ABSTRACT
The T-cell receptor (TCR) is a crucial molecule in cellular immunity. The single-chain T-cell receptor (scTCR) is a potential format in TCR therapeutics because it eliminates the possibility of αß-TCR mispairing. However, its poor stability and solubility impede the in vitro study and manufacturing of therapeutic applications. In this study, some conserved structural motifs are identified in variable domains regardless of germlines and species. Theoretical analysis helps to identify those unfavored factors and leads to a general strategy for stabilizing scTCRs by substituting residues at exact IMGT positions with beneficial propensities on the consensus sequence of germlines. Several representative scTCRs are displayed to achieve stability optimization and retain comparable binding affinities with the corresponding αß-TCRs in the range of µM to pM. These results demonstrate that our strategies for scTCR engineering are capable of providing the affinity-enhanced and specificity-retained format, which are of great value in facilitating the development of TCR-related therapeutics.
Subject(s)
Receptors, Antigen, T-Cell , Humans , Receptors, Antigen, T-Cell/chemistry , Receptors, Antigen, T-Cell/metabolism , Receptors, Antigen, T-Cell/immunology , Protein Stability , Receptors, Antigen, T-Cell, alpha-beta/chemistry , Receptors, Antigen, T-Cell, alpha-beta/metabolism , Amino Acid Sequence , Models, Molecular , Protein Engineering , Protein BindingABSTRACT
MOTIVATION: Phosphate binding plays an important role in modulating protein-protein interactions, which are ubiquitous in various biological processes. Accurate prediction of phosphate binding sites is an important but challenging task. Small size and diversity of phosphate binding sites lead to a substantial challenge for developing accurate prediction methods. RESULTS: Here, we present the phosphate binding site predictor (PBSP), a novel and accurate approach to identifying phosphate binding sites from protein structures. PBSP combines an energy-based ligand-binding sites identification method with reverse focused docking using a phosphate probe. We show that PBSP outperforms not only general ligand binding sites predictors but also other existing phospholigand-specific binding sites predictors. It achieves â¼95% success rate for top 10 predicted sites with an average Matthews correlation coefficient value of 0.84 for successful predictions. PBSP can accurately predict phosphate binding modes, with average position error of 1.4 and 2.4 Å in bound and unbound datasets, respectively. Lastly, visual inspection of the predictions is conducted. Reasons for failed predictions are further analyzed and possible ways to improve the performance are provided. These results demonstrate a novel and accurate approach to phosphate binding sites identification in protein structures. AVAILABILITY AND IMPLEMENTATION: The software and benchmark datasets are freely available at http://web.pkusz.edu.cn/wu/PBSP/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
