Modeling of the TCR-MHC-peptide complex11Edited by J. Thornton

Michielin, Olivier; Luescher, Immanuel F.; Karplus, Martin

doi:10.1006/jmbi.2000.3788

Cited by 30 publications

(24 citation statements)

References 60 publications

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“…al. [9] to build homology models of our target sequences using the 2bnr TCRpMHC complex along with TCR structures of our data set (see Methods and Table S1) as templates. This constrained the TCR binding orientation over the pMHC according to the known specific diagonal binding mode of Vα23-Vβ13 TCR bound to NY-ESO-1 [22].…”

Section: Resultsmentioning

confidence: 99%

“…The performance change can be explained by the accumulation of errors during the successive modeling of the loops; indeed errors during CDR2 modeling will impact the CDR1 modeling, whose error will, in turn, impact the CDR3 modeling. Successive-loops modeling of the CDR is however required in the general case since a standard homology modeling procedure cannot provide reliable structures for all CDR as TCR templates are in limited number and CDR conformations may differ from unbound to bound states [9] [22] [24] [25]. It is worth noting that, in our approach, the conformational space that is explored by CDR loops is much larger than the amplitude of CDR conformational change upon binding.…”

Section: Discussionmentioning

confidence: 99%

“…First, the homology module was used to build the overall TCRpMHC model, as previously described by our group [9]. The ab initio prediction was used next to refine the CDR loops that determine the TCR specificity for a pMHC complex (Figure 1).…”

Section: Methodsmentioning

confidence: 99%

“…Following the study of Michielin et al [9], we set up an expert modeling method, called TCRep 3D, dedicated to the modeling of high quality TCRpMHC complexes, and focusing on the CDR loops structure. This approach has been designed to include optimal automation to analyze numerous TCR sequences and provide functional insight on the interaction between TCR and pMHC.…”

Section: Introductionmentioning

confidence: 99%

“…This approach has been designed to include optimal automation to analyze numerous TCR sequences and provide functional insight on the interaction between TCR and pMHC. It makes use of homology models of TCRpMHC [10] [9], based on the constantly increasing list of available crystal structures that have been solved since the first one in 1996 [11] and are available in the Protein Data Bank [12] (http://www.rcsb.org/). Importantly, we developed in this study a dedicated method for systematic ab initio refinement of the six CDR loops using a simulated annealing approach.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2011

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TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2011

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An introduction to epitope prediction methods and software

Yang

2008

Reviews in Medical Virology

175

125

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In this paper, current prediction methods and algorithms for both T- and B cell epitopes are reviewed, and a comprehensive summary of epitope prediction software and databases currently available online is also provided. This review can offer researchers in this field a sense of direction and insights for future work. However, our main purpose is to introduce clinical and basic biomedical researchers who are not familiar with these biological analysis tools and databases to these online resources and to provide guidance on how to use them effectively.

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