side chain conformation
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Synthesis ◽  
2022 ◽  
Author(s):  
William D. Lubell ◽  
Yousra Hamdane ◽  
Julien Poupart

Abstract N-Amino-imidazol-2-one (Nai) residues are tools for studying peptide-backbone and side-chain conformation and function. Recent methods for substituted Nai residue synthesis, conformational analysis by X-ray crystallography and computation, and biomedical applications are reviewed, demonstrating the utility of this constrained residue to favor biologically active turn conformers with defined χ-dihedral angle orientations.1 Introduction2 Synthetic Methods3 Conformational Analysis4 Biomedical Applications5 Conclusions


Author(s):  
Jesús San Fabián ◽  
Ignacio Ema ◽  
Salama Omar ◽  
Jose Manuel García de la Vega

2021 ◽  
Author(s):  
Gang Xu ◽  
Qinghua Wang ◽  
Jianpeng Ma

Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer library, which may have limitations on their accuracies and usages. In this study, we report an open-source toolkit for protein side-chain modeling, named OPUS-Rota4. It consists of three modules: OPUS-RotaNN2, which predicts protein side-chain dihedral angles; OPUS-RotaCM, which measures the distance and orientation information between the side chain of different residue pairs; and OPUS-Fold2, which applies the constraints derived from the first two modules to guide side-chain modeling. In summary, OPUS-Rota4 adopts the dihedral angles predicted by OPUS-RotaNN2 as its initial states, and uses OPUS-Fold2 to refine the side-chain conformation with the constraints derived from OPUS-RotaCM. In this case, we convert the protein side-chain modeling problem into a side-chain contact map prediction problem. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to include other differentiable energy terms into its side-chain modeling procedure. In other words, OPUS-Rota4 provides a platform in which the protein side-chain conformation can be dynamically adjusted under the influence of other processes, such as protein-protein interaction. We apply OPUS-Rota4 on 15 FM predictions submitted by Alphafold2 on CASP14, the results show that the side chains modeled by OPUS-Rota4 are closer to their native counterparts than the side chains predicted by Alphafold2.


2021 ◽  
Vol 500 ◽  
pp. 108254
Author(s):  
Parasuraman Rajasekaran ◽  
Michael G. Pirrone ◽  
David Crich

2020 ◽  
Vol 53 (24) ◽  
pp. 11142-11152
Author(s):  
Zhiqiang Cao ◽  
Zhaofan Li ◽  
Song Zhang ◽  
Luke Galuska ◽  
Tianyu Li ◽  
...  

2020 ◽  
Vol 295 (33) ◽  
pp. 11486-11494 ◽  
Author(s):  
Charlotte H. Coles ◽  
Catriona McMurran ◽  
Angharad Lloyd ◽  
Miriam Hock ◽  
Linda Hibbert ◽  
...  

T cell-mediated immunity is governed primarily by T cell receptor (TCR) recognition of peptide-human leukocyte antigen (pHLA) complexes and is essential for immunosurveillance and disease control. This interaction is generally stabilized by interactions between the HLA surface and TCR germline-encoded complementarity-determining region (CDR) loops 1 and 2, whereas peptide selectivity is guided by direct interactions with the TCR CDR3 loops. Here, we solved the structure of a newly identified TCR in complex with a clinically relevant peptide derived from the cancer testis antigen melanoma antigen-A4 (MAGE-A4). The TCR bound pHLA in a position shifted toward the peptide's N terminus. This enabled the TCR to achieve peptide selectivity via an indirect mechanism, whereby the TCR sensed the first residue of the peptide through HLA residue Trp-167, which acted as a tunable gateway. Amino acid substitutions at peptide position 1 predicted to alter the HLA Trp-167 side-chain conformation abrogated TCR binding, indicating that this indirect binding mechanism is essential for peptide recognition. These findings extend our understanding of the molecular rules that underpin antigen recognition by TCRs and have important implications for the development of TCR-based therapies.


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