCORE 3232B0-103172, 3200B0-103173) and was also supported by the Multidisciplinary Oncology Center (CePO) of the Lausanne University Hospital (CHUV), and the National Center of Competence in Research (NCCR).

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